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Jack Andersen & Joel Minnick, Databricks | AWS Marketplace Seller Conference 2022


 

(upbeat music) >> Welcome back everyone to The Cubes coverage here in Seattle, Washington. For AWS's Marketplace Seller Conference. It's the big news within the Amazon partner network, combining with marketplace, forming the Amazon partner organization. Part of a big reorg as they grow to the next level, NextGen cloud, mid-game on the chessboard. Cube's got it covered. I'm John Furry, your host at Cube. Great guests here from Data bricks. Both cube alumni's. Jack Anderson, GM and VP of the Databricks partnership team for AWS. You handle that relationship and Joel Minick vice president of product and partner marketing. You guys have the keys to the kingdom with Databricks and AWS. Thanks for joining. Good to see you again. >> Thanks for having us back. >> Yeah, John, great to be here. >> So I feel like we're at Reinvent 2013. Small event, no stage, but there's a real shift happening with procurement. Obviously it's a no brainer on the micro, you know, people should be buying online. Self-service, Cloud Scale. But Amazon's got billions being sold through their marketplace. They've reorganized their partner network. You can see kind of what's going on. They've kind of figured it out. Like let's put everything together and simplify and make it less of a website, marketplace. Merge our partner organizations, have more synergy and frictionless experiences so everyone can make more money and customer's are going to be happier. >> Yeah, that's right. >> I mean, you're running relationship. You're in the middle of it. >> Well, Amazon's mental model here is that they want the world's best ISVs to operate on AWS so that we can collaborate and co architect on behalf of customers. And that's exactly what the APO and marketplace allow us to do, is to work with Amazon on these really, you know, unique use cases. >> You know, I interviewed Ali many times over the years. I remember many years ago, maybe six, seven years ago, we were talking. He's like, "we're all in on AWS." Obviously now the success of Databricks, you've got multiple clouds, see that. Customers have choice. But I remember the strategy early on. It was like, we're going to be deep. So this is, speaks volumes to the relationship you have. Years. Jack, take us through the relationship that Databricks has with AWS from a partner perspective. Joel, and from a product perspective. Because it's not like you guys are Johnny come lately, new to the scene. >> Right. >> You've been there, almost president creation of this wave. What's the relationship and how does it relate to what's going on today? >> So most people may not know that Databricks was born on AWS. We actually did our first $100 million of revenue on Amazon. And today we're obviously available on multiple clouds. But we're very fond of our Amazon relationship. And when you look at what the APN allows us to do, you know, we're able to expand our reach and co-sell with Amazon, and marketplace broadens our reach. And so, we think of marketplace in three different aspects. We've got the marketplace private offer business, which we've been doing for a number of years. Matter of fact, we were driving well over a hundred percent year over year growth in private offers. And we have a nine figure business. So it's a very significant business. And when a customer uses a private offer, that private offer counts against their private pricing agreement with AWS. So they get pricing power against their private pricing. So it's really important it goes on their Amazon bill. In may we launched our pay as you go, on demand offering. And in five short months, we have well over a thousand subscribers. And what this does, is it really reduces the barriers to entry. It's low friction. So anybody in an enterprise or startup or public sector company can start to use Databricks on AWS, in a consumption based model, and have it go against their monthly bill. And so we see customers, you know, doing rapid experimentation, pilots, POCs. They're really learning the value of that first, use case. And then we see rapid use case expansion. And the third aspect is the consulting partner, private offer, CPPO. Super important in how we involve our partner ecosystem of our consulting partners and our resellers that are able to work with Databricks on behalf of customers. >> So you got the big contracts with the private offer. You got the product market fit, kind of people iterating with data, coming in with the buyers you get. And obviously the integration piece all fitting in there. >> Exactly. >> Okay, so those are the offers, that's current, what's in marketplace today. Is that the products... What are people buying? >> Yeah. >> I mean, I guess what's the... Joel, what are people buying in the marketplace? And what does it mean for them? >> So fundamentally what they're buying is the ability to take silos out of their organization. And that is the problem that Databricks is out there to solve. Which is, when you look across your data landscape today, you've got unstructured data, you've got structured data, you've got real time streaming data. And your teams are trying to use all of this data to solve really complicated problems. And as Databricks, as the Lakehouse Company, what we're helping customers do is, how do they get into the new world? How do they move to a place where they can use all of that data across all of their teams? And so we allow them to begin to find, through the marketplace, those rapid adoption use cases where they can get rid of these data warehousing, data lake silos they've had in the past. Get their unstructured and structured data onto one data platform, an open data platform, that is no longer adherent to any proprietary formats and standards and something they can, very much, very easily, integrate into the rest of their data environment. Apply one common data governance layer on top of that. So that from the time they ingest that data, to the time they use that data, to the time they share that data, inside and outside of their organization, they know exactly how it's flowing. They know where it came from. They know who's using it. They know who has access to it. They know how it's changing. And then with that common data platform, with that common governance solution, they'd being able to bring all of those use cases together. Across their real time streaming, their data engineering, their BI, their AI. All of their teams working on one set of data. And that lets them move really, really fast. And it also lets them solve challenges they just couldn't solve before. A good example of this, you know, one of the world's now largest data streaming platforms runs on Databricks with AWS. And if you think about what does it take to set that up? Well, they've got all this customer data that was historically inside of data warehouses. That they have to understand who their customers are. They have all this unstructured data, they've built their data science model, so they can do the right kinds of recommendation engines and forecasting around. And then they've got all this streaming data going back and forth between click stream data, from what the customers are doing with their platform and the recommendations they want to push back out. And if those teams were all working in individual silos, building these kinds of platforms would be extraordinarily slow and complex. But by building it on Databricks, they were able to release it in record time and have grown at a record pace to now be the number one platform. >> And this product, it's impacting product development. >> Absolutely. >> I mean, this is like the difference between lagging months of product development, to like days. >> Yes. >> Pretty much what you're getting at. >> Yes. >> So total agility. >> Mm-hmm. >> I got that. Okay, now, I'm a customer I want to buy in the marketplace, but you got direct Salesforce up there. So how do you guys look at this? Is there channel conflict? Are there comp programs? Because one of the things I heard today in on the stage from AWS's leadership, Chris, was up there speaking, and Mona was, "Hey, he's a CRO conference chief revenue officer" conversation. Which means someone's getting compensated. So, if I'm the sales rep at Databricks, what's my motion to the customer? Do I get paid? Does Amazon sell it? Take us through that. Is there channel conflict? Or, how do you handle it? >> Well, I'd add what Joel just talked about with, you know, with the solution, the value of the solution our entire offering is available on AWS marketplace. So it's not a subset, it's the entire Data Bricks offering. And- >> The flagship, all the, the top stuff. >> Everything, the flagship, the complete offering. So it's not segmented. It's not a sub segment. >> Okay. >> It's, you know, you can use all of our different offerings. Now when it comes to seller compensation, we view this two different ways, right? One is that AWS is also incented, right? Versus selling a native service to recommend Databricks for the right situation. Same thing with Databricks, our sales force wants to do the right thing for the customer. If the customer wants to use marketplace as their procurement vehicle. And that really helps customers because if you get Databricks and five other ISVs together, and let's say each ISV is spending, you're spending a million dollars. You have $5 million of spend. You put that spend through the flywheel with AWS marketplace, and then you can use that in your negotiations with AWS to get better pricing overall. So that's how we view it. >> So customers are driving. This sounds like. >> Correct. For sure. >> So they're looking at this as saying, Hey, I'm going to just get purchasing power with all my relationships. Because it's a solution architectural market, right? >> Yeah. It makes sense. Because if most customers will have a primary and secondary cloud provider. If they can consolidate, you know, multiple ISV spend through that same primary provider, you get pricing power. >> Okay, Joel, we're going to date ourselves. At least I will. So back in the old days, (group laughter) It used to be, do a Barney deal with someone, Hey, let's go to market together. You got to get paper, you do a biz dev deal. And then you got to say, okay, now let's coordinate our sales teams, a lot of moving parts. So what you're getting at here is that the alternative for Databricks, or any company is, to go find those partners and do deals, versus now Amazon is the center point for the customer. So you can still do those joint deals, but this seems to be flipping the script a little bit. >> Well, it is, but we still have vars and consulting partners that are doing implementation work. Very valuable work, advisory work, that can actually work with marketplace through the CPPO offering. So the marketplace allows multiple ways to procure your solution. >> So it doesn't change your business structure. It just makes it more efficient. >> That's correct. >> That's a great way to say it. >> Yeah, that's great. >> Okay. So, that's it. So that's just makes it more efficient. So you guys are actually incented to point customers to the marketplace. >> Yes. >> Absolutely. >> Economically. >> Economically, it's the right thing to do for the customer. It's the right thing to do for our relationship with Amazon. Especially when it comes back to co-selling, right? Because Amazon now is leaning in with ISVs and making recommendations for, you know, an ISV solution. And our teams are working backwards from those use cases, you know, to collaborate and land them. >> Yeah. I want to get that out there. Go ahead, Joel. >> So one of the other things I might add to that too, you know, and why this is advantageous for companies like Databricks to work through the marketplace. Is it makes it so much easier for customers to deploy a solution. It's very, literally, one click through the marketplace to get Databricks stood up inside of your environment. And so if you're looking at how do I help customers most rapidly adopt these solutions in the AWS cloud, the marketplace is a fantastic accelerator to that. >> You know, it's interesting. I want to bring this up and get your reaction to it because to me, I think this is the future of procurement. So from a procurement standpoint, I mean, again, dating myself, EDI back in the old days, you know, all that craziness. Now this is all the internet, basically through the console. I get the infrastructure side, you know, spin up and provision some servers, all been good. You guys have played well there in the marketplace. But now as we get into more of what I call the business apps, and they brought this up on stage. A little nuanced. Most enterprises aren't yet there of integrating tech, on the business apps, into the stack. This is where I think you guys are a use case of success where you guys have been successful with data integration. It's an integrators dilemma, not an innovator's dilemma. So like, I want to integrate. So now I have integration points with Databricks, but I want to put an app in there. I want to provision an application, but it has to be built. It's not, you don't buy it. You build, you got to build stuff. And this is the nuance. What's your reaction to that? Am I getting this right? Or am I off because, no one's going to be buying software like they used to. They buy software to integrate it. >> Yeah, no- >> Because everything's integrated. >> I think AWS has done a great job at creating a partner ecosystem, right? To give customers the right tools for the right jobs. And those might be with third parties. Databricks is doing the same thing with our partner connect program, right? We've got customer partners like Five Tran and DBT that, you know, augment and enhance our platform. And so you're looking at multi ISV architectures and all of that can be procured through the AWS marketplace. >> Yeah. It's almost like, you know, bundling and un bundling. I was talking about this with, with Dave Alante about Supercloud. Which is why wouldn't a customer want the best solution in their architecture? Period. In its class. If someone's got API security or an API gateway. Well, you know, I don't want to be forced to buy something because it's part of a suite. And that's where you see things get sub optimized. Where someone dominates a category and they have, oh, you got to buy my version of this. >> Joel and I were talking, we were actually saying, what's really important about Databricks, is that customers control the data, right? You want to comment on that? >> Yeah. I was going to say, you know, what you're pushing on there, we think is extraordinarily, you know, the way the market is going to go. Is that customers want a lot of control over how they build their data stack. And everyone's unique in what tools are the right ones for them. And so one of the, you know, philosophically, I think, really strong places, Databricks and AWS have lined up, is we both take an approach that you should be able to have maximum flexibility on the platform. And as we think about the Lakehouse, one thing we've always been extremely committed to, as a company, is building the data platform on an open foundation. And we do that primarily through Delta Lake and making sure that, to Jack's point, with Databricks, the data is always in your control. And then it's always stored in a completely open format. And that is one of the things that's allowed Databricks to have the breadth of integrations that it has with all the other data tools out there. Because you're not tied into any proprietary format, but instead are able to take advantage of all the innovation that's happening out there in the open source ecosystem. >> When you see other solutions out there that aren't as open as you guys, you guys are very open by the way, we love that too. We think that's a great strategy, but what am I foreclosing if I go with something else that's not as open? What's the customer's downside as you think about what's around the corner in the industry? Because if you believe it's going to be open, open source, which I think open source software is the software industry, and integration is a big deal. Because software's going to be plentiful. >> Sure. >> Let's face it. It's a good time to be in software business. But Cloud's booming. So what's the downside, from your Databricks perspective? You see a buyer clicking on Databricks versus that alternative. What's potentially should they be a nervous about, down the road, if they go with a more proprietary or locked in approach? >> Yeah. >> Well, I think the challenge with proprietary ecosystems is you become beholden to the ability of that provider to both build relationships and convince other vendors that they should invest in that format. But you're also, then, beholden to the pace at which that provider is able to innovate. >> Mm-hmm. >> And I think we've seen lots of times over history where, you know, a proprietary format may run ahead, for a while, on a lot of innovation. But as that market control begins to solidify, that desire to innovate begins to degrade. Whereas in the open formats- >> So extract rents versus innovation. (John laughs) >> Exactly. Yeah, exactly. >> I'll say it. >> But in the open world, you know, you have to continue to innovate. >> Yeah. >> And the open source world is always innovating. If you look at the last 10 to 15 years, I challenge you to find, you know, an example where the innovation in the data and AI world is not coming from open source. And so by investing in open ecosystems, that means you are always going to be at the forefront of what is the latest. >> You know, again, not to date myself again, but you look back at the eighties and nineties, the protocol stacked with proprietary. >> Yeah. >> You know, SNA and IBM, deck net was digital. You know the rest. And then TCPIP was part of the open systems interconnect. >> Mm-hmm. >> Revolutionary (indistinct) a big part of that, as well as my school did. And so like, you know, that was, but it didn't standardize the whole stack. It stopped at IP and TCP. >> Yeah. >> But that helped inter operate, that created a nice defacto. So this is a big part of this mid game. I call it the chessboard, you know, you got opening game and mid-game, then you get the end game. You're not there at the end game yet at Cloud. But Cloud- >> There's, always some form of lock in, right? Andy Jazzy will address it, you know, when making a decision. But if you're going to make a decision you want to reduce- You don't want to be limited, right? So I would advise a customer that there could be limitations with a proprietary architecture. And if you look at what every customer's trying to become right now, is an AI driven business, right? And so it has to do with, can you get that data out of silos? Can you organize it and secure it? And then can you work with data scientists to feed those models? >> Yeah. >> In a very consistent manner. And so the tools of tomorrow will, to Joel's point, will be open and we want interoperability with those tools. >> And choice is a matter too. And I would say that, you know, the argument for why I think Amazon is not as locked in as maybe some other clouds, is that they have to compete directly too. Redshift competes directly with a lot of other stuff. But they can't play the bundling game because the customers are getting savvy to the fact that if you try to bundle an inferior product with something else, it may not work great at all. And they're going to be, they're onto it. This is the- >> To Amazon's credit by having these solutions that may compete with native services in marketplace, they are providing customers with choice, low price- >> And access to the core value. Which is the hardware- >> Exactly. >> Which is their platform. Okay. So I want to get you guys thought on something else I see emerging. This is, again, kind of Cube rumination moment. So on stage, Chris unpacked a lot of stuff. I mean this marketplace, they're touching a lot of hot buttons here, you know, pricing, compensation, workflows, services behind the curtain. And one of those things he mentioned was, they talk about resellers or channel partners, depending upon what you talk about. We believe, Dave and I believe on the Cube, that the entire indirect sales channel of the industry is going to be disrupted radically. Because those players were selling hardware in the old days and software. That game is going to change. You mentioned you guys have a program, let me get your thoughts on this. We believe that once this gets set up, they can play in this game and bring their services in. Which means that the old reseller channels are going to be rewritten. They're going to be refactored with this new kinds of access. Because you've got scale, you've got money and you've got product. And you got customers coming into the marketplace. So if you're like a reseller that sold computers to data centers or software, you know, a value added reseller or VAB or business. >> You've got to evolve. >> You got to, you got to be here. >> Yes. >> Yeah. >> How are you guys working with those partners? Because you say you have a product in your marketplace there. How do I make money if I'm a reseller with Databricks, with Amazon? Take me through that use case. >> Well I'll let Joel comment, but I think it's pretty straightforward, right? Customers need expertise. They need knowhow. When we're seeing customers do mass migrations to the cloud or Hadoop specific migrations or data transformation implementations. They need expertise from consulting and SI partners. If those consulting and SI partners happen to resell the solution as well. Well, that's another aspect of their business. But I really think it is the expertise that the partners bring to help customers get outcomes. >> Joel, channel big opportunity for Amazon to reimagine this. >> For sure. Yeah. And I think, you know, to your comment about how do resellers take advantage of that, I think what Jack was pushing on is spot on. Which is, it's becoming more and more about the expertise you bring to the table. And not just transacting the software. But now actually helping customers make the right choices. And we're seeing, you know, both SIs begin to be able to resell solutions and finding a lot of opportunity in that. >> Yeah. And I think we're seeing traditional resellers begin to move into that SI model as well. And that's going to be the evolution that this goes. >> At the end of the day, it's about services, right? >> For sure. Yeah. >> I mean... >> You've got a great service. You're going to have high gross profits. >> Yeah >> Managed service provider business is alive and well, right? Because there are a number of customers that want that type of a service. >> I think that's going to be a really hot, hot button for you guys. I think being the way you guys are open, this channel, partner services model coming in, to the fold, really kind of makes for kind of that Supercloud like experience, where you guys now have an ecosystem. And that's my next question. You guys have an ecosystem going on, within Databricks. >> For sure. >> On top of this ecosystem. How does that work? This is kind of like, hasn't been written up in business school and case studies yet. This is new. What is this? >> I think, you know, what it comes down to is, you're seeing ecosystems begin to evolve around the data platforms. And that's going to be one of the big, kind of, new horizons for us as we think about what drives ecosystems. It's going to be around, well, what's the data platform that I'm using? And then all the tools that have to encircle that to get my business done. And so I think there's, you know, absolutely ecosystems inside of the AWS business on all of AWS's services, across data analytics and AI. And then to your point, you are seeing ecosystems now arise around Databricks in its Lakehouse platform as well. As customers are looking at well, if I'm standing these Lakehouses up and I'm beginning to invest in this, then I need a whole set of tools that help me get that done as well. >> I mean you think about ecosystem theory, we're living a whole nother dream. And I'm not kidding. It hasn't yet been written up and for business school case studies is that, we're now in a whole nother connective tissue, ecology thing happening. Where you have dependencies and value proposition. Economics, connectedness. So you have relationships in these ecosystems. >> And I think one of the great things about the relationships with these ecosystems, is that there's a high degree of overlap. >> Yeah. >> So you're seeing that, you know, the way that the cloud business is evolving, the ecosystem partners of Databricks, are the same ecosystem partners of AWS. And so as you build these platforms out into the cloud, you're able to really take advantage of best of breed, the broadest set of solutions out there for you. >> Joel, Jack, I love it because you know what it means? The best ecosystem will win, if you keep it open. >> Sure, sure. >> You can see everything. If you're going to do it in the dark, you know, you don't know the outcome. I mean, this is really kind of what we're talking about. >> And John, can I just add that when I was at Amazon, we had a theory that there's buyers and builders, right? There's very innovative companies that want to build things themselves. We're seeing now that that builders want to buy a platform. Right? >> Yeah. >> And so there's a platform decision being made and that ecosystem is going to evolve around the platform. >> Yeah, and I totally agree. And the word innovation gets kicked around. That's why, you know, when we had our Supercloud panel, it was called the innovators dilemma, with a slash through it, called the integrater's dilemma. Innovation is the digital transformation. So- >> Absolutely. >> Like that becomes cliche in a way, but it really becomes more of a, are you open? Are you integrating? If APIs are connective tissue, what's automation, what's the service messages look like? I mean, a whole nother set of, kind of thinking, goes on in these new ecosystems and these new products. >> And that thinking is, has been born in Delta Sharing, right? So the idea that you can have a multi-cloud implementation of Databricks, and actually share data between those two different clouds, that is the next layer on top of the native cloud solution. >> Well, Databricks has done a good job of building on top of the goodness of, and the CapEx gift from AWS. But you guys have done a great job taking that building differentiation into the product. You guys have great customer base, great growing ecosystem. And again, I think a shining example of what every enterprise is going to do. Build on top of something, operating model, get that operating model, driving revenue. >> Mm-hmm. >> Yeah. >> Whether, you're Goldman Sachs or capital one or XYZ corporation. >> S and P global, NASDAQ. >> Yeah. >> We've got, you know, the biggest verticals in the world are solving tough problems with Databricks. I think we'd be remiss because if Ali was here, he would really want to thank Amazon for all of the investments across all of the different functions. Whether it's the relationship we have with our engineering and service teams. Our marketing teams, you know, product development. And we're going to be at Reinvent. A big presence at Reinvent. We're looking forward to seeing you there, again. >> Yeah. We'll see you guys there. Yeah. Again, good ecosystem. I love the ecosystem evolutions happening. This NextGen Cloud is here. We're seeing this evolve, kind of new economics, new value propositions kind of scaling up. Producing more. So you guys are doing a great job. Thanks for coming on the Cube and taking the time. Joel, great to see you at the check. >> Thanks for having us, John. >> Okay. Cube coverage here. The world's changing as APN comes together with the marketplace for a new partner organization at Amazon web services. The Cube's got it covered. This should be a very big, growing ecosystem as this continues. Billions of being sold through the marketplace. And of course the buyers are happy as well. So we've got it all covered. I'm John Furry. your host of the cube. Thanks for watching. (upbeat music)

Published Date : Oct 10 2022

SUMMARY :

You guys have the keys to the kingdom on the micro, you know, You're in the middle of it. you know, unique use cases. to the relationship you have. and how does it relate to And so we see customers, you know, And obviously the integration Is that the products... buying in the marketplace? And that is the problem that Databricks And this product, it's the difference between So how do you guys look at So it's not a subset, it's the Everything, the flagship, and then you can use So customers are driving. For sure. Hey, I'm going to just you know, multiple ISV spend here is that the alternative So the marketplace allows multiple ways So it doesn't change So you guys are actually incented It's the right thing to do for out there. the marketplace to get Databricks stood up I get the infrastructure side, you know, Databricks is doing the same thing And that's where you see And that is one of the things that aren't as open as you guys, down the road, if they go that provider is able to innovate. that desire to innovate begins to degrade. So extract rents versus innovation. Yeah, exactly. But in the open world, you know, And the open source the protocol stacked with proprietary. You know the rest. And so like, you know, that was, I call it the chessboard, you know, And if you look at what every customer's And so the tools of tomorrow And I would say that, you know, And access to the core value. to data centers or software, you know, How are you guys working that the partners bring to to reimagine this. And I think, you know, And that's going to be the Yeah. You're going to have high gross profits. that want that type of a service. I think being the way you guys are open, This is kind of like, And so I think there's, you know, So you have relationships And I think one of the great things And so as you build these because you know what it means? in the dark, you know, that want to build things themselves. to evolve around the platform. And the word innovation more of a, are you open? So the idea that you and the CapEx gift from AWS. Whether, you're Goldman for all of the investments across Joel, great to see you at the check. And of course the buyers

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Jack Andersen & Joel Minnick, Databricks | AWS Marketplace Seller Conference 2022


 

>>Welcome back everyone to the cubes coverage here in Seattle, Washington, AWS's marketplace seller conference. It's the big news within the Amazon partner network, combining with marketplaces, forming the Amazon partner organization, part of a big reorg as they grow the next level NextGen cloud mid-game on the chessboard. Cube's got cover. I'm John fur, host of Cub, a great guests here from data bricks, both cube alumnis, Jack Anderson, GM of the and VP of the data bricks partnership team. For ADOS, you handle that relationship and Joel Minick vice president of product and partner marketing. You guys are the, have the keys to the kingdom with data, bricks, and AWS. Thanks for joining. Thanks for good to see you again. Thanks for >>Having us back. Yeah, John, great to be here. >>So I feel like we're at reinvent 2013 small event, no stage, but there's a real shift happening with procurement. Obviously it makes it's a no brainer on the micro, you know, people should be buying online self-service cloud scale, but Amazon's got billions being sold to their marketplace. They've reorganized their partner network. You can see kind of what's going on. They've kind of figured it out. Like let's put everything together and simplify and make it less of a website marketplace merge our partner to have more synergy and friction, less experiences so everyone can make more money and customer's gonna be happier. >>Yeah, that's right. >>I mean, you're run relationship. You're in the middle of it. >>Well, Amazon's mental model here is that they want the world's best ISVs to operate on AWS so that we can collaborate and co architect on behalf of customers. And that's exactly what the APO and marketplace allow us to do is to work with Amazon on these really, you know, unique use cases. >>You know, I interviewed Ali many times over the years. I remember many years ago, I think six, maybe six, seven years ago, we were talking. He's like, we're all in ons. Obviously. Now the success of data bricks, you've got multiple clouds. See that customers have choice, but I remember the strategy early on. It was like, we're gonna be deep. So this is speaks volumes to the, the relationship you have years. Jack take us through the relationship that data bricks has with AWS from a, from a partner perspective, Joel, and from a product perspective, because it's not like you got to Johnny come lately new to the new, to the scene, right? We've been there almost president creation of this wave. What's the relationship and has it relate to what's going on today? >>So, so most people may not know that data bricks was born on AWS. We actually did our first 100 million of revenue on Amazon. And today we're obviously available on multiple clouds, but we're very fond of our Amazon relationship. And when you look at what the APN allows us to do, you know, we're able to expand our reach and co-sell with Amazon and marketplace broadens our reach. And so we think of marketplace in three different aspects. We've got the marketplace, private offer business, which we've been doing for a number of years. Matter of fact, we we're driving well over a hundred percent year over year growth in private offers and we have a nine figure business. So it's a very significant business. And when a customer uses a private offer that private offer counts against their private pricing agreement with AWS. So they get pricing power against their, their private pricing. >>So it's really important. It goes on their Amazon bill in may. We launched our pay as you go on demand offering. And in five short months, we have well over a thousand subscribers. And what this does is it really reduces the barriers to entry it's low friction. So anybody in an enterprise or startup or public sector company can start to use data bricks on AWS and pay consumption based model and have it go against their monthly bill. And so we see customers, you know, doing rapid experimentation pilots, POCs, they're, they're really learning the value of that first use case. And then we see rapid use case expansion. And the third aspect is the consulting partner, private offers C P O super important in how we involve our partner ecosystem of our consulting partners and our resellers that are able to work with data bricks on behalf of customers. >>So you got the big contracts with the private offer. You got the product market fit, kind of people iterating with data coming in with, with the buyers you go. And obviously the integration piece all fitting in there. Exactly. Exactly. Okay. So that's that those are the offers that's current and what's in marketplace today. Is that the products, what are, what are people buying? I mean, I guess what's the Joel, what are, what are people buying in the marketplace and what does it mean for >>Them? So fundamentally what they're buying is the ability to take silos out of their organization. And that's, that is the problem that data bricks is out there to solve, which is when you look across your data landscape today, you've got unstructured data, you've got structured data, you've got real time streaming data, and your teams are trying to use all of this data to solve really complicated problems. And as data bricks as the lake house company, what we're helping customers do is how do they get into the new world? How do they move to a place where they can use all of that data across all of their teams? And so we allow them to begin to find through the marketplace, those rapid adoption use cases where they can get rid of these data, warehousing data lake silos they've had in the past, get their unstructured and structured data onto one data platform and open data platform that is no longer adherent to any proprietary formats and standards and something. >>They can very much, very easily integrate into the rest of their data environment, apply one common data governance layer on top of that. So that from the time they ingest that data to the time they use that data to the time they share that data inside and outside of their organization, they know exactly how it's flowing. They know where it came from. They know who's using it. They know who has access to it. They know how it's changing. And then with that common data platform with that common governance solution, they'd being able to bring all of those use cases together across their real time, streaming their data engineering, their BI, their AI, all of their teams working on one set of data. And that lets them move really, really fast. And it also lets them solve challenges. They just couldn't solve before a good example of this, you know, one of the world's now largest data streaming platforms runs on data bricks with AWS. >>And if you think about what does it take to set that up? Well, they've got all this customer data that was historically inside of data warehouses, that they have to understand who their customers are. They have all this unstructured data, they've built their data science model, so they can do the right kinds of recommendation engines and forecasting around. And then they've got all this streaming data going back and forth between click stream data from what the customers are doing with their platform and the recommendations they wanna push back out. And if those teams were all working in individual silos, building these kinds of platforms would be extraordinarily slow and complex, but by building it on data bricks, they were able to release it in record time and have grown at, at record pace >>To not be that's product platform that's impacting product development. Absolutely. I mean, this is like the difference between lagging months of product development to like days. Yes. Pretty much what you're getting at. Yeah. So total agility. I got that. Okay. Now I'm a customer I wanna buy in the marketplace, but I also, you got direct Salesforce up there. So how do you guys look at this? Is there channel conflict? Are there comp programs? Because one of the things I heard today in on the stage from a Davis's leadership, Chris was up there speaking and, and, and moment I was, Hey, he's a CRO conference, chief revenue officer conversation, which means someone's getting compensated. So if I'm the sales rep at data bricks, what's my motion to the customer. Do I get paid? Does Amazon sell it? Take us through that. Is there channel conflict? Is there or an audio lift? >>Well, I I'd add what Joel just talked about with, with, you know, what the solution, the value of the solution our entire offering is available on AWS marketplace. So it's not a subset, the entire data bricks offering and >>The flagship, all the, the top, >>Everything, the flagship, the complete offering. So it's not, it's not segmented. It's not a sub segment. It's it's, you know, you can use all of our different offerings. Now when it comes to seller compensation, we, we, we view this two, two different ways, right? One is that AWS is also incented, right? Versus selling a native service to recommend data bricks for the right situation. Same thing with data bricks. Our Salesforce wants to do the right thing for the customer. If the customer wants to use marketplace as their procurement vehicle. And that really helps customers because if you get data bricks and five other ISVs together, and let's say each ISV is spending, you're spending a million dollars, you have $5 million of spend, you put that spend through the flywheel with AWS marketplace. And then you can use that in your negotiations with AWS to get better pricing overall. So that's how we, >>We do it. So customers are driving. This sounds like, correct. For sure. So they're looking at this as saying, Hey, I'm gonna just get purchasing power with all my relationships because it's a solution architectural market, right? >>Yeah. It makes sense. Because if most customers will have a primary and secondary cloud provider, if they can consolidate, you know, multiple ISV spend through that same primary provider, you get pricing >>Power, okay, Jill, we're gonna date ourselves. At least I will. So back in the old days, it used to be, do a Barney deal with someone, Hey, let's go to market together. You gotta get paper, you do a biz dev deal. And then you gotta say, okay, now let's coordinate our sales teams, a lot of moving parts. So what you're getting at here is that the alternative for data bricks or any company is to go find those partners and do deals versus now Amazon is the center point for the customer so that you can still do those joint deals. But this seems to be flipping the script a little bit. >>Well, it is, but we still have VAs and consulting partners that are doing implementation work very valuable work advisory work that can actually work with marketplace through the C PPO offering. So the marketplace allows multiple ways to procure your >>Solution. So it doesn't change your business structure. It just makes it more efficient. That's >>Correct. >>That's a great way to say it. Yeah, >>That's great. So that's so that's it. So that's just makes it more efficient. So you guys are actually incented to point customers to the marketplace. >>Yes, >>Absolutely. Economically. Yeah. >>E economically it's the right thing to do for the customer. It's the right thing to do for our relationship with Amazon, especially when it comes back to co-selling right? Because Amazon now is leaning in with ISVs and making recommendations for, you know, an ISV solution and our teams are working backwards from those use cases, you know, to collaborate, land them. >>Yeah. I want, I wanna get that out there. Go ahead, Joel. >>So one of the other things I might add to that too, you know, and why this is advantageous for, for companies like data bricks to, to work through the marketplace, is it makes it so much easier for customers to deploy a solution. It's, it's very, literally one click through the marketplace to get data bricks stood up inside of your environment. And so if you're looking at how do I help customers most rapidly adopt these solutions in the AWS cloud, the marketplace is a fantastic accelerator to that. You >>Know, it's interesting. I wanna bring this up and get your reaction to it because to me, I think this is the future of procurement. So from a procurement standpoint, I mean, again, dating myself EDI back in the old days, you know, all that craziness. Now this is all the, all the internet, basically through the console, I get the infrastructure side, you know, spin up and provision. Some servers, all been good. You guys have played well there in the marketplace. But now as we get into more of what I call the business apps, and they brought this up on stage little nuance, most enterprises aren't yet there of integrating tech on the business apps, into the stack. This is where I think you guys are a use case of success where you guys have been successful with data integration. It's an integrator's dilemma, not an innovator's dilemma. So like, I want to integrate, so now I have integration points with data bricks, but I want to put an app in there. I want to provision an application, but it has to be built. It's not, you don't buy it. You build, you gotta build stuff. And this is the nuance. What's your reaction to that? Am I getting this right? Or, or am I off because no, one's gonna be buying software. Like they used to, they buy software to integrate it. >>Yeah, >>No, I, cause everything's integrated. >>I think AWS has done a great job at creating a partner ecosystem, right. To give customers the right tools for the right jobs. And those might be with third parties, data bricks is doing the same thing with our partner connect program. Right. We've got customer, customer partners like five tra and D V T that, you know, augment and enhance our platform. And so you, you're looking at multi ISV architectures and all of that can be procured through the AWS marketplace. >>Yeah. It's almost like, you know, bundling and unbundling. I was talking about this with, with Dave ante about Supercloud, which is why wouldn't a customer want the best solution in their architecture period. And it's class. If someone's got API security or an API gateway. Well, you know, I don't wanna be forced to buy something because it's part of a suite and that's where you see things get suboptimized where someone dominates a category and they have, oh, you gotta buy my version of this. Yeah. >>Joel, Joel. And that's Joel and I were talking, we're actually saying what what's really important about Databricks is that customers control the data. Right? You wanna comment on that? >>Yeah. I was say the, you know what you're pushing on there we think is extraordinarily, you know, the way the market is gonna go is that customers want a lot of control over how they build their data stack. And everyone's unique in what tools are the right ones for them. And so one of the, you know, philosophically I think really strong places, data, bricks, and AWS have lined up is we both take an approach that you should be able to have maximum flexibility on the platform. And as we think about the lake house, one thing we've always been extremely committed to as a company is building the data platform on an open foundation. And we do that primarily through Delta lake and making sure that to Jack's point with data bricks, the data is always in your control. And then it's always stored in a completely open format. And that is one of the things that's allowed data bricks to have the breadth of integrations that it has with all the other data tools out there, because you're not tied into any proprietary format, but instead are able to take advantage of all the innovation that's happening out there in the open source ecosystem. >>When you see other solutions out there that aren't as open as you guys, you guys are very open by the way, we love that too. We think that's a great strategy, but what's the, what am I foreclosing? If I go with something else that's not as open what what's the customer's downside as you think about what's around the corner in the industry. Cuz if you believe it's gonna be open, open source, which I think opens our software is the software industry and integration is a big deal, cuz software's gonna be plentiful. Let's face it. It's a good time to be in software business, but cloud's booming. So what's the downside from your data bricks perspective, you see a buyer clicking on data bricks versus that alternative what's potentially is should they be a nervous about down the road if they go with a more proprietary or locked in approach? Well, >>I think the challenge with proprietary ecosystems is you become beholden to the ability of that provider to both build relationships and convince other vendors that they should invest in that format. But you're also then beholden to the pace at which that provider is able to innovate. And I think we've seen lots of times over history where, you know, a proprietary format may run ahead for a while on a lot of innovation. But as that market control begins to solidify that desire to innovate begins to, to degrade, whereas in the open format. So >>Extract rents versus innovation. Exactly. >>Yeah, exactly. >>But >>I'll say it in the open world, you know, you have to continue to innovate. Yeah. And the open source world is always innovating. If you look at the last 10 to 15 years, I challenge you to find, you know, an example where the innovation in the data and AI world is not coming from open source. And so by investing in open ecosystems, that means you were always going to be at the forefront of what is the >>Latest, you know, again, not to date myself again, but you look back at the eighties and nineties, the protocol stacked for proprietary. Yeah. You know, SNA at IBM deck net was digital, you know, the rest is, and then TCP, I P was part of the open systems, interconnect, revolutionary Oly, a big part of that as well as my school did. And so like, you know, that was, but it didn't standardize the whole stack. It stopped at IP and TCP. Yeah. But that helped interoperate, that created a nice defacto. So this is a big part of this mid game. I call it the chessboard, you know, you got opening game and mid game. Then you got the end game and we're not there. The end game yet cloud the cloud. >>There's, there's always some form of lock in, right. Andy jazzy will, will address it, you know, when making a decision. But if you're gonna make a decision you want to reduce as you don't wanna be limited. Right. So I would advise a customer that there could be limitations with a proprietary architecture. And if you look at what every customer's trying to become right now is an AI driven business. Right? And so it has to do with, can you get that data outta silos? Can you, can you organize it and secure it? And then can you work with data scientists to feed those models? Yeah. In a, in a very consistent manner. And so the tools of tomorrow will to Joel's point will be open and we want interoperability with those >>Tools and, and choice is a matter too. And I would say that, you know, the argument for why I think Amazon is not as locked in as maybe some other clouds is that they have to compete directly too. Redshift competes directly with a lot of other stuff, but they can't play the bundling game because the customers are getting savvy to the fact that if you try to bundle an inferior product with something else, it may not work great at all. And they're gonna be they're onto it. This is >>The Amazon's credit by having these, these solutions that may compete with native services in marketplace, they are providing customers with choice, low >>Price and access to the S and access to the core value. Exactly. Which the >>Hardware, which is their platform. Okay. So I wanna get you guys thought on something else. I, I see emerging, this is again kind of cube rumination moment. So on stage Chris unpacked, a lot of stuff. I mean this marketplace, they're touching a lot of hot buttons here, you know, pricing compensation, workflows services behind the curtain. And one of the things he mentioned was they talk about resellers or channel partners, depending upon what you talk about. We believe Dave and I believe on the cube that the entire indirect sales channel of the industry is gonna be disrupted radically because those players were selling hardware in the old days and software, that game is gonna change. You know, you mentioned you guys have a program, want to get your thoughts on this. We believe that once this gets set up, they can play in this game and bring their services in which means that the old reseller channels are gonna be rewritten. They're gonna be refactored with this new kinds of access. Cuz you've got scale, you've got money and you've got product and you got customers coming into the marketplace. So if you're like a reseller that sold computers to data centers or software, you know, value added reseller or V or business, >>You've gotta evolve. >>You gotta, you gotta be here. Yes. How are you guys working with those partners? Cuz you say you have a part in your marketplace there. How do I make money? If I'm a reseller with data bricks with eight Amazon, take me through that use case. >>Well I'll let Joel comment, but I think it's, it's, it's pretty straightforward, right? Customers need expertise. They need knowhow. When we're seeing customers do mass migrations to the cloud or Hadoop specific migrations or data transformation implementations, they need expertise from consulting and SI partners. If those consulting SI partners happen to resell the solution as well. Well, that's another aspect of their business, but I really think it is the expertise that the partners bring to help customers get outcomes. >>Joel, channel big opportunity for re re Amazon to reimagine this. >>For sure. Yeah. And I think, you know, to your comment about how to resellers take advantage of that, I think what Jack was pushing on is spot on, which is it's becoming more about more and more about the expertise you bring to the table and not just transacting the software, but now actually helping customers make the right choices. And we're seeing, you know, both SI begin to be able to resell solutions and finding a lot of opportunity in that. Yeah. And I think we're seeing traditional resellers begin to move into that SI model as well. And that's gonna be the evolution that >>This gets at the end of the day. It's about services for sure, for sure. You've got a great service. You're gonna have high gross profits. And >>I think that the managed service provider business is alive and well, right? Because there are a number of customers that want that, that type of a service. >>I think that's gonna be a really hot, hot button for you guys. I think being the way you guys are open this channel partner services model coming in to the fold really kind of makes for kind of that super cloudlike experience where you guys now have an ecosystem. And that's my next question. You guys have an ecosystem going on within data bricks for sure. On top of this ecosystem, how does that work? This is kinda like hasn't been written up in business school and case studies yet this is new. What is this? >>I think, you know, what it comes down to is you're seeing ecosystems begin to evolve around the data platforms and that's gonna be one of the big kind of new horizons for us as we think about what drives ecosystems it's going to be around. Well, what is the, what's the data platform that I'm using and then all the tools that have to encircle that to get my business done. And so I think there's, you know, absolutely ecosystems inside of the AWS business on all of AWS's services, across data analytics and AI. And then to your point, you are seeing ecosystems now arise around data bricks in its Lakehouse platform, as well as customers are looking at well, if I'm standing these Lakehouse up and I'm beginning to invest in this, then I need a whole set of tools that help me get that done as well. >>I mean you think about ecosystem theory, we're living a whole nother dream and I'm, and I'm not kidding. It hasn't yet been written up and for business school case studies is that we're now in a whole nother connective tissue ecology thing happening where you have dependencies and value proposition economics connectedness. So you have relationships in these ecosystems. >>And I think one of the great things about relationships with these ecosystems is that there's a high degree of overlap. Yeah. So you're seeing that, you know, the way that the cloud business is evolving, the, the ecosystem partners of data bricks are the same ecosystem partners of AWS. And so as you build these platforms out into the cloud, you're able to really take advantage of best of breed, the broadest set of solutions out there for >>You. Joel, Jack, I love it because you know what it means the best ecosystem will win. If you keep it open. Sure. You can see everything. If you're gonna do it in the dark, you know, you don't know the outcome. I mean, this is really kind we're talking about. >>And John, can I just add that when I was in Amazon, we had a, a theory that there's buyers and builders, right? There's very innovative companies that want to build things themselves. We're seeing now that that builders want to buy a platform. Right? Yeah. And so there's a platform decision being made and that ecosystem gonna evolve around the >>Platform. Yeah. And I totally agree. And, and, and the word innovation get kicks around. That's why, you know, when we had our super cloud panel was called the innovators dilemma with a slash through it called the integrated dilemma, innovation is the digital transformation. So absolutely like that becomes cliche in a way, but it really becomes more of a, are you open? Are you integrating if APIs are the connective tissue, what's automation, what's the service message look like. I mean, a whole nother set of kind of thinking goes on and these new ecosystems and these new products >>And that, and that thinking is, has been born in Delta sharing. Right? So the idea that you can have a multi-cloud implementation of data bricks, and actually share data between those two different clouds, that is the next layer on top of the native cloud >>Solution. Well, data bricks has done a good job of building on top of the goodness of, and the CapEx gift from AWS. But you guys have done a great job taking that building differentiation into the product. You guys have great customer base, great grow ecosystem. And again, I think in a shining example of what every enterprise is going to do, build on top of something operating model, get that operating model, driving revenue. >>Yeah. >>Well we, whether whether you're Goldman Sachs or capital one or XYZ corporation >>S and P global NASDAQ, right. We've got, you know, these, the biggest verticals in the world are solving tough problems with data breaks. I think we'd be remiss cuz if Ali was here, he would really want to thank Amazon for all of the investments across all of the different functions, whether it's the relationship we have with our engineering and service teams. Yeah. Our marketing teams, you know, product development and we're gonna be at reinvent the big presence of reinvent. We're looking forward to seeing you there again. >>Yeah. We'll see you guys there. Yeah. Again, good ecosystem. I love the ecosystem evolutions happening this next gen cloud is here. We're seeing this evolve kind of new economics, new value propositions kind of scaling up, producing more so you guys are doing a great job. Thanks for coming on the Cuban, taking time. Chill. Great to see you at the check. Thanks for having us. Thanks. Going. Okay. Cube coverage here. The world's changing as APN comes to give the marketplace for a new partner organization at Amazon web services, the Cube's got a covered. This should be a very big growing ecosystem as this continues, billions of being sold through the marketplace. Of course the buyers are happy as well. So we've got it all covered. I'm John furry, your host of the cube. Thanks for watching.

Published Date : Sep 21 2022

SUMMARY :

Thanks for good to see you again. Yeah, John, great to be here. Obviously it makes it's a no brainer on the micro, you know, You're in the middle of it. you know, unique use cases. So this is speaks volumes to the, the relationship you have years. And when you look at what the APN allows us to do, And so we see customers, you know, doing rapid experimentation pilots, POCs, So you got the big contracts with the private offer. And that's, that is the problem that data bricks is out there to solve, They just couldn't solve before a good example of this, you know, And if you think about what does it take to set that up? So how do you guys look at this? Well, I I'd add what Joel just talked about with, with, you know, what the solution, the value of the solution our entire offering And that really helps customers because if you get data bricks So they're looking at this as saying, you know, multiple ISV spend through that same primary provider, you get pricing And then you gotta say, okay, now let's coordinate our sales teams, a lot of moving parts. So the marketplace allows multiple ways to procure your So it doesn't change your business structure. Yeah, So you guys are actually incented to Yeah. It's the right thing to do for our relationship with Amazon, So one of the other things I might add to that too, you know, and why this is advantageous for, I get the infrastructure side, you know, spin up and provision. you know, augment and enhance our platform. you know, I don't wanna be forced to buy something because it's part of a suite and the data. And that is one of the things that's allowed data bricks to have the breadth of integrations that it has with When you see other solutions out there that aren't as open as you guys, you guys are very open by the I think the challenge with proprietary ecosystems is you become beholden to the Exactly. I'll say it in the open world, you know, you have to continue to innovate. I call it the chessboard, you know, you got opening game and mid game. And so it has to do with, can you get that data outta silos? And I would say that, you know, the argument for why I think Amazon Price and access to the S and access to the core value. So I wanna get you guys thought on something else. You gotta, you gotta be here. If those consulting SI partners happen to resell the solution as well. And we're seeing, you know, both SI begin to be This gets at the end of the day. I think that the managed service provider business is alive and well, right? I think being the way you guys are open this channel I think, you know, what it comes down to is you're seeing ecosystems begin to evolve around So you have relationships in And so as you build these platforms out into the cloud, you're able to really take advantage you don't know the outcome. And John, can I just add that when I was in Amazon, we had a, a theory that there's buyers and builders, That's why, you know, when we had our super cloud panel So the idea that you can have a multi-cloud implementation of data bricks, and actually share data But you guys have done a great job taking that building differentiation into the product. We're looking forward to seeing you there again. Great to see you at the check.

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Javier de la Torre, Carto | CUBE Conversation


 

>>Hey everyone. Welcome to this cube conversation featuring Carto I'm Lisa Martin. And today we're excited to be joined by Javier Delatorre, the founder and chief strategy officer at Carto. We're going to be talking about how Carto is bringing cloud native spatial analysis to the cloud with AWS. How do you are great to have you on the program? Talk to us about cartel. What do you guys do? >>Great. So, uh, part two is a location intelligence platform, but we really use some neighboring organizations to work with location data on the AWS cloud. So essentially enabling organizations to analyze what do they, what should they open new stores? Whereas today probably the new internet, in essence, understanding the locations. I mentioned just helping them to figure out where to do things >>From Carter's perspective. Talk to me about why spatial analysis, location data is important. What power does it give to businesses in any industry? >>Right. I mean, we like to say that everything happens somewhere, right? So we understand that, you know, like the physical world is a very important dimension. So understanding where things happens and the relation within space is a pretty fundamental dimension when it comes to another. I like to put examples of, um, before your neighbors, uh, install alarms in their phones, the likelihood that you will get an alarm is also versus quite a lot. So that's eight years old, says that we are influenced by things that happens around us. And if you can model and understand those spacial relations, you can then look to optimize or predict what is going to happen based on where things are happening. And this is something that we've seen a lot, for example, with the pandemic, but now we're seeing, you know, like many organizations utilizing it for yeah. For finding out where they can find new customers, stores, like say, where did they deploy the new infrastructure? Everything that the ANZ has a spatial component. And that's what is spatial analytics and location intelligence allows you to do? >>Give me some examples of spatial data. And the first thing that pops into my mind is GPS. But I know that there's a lot more than that. >>Uh, GPS has been one of the most important types of data for, so since you know, the inability of GPS and, and with mobile and different sensors are staring at it, we've seen an incredible amount of location data coming into place, but you're right. There's many other types of location data that people tend not to be so aware. I'd say any company that is handling customers, you know, they're likely going to have their addresses. So we have the address of the customer. You have a location already, we'll have, we'll call that the process of geocoding. We transform an address that coordinates, right? But you also have the same, you know, with bees, you have the same, uh, with many different sip codes, it's many different ways that you can represent location. And once you identify those, uh, location bits in your data, then you can start thinking about what type of analysis you can do with them. So it is, like I said, like in many, many places, but definitely the, the rise of, uh, GPS and sensors have been very dramatic. Now we see in also like acute stream of location data coming, for example, from satellites, you know, with all these constellations of satellites, capturing daily images on from earlier, that is also giving us a lot of contextual information. But so it is, you know, mobile phones, when you connect to cell towers, there's many different businesses that are now kind of giving us location data. >>So you alluded to that earlier, a lot more businesses are using location data in their strategies. Talk to me about the acceleration that you seen of that in the last couple of years alone. >>Yeah. So I think one thing that we see in, you know, like massively on the industry obviously is these companies are going through the digital transformation. They are applying analytics to bigger and bigger areas of their, of their, of their business, right. And in a way to showcase, to kind of came as while the last time I mentioned that a lot of organizations started to look at, and over the last few years, we've seen that change in a lot. We've seen it within the many more organized spaces. Now making the questions around where things happens, how does actually matter to my business. So this is celebration, you know, has the sensitive men that many more people are now starting to look at, not only seeing things on a map, like, you know, where my customers are, where my warehouses are, my logistics supply chain, where is it located? >>Now, we're starting to see many more organizations looking at questions about how can I predict where something is going to happen, or how can I optimize my business process so that, um, you know, I, I try to reduce the number of kilometers that I have to drive miles. So, um, I guess it's a mix of the need for sustainability optimizing the business process. And the fact that more and more organizations are starting to do much more deep transformation that now location data has become a much more interesting aspect for many more organizations. So I think all these things together has to make in a way that perfect storm. And now we've seen a lot of the men too, um, for companies that want to go will be John seeing things in a map to understanding why things happen in those spaces. And that's, I think that like, again, a multitude of drivers, you know, that is supposed to in this industry. >>Can you talk about some of the key use cases and maybe some of the vertical industries where you've really seen this takeoff in the last couple of years? >>Yes. And I think he's just in a way, one of the most interesting factors of our industry traditional industries have been on the area around security in the public sector was very much on the military and the, in the, in the, uh, intelligence ecosystem. But now we've seen tremendous adoption on industries like retail, right, where they are lying now consolidating what is their, what is their physical presence? Where do they open stores? You know, like, uh, food chains, what do they open restaurants? And it's a much more analytical process now towards making businesses because, and that involves the usage of location intelligence and space analytics. We do touch one, but we still also like tremendous increase in usage on things like telcos telecommunication. Now with all the deployment of 5g networks, fiber optics, most of those operators require a very good understanding of where you should apply your networks, which, which areas you want to go start first tablet, smart CapEx car, like a strategy. >>So that's telco, I would say it's also has been a tremendous increase. Um, the public secretary is obviously very important, you know, especially, you know, with a lot of the, in a way we all got to master or do you know why geography matters? You know, how to understand your location. Um, and the last one that I would say that it's also connected very much with climate change, transportation and logistics are very, very important factor now. So understanding what is the best strategies for last mile delivery, how to organize your warehouses to better meet your needs. Those are the places that now we're seeing really growing really fast. >>So tremendous amount of use cases, a lot of opportunity there for optimization. How have companies traditionally analyze spatial data and why does that need to change? >>Yeah, so, um, I mean, to a certain extent, I would like to say that there's not been, um, that much use of location data. And that I think is one of the most exciting parts that for many organizations, this is the first time that they're looking at location as a, as a need. I mentioned that they need to understand. So there were, there were several organizations doing already a spatial analytics, but right now it's really, we really see in the expansion of our industry and you're not catching up in, in major, uh, major companies. So those are not like more advanced, you know, we'll have used so-called the traditional GIS systems. GIS is a, is a type of software. That's been existing for many years, but it's only the second used by a very small needs of analysts. You have to go almost four years to school, you know, to become a GIS expert and then do GIS analyst. >>This is right now trending dramatically. And I think, you know, Carter's part of that, uh, transition to necessity, making best patient analysis and GIS part of just the generic general analytics. And I think this is one of the most exciting times that we have, because we've seen the demo by station of his face. And it takes now to imagine why there are, so now we've seen, you know, like analysts that, you know, used to be just to know how to make a map. So things are not with a map, you know, where, where something was happening. Now we starting to see them making much more interesting plastics. So I'm like, okay, if it happens here, where else could they be happened? Right. So that's what I, right now, they, the, the, the huge statements, I'd say, I'd say like many organizations is the first time they go into jail. People like me for being very passionate about the possibilities of really improving processes. I mean, this is super, super exciting time. >>I can definitely feel your passion here through zoom, or talk to me a little bit about how cartel and AWS are helping organizations to embrace the democratization of spatial data and really unlock its super powers. >>Yeah. Well, I mean, obviously, you know, that AWS as the leader on the cloud, in a way that has fundamentally changed the way that we think about like analytics, right? So, um, not only the clouds provide us with the scalability, scalability, affordable the scale of anything. So that's one of the things that, you know, has been incredibly, um, transformative in our industry, uh, with AWS. Now we can do analysis at the scale that wasn't possible before. So that's, that's, that's one thing. So for us, you know, what we've embarked with AWS is rethinking how we can do a spatial analytics in the cloud. We're calling it car to cloud native is providing a full cloud native approach towards performing the spatial analytics, traditional GIS. And for us to utilize this game, even as huge amount of scalability, we use services like Retsef the now with their server last capabilities, we like a, an organization have their data already on that data warehouse on breaths test and using Kartra space. >>now they can do a special ethics directly on the warehouse. This is one of the biggest characteristics of cartel made by being the first cloud data platform. Every computing that we do actually gets pushed down to the warehouse. So the customer is already using the computing engine that they're already, they've been using it for many other things they're paying for already. And they give us scalability. Uh, also very cost-effectiveness this storage competed in separation that the rest of service provides. It makes it very competitive from a call like a cost perspective, and then also is very convenient. So it means that you can use just traditional sequel that are many analysts, know how to use it within the tools that they've been using for many. So I think the participation is essential to read safe, and then also with incorporating the Amazon location services. So we can talk to, and it certainly provides a cloud native it's scalable, affordable, efficient, and much more easy to use solution to performance, space analytics that anything that has been done before. >>It's a tremendous amount of opportunity. It sounds like we're just scratching the surface, but really interesting things that cartoon was doing and how you're enabling organizations in every industry to accelerate the use of spatial data. Javier, thank you so much for joining me on the program today. Fascinating information and best of luck to you. >>Thank you very much >>For Javier Delatorre I'm Lisa Martin. You're watching the cubes stay right here for more coverage of the hybrid tech event world.

Published Date : Mar 23 2022

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FINANCIAL SERVICES V1b | Cloudera


 

>>Uh, hi, I'm Joe Rodriguez, managing director of financial services at Cloudera. Uh, welcome to the fight fraud with a data session, uh, at Cloudera, we believe that fighting fraud with, uh, uh, begins with data. Um, so financial services is Cloudera's largest industry vertical. We have approximately 425 global financial services customers, uh, which consists of 82 out of a hundred of the largest global banks of which we have 27 that are globally systemic banks, uh, four out of the five top, uh, stock exchanges, uh, eight out of the top 10 wealth management firms and all four of the top credit card networks. So as you can see most financial services institutions, uh, utilize Cloudera for data analytics and machine learning, uh, we also have over 20 central banks and a dozen or so financial regulators. So it's an incredible footprint which gives Cloudera lots of insight into the many innovations, uh, that our customers are coming up with. Uh, criminals can steal thousands of dollars before a fraudulent transaction is detected. So the cost of, uh, to purchase a, your account data is well worth the price to fraudsters. Uh, according to Experian credit and debit card account information sells on the dark web for a mere $5 with the CVV number and up to $110. If it comes with all the bank information, including your name, social security number, date of birth, uh, complete account numbers and, and other personal data. >>Um, our customers have several key data and analytics challenges when it comes to fighting financial crime. The volume of data that they need to deal with is, is huge and growing exponentially. Uh, all this data needs to be evaluated in real time. Uh, there is, uh, there are new sources of, of streaming data that need to be integrated with existing, uh, legacy data sources. This includes, um, biometrics data and enhanced, uh, authentication, uh, video surveillance call center data. And of course all that needs to be integrated with existing legacy data sources. Um, there is an analytics arms race between the banks and the criminals and the criminal networks never stop innovating. They also we'll have to deal with, uh, disjointed security and governance, security and governance policies are often set per data source, uh, or application requiring redundant work, work across workloads. And, and they have to deal with siloed environments, um, the specialized nature of platforms and people results in disparate data sources and data management processes, uh, this duplicates efforts and, uh, divides the, the business risk and crime teams, limiting collaboration opportunities between CDP enhances financial crime solutions, uh, to be holistic by eliminating data gaps between siloed solutions with, uh, an enterprise data approach, uh, advanced, uh, data analytics and machine learning, uh, by deploying an enterprise wide data platform, you reduce siloed divisions between business risk and crime teams and enable better collaboration through industrialized machine learning. >>Uh, you tighten up the loop between, uh, detection and new fraud patterns. Cloudera provides the data platform on which a best of breed applications can run and leverage integrated machine learning cloud Derrick stands rather than replaces your existing fraud modeling applications. So Oracle SAS Actimize to, to name a few, uh, integrate with an enterprise data hub to scale the data increased speed and flexibility and improve efficacy of your entire fraud system. It also centralizes the fraud workload on data that can be used for other use cases in applications like enhanced KYC and a customer 360 4 example. >>I just, I wanted to highlight a couple of our partners in financial crime prevention, uh, semi dine, and Quintex, uh, uh, so send me nine provides fraud simulation using agent-based modeling, uh, machine learning techniques, uh, to generate synthetic transaction data. This data simulates potential fraud scenarios in a cost-effective, uh, GDPR compliant, virtual environment, significantly improved financial crime detection systems, semi dine identifies future fraud topologies, uh, from millions of, of simulations that can be used to dynamically train, uh, new machine learning algorithms for enhanced fraud identification and context, um, uh, connects the dots within your data, using dynamic entity resolution, and advanced network analytics to create context around your customers. Um, this enables you to see the bigger picture and automatically assesses potential criminal beads behavior. >>Now let's go some of our, uh, customers, uh, and how they're using cloud caldera. Uh, first we'll talk about, uh, United overseas bank, or you will be, um, you'll be, is a leading full service bank in, uh, in Asia. It, uh, with, uh, a network of more than 500 offices in, in 19 countries and territories in Asia, Pacific, Western Europe and north America UA, um, UOB built a modern data platform on Cloudera that gives it the flexibility and speed to develop new AI and machine learning solutions and to create a data-driven enterprise. Um, you'll be set up, uh, set up it's big data analytics center in 2017. Uh, it was Singapore's first centralized big data unit, uh, within a bank to deepen the bank's data analytic capabilities and to use data insights to enhance, uh, the banks, uh, uh, performance essential to this work was implementing a platform that could cost efficiently, bring together data from dozens of separate systems and incorporate a range of unstructured data, including, uh, voice and text, um, using Cloudera CDP and machine learning. >>UOB gained a richer understanding of its customer preferences, uh, to help make their, their banking experience simpler, safer, and more reliable. Working with Cloudera UOB has a big data platform that gives business staff and data scientists faster access to relevant and quality data for, for self-service analytics, machine learning and, uh, emerging artificial intelligence solutions. Um, with new self-service analytics and machine learning driven insights, you'll be, uh, has realized improvements in, in digital banking, asset management, compliance, AML, and more, uh, advanced AML detection capabilities, help analysts detect suspicious transactions either based on hidden relationships of shell companies and, uh, high risk individuals, uh, with, uh, Cloudera and machine learning, uh, technologies. You you'll be, uh, was able to enhance AML detection and reduce the time to identify new links from months 2, 3, 3 weeks. >>Excellent mass let's speak about MasterCard. So MasterCard's principle businesses to process payments between banks and merchants and the credit issuing banks and credit unions of the purchasers who use the MasterCard brand debit and credit cards to make purchases MasterCard chose Cloudera enterprise for fraud detection, and to optimize their DW infrastructure, delivering deepens insights and best practices in big data security and compliance. Uh, next let's speak about, uh, bank Rakka yet, uh, in Indonesia or Bri. Um, it, VRI is one of the largest and oldest banks in Indonesia and engages in the provision of general banking services. Uh, it's headquartered in Jakarta Indonesia. Uh, Bri is well known for its focus on financing initiatives and serves over 75 million customers through it's more than 11,000 offices and rural service outposts. Uh, Bri required better insight to understand customer activity and identify fraudulent transactions. Uh, the bank needed a solid foundation that allowed it to leverage the power of advanced analytics, artificial intelligence, and machine learning to gain better understanding of customers and the market. >>Uh, Bri used, uh, Cloudera enterprise data platform to build an agile and reliable, predictive augmented intelligence solution, uh, to enhance its credit scoring system and to address the rising concern around data security from regulators, uh, and customers, uh, Bri developed a real-time fraud detection service, uh, powered by Cloudera and Kafka. Uh, Bri's data scientists developed a machine learning model for fraud detection by creating a behavioral scoring model based on customer savings, uh, loan transactions, deposits, payroll and other financial, um, uh, real-time time data. Uh, this led to improvements in its fraud detection and credit scoring capabilities, as well as the development of a, of a new digital microfinancing product, uh, with the enablement of real-time fraud detection, VRI was able to reduce the rate of fraud by 40%. Uh, it improved, uh, relationship manager productivity by two and a half fold. Uh, it improved the credit score scoring system to cut down on micro-financing loan processing times from two weeks to two days to now two minutes. So fraud prevention is a good area to start with a data focus. If you haven't already, it offers a quick return on investment, uh, and it's a focused area. That's not too entrenched across the company, uh, to learn more about fraud prevention, uh, go to kroger.com and to schedule, and you should schedule a meeting with Cloudera, uh, to learn even more. Uh, and with that, thank you for listening and thank you for your time. >>Welcome to the customer. Obsession begins with data session. Uh, thank you for, for attending. Um, at Cloudera, we believe that a custom session begins with, uh, with, with data, um, and, uh, you know, financial services is Cloudera is largest industry vertical. We have approximately 425 global financial services customers, uh, which consists of 82 out of a hundred of the largest global banks of which we have 27 that are globally systemic banks, uh, four out of the five top stock exchanges, eight out of the 10 top wealth management firms and all four of the top credit card networks. Uh, so as you can see most financial services institutions utilize Cloudera for data analytics and machine learning. Uh, we also have over 20 central banks and it doesn't or so financial regulators. So it's an incredible footprint, which glimpse Cloudera, lots of insight into the many innovations that our customers are coming up with. >>Customers have grown more independent and demanding. Uh, they want the ability to perform many functions on their own and, uh, be able to do it. Uh, he do them on their mobile devices, uh, in a recent Accenture study, more than 50% of customers, uh, are focused on, uh, improving their customer experience through more personalized offers and advice. The study found that 75% of people are actually willing to share their data for better personalized offers and more efficient and intuitive services to get it better, better understanding of your customers, use all the data available to develop a complete view of your customer and, uh, and better serve them. Uh, this also breaks down, uh, costly silos, uh, shares data in, in accordance with privacy laws and assists with regulatory advice. It's so different organizations are going to be at different points in their data analytics and AI journey. >>Uh, there are several degrees of streaming and batch data, both structured and unstructured. Uh, you need a platform that can handle both, uh, with common, with a common governance layer, um, near real time. And, uh, real-time sources help make data more relevant. So if you look at this graphic, looking at it from left to right, uh, normal streaming and batch data comes from core banking and, uh, and lending operations data in pretty much a structured format as financial institutions start to evolve. Uh, they start to ingest near real-time streaming data that comes not only from customers, but also from, from newsfeeds for example, and they start to capture more behavioral data that they can use to evolve their models, uh, and customer experience. Uh, ultimately they start to ingest more real time streaming data, not only, um, standard, uh, sources like market and transaction data, but also alternative sources such as social media and connected sources, such as wearable devices, uh, giving them more, more data, better data, uh, to extract intelligence and drive personalized actions based on data in real time at the right time, um, and use machine learning and AI, uh, to drive anomaly detection and protect and predict, uh, present potential outcomes. >>So this is another way to look at it. Um, this slide shows the progression of the big data journey as it relates to a customer experience example, um, the dark blue represents, um, visibility or understanding your customer. So we have a data warehouse and are starting to develop some analytics, uh, to know your customer and start to provide a better customer 360 experience. Uh, the medium blue area, uh, is a customer centric or where we learn, uh, the customer's behavior. Uh, at this point we're improving our analytics, uh, gathering more customer centric information to perform, uh, some more exploratory, uh, data sciences. And we can start to do things like cross sell or upsell based on the customer's behavior, which should improve, uh, customer retention. The light blue area is, uh, is proactive customer inter interactions, or where we now have the ability, uh, to predict customers needs and wants and improve our interaction with the customer, uh, using applied machine learning and, and AI, uh, the Cloudera data platform, um, you know, business use cases require enabling, uh, the end-to-end journey, which we referred to as the data life cycle, uh, what the data life cycle, what is the data life cycle that our customers want, uh, to take their data through, to enable the end to end data journey. >>If you ask our customers, they want different types of analytics, uh, for their diverse user bases to help them implement their, their, their use cases while managed by a centralized security and governance later layer. Uh, in other words, um, the data life cycle to them provides multifunction analytics, uh, at each stage, uh, within the data journey, uh, that, uh, integrated and centralized, uh, security, uh, and governance, for example, uh, enterprise data consists of real time and transactional type type data. Examples include, uh, click stream data, web logs, um, machine generated, data chat bots, um, call center interactions, uh, transactions, uh, within legacy applications, market data, et cetera. We need to manage, uh, that data life cycle, uh, to provide real enterprise data insights, uh, for use cases around enhanced them, personalized customer experience, um, customer journey analytics next best action, uh, sentiment and churn analytics market, uh, campaign optimization, uh, mortgage, uh, processing optimization and so on. >>Um, we bring a diverse set of data then, um, and then enrich it with other data about our customers and products, uh, provide reports and dashboards such as customer 360 and use predictions from machine models to provide, uh, business decisions and, and offers of, uh, different products and services to customers and maintain customer satisfaction, um, by using, um, sentiment and churn analytics. These examples show that, um, the whole data life cycle is involved, um, and, uh, is in continuous fashion in order to meet these types of use cases, uh, using a single cohesive platform that can be, uh, that can be served by CDP, uh, the data, the Cloudera data platform. >>Okay. Uh, let's talk about, uh, some of the experiences, uh, from our customers. Uh, first we'll talk about Bunco suntan there. Um, is a major global bank headquartered in Spain, uh, with, uh, major operations and subsidiaries all over Europe and north and, and south America. Uh, one of its subsidiaries, something there UK wanted to revolutionize the customer experience with the use of real time data and, uh, in app analytics, uh, for mobile users, however, like many financial institutions send them there had a, he had a, had a large number of legacy data warehouses spread across many business use, and it's within consistent data and different ways of calculating the same metrics, uh, leading to different results. As a result, the company couldn't get the comprehensive customer insights it needed. And, uh, and business staff often worked on multiple versions of the truth. Sometime there worked with Cloudera to improve a single data platform that could support all its workloads, including self-service analytics, uh, operational analytics and data science processes, processing processing, 10 million transactions daily or 30,000 transactions per second at peak times. >>And, uh, bringing together really, uh, nearly two to two petabytes of data. The platform provides unprecedented, uh, customer insight and business value across the organization, uh, over 80 cents. And there has realized impressive, uh, benefits spanning, uh, new revenues, cost savings and risk reductions, including creating analytics for, for corporate customers with near real-time shopping behavior, um, and, and helping identify 7,000 new corporate, uh, customer prospects, uh, reducing capital expenditures by, uh, 3.2 million annually and decreasing operating expenses by, uh, 650,000, um, enabling marketing to realize, uh, 2.4 million in annual savings on, on cash, on commercial transactions, um, and protecting 3.7 million customers from financial crime impacts through 95, new proactive control alerts, improving risk and capital calculations to reduce the amount of money. It must set aside, uh, as part of a, as part of risk mandates. Uh, for example, in one instance, the risk team was able to release a $5.2 million that it had withheld for non-performing credit card loans by properly identifying healthy accounts miscategorized as high risk next, uh, let's uh, talk about, uh, Rabobank. >>Um, Rabobank is one of the largest banks in the Netherlands, uh, with approximately 8.3 million customers. Uh, it was founded by farmers in the late 19th century and specializes in agricultural financing and sustainability oriented banking, uh, in order to help its customers become more self-sufficient and, uh, improve their financial situations such as debt settlement, uh, rebel bank needed to access, uh, to a varied mix of high quality, accurate, and timely customer data, the talent, uh, to provide this insight, however, was the ability to execute sophisticated and timely data analytics at scale Rabobank was also faced with the challenge of, uh, shortening time to market. Uh, it needed easier access to customer data sets to ensure that they were using and receiving the right financial support at the right time with, with, uh, data quality and speed of processing. Um, highlighted as two vital areas of improvement, Rabobank was looking to incorporate, um, or create new data in an environment that would not only allow the organization to create a centralized repository of high quality data, but also allow them to stream and, uh, conduct data analytics on the fly, uh, to create actionable insights and deliver a strong customer experience bank level Cloudera due to its ability to cope with heavy pressures on data processing and its capability of ingesting large quantities of real time streaming data. >>They were able to quickly create a new data lake that allowed for faster queries of both historical and real time data to analyze customer loan repayment patterns, uh, to up to the minute transaction records, um, Robert bank and, and its customers could now immediately access, uh, the valuable data needed to help them understand, um, the status of their financial situation in this enabled, uh, rebel bank to spot financial disasters before they happened, enabling them to gain deep and timely insights into which customers were at risk of defaulting on loans. Um, having established the foundation of a modern data architecture Rabobank is now able to run sophisticated machine learning algorithms and, uh, financial models, uh, to help customers manage, um, financial, uh, obligations, um, including, uh, long repayments and are able to generate accurate, uh, current real liquidity. I refuse, uh, next, uh, let's uh, speak about, um, uh, OVO. >>Uh, so OVO is the leading digital payment rewards and financial services platform in Indonesia, and is present in 115 million devices across the company across the country. Excuse me. Um, as the volume of, of products within Obos ecosystem increases, the ability to ensure marketing effectiveness is critical to avoid unnecessary waste of time and resources, unlike competitors, uh, banks, w which use traditional mass marketing, uh, to reach customers over, oh, decided to embark on a, on a bold new approach to connect with customers via, uh, ultra personalized marketing, uh, using the Cloudera stack. The team at OVO were able to implement a change point detection algorithm, uh, to discover customer life stage changes. This allowed OVO, uh, to, uh, build a segmentation model of one, uh, the contextual offer engine Bill's recommendation algorithms on top of the product, uh, including collaborative and context-based filters, uh, to detect changes in consumer consumption patterns. >>As a result, OVO has achieved a 15% increase in revenue, thanks to this, to this project, um, significant time savings through automation and eliminating the chance of human error and have reduced engineers workloads by, by 30%. Uh, next let's talk about, uh, bank Bri, uh, bank Bri is one of the largest and oldest, uh, banks in Indonesia, um, engaging in, in general banking services, uh, for its customers. Uh, they are headquartered in, in Jakarta Indonesia, uh, PR is a well-known, uh, for its, uh, focused on micro-financing initiative initiatives and serves over 75 million customers through more than 11,000 offices and rural outposts, um, Bri needed to gain better understanding of their customers and market, uh, to improve the efficiency of its operations, uh, reduce losses from non-performing loans and address the rising concern around data security from regulators and consumers, uh, through enhanced fraud detection. This would require the ability to analyze the vast amounts of, uh, historical financial data and use those insights, uh, to enhance operations and, uh, deliver better service. >>Um, Bri used Cloudera's enterprise data platform to build an agile and reliable, uh, predictive augmented intelligence solution. Uh, Bri was now able to analyze 124 years worth of historical financial data and use those insights to enhance its operations and deliver better services. Um, they were able to, uh, enhance their credit scoring system, um, the solution analyzes customer transaction data, and predicts the probability of a customer defaulting on, on payments. Um, the following month, it also alerts Bri's loan officers, um, to at-risk customers, prompting them to take the necessary action to reduce the likelihood of the net profit lost, uh, this resulted in improved credit, improved credit scoring system, uh, that cut down the approval of micro financing loans, uh, from two weeks to two days to, to two minutes and, uh, enhanced fraud detection. >>All right. Uh, this example shows a tabular representation, uh, the evolution of a customer retention use case, um, the evolution of data and analytics, uh, journey that, uh, that for that use case, uh, from aware, uh, text flirtation, uh, to optimization, to being transformative, uh, with every level, uh, data sources increase. And, uh, for the most part, uh, are, are less, less standard, more dynamic and less structured, but always adding more value, more insights into the customer, uh, allowing us to continuously improve our analytics, increase the velocity of the data we ingest, uh, from, from batch, uh, to, uh, near real time, uh, to real-time streaming, uh, the volume of data we ingest continually increases and we progress, uh, the value of the data on our customers, uh, is continuously improving, allowing us to interact more proactively and more efficiently. And, and with that, um, I would, uh, you know, ask you to consider and assess if you are using all the, uh, the data available to understand, uh, and service your customers, and to learn more about, about this, um, you know, visit cloudera.com and schedule a meeting with Cloudera to learn more. And with that, thank you for your time. And thank you for listening.

Published Date : Aug 4 2021

SUMMARY :

So the cost of, uh, to purchase a, approach, uh, advanced, uh, data analytics and machine learning, uh, integrate with an enterprise data hub to scale the data increased uh, semi dine, and Quintex, uh, uh, so send me nine provides fraud uh, the banks, uh, uh, performance essential to this uh, to help make their, their banking experience simpler, safer, uh, bank Rakka yet, uh, in Indonesia or Bri. the company, uh, to learn more about fraud prevention, uh, go to kroger.com uh, which consists of 82 out of a hundred of the largest global banks of which we have 27 this also breaks down, uh, costly silos, uh, uh, giving them more, more data, better data, uh, to extract to develop some analytics, uh, to know your customer and start to provide We need to manage, uh, and offers of, uh, different products and services to customers and maintain customer satisfaction, the same metrics, uh, leading to different results. as high risk next, uh, let's uh, on the fly, uh, to create actionable insights and deliver a strong customer experience next, uh, let's uh, speak about, um, uh, This allowed OVO, uh, to, uh, build a segmentation model uh, to improve the efficiency of its operations, uh, reduce losses from reduce the likelihood of the net profit lost, uh, to being transformative, uh, with every level, uh, data sources increase.

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JG Chirapurath, Microsoft | theCUBE on Cloud 2021


 

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle. Okay, >>we're now going to explore the vision of the future of cloud computing From the perspective of one of the leaders in the field, J G >>Share >>a pure off is the vice president of As Your Data ai and Edge at Microsoft G. Welcome to the Cuban cloud. Thanks so much for participating. >>Well, thank you, Dave, and it's a real pleasure to be here with you. And I just wanna welcome the audience as well. >>Well, jg judging from your title, we have a lot of ground to cover, and our audience is definitely interested in all the topics that are implied there. So let's get right into it. You know, we've said many times in the Cube that the new innovation cocktail comprises machine intelligence or a I applied to troves of data. With the scale of the cloud. It's it's no longer, you know, we're driven by Moore's law. It's really those three factors, and those ingredients are gonna power the next wave of value creation and the economy. So, first, do you buy into that premise? >>Yes, absolutely. we do buy into it. And I think, you know, one of the reasons why we put Data Analytics and Ai together is because all of that really begins with the collection of data and managing it and governing it, unlocking analytics in it. And we tend to see things like AI, the value creation that comes from a I as being on that continues off, having started off with really things like analytics and proceeding toe. You know, machine learning and the use of data. Interesting breaks. Yes. >>I'd like to get some more thoughts around a data and how you see the future data and the role of cloud and maybe how >>Microsoft, you >>know, strategy fits in there. I mean, you, your portfolio, you got you got sequel server, Azure, Azure sequel. You got arc, which is kinda azure everywhere for people that aren't familiar with that. You've got synapse. Which course that's all the integration a data warehouse, and get things ready for B I and consumption by the business and and the whole data pipeline and a lot of other services as your data bricks you got You got cosmos in their, uh, Blockchain. You've got open source services like Post Dress and my sequel. So lots of choices there. And I'm wondering, you know, how do you think about the future of Of of Cloud data platforms? It looks like your strategies, right tool for the right job? Is that fair? >>It is fair, but it's also just to step back and look at it. It's fundamentally what we see in this market today is that customer was the Sikh really a comprehensive proposition? And when I say a comprehensive proposition, it is sometimes not just about saying that. Hey, listen way No, you're a sequel server company. We absolutely trust that you have the best Azure sequel database in the cloud, but tell us more. We've got data that's sitting in her group systems. We've got data that's sitting in Post Press in things like mongo DB, right? So that open source proposition today and data and data management and database management has become front and center, so are really sort of push. There is when it comes to migration management, modernization of data to present the broadest possible choice to our customers so we can meet them where they are. However, when it comes to analytics. One of the things they asked for is give us a lot more convergence use. You know it, really, it isn't about having 50 different services. It's really about having that one comprehensive service that is converged. That's where things like synapse Fitzer, where in just land any kind of data in the leg and then use any compute engine on top of it to drive insights from it. So, fundamentally, you know, it is that flexibility that we really sort of focus on to meet our customers where they are and really not pushing our dogma and our beliefs on it. But to meet our customers according to the way they have deployed stuff like this. >>So that's great. I want to stick on this for a minute because, you know, I know when when I have guests on like yourself, do you never want to talk about you know, the competition? But that's all we ever talk about. That's all your customers ever talk about, because because the counter to that right tool for the right job and that I would say, is really kind of Amazon's approach is is that you got the single unified data platform, the mega database that does it all. And that's kind of Oracle's approach. It sounds like you wanna have your cake and eat it, too, so you you got the right tool for the right job approach. But you've got an integration layer that allows you to have that converge database. I wonder if you could add color to that and you confirm or deny what I just said. >>No, that's a That's a very fair observation, but I I say there's a nuance in what I sort of describe when it comes to data management. When it comes to APS, we have them customers with the broadest choice. Even in that, even in that perspective, we also offer convergence. So, case in point, when you think about Cosmos TV under that one sort of service, you get multiple engines, but with the same properties, right global distribution, the five nines availability. It gives customers the ability to basically choose when they have to build that new cloud native AB toe, adopt cosmos Davey and adopted in a way that it's and choose an engine that is most flexible. Tow them, however you know when it comes to say, you know, writing a sequel server, for example from organizing it you know you want. Sometimes you just want to lift and shift it into things. Like I asked In other cases, you want to completely rewrite it, so you need to have the flexibility of choice there that is presented by a legacy off What's its on premises? When it moved into things like analytics, we absolutely believe in convergence, right? So we don't believe that look, you need to have a relation of data warehouse that is separate from a loop system that is separate from, say, a B I system. That is just, you know, it's a bolt on for us. We love the proposition off, really building things that are so integrated that once you land data, once you prep it inside the lake, you can use it for analytics. You can use it for being. You can use it for machine learning. So I think you know, are sort of differentiated. Approach speaks for itself there. Well, >>that's that's interesting, because essentially, again, you're not saying it's an either or, and you're seeing a lot of that in the marketplace. You got some companies say no, it's the Data Lake and others saying No, no put in the data warehouse and that causes confusion and complexity around the data pipeline and a lot of calls. And I'd love to get your thoughts on this. Ah, lot of customers struggled to get value out of data and and specifically data product builders of frustrated that it takes too long to go from. You know, this idea of Hey, I have an idea for a data service and it could drive monetization, but to get there, you gotta go through this complex data lifecycle on pipeline and beg people to add new data sources. And do you do you feel like we have to rethink the way that we approach data architectures? >>Look, I think we do in the cloud, and I think what's happening today and I think the place where I see the most amount of rethink the most amount of push from our customers to really rethink is the area of analytics in a I. It's almost as if what worked in the past will not work going forward. Right? So when you think about analytics on in the Enterprise today, you have relational systems, you have produced systems. You've got data marts. You've got data warehouses. You've got enterprise data warehouses. You know, those large honking databases that you use, uh, to close your books with right? But when you start to modernize it, what deep you are saying is that we don't want to simply take all of that complexity that we've built over say, you know, 34 decades and simply migrated on mass exactly as they are into the cloud. What they really want is a completely different way of looking at things. And I think this is where services like synapse completely provide a differentiated proposition to our customers. What we say there is land the data in any way you see shape or form inside the lake. Once you landed inside the lake, you can essentially use a synapse studio toe. Prep it in the way that you like, use any compute engine of your choice and and operate on this data in any way that you see fit. So, case in point, if you want to hydrate relation all data warehouse, you can do so if you want to do ad hoc analytics using something like spark. You can do so if you want to invoke power. Bi I on that data or b i on that data you can do so if you want to bring in a machine learning model on this breath data you can do so, so inherently. So when customers buy into this proposition, what it solves for them and what it gives them is complete simplicity, right? One way to land the data, multiple ways to use it. And it's all eso. >>Should we think of synapse as an abstraction layer that abstracts away the complexity of the underlying technology? Is that a fair way toe? Think about it. >>Yeah, you can think of it that way. It abstracts away, Dave a couple of things. It takes away the type of data, you know, sort of the complexities related to the type of data. It takes away the complexity related to the size of data. It takes away the complexity related to creating pipelines around all these different types of data and fundamentally puts it in a place where it can be now consumed by any sort of entity inside the actual proposition. And by that token, even data breaks. You know, you can, in fact, use data breaks in in sort off an integrated way with a synapse, Right, >>Well, so that leads me to this notion of and then wonder if you buy into it s Oh, my inference is that a data warehouse or a data lake >>could >>just be a node in inside of a global data >>mesh on. >>Then it's synapses sort of managing, uh, that technology on top. Do you buy into that that global data mesh concept >>we do. And we actually do see our customers using synapse and the value proposition that it brings together in that way. Now it's not where they start. Often times when a customer comes and says, Look, I've got an enterprise data warehouse, I want to migrate it or I have a group system. I want to migrate it. But from there, the evolution is absolutely interesting to see. I give you an example. You know, one of the customers that we're very proud off his FedEx And what FedEx is doing is it's completely reimagining its's logistics system that basically the system that delivers What is it? The three million packages a day on in doing so in this covert times, with the view of basically delivering our covert vaccines. One of the ways they're doing it is basically using synapse. Synapse is essentially that analytic hub where they can get complete view into their logistic processes. Way things are moving, understand things like delays and really put all that together in a way that they can essentially get our packages and these vaccines delivered as quickly as possible. Another example, you know, is one of my favorite, uh, we see once customers buy into it, they essentially can do other things with it. So an example of this is, uh is really my favorite story is Peace Parks Initiative. It is the premier Air White Rhino Conservancy in the world. They essentially are using data that has landed in azure images in particular. So, basically, you know, use drones over the vast area that they patrol and use machine learning on this data to really figure out where is an issue and where there isn't an issue so that this part with about 200 rangers can scramble surgically versus having to read range across the last area that they cover. So What do you see here is you know, the importance is really getting your data in order. Landed consistently. Whatever the kind of data ideas build the right pipelines and then the possibilities of transformation are just endless. >>Yeah, that's very nice how you worked in some of the customer examples. I appreciate that. I wanna ask you, though, that that some people might say that putting in that layer while it clearly adds simplification and e think a great thing that they're begins over time to be be a gap, if you will, between the ability of that layer to integrate all the primitives and all the peace parts on that, that you lose some of that fine grain control and it slows you down. What would you say to that? >>Look, I think that's what we excel at, and that's what we completely sort of buy into on. It's our job to basically provide that level off integration that granularity in the way that so it's an art, absolutely admit it's an art. There are areas where people create simplicity and not a lot of you know, sort of knobs and dials and things like that. But there are areas where customers want flexibility, right? So I think just to give you an example of both of them in landing the data inconsistency in building pipelines, they want simplicity. They don't want complexity. They don't want 50 different places to do this. Just 100 to do it. When it comes to computing and reducing this data analyzing this data, they want flexibility. This is one of the reasons why we say, Hey, listen, you want to use data breaks? If you're you're buying into that proposition and you're absolutely happy with them, you can plug plug it into it. You want to use B I and no, essentially do a small data mart. You can use B I If you say that. Look, I've landed in the lake. I really only want to use em melt, bringing your animal models and party on. So that's where the flexibility comes in. So that's sort of really sort of think about it. Well, >>I like the strategy because, you know, my one of our guest, Jim Octagon, e E. I think one of the foremost thinkers on this notion of off the data mesh and her premises that that that data builders, data product and service builders air frustrated because the the big data system is generic to context. There's no context in there. But by having context in the big data architecture and system, you could get products to market much, much, much faster. So but that seems to be your philosophy. But I'm gonna jump ahead to do my ecosystem question. You've mentioned data breaks a couple of times. There's another partner that you have, which is snowflake. They're kind of trying to build out their own, uh, data cloud, if you will, on global mesh in and the one hand, their partner. On the other hand, there are competitors. How do you sort of balance and square that circle? >>Look, when I see snowflake, I actually see a partner. You know that when we essentially you know, we are. When you think about as you know, this is where I sort of step back and look at Azure as a whole and in azure as a whole. Companies like snowflakes are vital in our ecosystem, right? I mean, there are places we compete, but you know, effectively by helping them build the best snowflake service on Asia. We essentially are able toe, you know, differentiate and offer a differentiated value proposition compared to, say, a Google or on AWS. In fact, that's being our approach with data breaks as well, where you know they are effectively on multiple club, and our opportunity with data breaks is toe essentially integrate them in a way where we offer the best experience. The best integrations on Azure Barna That's always been a focus. >>That's hard to argue with. Strategy. Our data with our data partner eat er, shows Microsoft is both pervasive and impressively having a lot of momentum spending velocity within the budget cycles. I wanna come back thio ai a little bit. It's obviously one of the fastest growing areas in our in our survey data. As I said, clearly, Microsoft is a leader in this space. What's your what's your vision of the future of machine intelligence and how Microsoft will will participate in that opportunity? >>Yeah, so fundamentally, you know, we've built on decades of research around, you know, around, you know, essentially, you know, vision, speech and language that's being the three core building blocks and for the for a really focused period of time we focused on essentially ensuring human parody. So if you ever wondered what the keys to the kingdom are it, czar, it's the most we built in ensuring that the research posture that we've taken there, what we then done is essentially a couple of things we focused on, essentially looking at the spectrum. That is a I both from saying that, Hollis and you know it's gotta work for data. Analysts were looking toe basically use machine learning techniques, toe developers who are essentially, you know, coding and building a machine learning models from scratch. So for that select proposition manifesto us, as you know, really a. I focused on all skill levels. The other court thing we've done is that we've also said, Look, it will only work as long as people trust their data and they can trust their AI models. So there's a tremendous body of work and research we do in things like responsibility. So if you ask me where we sort of push on is fundamentally to make sure that we never lose sight of the fact that the spectrum off a I, and you can sort of come together for any skill level, and we keep that responsibly. I proposition. Absolutely strong now against that canvas, Dave. I'll also tell you that you know, as edge devices get way more capable, right where they can input on the edge, see a camera or a mike or something like that, you will see us pushing a lot more of that capability onto the edge as well. But to me, that's sort of a modality. But the core really is all skill levels and that responsible denia. >>Yeah, So that that brings me to this notion of wanna bring an edge and and hybrid cloud Understand how you're thinking about hybrid cloud multi cloud. Obviously one of your competitors, Amazon won't even say the word multi cloud you guys have, Ah, you know, different approach there. But what's the strategy with regard? Toe, toe hybrid. You know, Do you see the cloud you bringing azure to the edge? Maybe you could talk about that and talk about how you're different from the competition. >>Yeah, I think in the edge from Annette, you know, I live in I'll be the first one to say that the word nge itself is conflated. Okay, It's, uh but I will tell you, just focusing on hybrid. This is one of the places where you know I would say the 2020 if I would have looked back from a corporate perspective. In particular, it has Bean the most informative because we absolutely saw customers digitizing moving to the cloud. And we really saw hybrid in action. 2020 was the year that hybrid sort of really became really from a cloud computing perspective and an example of this is we understood it's not all or nothing. So sometimes customers want azure consistency in their data centers. This is where things like Azure stack comes in. Sometimes they basically come to us and say, We want the flexibility of adopting flexible pattern, you know, platforms like, say, containers orchestra, Cuban Pettis, so that we can essentially deployed wherever you want. And so when we design things like art, it was built for that flexibility in mind. So here is the beauty of what's something like our can do for you. If you have a kubernetes endpoint anywhere we can deploy and as your service onto it, that is the promise, which means if for some reason, the customer says that. Hey, I've got this kubernetes endpoint in AWS and I love as your sequel. You will be able to run as your sequel inside AWS. There's nothing that stops you from doing it so inherently you remember. Our first principle is always to meet our customers where they are. So from that perspective, multi cloud is here to stay. You know, we're never going to be the people that says, I'm sorry, we will never see a But it is a reality for our customers. >>So I wonder if we could close. Thank you for that by looking, looking back and then and then ahead. And I wanna e wanna put forth. Maybe it's, Ah criticism, but maybe not. Maybe it's an art of Microsoft, but But first you know, you get Microsoft an incredible job of transitioning. It's business as your nominee president Azzawi said. Our data shows that so two part question First, Microsoft got there by investing in the cloud, really changing its mind set, I think, in leveraging its huge software state and customer base to put Azure at the center of its strategy, and many have said me included that you got there by creating products that air Good enough. You know, we do a 1.0, it's not that great. And the two Dato, and maybe not the best, but acceptable for your customers. And that's allowed you to grow very rapidly expanding market. >>How >>do you respond to that? Is that is that a fair comment? Ume or than good enough? I wonder if you could share your >>thoughts, gave you? You hurt my feelings with that question. I don't hate me, g getting >>it out there. >>So there was. First of all, thank you for asking me that. You know, I am absolutely the biggest cheerleader. You'll find a Microsoft. I absolutely believe you know that I represent the work off almost 9000 engineers and we wake up every day worrying about our customer and worrying about the customer condition and toe. Absolutely. Make sure we deliver the best in the first time that we do. So when you take the platter off products we've delivered in nausea, be it as your sequel, be it as your cosmos TV synapse as your data breaks, which we did in partnership with data breaks, a za machine learning and recently when we prevail, we sort off, you know, sort of offered the world's first comprehensive data government solution in azure purview. I would humbly submit to you that we're leading the way and we're essentially showing how the future off data ai and the actual work in the cloud. >>I'd be disappointed if you if you had If you didn't, if you capitulated in any way J g So so thank you for that. And the kind of last question is, is looking forward and how you're thinking about the future of cloud last decade. A lot about your cloud migration simplifying infrastructure management, deployment SAS if eyeing my enterprise, lot of simplification and cost savings. And, of course, the redeployment of resource is toward digital transformation. Other other other valuable activities. How >>do >>you think this coming decade will will be defined? Will it be sort of more of the same? Or is there Is there something else out there? >>I think I think that the coming decade will be one where customers start one law outside value out of this. You know what happened in the last decade when people leave the foundation and people essentially looked at the world and said, Look, we've got to make the move, you know, the largely hybrid, but we're going to start making steps to basically digitize and modernize our platforms. I would tell you that with the amount of data that people are moving to the cloud just as an example, you're going to see use of analytics ai for business outcomes explode. You're also going to see a huge sort of focus on things like governance. You know, people need to know where the data is, what the data catalog continues, how to govern it, how to trust this data and given all other privacy and compliance regulations out there. Essentially, they're complying this posture. So I think the unlocking of outcomes versus simply Hey, I've saved money Second, really putting this comprehensive sort off, you know, governance, regime in place. And then, finally, security and trust. It's going to be more paramount than ever before. Yeah, >>nobody's gonna use the data if they don't trust it. I'm glad you brought up your security. It's It's a topic that hits number one on the CEO list. J G. Great conversation. Obviously the strategy is working, and thanks so much for participating in Cuba on cloud. >>Thank you. Thank you, David. I appreciate it and thank you to. Everybody was tuning in today. >>All right? And keep it right there. I'll be back with our next guest right after this short break.

Published Date : Jan 22 2021

SUMMARY :

cloud brought to you by silicon angle. a pure off is the vice president of As Your Data ai and Edge at Microsoft And I just wanna welcome the audience as you know, we're driven by Moore's law. And I think, you know, one of the reasons why And I'm wondering, you know, how do you think about the future of Of So, fundamentally, you know, it is that flexibility that we really sort of focus I want to stick on this for a minute because, you know, I know when when I have guests So I think you know, are sort of differentiated. but to get there, you gotta go through this complex data lifecycle on pipeline and beg people to in the Enterprise today, you have relational systems, you have produced systems. Is that a fair way toe? It takes away the type of data, you know, sort of the complexities related Do you buy into that that global data mesh concept is you know, the importance is really getting your data in order. that you lose some of that fine grain control and it slows you down. So I think just to give you an example of both I like the strategy because, you know, my one of our guest, Jim Octagon, I mean, there are places we compete, but you know, effectively by helping them build It's obviously one of the fastest growing areas in our So for that select proposition manifesto us, as you know, really a. You know, Do you see the cloud you bringing azure to the edge? Cuban Pettis, so that we can essentially deployed wherever you want. Maybe it's an art of Microsoft, but But first you know, you get Microsoft You hurt my feelings with that question. when we prevail, we sort off, you know, sort of offered the world's I'd be disappointed if you if you had If you didn't, if you capitulated in any way J g So Look, we've got to make the move, you know, the largely hybrid, I'm glad you brought up your security. I appreciate it and thank you to. And keep it right there.

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AWS Executive Summit 2020


 

>>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to cube three 60 fives coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight. Today we are joined by a cube alum Karthik NurAin. He is Accenture senior managing director and lead Accenture cloud. First, welcome back to the show Karthik. >>Thank you. Thanks for having me here. >>Always a pleasure. So I want to talk to you. You are an industry veteran, you've been in Silicon Valley for decades. Um, I want to hear from your perspective what the impact of the COVID-19 pandemic has been, what are you hearing from clients? What are they struggling with? What are their challenges that they're facing day to day? >>I think, um, COVID-19 is being a eye-opener from, you know, various facets, you know, um, first and foremost, it's a, it's a head, um, situation that everybody's facing, which is not just, uh, highest economic bearings to it. It has enterprise, um, an organization with bedding to it. And most importantly, it's very personal to people, um, because they themselves and their friends, family near and dear ones are going to this challenge, uh, from various different dimension. But putting that aside, when you come to it from an organization enterprise standpoint, it has changed everything well, the behavior of organizations coming together, working in their campuses, working with each other as friends, family, and, uh, um, near and dear colleagues, all of them are operating differently. So that's what big change to get things done in a completely different way, from how they used to get things done. >>Number two, a lot of things that were planned for normal scenarios, like their global supply chain, how they interact with their client customers, how they coordinate with their partners on how that employees contribute to the success of an organization at all changed. And there are no data models that give them a hint of something like this for them to be prepared for this. So we are seeing organizations, um, that have adapted to this reasonably okay, and are, you know, launching to innovate faster in this. And there are organizations that have started with struggling, but are continuing to struggle. And the gap, uh, between the leaders and legs are widening. So this is creating opportunities in a different way for the leaders, um, with a lot of pivot their business, but it's also creating significant challenge for the lag guides, uh, as we defined in our future systems research that we did a year ago, uh, and those organizations are struggling further. So the gap is actually whitening. >>So you've just talked about the widening gap. I've talked about the tremendous uncertainty that so many companies, even the ones who have adapted reasonably well, uh, in this, in this time, talk a little bit about Accenture cloud first and why, why now? >>I think it's a great question. Um, we believe that for many of our clients COVID-19 has turned, uh, cloud from an experimentation aspiration to an origin mandate. What I mean by that is everybody has been doing something on the other end cloud. There's no company that says we don't believe in cloud. Uh, our, we don't want to do cloud. It was how much they did in cloud. And they were experimenting. They were doing the new things in cloud. Um, but they were operating a lot of their core business outside the cloud or not in the cloud. Those organizations have struggled to operate in this new normal, in a remote fashion as with us, uh, that ability to pivot to all the changes the pandemic has brought to them. But on the other hand, the organizations that had a solid foundation in cloud were able to collect faster and not actually gone into the stage of innovating faster and driving a new behavior in the market, new behavior within their organization. >>So we are seeing that spend to make is actually fast-forwarded something that we always believed was going to happen. This, uh, uh, moving to cloud over the next decade is fast, forwarded it to, uh, happen in the next three to five years. And it's created this moment where it's a once in an era, really replatforming of businesses in the cloud that we are going to see. And we see this moment as a cloud first moment where organizations will use cloud as the, the canvas and the foundation with which they're going to reimagine their business after they were born in the cloud. Uh, and this requires a whole new strategy. Uh, and as Accenture, we are getting a lot in cloud, but we thought that this is the moment where we bring all of that capabilities together because we need a strategy for addressing, moving to cloud are embracing cloud in a holistic fashion. And that's what Accenture cloud first brings together a holistic strategy, a team that's 70,000 plus people that's coming together with rich cloud skills, but investing to tie in all the various capabilities of cloud to Delaware, that holistic strategy to our clients. So I want you to >>Delve into a little bit more about what this strategy actually entails. I mean, it's clearly about embracing change and being willing to experiment and, and having capabilities to innovate. Can you tell us a little bit more about what this strategy entails? >>Yeah. The reason why we say that there's a need for the strategy is, like I said, COVID is not new. There's almost every customer client is doing something with the cloud, but all of them have taken different approaches to cloud and different boundaries to cloud. Some organizations say, I just need to consolidate my multiple data centers to a small data center footprint and move the nest to cloud. Certain other organizations say that well, I'm going to move certain workloads to cloud. Certain other organizations said, well, I'm going to build this Greenfield application or workload in cloud. Certain other said, um, I'm going to use the power of AI ML in the cloud to analyze my data and drive insights. But a cloud first strategy is all of this tied with the corporate strategy of the organization with an industry specific cloud journey to say, if in this current industry, if I were to be reborn in the cloud, would I do it in the exact same passion that I did in the past, which means that the products and services that they offer need to be the matching, how they interact with that customers and partners need to be revisited, how they bird and operate their IP systems need to be the, imagine how they unearthed the data from all the systems under which they attract need to be liberated so that you could drive insights of cloud. >>First strategy. Hans is a corporate wide strategy, and it's a C-suite responsibility. It doesn't take the ownership away from the CIO or CIO, but the CIO is, and CDI was felt that it was just their problem and they were to solve it. And everyone as being a customer, now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's agenda, where probably the CDI is the instrument to execute that that's a holistic cloud-first strategy >>And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, as you were saying, this idea of being reborn in the cloud. So now how do I think about things? How do I communicate? How do I collaborate? How do I get done? What I need to get done. Talk a little bit about how this has changed, the way you support your clients and how Accenture cloud first is changing your approach to cloud services. >>Wonderful. Um, you know, I did not color one very important aspect in my previous question, but that's exactly what you just asked me now, which is to do all of this. I talked about all of the vehicles, uh, an organization or an enterprise is going to go to, but the good part is they have one constant. And what is that? That is their employees, uh, because you do, the employees are able to embrace this change. If they are able to, uh, change them, says, pivot them says retool and train themselves to be able to operate in this new cloud. First one, the ability to reimagine every function of the business would be happening at speed. And cloud first approach is to do all of this at speed, because innovation is deadly proposed there, do the rate of probability on experimentation. You need to experiment a lot for any kind of experimentation. >>There's a probability of success. Organizations need to have an ability and a mechanism for them to be able to innovate faster for which they need to experiment a lot. The more the experiment and the lower cost at which they experiment is going to help them experiment a lot and experiment demic speed, fail fast, succeed more. And hence, they're going to be able to operate this at speed. So the cloud-first mindset is all about speed. I'm helping the clients fast track that innovation journey, and this is going to happen. Like I said, across the enterprise and every function across every department, I'm the agent of this change is going to be the employee's weapon, race, this change through new skills and new grueling and new mindset that they need to adapt to. >>So Karthik what you're describing it, it sounds so exciting. And yet for a pandemic wary workforce, that's been working remotely that may be dealing with uncertainty if for their kid's school and for so many other aspects of their life, it sounds hard. So how are you helping your clients, employees get onboard with this? And because the change management is, is often the hardest part. >>Yeah, I think it's, again, a great question. A bottle has only so much capacity. Something got to come off for something else to go in. That's what you're saying is absolutely right. And that is again, the power of cloud. The reason why cloud is such a fundamental breakthrough technology and capability for us to succeed in this era, because it helps in various forms. What we talked so far is the power of innovation that could create, but cloud can also simplify the life of the employees in an enterprise. There are several activities and tasks that people do in managing their complex infrastructure, complex ID landscape. They used to do certain jobs and activities in a very difficult, uh, underground about with cloud has simplified. And democratised a lot of these activities. So that things which had to be done in the past, like managing the complexity of the infrastructure, keeping them up all the time, managing the, um, the obsolescence of the capabilities and technologies and infrastructure, all of that could be offloaded to the cloud. >>So that the time that is available for all of these employees can be used to further innovate. Every organization is good to spend almost the same amount of money, but rather than spending activities, by looking at the rear view mirror on keeping the lights on, they're going to spend more money, more time, more energy, and spend their skills on things that are going to add value to their organization. Because you, every innovation that an enterprise can give to their end customer need not come from that enterprise. The word of platform economy is about democratising innovation. And the power of cloud is to get all of these capabilities from outside the four walls of the enterprise, >>It will add value to the organization, but I would imagine also add value to that employee's life because that employee, the employee will be more engaged in his or her job and therefore bring more excitement and energy into her, his or her day-to-day activities too. >>Absolutely. Absolutely. And this is, this is a normal evolution we would have seen everybody would have seen in their lives, that they keep moving up the value chain of what activities that, uh, gets performed buying by those individuals. And there's this, um, you know, no more true than how the United States, uh, as an economy has operated where, um, this is the power of a powerhouse of innovation, where the work that's done inside the country keeps moving up to that. You change. And, um, us leverages the global economy for a lot of things that is required to power the United States and that global economic, uh, phenomenon is very proof for an enterprise as well. There are things that an enterprise needs to do them soon. There are things an employee needs to do themselves. Um, but there are things that they could leverage from the external innovation and the power of innovation that is coming from technologies like cloud. >>So at Accenture, you have long, long, deep Stan, sorry, you have deep and long standing relationships with many cloud service providers, including AWS. How does the Accenture cloud first strategy, how does it affect your relationships with those providers? >>Yeah, we have great relationships with cloud providers like AWS. And in fact, in the cloud world, it was one of the first, um, capability that we started about years ago, uh, when we started developing these capabilities. But five years ago, we hit a very important milestone where the two organizations came together and said that we are forging a pharma partnership with joint investments to build this partnership. And we named that as a Accenture, AWS business group ABG, uh, where we co-invest and brought skills together and develop solutions. And we will continue to do that. And through that investment, we've also made several acquisitions that you would have seen in the recent times, like, uh, an invoice and gecko that we made acquisitions in in Europe. But now we're taking this to the next level. What we are saying is two cloud first and the $3 billion investment that we are bringing in, uh, through cloud first, we are going to make specific investment to create unique joint solution and landing zones foundation, um, cloud packs with which clients can accelerate their innovation or their journey to cloud first. >>And one great example is what we are doing with Takeda, uh, billable, pharmaceutical giant, um, between we've signed a five-year partnership. And it was out in the media just a month ago or so, where we are, the two organizations are coming together. We have created a partnership as a power of three partnership where the three organizations are jointly hoarding hats and taking responsibility for the innovation and the leadership position that Decatur wants to get to with this. We are going to simplify their operating model and organization by providing it flexibility. We're going to provide a lot more insights. Tequila has a 230 year old organization. Imagine the amount of trapped data and intelligence that is there. How about bringing all of that together with the power of AWS and Accenture and Takeda to drive more customer insights, um, come up with breakthrough, uh, R and D uh, accelerate clinical trials and improve the patient experience using AI ML and edge technologies. So all of these things that we will do through this partnership with joint investment from Accenture cloud first, as well as partner like AWS, so that Takeda can realize their gain. And, uh, they're seeing you actually made a statement that five years from now, every ticket an employee will have an AI assistant. That's going to make that beginner employee move up the value chain on how they contribute and add value to the future of tequila with the AI assistant, making them even more equipped and smarter than what they could be otherwise. >>So, one last question to close this out here. What is your future vision for, for Accenture cloud first? What are we going to be talking about at next year's Accenture executive summit? Yeah, the future >>Is going to be, um, evolving, but the part that is exciting to me, and this is, uh, uh, a fundamental belief that we are entering a new era of industrial revolution from industry first, second, and third industry. The third happened probably 20 years ago with the advent of Silicon and computers and all of that stuff that happened here in the Silicon Valley. I think the fourth industrial revolution is going to be in the cross section of, uh, physical, digital and biological boundaries. And there's a great article, um, in what economic forum that, that people, uh, your audience can Google and read about it. Uh, but the reason why this is very, very important is we are seeing a disturbing phenomenon that over the last 10 years, they are seeing a Blackwing of the, um, labor productivity and innovation, which has dropped to about 2.1%. When you see that kind of phenomenon over that longer period of time, there has to be breakthrough innovation that needs to happen to come out of this barrier and get to the next base camp, as I would call it to further this productivity, um, lack that we are seeing, and that is going to happen in the intersection of the physical, digital and biological boundaries. >>And I think cloud is going to be the connective tissue between all of these three, to be able to provide that where it's the edge, especially is going to come closer to the human lives. It's going to come from cloud pick totally in your mind, you can think about cloud as central, either in a private cloud, in a data center or in a public cloud, you know, everywhere. But when you think about edge, it's going to be far reaching and coming close to where we live and maybe work and very, um, get entertained and so on and so forth. And there's going to be, uh, intervention in a positive way in the field of medicine, in the field of entertainment, in the field of, um, manufacturing in the field of, um, uh, you know, mobility. When I say mobility, human mobility, people, transportation, and so on and so forth with all of this stuff, cloud is going to be the connective tissue and the vision of cloud first is going to be, uh, you know, blowing through this big change that is going to happen. And the evolution that is going to happen where, you know, the human grace of mankind, um, our person kind of being very gender neutral in today's world. Um, go first needs to be that beacon of, uh, creating the next generation vision for enterprises to take advantage of that kind of an exciting future. And that's why it, Accenture. We say, let there be change as our, as a purpose. >>I genuinely believe that cloud first is going to be in the forefront of that change agenda, both for Accenture as well as for the rest of the world. Excellent. Let there be change, indeed. Thank you so much for joining us Karthik. A pleasure I'm Rebecca night's stay tuned for more of Q3 60 fives coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS >>Welcome everyone to the Q virtual and our coverage of the Accenture executive summit, which is part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the green, the cloud and joining me is Kishor Dirk. He is Accenture senior managing director cloud first global services lead. Thank you so much for coming on the show. Kishor nice to meet you. So I want to start by asking you what it is that we mean when we say green cloud, we know that sustainability is a business imperative. So many organizations around the world are committing to responsible innovation, lowering carbon emissions, but what's this, what is it? What does it mean when they talk about cloud from a sustainability perspective? I think it's about responsible innovation being cloud is a cloud first approach that has profits and benefit the clients by helping reduce carbon emissions. >>Think about it this way. You have a large number of data centers. Each of these data centers are increasing by 14% every year. And this double digit growth. What you're seeing is these data centers and the consumption is nearly coolant to the kind of them should have a country like Spain. So the magnitude of the problem that is out there and how do we pursue a green approach. If you look at this, our Accenture analysis, in terms of the migration to public cloud, we've seen that we can reduce that by 59 million tons of CO2 per year with just the 5.9% reduction in total ID emissions and equates this to 22 million cars off the road. And the magnitude of reduction can go a long way in meeting climate change commitments, particularly for data sensitive. >>Wow, that's incredible. What the numbers that you're putting forward are, are absolutely mind blowing. So how does it work? Is it a simple cloud migration? So, you know, when companies begin their cloud journey and then they confront, uh, with them a lot of questions, the decision to make, uh, this particular, uh, element sustainable in the solution and benefits they drive and they have to make wise choices, and then they will be unprecedented level of innovation leading to both a greener planet, as well as, uh, a greener balance sheet, I would say, uh, so effectively it's all about ambition data, the ambition, greater the reduction in carbon emissions. So from a cloud migration perspective, we look at it as a, as a simple solution with approaches and sustainability benefits, uh, that vary based on things it's about selecting the right cloud provider, a very carbon thoughtful provider and the first step towards a sustainable cloud journey. >>And here we're looking at cloud operators, obviously they have different corporate commitments towards sustainability, and that determines how they plan, how they build, uh, their, uh, uh, the data centers, how they are consumed and assumptions that operate there and how they, or they retire their data centers. Then, uh, the next element that you want to do is how do you build it ambition, you know, for some of the companies, uh, and average on-prem, uh, drives about 65% energy reduction and the carbon emissions and reduction number was 84%, which is kind of good, I would say. But then if you could go up to 98% by configuring applications to the cloud, that is significant benefit for, uh, for the board. And obviously it's a, a greener cloud that we're talking about. And then the question is, how far can you go? And, uh, you know, the, obviously the companies have to unlock greater financial societal environmental benefits, and Accenture has this cloud based circular operations and sustainable products and services that we bring into play. So it's a, it's a very thoughtful, broader approach that w bringing in, in terms of, uh, just a simple concept of cloud migration, >>We know that in the COVID era, shifting to the cloud has really become a business imperative. How is Accenture working with its clients at a time when all of this movement has been accelerated? How do you partner and what is your approach in terms of helping them with their migration? >>Yeah, I mean, let, let me talk a little bit about the pandemic and the crisis that is there today. And if you really look at that in terms of how we partnered with a lot of our clients in terms of the cloud first approach, I'll give you a couple of examples. We worked with rolls Royce, McLaren, DHL, and others, as part of the ventilator challenge consortium, again, to, uh, coordinate production of medical ventilator surgically needed for the UK health service. Many of these farms I've taken similar initiatives in, in terms of, uh, you know, from a few manufacturers hand sanitizers and to hand sanitizers, and again, leading passionate labels, making PPE, and again, at the UN general assembly, we launched the end-to-end integration guide that helps company essentially to have a sustainable development goals. And that's how we have parking at a very large scale. >>Uh, and, and if you really look at how we work with our clients and what is Accenture's role there, uh, you know, from, in terms of our clients, you know, there are multiple steps that we look at. One is about, uh, planning, building, deploying, and managing an optimal green cloud solution. And Accenture has this concept of, uh, helping clients with a platform to kind of achieve that goal. And here we are having, we are having a platform or a mine app, which has a module called BGR advisor. And this is a capability that helps you provide optimal green cloud, uh, you know, a business case, and obviously a blueprint for each of our clients and right from the start in terms of how do we complete cloud migration recommendation to an improved solution, accurate accuracy to obviously bringing in the end to end perspective, uh, you know, with this green card advisor capability, we're helping our clients capture what we call as a carbon footprint for existing data centers and provide, uh, I would say the current cloud CO2 emission score that, you know, obviously helps them, uh, with carbon credits that can further that green agenda. >>So essentially this is about recommending a green index score, reducing carbon footprint for migration migrating for green cloud. And if we look at how Accenture itself is practicing what we preach, 95% of our applications are in the cloud. And this migration has helped us, uh, to lead to about $14.5 million in benefit. And in the third year and another 3 million analytics costs that are saved through right-sizing a service consumption. So it's a very broad umbrella and a footprint in terms of how we engage societaly with the UN or our clients. And what is it that we exactly bring to our clients in solving a specific problem? >>Accenture isn't is walking the walk, as you say yes. >>So that's that instead of it, we practice what we preach, and that is something that we take it to heart. We want to have a responsible business and we want to practice it. And we want to advise our clients around that >>You are your own use case. And so they can, they know they can take your advice. So talk a little bit about, um, the global, the cooperation that's needed. We know that conquering this pandemic is going to take a coordinated global effort and talk a little bit about the great reset initiative. First of all, what is that? Why don't we, why don't we start there and then we can delve into it a little bit more. >>Okay. So before we get to how we are cooperating, the great reset, uh, initiative is about improving the state of the world. And it's about a group of global stakeholders cooperating to simultaneously manage the direct consequences of their COVID-19 crisis. Uh, and in spirit of this cooperation that we're seeing during COVID-19, uh, which will obviously either to post pandemic, to tackle the world's pressing issues. As I say, uh, we are increasing companies to realize a combined potential of technology and sustainable impact to use enterprise solutions, to address with urgency and scale, and, um, obviously, uh, multiple challenges that are facing our world. One of the ways that you're increasing, uh, companies to reach their readiness cloud with Accenture's cloud core strategy is to build a solid foundation that is resilient and will be able to faster to the current, as well as future times. Now, when you think of cloud as the foundation, uh, that drives the digital transformation, it's about scale speed, streamlining your operations, and obviously reducing costs. >>And as these businesses seize the construct of cloud first, they must remain obviously responsible and trusted. Now think about this, right, as part of our analysis, uh, that profitability can co-exist with responsible and sustainable practices. Let's say that all the data centers, uh, migrated from on-prem to cloud based, we estimate that would reduce carbon emissions globally by 60 million tons per year. Uh, and think about it this way, right? Easier metric would be taking out 22 million cars off the road. Um, the other examples that you've seen, right, in terms of the NHS work that they're doing, uh, in, in UK to build, uh, uh, you know, uh, Microsoft teams in based integration. And, uh, the platform rolled out for 1.2 million in interest users, uh, and got 16,000 users that we were able to secure, uh, instant messages, obviously complete audio video calls and host virtual meetings across India. So, uh, this, this work that we did with NHS is something that we have are collaborating with a lot of tools and powering businesses. >>Well, you're vividly describing the business case for sustainability. What do you see as the future of cloud when thinking about it from this lens of sustainability, and also going back to what you were talking about in terms of how you are helping your, your fostering cooperation within these organizations. >>Yeah, that's a very good question. So if you look at today, right, businesses are obviously environmentally aware and they are expanding efforts to decrease power consumption, carbon emissions, and they want to run a sustainable operational efficiency across all elements of their business. And this is an increasing trend, and there is that option of energy efficient infrastructure in the global market. And this trend is the cloud first thinking. And with the right cloud migration that we've been discussing is about unlocking new opportunity, like clean energy foundations enable enabled by cloud based geographic analysis, material, waste reductions, and better data insights. And this is something that, uh, uh, we'll we'll drive, uh, with obviously faster analytics platform that is out there. Now, the sustainability is actually the future of business, which is companies that are historically different, the financial security or agility benefits to cloud. Now sustainability becomes an imperative for them. And I would on expedience Accenture's experience with cloud migrations, we have seen 30 to 40% total cost of ownership savings. And it's driving a greater workload, flexibility, better service, your obligation, and obviously more energy efficient, uh, public clouds that cost we'll see that, that drive a lot of these enterprise own data centers. So in our view, what we are seeing is that this, this, uh, sustainable cloud position helps, uh, helps companies to, uh, drive a lot of the goals in addition to their financial and other goods. >>So what should organizations who are, who are watching this interview and saying, Hey, I need to know more, what, what do you recommend to them? And what, where should they go to get more information on Greenplum? >>No, if you you're, if you are a business leader and you're thinking about which cloud provider is good, or how, how should applications be modernized to meet our day-to-day needs, which cloud driven innovations should be priorities. Uh, you know, that's why Accenture, uh, formed up the cloud first organization and essentially to provide the full stack of cloud services to help our clients become a cloud first business. Um, you know, it's all about excavation, uh, the digital transformation innovating faster, creating differentiated, uh, and sustainable value for our clients. And we're powering it up at 70,000 cloud professionals, $3 billion investment, and, uh, bringing together and services for our clients in terms of cloud solutions. And obviously the ecosystem partnership that we have that we are seeing today, uh, and the assets that help our clients realize their goals. Um, and again, to do reach out to us, uh, we can help them determine obviously, an optimal, sustainable cloud for solution that meets the business needs and being unprecedented levels of innovation. Our experience will be our advantage. And now more than ever, Rebecca, >>Just closing us out here. Do you have any advice for these companies who are navigating a great deal of uncertainty? We, what, what do you think the next 12 to 24 months? What do you think that should be on the minds of CEOs as they go through? >>So, as CEO's are thinking about rapidly leveraging cloud, migrating to cloud, uh, one of the elements that we want them to be thoughtful about is can they do that, uh, with unprecedent level of innovation, but also build a greener planet and a greener balance sheet, if we can achieve this balance and kind of, uh, have a, have a world which is greener, I think the world will win. And we all along with Accenture clients will win. That's what I would say, uh, >>Optimistic outlook. And I will take it. Thank you so much. Kishor for coming on the show >>That was >>Accenture's Kishor Dirk, I'm Rebecca Knight stay tuned for more of the cube virtuals coverage of the Accenture executive summit >>Around the globe. >>It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtual and our coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the power of three. And what happens when you bring together the scientific know-how of a global bias biopharmaceutical powerhouse in Takeda, a leading cloud services provider in AWS, and Accenture's ability to innovate, execute, and deliver innovation. Joining me to talk about these things. We have Aaron, sorry, Arjun, baby. He is the senior managing director and chairman of Accenture's diamond leadership council. Welcome Arjun Karl hick. He is the chief digital and information officer at Takeda. >>What is your bigger, thank you, Rebecca >>And Brian bowhead, global director, and head of the Accenture AWS business group at Amazon web services. Thanks so much for coming on. Thank you. So, as I said, we're talking today about this relationship between, uh, your three organizations. Carl, I want to talk with you. I know you're at the beginning of your cloud journey. What was the compelling reason? What, what, why, why move to the cloud and why now? >>Yeah, no, thank you for the question. So, you know, as a biopharmaceutical leader, we're committed to bringing better health and a brighter future to our patients. We're doing that by translating science into some really innovative and life transporting therapies, but throughout, you know, we believe that there's a responsible use of technology, of data and of innovation. And those three ingredients are really key to helping us deliver on that promise. And so, you know, while I think, uh, I'll call it, this cloud journey is already always been a part of our strategy. Um, and we've made some pretty steady progress over the last years with a number of I'll call it diverse approaches to the digital and AI. We just weren't seeing the impact at scale that we wanted to see. Um, and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and, uh, broaden that shift. >>And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. One of those has been certainly a number of the large acquisitions we've made Shire, uh, being the most pressing example, uh, but also the global pandemic, both of those highlight the need for us to move faster, um, at the speed of cloud, ultimately. Uh, and so we started thinking outside of the box because it was taking us too long and we decided to leverage this strategic partner model. Uh, and it's giving us a chance to think about our challenges very differently. We call this the power of three, uh, and ultimately our focus is singularly on our patients. I mean, they're waiting for us. We need to get there faster. It can take years. And so I think that there is a focus on innovation, um, at a rapid speed, so we can move ultimately from treating conditions to keeping people healthy. >>So as you are embarking on this journey, what are some of the insights you want to share about, about what you're seeing so far? >>Yeah, no, it's a great question. So, I mean, look, maybe right before I highlight some of the key insights, uh, I would say that, you know, with cloud now as the, as the launchpad for innovation, you know, our vision all along has been that in less than 10 years, we want every single to kid, uh, associate we're employed to be empowered by an AI assistant. And I think that, you know, that's going to help us make faster, better decisions. That'll help us, uh, fundamentally deliver transformative therapies and better experiences to, to that ecosystem, to our patients, to physicians, to payers, et cetera, much faster than we previously thought possible. Um, and I think that technologies like cloud and edge computing together with a very powerful I'll call it data fabric is going to help us to create this, this real-time, uh, I'll call it the digital ecosystem. >>The data has to flow ultimately seamlessly between our patients and providers or partners or researchers, et cetera. Uh, and so we've been thinking about this, uh, I'll call it legal, hold up, sort of this pyramid, um, that helps us describe our vision. Uh, and a lot of it has to do with ultimately modernizing the foundation, modernizing and rearchitecting, the platforms that drive the company, uh, heightening our focus on data, which means that there's an accelerated shift towards enterprise data platforms and digital products. And then ultimately, uh, uh, P you know, really an engine for innovation sitting at the very top. Um, and so I think with that, you know, there's a few different, uh, I'll call it insights that, you know, are quickly kind of come zooming into focus. I would say one is this need to collaborate very differently. Um, you know, not only internally, but you know, how do we define ultimately, and build a connected digital ecosystem with the right partners and technologies externally? >>I think the second, uh, component that maybe people don't think as much about, but, you know, I find critically important is for us to find ways of really transforming our culture. We have to unlock talent and shift the culture certainly as a large biopharmaceutical very differently. And then lastly, you've touched on it already, which is, you know, innovation at the speed of cloud. How do we re-imagine that, you know, how do ideas go from getting tested and months to kind of getting tested in days? You know, how do we collaborate very differently? Uh, and so I think those are three, uh, perhaps of the larger I'll call it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. >>So Arjun, I want to bring you into this conversation a little bit. Let's, let's delve into those a bit. Talk first about the collaboration, uh, that Carl was referencing there. How, how have you seen that it is enabling, uh, colleagues and teams to communicate differently and interact in new and different ways? Uh, both internally and externally, as Carl said, >>No, th thank you for that. And, um, I've got to give call a lot of credit, because as we started to think about this journey, it was clear, it was a bold ambition. It was, uh, something that, you know, we had all to do differently. And so the, the concept of the power of three that Carl has constructed has become a label for us as a way to think about what are we going to do to collectively drive this journey forward. And to me, the unique ways of collaboration means three things. The first one is that, um, what is expected is that the three parties are going to come together and it's more than just the sum of our resources. And by that, I mean that we have to bring all of ourselves, all of our collective capabilities, as an example, Amazon has amazing supply chain capabilities. >>They're one of the best at supply chain. So in addition to resources, when we have supply chain innovations, uh, that's something that they're bringing in addition to just, uh, talent and assets, similarly for Accenture, right? We do a lot, uh, in the talent space. So how do we bring our thinking as to how we apply best practices for talent to this partnership? So, um, as we think about this, so that's, that's the first one, the second one is about shared success very early on in this partnership, we started to build some foundations and actually develop seven principles that all of us would look at as the basis for this success shared success model. And we continue to hold that sort of in the forefront, as we think about this collaboration. And maybe the third thing I would say is this one team mindset. So whether it's the three of our CEOs that get together every couple of months to think about, uh, this partnership, or it is the governance model that Carl has put together, which has all three parties in the governance and every level of leadership, we always think about this as a collective group, so that we can keep that front and center. >>And what I think ultimately has enabled us to do is it allowed us to move at speed, be more flexible. And ultimately all we're looking at the target the same way, the North side, the same way. >>Brian, what about you? What have you observed and what are you thinking about in terms of how this is helping teams collaborate differently? >>Yeah, absolutely. And RJ made some, some great points there. And I think if you really think about what he's talking about, it's that, that diversity of talent, diversity of skill and viewpoint and even culture, right? And so we see that in the power of three. And then I think if we drill down into what we see at Takeda, and frankly, Takeda was, was really, I think, pretty visionary and on their way here, right. And taking this kind of cross-functional approach and applying it to how they operate day to day. So moving from a more functional view of the world to more of a product oriented view of the world, right? So when you think about we're going to be organized around a product or a service or a capability that we're going to provide to our customers or our patients or donors in this case, it implies a different structure, although altogether, and a different way of thinking, right? >>Because now you've got technical people and business experts and marketing experts, all working together in this is sort of cross collaboration. And what's great about that is it's really the only way to succeed with cloud, right? Because the old ways of thinking where you've got application people and infrastructure, people in business, people is suboptimal, right? Because we can all access this tool was, and these capabilities and the best way to do that, isn't across kind of a cross collaborative way. And so this is product oriented mindset. It's a keto was already on. I think it's allowed us to move faster in those areas. >>Carl, I want to go back to this idea of unlocking talent and culture. And this is something that both Brian and Arjun have talked about too. People are, are an essential part of their, at the heart of your organization. How will their experience of work change and how are you helping re-imagine and reinforce a strong organizational culture, particularly at this time when so many people are working remotely. >>Yeah. It's a great question. And it's something that, you know, I think we all have to think a lot about, I mean, I think, um, you know, driving this, this call it, this, this digital and data kind of capability building, uh, takes a lot of, a lot of thinking. So, I mean, there's a few different elements in terms of how we're tackling this one is we're recognizing, and it's not just for the technology organization or for those actors that, that we're innovating with, but it's really across all of the Cato where we're working through ways of raising what I'll call the overall digital leaders literacy of the organization, you know, what are the, you know, what are the skills that are needed almost at a baseline level, even for a global bio-pharmaceutical company and how do we deploy, I'll call it those learning resources very broadly. >>And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are very specialized skills that are needed. Uh, my organization is one of those. And so, you know, we're fostering ways in which, you know, we're very kind of quickly kind of creating, uh, avenues excitement for, for associates in that space. So one example specifically, as we use, you know, during these very much sort of remote, uh, sort of days, we, we use what we call global it days, and we set a day aside every single month and this last Friday, um, you know, we, we create during that time, it's time for personal development. Um, and we provide active seminars and training on things like, you know, robotic process automation, data analytics cloud, uh, in this last month we've been doing this for months and months now, but in his last month, more than 50% of my organization participated, and there's this huge positive shift, both in terms of access and excitement about really harnessing those new skills and being able to apply them. >>Uh, and so I think that that's, you know, one, one element that, uh, can be considered. And then thirdly, um, of course, every organization to work on, how do you prioritize talent, acquisition and management and competencies that you can't rescale? I mean, there are just some new capabilities that we don't have. And so there's a large focus that I have with our executive team and our CEO and thinking through those critical roles that we need to activate in order to kind of, to, to build on this, uh, this business led cloud transformation. And lastly, probably the hardest one, but the one that I'm most jazzed about is really this focus on changing the mindsets and behaviors. Um, and I think there, you know, this is where the power of three is, is really, uh, kind of coming together nicely. I mean, we're working on things like, you know, how do we create this patient obsessed curiosity, um, and really kind of unlock innovation with a real, kind of a growth mindset. >>Uh, and the level of curiosity that's needed, not to just continue to do the same things, but to really challenge the status quo. So that's one big area of focus we're having the agility to act just faster. I mean, to worry less, I guess I would say about kind of the standard chain of command, but how do you make more speedy, more courageous decisions? And this is places where we can emulate the way that a partner like AWS works, or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently to a number of partnerships that we can build. So we can break down some of these barriers and use these networks, um, whether it's within our own internal ecosystem or externally to help, to create value faster. So a lot of energy around ways of working and we'll have to check back in, but I mean, we're early in on this mindset and behavioral shift, um, but a lot of good early momentum. >>Carl you've given me a good segue to talk to Brian about innovation, because you said a lot of the things that I was the customer obsession and this idea of innovating much more quickly. Obviously now the world has its eyes on drug development, and we've all learned a lot about it, uh, in the past few months and accelerating drug development is all, uh, is of great interest to all of us. Brian, how does a transformation like this help a company's, uh, ability to become more agile and more innovative and at a quicker speed to, >>Yeah, no, absolutely. And I think some of the things that Carl talked about just now are critical to that, right? I think where sometimes folks fall short is they think, you know, we're going to roll out the technology and the technology is going to be the silver bullet where we're, in fact it is the culture. It is, is the talent. And it's the focus on that. That's going to be, you know, the determinant of success. And I will say, you know, in this power of three arrangement and Carl talked a little bit about the pyramid, um, talent and culture and that change, and the kind of thinking about that has been a first-class citizen since the very beginning, right. That absolutely is critical for, for being there. Um, and, and so that's been, that's been key. And so we think about innovation at Amazon and AWS, and Carl mentioned some of the things that, you know, partner like AWS can bring to the table is we talk a lot about builders, right? >>So kind of obsessive about builders. Um, and, and we meet what we mean by that is we at Amazon, we hire for builders, we cultivate builders and we like to talk to our customers about it as well. And it also implies a different mindset, right? When you're a builder, you have that, that curiosity, you have that ownership, you have that stake in whatever I'm creating, I'm going to be a co-owner of this product or this service, right. Getting back to that kind of product oriented mindset. And it's not just the technical people or the it people who are builders. It is also the business people as, as Carl talked about. Right. So when we start thinking about, um, innovation again, where we see folks kind of get into a little bit of a innovation pilot paralysis, is that you can focus on the technology, but if you're not focusing on the talent and the culture and the processes and the mechanisms, you're going to be putting out technology, but you're not going to have an organization that's ready to take it and scale it and accelerate it. >>Right. And so that's, that's been absolutely critical. So just a couple of things we've been doing with, with Takeda and Decatur has really been leading the way is, think about a mechanism and a process. And it's really been working backward from the customer, right? In this case, again, the patient and the donor. And that was an easy one because the key value of Decatur is to be a patient focused bio-pharmaceutical right. So that was embedded in their DNA. So that working back from that, that patient, that donor was a key part of that process. And that's really deep in our DNA as well. And Accenture's, and so we were able to bring that together. The other one is, is, is getting used to experimenting and even perhaps failing, right. And being able to iterate and fail fast and experiment and understanding that, you know, some decisions, what we call it at Amazon or two-way doors, meaning you can go through that door, not like what you see and turn around and go back. And cloud really helps there because the costs of experimenting and the cost of failure is so much lower than it's ever been. You can do it much faster and the implications are so much less. So just a couple of things that we've been really driving, uh, with the cadence around innovation, that's been really critical. Carl, where are you already seeing signs of success? >>Yeah, no, it's a great question. And so we chose, you know, uh, with our focus on innovation to try to unleash maybe the power of data digital in, uh, in focusing on what I call sort of a Maven. And so we chose our, our, our plasma derived therapy business, um, and you know, the plasma-derived therapy business unit, it develops critical life-saving therapies for patients with rare and complex diseases. Um, but what we're doing is by bringing kind of our energy together, we're focusing on creating, I'll call it state of the art digitally connected donation centers. And we're really modernizing, you know, the, the, the donor experience right now, we're trying to, uh, improve also I'll call it the overall plasma collection process. And so we've, uh, selected a number of alcohol at a very high speed pilots that we're working through right now, specifically in this, in this area. And we're seeing >>Really great results already. Um, and so that's, that's one specific area of focus are Jen, I want you to close this out here. Any ideas, any best practices advice you would have for other pharmaceutical companies that are, that are at the early stage of their cloud journey? Yes. Sorry. Arjun. >>Yeah, no, I was breaking up a bit. No, I think they, um, the key is what what's sort of been great for me to see is that when people think about cloud, you know, you always think about infrastructure technology. The reality is that the cloud is really the true enabler for innovation and innovating at scale. And, and if you think about that, right, in all the components that you need, uh, ultimately that's where the value is for the company, right? Because yes, you're going to get some cost synergies and that's great, but the true value is in how do we transform the organization in the case of the Qaeda and the life sciences clients, right. We're trying to take a 14 year process of research and development that takes billions of dollars and compress that right. Tremendous amounts of innovation opportunity. You think about the commercial aspect, lots of innovation can come there. The plasma derived therapy is a great example of how we're going to really innovate to change the trajectory of that business. So I think innovation is at the heart of what most organizations need to do. And the formula, the cocktail that Takeda has constructed with this Fuji program really has all the ingredients, um, that are required for that success. >>Great. Well, thank you so much. Arjun, Brian and Carl was really an enlightening conversation. >>Thank you. Yeah, it's been fun. Thanks Rebecca. >>And thank you for tuning into the cube. Virtual is coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of Accenture executive summit here at AWS reinvent. I'm your host Rebecca Knight for this segment? We have two guests. First. We have Helen Davis. She is the senior director of cloud platform services, assistant director for it and digital for the West Midlands police. Thanks so much for coming on the show, Helen, and we also have Matthew lb. He is Accenture health and public service associate director and West Midlands police account lead. Thanks so much for coming on the show. Matthew, thank you for joining us. So we are going to be talking about delivering data-driven insights to the West Midlands police force. Helen, I want to start with >>You. Can you tell us a little bit about the West Midlands police force? How big is the force and also what were some of the challenges that you were grappling with prior to this initiative? >>Yeah, certainly. So Westerners police is the second largest police force in the UK, outside of the metropolitan police in London. Um, we have an excessive, um, 11,000 people work at Westman ins police serving communities, um, through, across the Midlands region. So geographically, we're quite a big area as well, as well as, um, being population, um, density, having that as a, at a high level. Um, so the reason we sort of embarked on the data-driven insights platform and it, which was a huge change for us was for a number of reasons. Um, namely we had a lot of disparate data, um, which was spread across a range of legacy systems that were many, many years old, um, with some duplication of what was being captured and no single view for offices or, um, support staff. Um, some of the access was limited. You have to be in a, in an actual police building on a desktop computer to access it. Um, other information could only reach the offices on the front line, through a telephone call back to one of our enabling services where they would do a manual checkup, um, look at the information, then call the offices back, um, and tell them what they needed to know. So it was a very long laborious, um, process and not very efficient. Um, and we certainly weren't exploiting the data that we had in a very productive way. >>So it sounds like as you're describing, and I'm old clunky system that needed a technological, uh, reimagination. So what was the main motivation for, for doing, for making this shift? >>It was really, um, about making us more efficient and more effective in how we do how we do business. So, um, you know, certainly as a, as an it leader and some of my operational colleagues, we recognize the benefits, um, that data analytics could bring in, uh, in a policing environment, not something that was, um, really done in the UK at the time. You know, we have a lot of data, so we're very data rich and the information that we have, but we needed to turn it into information that was actionable. So that's where we started looking for, um, technology partners and suppliers to help us and sort of help us really with what's the art of the possible, you know, this hasn't been done before. So what could we do in this space? That's appropriate, >>Helen. I love that idea. What is the art of the possible, can you tell us a little bit about why you chose AWS? >>I think really, you know, as with all things and when we're procuring a partner in the public sector that, you know, there are many rules and regulations quite rightly as you would expect that to be because we're spending public money. So we have to be very, very careful and, um, it's, it's a long process and we have to be open to public scrutiny. So, um, we sort of look to everything, everything that was available as part of that process, but we recognize the benefits that Clyde would provide in this space because, you know, we're like moving to a cloud environment. We would literally be replacing something that was legacy with something that was a bit more modern. Um, that's not what we wanted to do. Our ambition was far greater than that. So I think, um, in terms of AWS, really, it was around scalability, interoperability, you know, just us things like the disaster recovery service, the fact that we can scale up and down quickly, we call it dialing up and dialing back. Um, you know, it's it's page go. So it just sort of ticked all the boxes for us. And then we went through the full procurement process, fortunately, um, it came out on top for us. So we were, we were able to move forward, but it just sort of had everything that we were looking for in that space. >>Matthew, I want to bring you into the conversation a little bit here. How are you working with a wet with the West Midlands police, sorry. And helping them implement this cloud-first >>Yeah, so I guess, um, by January the West Midlands police started, um, favorite five years ago now. So, um, we set up a partnership with the fools. I wanted to operate in a way that was very different to a traditional supplier relationship. Um, secretary that the data difference insights program is, is one of many that we've been working with last on, um, over the last five years, um, as having said already, um, cloud gave a number of, uh, advantages certainly from a big data perspective and things that, that enabled us today. Um, I'm from an Accenture perspective that allowed us to bring in a number of the different teams that we have say, cloud teams, security teams, um, and drafted from an insurance perspective, as well as the more traditional services that people would associate with the country. >>I mean, so much of this is about embracing comprehensive change to experiment and innovate and try different things. Matthew, how, how do you help, uh, an entity like West Midlands police think differently when they are, there are these ways of doing things that people are used to, how do you help them think about what is the art of the possible, as Helen said, >>There's a few things to that enable those being critical is trying to co-create solutions together. Yeah. There's no point just turning up with, um, what we think is the right answer, try and say, um, collectively work three, um, the issues that the fullest is seeing and the outcomes they're looking to achieve rather than simply focusing on a long list of requirements, I think was critical and then being really open to working together to create the right solution. Um, rather than just, you know, trying to pick something off the shelf that maybe doesn't fit the forces requirements in the way that it should too, >>Right. It's not always a one size fits all. >>Obviously, you know, today what we believe is critical is making sure that we're creating something that met the forces needs, um, in terms of the outcomes they're looking to achieve the financial envelopes that were available, um, and how we can deliver those in a, uh, iterative agile way, um, rather than spending years and years, um, working towards an outcome, um, that is gonna update before you even get that. >>So Helen, how, how are things different? What kinds of business functions and processes have been re-imagined in, in light of this change and this shift >>It's, it's actually unrecognizable now, um, in certain areas of the business as it was before. So to give you a little bit of, of context, when we, um, started working with essentially an AWS on the data driven insights program, it was very much around providing, um, what was called locally, a wizzy tool for our intelligence analyst to interrogate data, look at data, you know, decide whether they could do anything predictive with it. And it was very much sort of a back office function to sort of tidy things up for us and make us a bit better in that, in that area or a lot better in that area. And it was rolled out to a number of offices, a small number on the front line. Um, and really it was, um, in line with a mobility strategy that we, hardware officers were getting new smartphones for the first time, um, to do sort of a lot of things on, on, um, policing apps and things like that to again, to avoid them, having to keep driving back to police stations, et cetera. >>And the pilot was so successful. Every officer now has access to this data, um, on their mobile devices. So it literally went from a handful of people in an office somewhere using it to do sort of clever whizzbang things to, um, every officer in the force, being able to access that level of data at their fingertips. Literally. So what they were touched we've done before is if they needed to check and address or check details of an individual, um, just as one example, they would either have to, in many cases, go back to a police station to look it up themselves on a desktop computer. Well, they would have to make a call back to a centralized function and speak to an operator, relay the questions, either, wait for the answer or wait for a call back with the answer when those people are doing the data interrogation manually. >>So the biggest change for us is the self-service nature of the data we now have available. So officers can do it themselves on their phone, wherever they might be. So the efficiency savings from that point of view are immense. And I think just parallel to that is the quality of our, because we had a lot of data, but just because you've got a lot of data and a lot of information doesn't mean it's big data and it's valuable necessarily. Um, so again, it was having the single source of truth as we, as we call it. So you know that when you are completing those safe searches and getting the responses back, that it is the most accurate information we hold. And also you're getting it back within minutes, as opposed to, you know, half an hour, an hour or a drive back to a station. So it's making officers more efficient and it's also making them safer. The more efficient they are, the more time they have to spend out with the public doing what they, you know, we all should be doing, >>Seen that kind of return on investment, because what you were just describing with all the steps that we needed to be taken in prior to this, to verify an address say, and those are precious seconds when someone's life is on the line in, in sort of in the course of everyday police work. >>Absolutely. Yeah, absolutely. It's difficult to put a price on it. It's difficult to quantify. Um, but all the, you know, the minutes here and that certainly add up to a significant amount of efficiency savings, and we've certainly been able to demonstrate the officers are spending less time up police stations as a result or more time out on the front frontline also they're safer because they can get information about what may or may not be and address what may or may not have occurred in an area before very, very quickly without having to wait. >>Thank you. I want to hear your observations of working so closely with this West Midlands police. Have you noticed anything about changes in its culture and its operating model in how police officers interact with one another? Have you seen any changes since this technology change? >>What's unique about the Western new misplaces, the buy-in from the top down, the chief and his exact team and Helen as the leader from an IOT perspective, um, the entire force is bought in. So what is a significant change program? Uh, I'm not trickles three. Um, everyone in the organization, um, change is difficult. Um, and there's a lot of time effort. That's been put into both the technical delivery and the business change and adoption aspects around each of the projects. Um, but you can see the step change that is making in each aspect to the organization, uh, and where that's putting West Midlands police as a leader in, um, technology I'm policing in the UK. And I think globally, >>And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain intransigence in workplaces about this is just the way we've always done things and we're used to this and don't try us to get us. Don't try to get us to do anything new here. It works. How do you get the buy-in that you need to do this kind of digital transformation? >>I think it, it would be wrong to say it was easy. Um, um, we also have to bear in mind that this was one program in a five-year program. So there was a lot of change going on, um, both internally for some of our back office functions, as well as front Tai, uh, frontline offices. So with DDI in particular, I think the stat change occurred when people could see what it could do for them. You know, we had lots of workshops and seminars where we all talk about, you know, big data and it's going to be great and it's data analytics and it's transformational, you know, and quite rightly people that are very busy doing a day job that not necessarily technologists in the main and, you know, are particularly interested quite rightly so in what we are not dealing with the cloud, you know? >>And it was like, yeah, okay. It's one more thing. And then when they started to see on that, on their phones and what teams could do, that's when it started to sell itself. And I think that's when we started to see, you know, to see the stat change, you know, and, and if we, if we have any issues now it's literally, you know, our help desks in meltdown. Cause everyone's like, well, we call it manage without this anymore. And I think that speaks for itself. So it doesn't happen overnight. It's sort of incremental changes and then that's a step change in attitude. And when they see it working and they see the benefits, they want to use it more. And that's how it's become fundamental to all policing by itself, really, without much selling >>You, Helen just made a compelling case for how to get buy in. Have you discovered any other best practices when you are trying to get everyone on board for this kind of thing? >>We've um, we've used a lot of the traditional techniques, things around comms and engagement. We've also used things like, um, the 30 day challenge and nudge theory around how can we gradually encourage people to use things? Um, I think there's a point where all of this around, how do we just keep it simple and keep it user centric from an end user perspective? I think DDI is a great example of where the, the technology is incredibly complex. The solution itself is, um, you know, extremely large and, um, has been very difficult to, um, get delivered. But at the heart of it is a very simple front end for the user to encourage it and take that complexity away from them. Uh, I think that's been critical through the whole piece of DDR. >>One final word from Helen. I want to hear, where do you go from here? What is the longterm vision? I know that this has made productivity, um, productivity savings equivalent to 154 full-time officers. Uh, what's next, >>I think really it's around, um, exploiting what we've got. Um, I use the phrase quite a lot, dialing it up, which drives my technical architects crazy. But so, because it's apparently not that simple, but, um, you know, we've, we've been through significant change in the last five years and we are still continuing to batch all of those changes into everyday, um, operational policing. But what we need to see is we need to exploit and build on the investments that we've made in terms of data and claims specifically, the next step really is about expanding our pool of data and our functions. Um, so that, you know, we keep getting better and better at this. And the more we do, the more data we have, the more refined we can be, the more precise we are with all of our actions. Um, you know, we're always being expected to, again, look after the public purse and do more for less. >>And I think this is certainly an and our cloud journey and, and cloud first by design, which is where we are now, um, is helping us to be future-proofed. So for us, it's very much an investment. And I see now that we have good at embedded in operational policing for me, this is the start of our journey, not the end. So it's really exciting to see where we can go from here. Exciting times. Indeed. Thank you so much. Lily, Helen and Matthew for joining us. I really appreciate it. Thank you. And you are watching the cube stay tuned for more of the cubes coverage of the AWS reinvent Accenture executive summit. I'm Rebecca Knight from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to the cube virtual coverage of the executive summit at AWS reinvent 2020 virtual. This is the cube virtual. We can't be there in person like we are every year we have to be remote. This executive summit is with special programming supported by Accenture where the cube virtual I'm your host John for a year, we had a great panel here called uncloud first digital transformation from some experts, Stuart driver, the director of it and infrastructure and operates at lion Australia, Douglas Regan, managing director, client account lead at lion for Accenture as a deep Islam associate director application development lead for Centure gentlemen, thanks for coming on the cube virtual that's a mouthful, all that digital, but the bottom line it's cloud transformation. This is a journey that you guys have been on together for over 10 years to be really a digital company. Now, some things have happened in the past year that kind of brings all this together. This is about the next generation organization. So I want to ask Stuart you first, if you can talk about this transformation at lion has undertaken some of the challenges and opportunities and how this year in particular has brought it together because you know, COVID has been the accelerant of digital transformation. Well, if you're 10 years in, I'm sure you're there. You're in the, uh, on that wave right now. Take a minute to explain this transformation journey. >>Yeah, sure. So a number of years back, we, we looked at kind of our infrastructure in our landscape trying to figure out where we >>Wanted to go next. And we were very analog based and stuck in the old it groove of, you know, Capitol reef rash, um, struggling to transform, struggling to get to a digital platform and we needed to change it up so that we could become very different business to the one that we were back then obviously cloud is an accelerant to that. And we had a number of initiatives that needed a platform to build on. And a cloud infrastructure was the way that we started to do that. So we went through a number of transformation programs that we didn't want to do that in the old world. We wanted to do it in a new world. So for us, it was partnering up with a dried organizations that can take you on the journey and, uh, you know, start to deliver bit by bit incremental progress, uh, to get to the, uh, I guess the promise land. >>Um, we're not, not all the way there, but to where we're on the way along. And then when you get to some of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually change pretty quickly, um, provide capacity and, uh, and increase your environments and, you know, do the things that you need to do in a much more dynamic way than we would have been able to previously where we might've been waiting for the hardware vendors, et cetera, to deliver capacity. So for us this year, it's been a pretty strong year from an it perspective and delivering for the business needs >>Before I hit the Douglas. I want to just real quick, a redirect to you and say, you know, if all the people said, Oh yeah, you got to jump on cloud, get in early, you know, a lot of naysayers like, well, wait till to mature a little bit, really, if you got in early and you, you know, paying your dues, if you will taking that medicine with the cloud, you're really kind of peaking at the right time. Is that true? Is that one of the benefits that comes out of this getting in the cloud? Yeah, >>John, this has been an unprecedented year, right. And, um, you know, Australia, we had to live through Bush fires and then we had covert and, and then we actually had to deliver a, um, a project on very nice transformational project, completely remote. And then we also had had some, some cyber challenges, which is public as well. And I don't think if we weren't moved into and enabled through the cloud, we would have been able to achieve that this year. It would have been much different and would have been very difficult to do the backing. We're able to work and partner with Amazon through this year, which is unprecedented and actually come out the other end and we've delivered a brand new digital capability across the entire business. Um, in many, you know, wouldn't have been impossible if we could, I guess, stayed in the old world. The fact that we were moved into the new Naval by the new allowed us to work in this unprecedented year. >>Just quilt. What's your personal view on this? Because I've been saying on the Cuban reporting necessity is the mother of all invention and the word agility has been kicked around as kind of a cliche, Oh, it'd be agile. You know, we're going to get the city, you get a minute on specifically, but from your perspective, uh, Douglas, what does that mean to you? Because there is benefits there for being agile. And >>I mean, I think as Stuart mentioned, right, in a lot of these things we try to do and, you know, typically, you know, hardware and, uh, the last >>To be told and, and, and always on the critical path to be done, we really didn't have that in this case, what we were doing with our projects in our deployments, right. We were able to move quickly able to make decisions in line with the business and really get things going. Right. So you see a lot of times in a traditional world, you have these inhibitors, you have these critical path, it takes weeks and months to get things done as opposed to hours and days, and, and truly allowed us to, we had to, you know, VJ things, move things. And, you know, we were able to do that in this environment with AWS to support and the fact that they can kind of turn things off and on as quickly as we needed. >>Yeah. Cloud-scale is great for speed. So DECA, Gardez get your thoughts on this cloud first mission, you know, it, you know, the dev ops world, they saw this early, that jumping in there, they saw the, the, the agility. Now the theme this year is modern applications with the COVID pandemic pressure, there's real business pressure to make that happen. How did you guys learn to get there fast? And what specifically did you guys do at Accenture and how did it all come together? Can you take us inside kind of how it played out? >>Right. So, yeah, we started off with, as we do in most cases with a much more bigger group, and we worked with lions functional experts and, uh, the lost knowledge that allowed the infrastructure had. Um, we then applied our journey to cloud strategy, which basically revolves around the seminars and, and, uh, you know, the deep three steps from our perspective, uh, assessing the current and bottom and setting up the new cloud environment. And as we go modernizing and, and migrating these applications to the cloud now, you know, one of the key things that, uh, you know, we learned along this journey was that, you know, you can have the best plans, but bottom line that we were dealing with, we often than not have to make changes, uh, what a lot of agility and also work with a lot of collaboration with the, uh, lion team, as well as, uh, uh, AWS. I think the key thing for me was being able to really bring it all together. It's not just, uh, you know, we want to hear it's all of us working together to make this happen. >>What were some of the learnings real quick journey there? >>So I think perspective, the key learnings were that, you know, uh, you know, work, when you look back at, uh, the, the infrastructure that was that we were trying to migrate over to the cloud. A lot of the documentation, et cetera, was not, uh, available. We were having to, uh, figure out a lot of things on the fly. Now that really required us to have, uh, uh, people with deep expertise who could go into those environments and, and work out, uh, you know, the best ways to, to migrate the workloads to the cloud. Uh, I think, you know, the, the biggest thing for me was making sure all the had on that real SMEs across the board globally, that we could leverage across the various technologies, uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment with line. >>Let's do what I got to ask you. How did you address your approach to the cloud and what was your experience? >>Yeah, for me, it's around getting the foundations right. To start with and then building on them. Um, so, you know, you've got to have your, your, your process and you've got to have your, your kind of your infrastructure there and your blueprints ready. Um, AWS do a great job of that, right. Getting the foundations right. And then building upon it, and then, you know, partnering with Accenture allows you to do that very successfully. Um, I think, um, you know, the one thing that was probably surprising to us when we started down this journey and kind of after we got a long way down the track and looking backwards is actually how much you can just turn off. Right? So a lot of stuff that you, uh, you get electric with a legacy in your environment, and when you start to work through it with the types of people that civic just mentioned, you know, the technical expertise working with the business, um, you can really rationalize your environment and, uh, you know, cloud is a good opportunity to do that, to drive that legacy out. >>Um, so you know, a few things there, the other thing is, um, you've got to try and figure out the benefits that you're going to get out of moving here. So there's no point in just taking something that is not delivering a huge amount of value in the traditional world, moving it into the cloud, and guess what is going to deliver the same limited amount of value. So you've got to transform it, and you've got to make sure that you build it for the future and understand exactly what you're trying to gain out of it. So again, you need a strong collaboration. You need a good partners to work with, and you need good engagement from the business as well, because the kind of, uh, you know, digital transformation, cloud transformation, isn't really an it project, I guess, fundamentally it is at the core, but it's a business project that you've got to get the whole business aligned on. You've got to make sure that your investment streams are appropriate and that's, uh, you're able to understand the benefits and the value that say, you're going to drive back towards the business. >>Let's do it. If you don't mind me asking, what was some of the obstacles you encountered or learnings, um, that might different from the expectation we all been there, Hey, you know, we're going to change the world. Here's the sales pitch, here's the outcome. And then obviously things happen, you know, you learn legacy, okay. Let's put some containerization around that cloud native, um, all that rational. You're talking about what are, and you're going to have obstacles. That's how you learn. That's how perfection has developed. How, what obstacles did you come up with and how are they different from your expectations going in? >>Yeah, they're probably no different from other people that have gone down the same journey. If I'm totally honest, the, you know, 70 or 80% of what you do is relatively easy of the known quantity. It's relatively modern architectures and infrastructures, and you can upgrade, migrate, move them into the cloud, whatever it is, rehost, replatform, rearchitect, whatever it is you want to do, it's the other stuff, right? It's the stuff that always gets left behind. And that's the challenge. It's, it's getting that last bit over the line and making sure that you haven't been invested in the future while still carrying all of your legacy costs and complexity within your environment. So, um, to be quite honest, that's probably taken longer and has been more of a challenge than we thought it would be. Um, the other piece I touched on earlier on in terms of what was surprising was actually how much of, uh, your environment is actually not needed anymore. >>When you start to put a critical eye across it and understand, um, uh, ask the tough questions and start to understand exactly what, what it is you're trying to achieve. So if you ask a part of a business, do they still need this application or this service a hundred percent of the time, they will say yes until you start to lay out to them, okay, now I'm going to cost you this to migrate it or this, to run it in the future. And, you know, here's your ongoing costs and, you know, et cetera, et cetera. And then, uh, for a significant amount of those answers, you get a different response when you start to layer on the true value of it. So you start to flush out those hidden costs within the business, and you start to make some critical decisions as a company based on, uh, based on that. So that was a little tougher than we first thought and probably broader than we thought there was more of that than we anticipated, um, which actually results in a much cleaner environment, post post migration, >>You know, the old expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value Stuart and Siddique. Mainly if you can weigh in on this love to know the percentage of total cloud that you have now, versus when you started, because as you start to uncover whether it's by design for purpose, or you discover opportunity to innovate, like you guys have, I'm sure it kind of, you took on some territory inside Lyon, what percentage of cloud now versus start? >>Yeah. And at the start it was minimal, right. You know, close to zero, right. Single and single digits. Right. It was mainly SAS environments that we had, uh, sitting in clouds when we, uh, when we started, um, Doug mentioned earlier on a really significant transformation project, um, that we've undertaken and recently gone live on a multi-year one. Um, you know, that's all stood up on AWS and is a significant portion of our environment, um, in terms of what we can move to cloud. Uh, we're probably at about 80 or 90% now. And the balance bit is, um, legacy infrastructure that is just going to retire as we go through the cycle rather than migrate to the cloud. Um, so we are significantly cloud-based and, uh, you know, we're reaping the benefits of it in a year, like 2020, and makes you glad that you did all of the hard yards in the previous years when you started that business challenges thrown out as, >>So do you any common reaction still the cloud percentage penetration? >>Sorry, I didn't, I didn't guys don't, but I, I was going to say it was, I think it's like the 80 20 rule, right? We, we, we worked really hard in the, you know, I think 2018, 19 to get any person off, uh, after getting onto the cloud and, or the last year is the 20% that we have been migrating. And Stuart said like a non-athlete that is also, that's going to be the diet. And I think our next big step is going to be obviously, you know, the icing on the cake, which is to decommission all these apps as well. Right. So, you know, to get the real benefits out of, uh, the whole conservation program from a, uh, from a >>Douglas and Stewart, can you guys talk about the decision around the cloud because you guys have had success with AWS, why AWS how's that decision made? Can you guys give some insight into some of those thoughts? >>I can, I can start, start off. I think back when the decision was made and it was, Oh, it was a while back, um, you know, there's some clear advantages of moving relay, Ws, a lot of alignment with some of the significant projects and, uh, the trend, that particular one big transformation project that we've alluded to as well. Um, you know, we needed some, um, some very robust and, um, just future proof and, um, proven technology. And AWS gave that to us. We needed a lot of those blueprints to help us move down the path. We didn't want to reinvent everything. So, um, you know, having a lot of that legwork done for us and an AWS gives you that, right. And particularly when you partner up with, uh, with a company like Accenture as well, you get combinations of the technology and the skills and the knowledge to, to move you forward in that direction. >>So, um, you know, for us, it was a, uh, uh, it was a decision based on, you know, best of breed, um, you know, looking forward and, and trying to predict the future needs and, and, and kind of the environmental that we might need. Um, and, you know, partnering up with organizations that can take you on the journey. Yeah. And just to build on it. So obviously, you know, lion's like an NWS, but, you know, we knew it was a very good choice given that, um, uh, the skills and the capability that we had, as well as the assets and tools we had to get the most out of, um, out of AWS. And obviously our, our CEO globally is just spending, you know, announcement about a huge investment that we're making in cloud. Um, but you know, we've, we've worked very well. AWS, we've done some joint workshops and joint investments, um, some joint POC. So yeah, w we have a very good working relationship, AWS, and I think, um, one incident to reflect upon whether it's cyber it's and again, where we actually jointly, you know, dove in with, um, with Amazon and some of their security experts and our experts. And we're able to actually work through that with mine quite successful. So, um, you know, really good behaviors as an organization, but also really good capabilities. >>Yeah. As you guys, you're essential cloud outcomes, research shown, it's the cycle of innovation with the cloud. That's creating a lot of benefits, knowing what you guys know now, looking back certainly COVID is impacted a lot of people kind of going through the same process, knowing what you guys know now, would you advocate people to jump on this transformation journey? If so, how, and what tweaks they make, which changes, what would you advise? >>Uh, I might take that one to start with. Um, I hate to think where we would have been when, uh, COVID kicked off here in Australia and, you know, we were all sent home, literally were at work on the Friday, and then over the weekend. And then Monday, we were told not to come back into the office and all of a sudden, um, our capacity in terms of remote access and I quadrupled, or more four, five X, what we had on the Friday we needed on the Monday. And we were able to stand that up during the day Monday into Tuesday, because we were cloud-based and, uh, you know, we just spun up your instances and, uh, you know, sort of our licensing, et cetera. And we had all of our people working remotely, um, within, uh, you know, effectively one business day. Um, I know peers of mine in other organizations and industries that are relying on kind of a traditional wise and getting hardware, et cetera, that were weeks and months before they could get there the right hardware to be able to deliver to their user base. >>So, um, you know, one example where you're able to scale and, uh, um, get, uh, get value out of this platform beyond probably what was anticipated at the time you talk about, um, you know, less the, in all of these kinds of things. And you can also think of a few scenarios, but real world ones where you're getting your business back up and running in that period of time is, is just phenomenal. There's other stuff, right? There's these programs that we've rolled out, you do your sizing, um, and in the traditional world, you would just go out and buy more servers than you need. And, you know, probably never realize the full value of those, you know, the capability of those servers over the life cycle of them. Whereas, you know, in a cloud world, you put in what you think is right. And if it's not right, you pump it up a little bit when, when all of your metrics and so on, tell you that you need to bump it up. And conversely you scale it down at the same rate. So for us, with the types of challenges and programs and, uh, uh, and just business need, that's come at as this year, uh, we wouldn't have been able to do it without a strong cloud base, uh, to, uh, to move forward. >>You know, Douglas, one of the things I talked to, a lot of people on the right side of history who have been on the right wave with cloud, with the pandemic, and they're happy, they're like, and they're humble. Like, well, we're just lucky, you know, luck is preparation meets opportunity. And this is really about you guys getting in early and being prepared and readiness. This is kind of important as people realize, then you gotta be ready. I mean, it's not just, you don't get lucky by being in the right place, the right time. And there were a lot of companies were on the wrong side of history here who might get washed away. This is a super important, I think, >>To echo and kind of building on what Stewart said. I think that the reason that we've had success and I guess the momentum is we didn't just do it in isolation within it and technology. It was actually linked to broader business changes, you know, creating basically a digital platform for the entire business, moving the business, where are they going to be able to come back stronger after COVID, when they're actually set up for growth, um, and actually allows, you know, a line to achievements growth objectives, and also its ambitions as far as what it wants to do, uh, with growth in whatever they make, do with acquiring other companies and moving into different markets and launching new products. So we've actually done it in a way that is, you know, real and direct business benefit, uh, that actually enables line to grow >>General. I really appreciate you coming. I have one final question. If you can wrap up here, uh, Stuart and Douglas, you don't mind weighing in what's the priorities for the future. What's next for lion in a century >>Christmas holidays, I'll start Christmas holidays. I spent a good year and then a, and then a reset, obviously, right? So, um, you know, it's, it's figuring out, uh, transform what we've already transformed, if that makes sense. So God, a huge proportion of our services sitting in the cloud. Um, but we know we're not done even with the stuff that is in there. We need to take those next steps. We need more and more automation and orchestration. We need to, um, our environment is more future proof. We need to be able to work with the business and understand what's coming at them so that we can, um, you know, build that into, into our environment. So again, it's really transformation on top of transformation is the way that I'll describe it. And it's really an open book, right? Once you get it in and you've got the capabilities and the evolving tool sets that AWS continue to bring to the market based, um, you know, working with the partners to, to figure out how we unlock that value, um, you know, drive our costs down efficiency, uh, all of those kind of, you know, standard metrics. >>Um, but you know, we're looking for the next things to transform and showed value back out to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with and understand how we can better meet their needs. Yeah, I think just to echo that, I think it's really leveraging this and then did you capability they have and getting the most out of that investment. And then I think it's also moving to, uh, and adopting more new ways of working as far as, you know, the speed of the business, um, is getting up to speed in the market is changing. So being able to launch and do things quickly and also, um, competitive and efficient operating costs, uh, now that they're in the cloud, right? So I think it's really leveraging the most out of the platform and then, you know, being efficient in launching things. So putting them with >>Siddique, any word from you on your priorities by you see this year in folding, >>There's got to say like e-learning squares, right, for me around, you know, just journey. This is a journey to the cloud, right? >>And, uh, you know, as well dug into sort of Saturday, it's getting all, you know, different parts of the organization along the journey business to it, to your, uh, product lenders, et cetera. Right. And it takes time. It is tough, but, uh, uh, you know, you got to get started on it. And, you know, once we, once we finish off, uh, it's the realization of the benefits now that, you know, looking forward, I think for, from Alliance perspective, it is, uh, you know, once we migrate all the workloads to the cloud, it is leveraging, uh, all stack drive. And as I think Stewart said earlier, uh, with, uh, you know, the latest and greatest stuff that AWS it's basically working to see how we can really, uh, achieve more better operational excellence, uh, from a, uh, from a cloud perspective. >>Well, Stewart, thanks for coming on with a and sharing your environment and what's going on and your journey you're on the right wave. Did the work you're in, it's all coming together with faster, congratulations for your success, and, uh, really appreciate Douglas with Steve for coming on as well from essential. Thank you for coming on. Thanks, John. Okay. Just the cubes coverage of executive summit at AWS reinvent. This is where all the thought leaders share their best practices, their journeys, and of course, special programming with Accenture and the cube. I'm Sean ferry, your host, thanks for watching from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtuals coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First. We have Johan Krebbers. He is the GM digital emerging technologies and VP of it. Innovation at shell. Thank you so much for coming on the show, Johan you're welcome. And next we have Liz Dennett. She is the lead solution architect for O S D U on AWS. Thank you so much, Liz, maybe here. So I want to start our conversation by talking about OSD. You like so many great innovations. It started with a problem. Johann, what was the problem you were trying to solve at shell? We go back a couple of years, we started summer 2017, where we had a meeting with the guys from exploration in shell, and the main problem they had, of course, they got lots of lots of data, but are unable to find the right data. They need to work from all over the place and told him >>To, and we'll probably try to solve is how that person working exploration could find their proper date, not just a day, but also the date you really needed that we did probably talked about is summer 2017. And we said, okay, the only way ABC is moving forward is to start pulling that data into a single data platform. And that, that was at the time that we called it as the, you, the subsurface data universe in there was about the shell name was so in, in January, 2018, we started a project with Amazon to start grating a co fricking that building, that Stu environment, that the, the universe, so that single data level to put all your exploration and Wells data into that single environment that was intent. And every cent, um, already in March of that same year, we said, well, from Michele point of view, we will be far better off if we could make this an industry solution and not just a shelf solution, because Shelby, Shelby, if you can make an industry solution, but people are developing applications for it. >>It also is far better than for shell to say we haven't shell special solution because we don't make money out of how we start a day that we can make money out of it. We have access to the data, we can explore the data. So storing the data we should do as efficiently possibly can. So we monitor, we reach out to about eight or nine other last, uh, or I guess operators like the economics, like the tutorials, like the shepherds of this world and say, Hey, we inshallah doing this. Do you want to join this effort? And to our surprise, they all said, yes. And then in September, 2018, we had our kickoff meeting with your open group where we said, we said, okay, if you want to work together and lots of other companies, we also need to look at, okay, how, how we organize that. >>Or if you started working with lots of large companies, you need to have some legal framework around some framework around it. So that's why we went to the open group and say, okay, let's, let's form the old forum as we call it at the time. So it's September, 2080, where I did a Galleria in Houston, but the kickoff meeting for the OT four with about 10 members at the time. So that's just over two years ago, we started an exercise for me called ODU. They kicked it off. Uh, and so that's really them will be coming from and how we've got there. Also >>The origin story. Um, what, so what digging a little deeper there? What were some of the things you were trying to achieve with the OSU? >>Well, a couple of things we've tried to achieve with you, um, first is really separating data from applications for what is, what is the biggest problem we have in the subsurface space that the data and applications are all interlinked or tied together. And if, if you have them and a new company coming along and say, I have this new application and he's access to the data that is not possible because the data often interlinked with the application. So the first thing we did is really breaking the link between the application, the data as those levels, the first thing we did, secondly, put all the data to a single data platform, take the silos out what was happening in the sub-service space. They got all the data in what we call silos in small little islands out there. So what we're trying to do is first break the link to great, great. >>They put the data single day, the bathroom, and the third part, put a standard layer on top of that, it's an API layer on top to equate a platform. So we could create an ecosystem out of companies to start a valving Schoff application on top of dev data platform across you might have a data platform, but you're only successful if have a rich ecosystem of people start developing applications on top of that. And then you can export the data like small companies, last company, university, you name it, we're getting after create an ecosystem out here. So the three things were first break the link between application data, just break it and put data at the center and also make sure that data, this data structure would not be managed by one company, but it would only be met. It would be managed the data structures by the ODI forum. Secondly, then put a, the data, a single data platform certainly then has an API layer on top and then create an ecosystem. Really go for people, say, please start developing applications, because now you had access to the data. I've got the data no longer linked to somebody whose application was all freely available, but an API layer that was, that was all September, 2018, more or less. >>And hear a little bit. Can you talk a little bit about some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? Yeah, absolutely. And this whole thing is Johann said started with a challenge that was really brought out at shell. The challenges that geoscientists spend up to 70% of their time looking for data. I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out how we could address that one problem, we worked together to really understand the root cause of these challenges and working backwards from that use case OSU and OSU on AWS has really enabled customers to create solutions that span, not just this in particular problem, but can really scale to be inclusive of the entire energy value chain and deliver value from these use cases to the energy industry and beyond. Thank you, Lee, uh, Johann. So talk a little bit about Accenture's cloud first approach and how it has, uh, helped shell work faster and better with speed. >>Well, of course, access a cloud first approach only works together. It's been an Amazon environment, AWS environment. So we're really looking at, uh, at, at Accenture and others altogether helping shell in this space. Now the combination of the two is what we're really looking at, uh, where access of course can be recent knowledge student to that environment operates support knowledge, do an environment. And of course, Amazon will be doing that to today's environment that underpinning their services, et cetera. So, uh, we would expect a combination, a lot of goods when we started rolling out and put in production, the old you are three and bug because we are anus. Then when the release feed comes to the market in Q1, next year of ODU have already started going to Audi production inside shell. But as the first release, which is ready for prime time production across an enterprise will be released just before Christmas, last year when he's still in may of this year. But really three is the first release we want to use for full scale production deployment inside shell, and also the operators around the world. And there is one Amazon, sorry, at that one. Um, extensive can play a role in the ongoing, in the, in deployment building up, but also support environment. >>So one of the other things that we talk a lot about here on the cube is sustainability. And this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSD you, uh, help organizations become, how is this a greener solution for companies? >>Well, first we make it's a greatest solution because you start making a much more efficient use of your resources, which is already an important one. The second thing we're doing is also, we started ODU in framers, in the oil and gas space in the expert development space. We've grown, uh, OTU in our strategy of growth. I was, you know, also do an alternative energy sociology. We'll all start supporting next year. Things like solar farms, wind farms, uh, the, the dermatomal environment hydration. So it becomes an and an open energy data platform, not just what I want to get into sleep. That's what new industry, any type of energy industry. So our focus is to create, bring the data of all those various energy data sources to get me to a single data platform you can to use AI and other technologies on top of that, to exploit the data, to meet again into a single data platform. >>Liz, I want to ask you about security because security is, is, is such a big concern when it comes to data. How secure is the data on OSD? You, um, actually, can I talk, can I do a follow up on this sustainability talking? Oh, absolutely. By all means. I mean, I want to interject though security is absolutely our top priority. I don't mean to move away from that, but with sustainability, in addition to the benefits of the OSU data platform, when a company moves from on-prem to the cloud, they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical data center. >>Now, a recent study by four 51 research found that AWS is infrastructure is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to higher, um, server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases for 51 found that AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSU are working to support our customers is they seek to better understand their workflows and make their legacy businesses less carbon intensive. >>That's that's incorrect. Those are those statistics are incredible. Do you want to talk a little bit now about security? Absolutely. And security will always be AWS is top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy. There are the security requirements for the military, local banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build and operate each of our regions. So that customers benefit from the only commercial cloud that's hat hits service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features as well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. Johann, I want you to talk a little bit about how OSD you can be used today. Does it only handle subsurface data? >>Uh, today it's Honda's subserves or Wells data, we go to add to that production around the middle of next year. That means that the whole upstate business. So we've got goes from exploration all the way to production. You've made it together into a single data platform. So production will be added around Q3 of next year. Then a principal. We have a difficult, the elder data that single environment, and we want to extend them to other data sources or energy sources like solar farms, wind farms, uh, hydrogen, hydro, et cetera. So we're going to add a whore, a whole list of audit day energy source to them and be all the data together into a single data club. So we move from a falling guest data platform to an aniseed data platform. That's really what our objective is because the whole industry, if you look it over, look at our companies are all moving in. That same two acts of quantity of course, are very strong in oil and gas, but also increased the, got into the other energy sources like, like solar, like wind, like th like highly attended, et cetera. So we would be moving exactly. But that same method that, that, that the whole OSU can't really support at home. And as a spectrum of energy sources, >>Of course, and Liz and Johan. I want you to close us out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSD. You we'll start with you, Liz. What do you, what do you see as the future holding for this platform? Um, honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers, wherever their OSU journeys, take them, whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond, but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges, Johann first, nobody can look at any more nowadays, especially 10 years own objective is really in the next five years, you will become the key backbone for energy companies for storing your data. You are efficient intelligence and optimize the whole supply energy supply chain in this world down here, you'll uncovers Liz Dennett. Thank you so much for coming on the cube virtual I'm Rebecca Knight stay tuned for more of our coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight today we're welcoming back to Kubila. We have Kishor Dirk. He is the Accenture senior managing director cloud first global services lead. Welcome back to the show Kishore. Thank you very much. Nice to meet again. And, uh, Tristan moral horse set. He is the managing director, Accenture cloud first North America growth. Welcome back to you to trust and great to be back in grapes here again, Rebecca. Exactly. Even in this virtual format, it is good to see your faces. Um, today we're going to be talking about my nav and green cloud advisor capability. Kishor I want to start with you. So my nav is a platform that is really celebrating its first year in existence. Uh, November, 2019 is when Accenture introduced it. Uh, but it's, it has new relevance in light of this global pandemic that we are all enduring and suffering through. Tell us a little bit about the lineup platform, what it is that cloud platform to help our clients navigate the complexity of cloud and cloud decisions to make it faster. And obviously, you know, we have in the cloud, uh, you know, with >>The increased relevance and all the, especially over the last few months with the impact of COVID crisis and exhibition of digital transformation, you know, we are seeing the transformation or the acceleration to cloud much faster. This platform that you're talking about has enabled and 40 clients globally across different industries. You identify the right cloud solution, navigate the complexity, provide a cloud specific solution simulate for our clients to meet the strategy business needs, and the clients are loving it. >>I want to go to you now trust and tell us a little bit about how mine nav works and how it helps companies make good cloud choice. >>Yeah, so Rebecca, we we've talked about cloud is, is more than just infrastructure and that's what mine app tries to solve for it. It really looks at a variety of variables, including infrastructure operating model and fundamentally what client's business outcomes, um, uh, our clients are, are looking for and, and identifies the optimal solution for what they need. And we assign this to accelerate and we mentioned the pandemic. One of the big focus now is to accelerate. And so we worked through a three-step process. The first is scanning and assessing our client's infrastructure, their data landscape, their application. Second, we use our automated artificial intelligence engine to interact with. We have a wide variety and library of a collective plot expertise. And we look to recommend what is the enterprise architecture and solution. And then third, before we aligned with our clients, we look to simulate and test this scaled up model. And the simulation gives our clients a way to see what cloud is going to look like, feel like and how it's going to transform their business before they go there. >>Tell us a little bit about that in real life. Now as a company, so many of people are working remotely having to collaborate, uh, not in real life. How is that helping them right now? >>So, um, the, the pandemic has put a tremendous strain on systems, uh, because of the demand on those systems. And so we talk about resiliency. We also now need to collaborate across data across people. Um, I think all of us are calling from a variety of different places where our last year we were all at the VA cube itself. Um, and, and cloud technologies such as teams, zoom that we're we're leveraging now has fundamentally accelerated and clients are looking to onboard this for their capabilities. They're trying to accelerate their journey. They realize that now the cloud is what is going to become important for them to differentiate. Once we come out of the pandemic and the ability to collaborate with their employees, their partners, and their clients through these systems is becoming a true business differentiator for our clients. >>Keisha, I want to talk with you now about my navs multiple capabilities, um, and helping clients design and navigate their cloud journeys. Tell us a little bit about the green cloud advisor capability and its significance, particularly as so many companies are thinking more deeply and thoughtfully about sustainability. >>Yes. So since the launch of my lab, we continue to enhance, uh, capabilities for our clients. One of the significant, uh, capabilities that we have enabled is the being taught advisor today. You know, Rebecca, a lot of the businesses are more environmentally aware and are expanding efforts to decrease power consumption, uh, and obviously carbon emissions and, uh, and run a sustainable operations across every aspect of the enterprise. Uh, as a result, you're seeing an increasing trend in adoption of energy, efficient infrastructure in the global market. And one of the things that we did a lot of research we found out is that there's an ability to influence our client's carbon footprint through a better cloud solution. And that's what the internet brings to us, uh, in, in terms of a lot of the client connotation that you're seeing in Europe, North America and others, lot of our clients are accelerating to a green cloud strategy to unlock beta financial, societal and environmental benefit, uh, through obviously cloud-based circular, operational, sustainable products and services. That is something that we are enhancing my now, and we are having active client discussions at this point of time. >>So Tristan, tell us a little bit about how this capability helps clients make greener decisions. >>Yeah. Um, well, let's start about the investments from the cloud providers in renewable and sustainable energy. Um, they have most of the hyperscalers today, um, have been investing significantly on data centers that are run on renewable energy, some incredibly creative constructs on the how to do that. And sustainability is there for a key, um, key item of importance for the hyperscalers and also for our clients who now are looking for sustainable energy. And it turns out this marriage is now possible. I can, we marry the, the green capabilities of the comm providers with a sustainability agenda of our clients. And so what we look into the way the mine EF works is it looks at industry benchmarks and evaluates our current clients, um, capabilities and carpet footprint leveraging their existing data centers. We then look to model from an end-to-end perspective, how the, their journey to the cloud leveraging sustainable and, um, and data centers with renewable energy. We look at how their solution will look like and, and quantify carbon tax credits, um, improve a green index score and provide quantifiable, um, green cloud capabilities and measurable outcomes to our clients, shareholders, stakeholders, clients, and customers. Um, and our green plot advisers sustainability solutions already been implemented at three clients. And in many cases in two cases has helped them reduce the carbon footprint by up to 400% through migration from their existing data center to green cloud. Very, very, >>That is remarkable. Now tell us a little bit about the kinds of clients. Is this, is this more interesting to clients in Europe? Would you say that it's catching on in the United States? Where, what is the breakdown that you're seeing right now? >>Sustainability is becoming such a global agenda and we're seeing our clients, um, uh, tie this and put this at board level, um, uh, agenda and requirements across the globe. Um, Europe has specific constraints around data sovereignty, right, where they need their data in country, but from a green, a sustainability agenda, we see clients across all our markets, North America, Europe, and our growth markets adopt this. And we have seen case studies and all three months. >>Keisha, I want to bring you back into the conversation. Talk a little bit about how MindUP ties into Accenture's cloud first strategy, your Accenture's CEO, Julie Sweet has talked about post COVID leadership requiring every business to become a cloud first business. Tell us a little bit about how this ethos is in Accenture and how you're sort of looking outward with it too. >>So Rebecca mine is the launch pad, uh, to a cloud first transformation for our clients. Uh, Accenture, see your jewelry suite, uh, you know, shared the Accenture cloud first and our substantial investment demonstrate our commitment and is delivering greater value for our clients when they need it the most. And with the digital transformation requiring cloud at scale, you know, we're seeing that in the post COVID leadership, it requires that every business should become a cloud business. And my nap helps them get there by evaluating the cloud landscape, navigating the complexity, modeling architecting and simulating an optimal cloud solution for our clients. And as Justin was sharing a greener cloud. >>So Tristan, talk a little bit more about some of the real life use cases in terms of what are we, what are clients seeing? What are the results that they're having? >>Yes. Thank you, Rebecca. I would say two key things right around my neck. The first is the iterative process. Clients don't want to wait, um, until they get started, they want to get started and see what their journey is going to look like. And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need to move to cloud very quickly. And my nav is there to do that. So how do we do that? First is generating the business cases. Clients need to know in many cases that they have a business case by business case, we talk about the financial benefits, as well as the business outcomes, the green, green clot impact sustainability impacts with minus. We can build initial recommendations using a basic understanding of their environment and benchmarks in weeks versus months with indicative value savings in the millions of dollars arranges. >>So for example, very recently, we worked with a global oil and gas company, and in only two weeks, we're able to provide an indicative savings for $27 million over five years. This enabled the client to get started, knowing that there is a business case benefit and then iterate on it. And this iteration is, I would say the second point that is particularly important with my nav that we've seen in bank, the clients, which is, um, any journey starts with an understanding of what is the application landscape and what are we trying to do with those, these initial assessments that used to take six to eight weeks are now taking anywhere from two to four weeks. So we're seeing a 40 to 50% reduction in the initial assessment, which gets clients started in their journey. And then finally we've had discussions with all of the hyperscalers to help partner with Accenture and leverage mine after prepared their detailed business case module as they're going to clients. And as they're accelerating the client's journey, so real results, real acceleration. And is there a journey? Do I have a business case and furthermore accelerating the journey once we are by giving the ability to work in iterative approach. >>I mean, it sounds as though that the company that clients and and employees are sort of saying, this is an amazing time savings look at what I can do here in, in so much in a condensed amount of time, but in terms of getting everyone on board, one of the things we talked about last time we met, uh, Tristan was just how much, uh, how one of the obstacles is getting people to sign on and the new technologies and new platforms. Those are often the obstacles and struggles that companies face. Have you found that at all? Or what is sort of the feedback that you're getting from employers? >>Sorry. Yes. We clearly, there are always obstacles to a cloud journey. If there were an obstacles, all our clients would be, uh, already fully in the cloud. What man I gives the ability is to navigate through those, to start quickly. And then as we identify obstacles, we can simulate what things are going to look like. We can continue with certain parts of the journey while we deal with that obstacle. And it's a fundamental accelerator. Whereas in the past one, obstacle would prevent a class from starting. We can now start to address the obstacles one at a time while continuing and accelerating the contrary. That is the fundamental difference. >>Kishor I want to give you the final word here. Tell us a little bit about what is next for Accenture might have and what we'll be discussing next year at the Accenture executive summit >>Sort of echo, we are continuously evolving with our client needs and reinventing, reinventing for the future. For mine, as I've been taught advisor, our plan is to help our clients reduce carbon footprint and again, migrate to a green cloud. Uh, and additionally, we're looking at, you know, two capabilities, uh, which include sovereign cloud advisor, uh, with clients, especially in, in Europe and others are under pressure to meet, uh, stringent data norms that Kristen was talking about. And the sovereign cloud advisor health organization to create an architecture cloud architecture that complies with the green. Uh, I would say the data sovereignty norms that is out there. The other element is around data to cloud. We are seeing massive migration, uh, for, uh, for a lot of the data to cloud. And there's a lot of migration hurdles that come within that. Uh, we have expanded mine app to support assessment capabilities, uh, for, uh, assessing applications, infrastructure, but also covering the entire state, including data and the code level to determine the right cloud solution. So we are, we are pushing the boundaries on what mine app can do with mine. Have you created the ability to take the guesswork out of cloud navigate the complexity? We are roaring risks costs, and we are, you know, achieving client's static business objectives while building a sustainable alerts with being cloud >>Any platform that can take some of the guesswork out of the future. I'm I'm onboard with. Thank you so much, Tristin and Kishore. This has been a great conversation. >>Thank you. >>Stay tuned for more of the cubes coverage of the Accenture executive summit. I'm Rebecca Knight from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Hey, welcome back to the cubes coverage of 80 us reinvent 2020 virtual centric executive summit. The two great guests here to break down the analysis of the relationship with cloud and essential Brian bowhead director ahead of a century 80. It was business group at Amazon web services. And Andy T a B G the M is essentially Amazon business group lead managing director at Accenture. Uh, I'm sure you're super busy and dealing with all the action, Brian. Great to see you. Thanks for coming on. So thank you. You guys essentially has been in the spotlight this week and all through the conference around this whole digital transformation, essentially as business group is celebrating its fifth anniversary. What's new, obviously the emphasis of next gen post COVID generation, highly digital transformation, a lot happening. You got your five-year anniversary, what's new. >>Yeah, it, you know, so if you look back, it's exciting. Um, you know, so it was five years ago. Uh, it was actually October where we, where we launched the Accenture AWS business group. And if we think back five years, I think we're still at the point where a lot of customers were making that transition from, you know, should I move to cloud to how do I move to cloud? Right? And so that was one of the reasons why we launched the business group. And since, since then, certainly we've seen that transition, right? Our conversations today are very much around how do I move to cloud, help me move, help me figure out the business case and then pull together all the different pieces so I can move more quickly, uh, you know, with less risk and really achieve my business outcomes. And I would say, you know, one of the things too, that's, that's really changed over the five years. >>And what we're seeing now is when we started, right, we were focused on migration data and IOT as the big three pillars that we launched with. And those are still incredibly important to us, but just the breadth of capability and frankly, the, the, the breadth of need that we're seeing from customers. And obviously as AWS has matured over the years and launched our new capabilities, we're Eva with Accenture and in the business group, we've broadened our capabilities and deepened our capabilities over the, over the last five years as well. For instance, this year with, with COVID, especially, it's really forced our customers to think differently about their own customers or their citizens, and how do they service those citizens? So we've seen a huge acceleration around customer engagement, right? And we powered that with Accenture customer engagement platform powered by ADA, Amazon connect. And so that's been a really big trend this year. And then, you know, that broadens our capability from just a technical discussion to one where we're now really reaching out and, and, um, and helping transform and modernize that customer and citizen experience as well, which has been exciting to see. >>Yeah, Andy, I want to get your thoughts here. We've been reporting and covering essentially for years. It's not like it's new to you guys. I mean, five years is a great anniversary. You know, check is good relationship, but you guys have been doing the work you've been on the trend line. And then this hits and Andy said on his keynote and I thought he said it beautifully. And he even said it to me in my one-on-one interview with them was it's on full display right now, the whole digital transformation, everything about it is on full display and you're either were prepared for it or you kind of word, and you can see who's there. You guys have been prepared. This is not new. So give us the update from your perspective, how you're taking advantage of this, of this massive shift, highly accelerated digital transformation. >>Well, I think, I think you can be prepared, but you've also got to be prepared to always sort of, I think what we're seeing in, in, um, in, in, in, in recent times and particularly 20 w what is it I think today there are, um, full sense of the enterprise workloads, the cloud, um, you know, that leaves 96 percentile now for him. Um, and I, over the next four to >>Five years, um, we're going to see that sort of, uh, acceleration to the, to the cloud pick up, um, this year is, as Andy touched on, I think, uh, uh, on Tuesday in his, I think the pandemic is a forcing function, uh, for companies to, to really pause and think about everything from, from, you know, how they, um, manage that technology to infrastructure, to just to carotenoids where the data sets to what insights and intelligence that getting from that data. And then eventually even to, to the talent, the talent they have in the organization and how they can be competitive, um, their culture, their culture of innovation, of invention and reinvention. And so I think, I think, you know, when you, when you think of companies out there faced with these challenges, it, it forces us, it forces AWS, it forces AEG to come together and think through how can we help create value for them? How can we help help them move from sort of just causing and rethinking to having real plans in an action and that taking them, uh, into, into implementation. And so that's, that's what we're working on. Um, I think over the next five years, we're looking to just continue to come together and help these, these companies get to the cloud and get the value from the cloud because it's beyond just getting to the cloud attached to them and living in the cloud and, and getting the value from it. >>It's interesting. Andy was saying, don't just put your toe in the water. You got to go beyond the toe in the water kind of approach. Um, I want to get to that large scale cause that's the big pickup this week that I kind of walked away with was it's large scale. Acceleration's not just toe in the water experimentation. Can you guys share, what's causing this large scale end to end enterprise transformation? And what are some of the success criteria have you seen for the folks who have done that? >>Yeah. And I'll, I'll, I'll start. And at the end you can buy a lawn. So, you know, it's interesting if I look back a year ago at re-invent and when I did the cube interview, then we were talking about how the ABG, we were starting to see this shift of customers. You know, we've been working with customers for years on a single of what I'll call a single-threaded programs, right. We can do a migration, we could do SAP, we can do a data program. And then even last year, we were really starting to see customers ask. The question is like, what kind of synergies and what kind of economies of scale do I get when I start bringing these different threads together, and also realizing that it's, you know, to innovate for the business and build new applications, new capabilities. Well, that then is going to inform what data you need to, to hydrate those applications, right? Which then informs your data strategy while a lot of that data is then also embedded in your underlying applications that sit on premises. So you should be thinking through how do you get those applications into the cloud? So you need to draw that line through all of those layers. And that was already starting last year. And so last year we launched the joint transformation program with AEG. And then, so we were ready when this year happened and then it was just an acceleration. So things have been happening faster than we anticipated, >>But we knew this was going to be happening. And luckily we've been in a really good position to help some of our customers really think through all those different layers of kind of pyramid as we've been calling it along with the talent and change pieces, which are also so important as you make this transformation to cloud >>Andy, what's the success factors. Andy Jassy came on stage during the partner day, a surprise fireside chat with Doug Hume and talking about this is really an opportunity for partners to, to change the business landscape with enablement from Amazon. You guys are in a pole position to do that in the marketplace. What's the success factors that you see, >>Um, really from three, three fronts, I'd say, um, w one is the people. Um, and, and I, I, again, I think Andy touched on sort of eight, uh, success factors, uh, early in the week. And for me, it's these three areas that it sort of boils down to these three areas. Um, one is the, the, the, the people, uh, from the leaders that it's really important to set those big, bold visions point the way. And then, and then, you know, set top down goals. How are we going to measure Z almost do get what you measure, um, to be, you know, beyond the leaders, to, to the right people in the right position across the company. We we're finding a key success factor for these end to end transformations is not just the leaders, but you haven't poached across the company, working in a, in a collaborative, shared, shared success model, um, and people who are not afraid to, to invent and fail. >>And so that takes me to perhaps the second point, which is the culture, um, it's important, uh, with finding for the right conditions to be set in the company that enabled, uh, people to move at pace, move at speed, be able to fail fast, um, keep things very, very simple and just keep iterating and that sort of culture of iteration and improvement versus seeking perfection is, is super important for, for success. And then the third part of maybe touch on is, is partners. Um, I think, you know, as we move forward over the next five years, we're going to see an increasing number of players in the ecosystem in the enterprise and state. Um, you're going to see more and more SAS providers. And so it's important for companies and our joint clients out there to pick partners like, um, like AWS or, or Accenture or others, but to pick partners who have all worked together and you have built solutions together, and that allows them to get speed to value quicker. It allows them to bring in pre-assembled solutions, um, and really just drive that transformation in a quicker, it sorts of manner. >>Yeah, that's a great point worth calling out, having that partnership model that's additive and has synergy in the cloud, because one of the things that came out of this this week, this year is reinvented, is there's new things going on in the public cloud, even though hybrid is an operating model, outpost and super relevant. There, there are benefits for being in the cloud and you've got partners API, for instance, and have microservices working together. This is all new, but I got, I got to ask that on that thread, Andy, where did you see your customers going? Because I think, you know, as you work backwards from the customers, you guys do, what's their needs, how do you see them? W you know, where's the puck going? Where can they skate where the puck's going, because you can almost look forward and say, okay, I've got to build modern apps. I got to do the digital transformation. Everything is a service. I get that, but what are they, what solutions are you building for them right now to get there? >>Yeah. And, and of course, with, with, you know, industries blurring and multiple companies, it's always hard to boil down to the exact situations, but you could probably look at it from a sort of a thematic lens. And what we're seeing is as the cloud transformation journey picks up, um, from us perspective, we've seen a material shift in the solutions and problems that we're trying to address with clients that they are asking for us, uh, to, to help, uh, address is no longer just the back office, where you're sort of looking at cost and efficiency and, um, uh, driving gains from that perspective. It's beyond that, it's now materially the top line. It's, how'd you get the driving to the, you know, speed to insights, how'd you get them decomposing, uh, their application set in order to derive those insights. Um, how'd you get them, um, to, to, um, uh, sort of adopt leading edge industry solutions that give them that jump start, uh, and that accelerant to winning the customers, winning the eyeballs. >>Um, and then, and then how'd, you help drive the customer experience. We're seeing a lot of push from clients, um, or ask for help on how do I optimize my customer experience in order to retain my eyeballs. And then how do I make sure I've got a soft self-learning ecosystem of play, um, where, uh, you know, it's not just a practical experience that I can sort of keep learning and iterating, um, how I treat my, my customers, um, and a lot of that, um, that still self-learning, that comes from, you know, putting in intelligence into your, into your systems, getting an AI and ML in there. And so, as a result of that work, we're seeing a lot of push and a lot of what we're doing, uh, is pouring investment into those areas. And then finally, maybe beyond the bottom line, and the top line is how do you harden that and protect that with, um, security and resilience? So I'll probably say those are the three areas. John, >>You know, the business model side, obviously the enablement is what Amazon has. Um, we see things like SAS factory coming on board and the partner network, obviously a century is a big, huge partner of you guys. Um, the business models there, you've got I, as, as doing great with chips, you have this data modeling this data opportunity to enable these modern apps. We heard about the partner strategy for me and D um, talking to me now about how can partners within even Accenture, w w what's the business model, um, side on your side that you're enabling this. Can you just share your thoughts on that? >>Yeah, yeah. And so it's, it's interesting. I think I'm going to build it and then build a little bit on some of the things that Andy really talked about there, right? And that we, if you think of that from the partnership, we are absolutely helping our customers with kind of that it modernization piece. And we're investing a lot and there's hard work that needs to get done there. And we're investing a lot as a partnership around the tools, the assets and the methodology. So in AWS and Accenture show up together as AEG, we are executing office single blueprint with a single set of assets, so we can move fast. So we're going to continue to do that with all the hybrid announcements from this past week, those get baked into that, that migration modernization theme, but the other really important piece here as we go up the stack, Andy mentioned it, right? >>The data piece, like so much of what we're talking about here is around data and insights. Right? I did a cube interview last week with, uh, Carl hick. Um, who's the CIO from Takeda. And if you hear Christophe Weber from Takeda talk, he talks about Takeda being a data company, data and insights company. So how do we, as a partnership, again, build the capabilities and the platforms like with Accenture's applied insights platform so that we can bootstrap and really accelerate our client's journey. And then finally, on the innovation on the business front, and Andy was touching on some of these, we are investing in industry solutions and accelerators, right? Because we know that at the end of the day, a lot of these are very similar. We're talking about ingesting data, using machine learning to provide insights and then taking action. So for instance, the cognitive insurance platform that we're working together on with Accenture, if they give out property and casualty claims and think about how do we enable touchless claims using machine learning and computer vision that can assess based on an image damage, and then be able to triage that and process it accordingly, right? >>Using all the latest machine learning capabilities from AWS with that deep, um, AI machine learning data science capability from Accenture, who knows all those algorithms that need to get built and build that library by doing that, we can really help these insurance companies accelerate their transformation around how they think about claims and how they can speed those claims on behalf of their policy holder. So that's an example of a, kind of like a bottom to top, uh, view of what we're doing in the partnership to address these new needs. >>That's awesome. Andy, I want to get back to your point about culture. You mentioned it twice now. Um, talent is a big part of the game here. Andy Jassy referenced Lambda. The next generation developers were using Lambda. He talked about CIO stories around, they didn't move fast enough. They lost three years. A new person came in and made it go faster. This is a new, this is a time for a certain kind of, um, uh, professional and individual, um, to, to be part of, um, this next generation. What's the talent strategy you guys have to attract and attain the best and retain the people. How do you do it? >>Um, you know, it's, it's, um, it's an interesting one. It's, it's, it's oftentimes a, it's, it's a significant point and often overlooked. Um, you know, people, people really matter and getting the right people, um, in not just in AWS or it, but then in our customers is super important. We often find that much of our discussions with, with our clients is centered around that. And it's really a key ingredient. As you touched on, you need people who are willing to embrace change, but also people who are willing to create new, um, to invent new, to reinvent, um, and to, to keep it very simple. Um, w we're we're we're seeing increasingly that you need people that have a sort of deep learning and a deep, uh, or deep desire to keep learning and to be very curious as, as they go along. Most of all, though, I find that, um, having people who are not willing or not afraid to fail is critical, absolutely critical. Um, and I think that that's, that's, uh, a necessary ingredient that we're seeing, um, our clients needing more off, um, because if you can't start and, and, and you can't iterate, um, you know, for fear of failure, you're in trouble. And, and I think Andy touched on that you, you know, where that CIO, that you referred to last three years, um, and so you really do need people who are willing to start not afraid to start, uh, and, uh, and not afraid to lead >>Was a gut check there. I just say, you guys have a great team over there. Everyone at the center I've interviewed strong, talented, and not afraid to lean in and, and into the trends. Um, I got to ask on that front cloud first was something that was a big strategic focus for Accenture. How does that fit into your business group? That's an Amazon focused, obviously they're cloud, and now hybrid everywhere, as I say, um, how does that all work it out? >>We're super excited about our cloud first initiative, and I think it fits it, um, really, uh, perfectly it's it's, it's what we needed. It's, it's, it's a, it's another accelerant. Um, if you think of count first, what we're doing is we're, we're putting together, um, uh, you know, capability set that will help enable him to and transformations as Brian touched on, you know, help companies move from just, you know, migrating to, to, to modernizing, to driving insights, to bringing in change, um, and, and, and helping on that, on that talent side. So that's sort of component number one is how does Accenture bring the best, uh, end to end transformation capabilities to our clients? Number two is perhaps, you know, how do we, um, uh, bring together pre-assembled as Brian touched on pre-assembled industry offerings to help as an accelerant, uh, for our, for our customers three years, as we touched on earlier is, is that sort of partnership with the ecosystem. >>We're going to see an increasing number of SAS providers in an estate, in the enterprise of snakes out there. And so, you know, panto wild cloud first, and our ABG strategy is to increase our touch points in our integrations and our solutions and our offerings with the ecosystem partners out there, the ISP partners out, then the SAS providers out there. And then number four is really about, you know, how do we, um, extend the definition of the cloud? I think oftentimes people thought of the cloud just as sort of on-prem and prem. Um, but, but as Andy touched on earlier this week, you know, you've, you've got this concept of hybrid cloud and that in itself, um, uh, is, is, is, you know, being redefined as well. You know, when you've got the intelligent edge and you've got various forms of the edge. Um, so that's the fourth part of, of, uh, of occupied for strategy. And for us was super excited because all of that is highly relevant for ABG, as we look to build those capabilities as industry solutions and others, and as when to enable our customers, but also how we, you know, as we, as we look to extend how we go to market, I'll join tele PS, uh, in, uh, in our respective skews and products. >>Well, what's clear now is that people now realize that if you contain that complexity, the upside is massive. And that's great opportunity for you guys. We got to get to the final question for you guys to weigh in on, as we wrap up next five years, Brian, Andy weigh in, how do you see that playing out? What do you see this exciting, um, for the partnership and the cloud first cloud, everywhere cloud opportunities share some perspective. >>Yeah, I, I think, you know, just kinda building on that cloud first, right? What cloud first, and we were super excited when cloud first was announced and you know, what it signals to the market and what we're seeing in our customers, which has cloud really permeates everything that we're doing now. Um, and so all aspects of the business will get infused with cloud in some ways, you know, it, it touches on, on all pieces. And I think what we're going to see is just a continued acceleration and getting much more efficient about pulling together the disparate, what had been disparate pieces of these transformations, and then using automation using machine learning to go faster. Right? And so, as we started thinking about the stack, right, well, we're going to get, I know we are, as a partnership is we're already investing there and getting better and more efficient every day as the migration pieces and the moving the assets to the cloud are just going to continue to get more automated, more efficient. And those will become the economic engines that allow us to fund the differentiated, innovative activities up the stack. So I'm excited to see us kind of invest to make those, those, um, those bets accelerated for customers so that we can free up capital and resources to invest where it's going to drive the most outcome for their end customers. And I think that's going to be a big focus and that's going to have the industry, um, you know, focus. It's going to be making sure that we can >>Consume the latest and greatest of AWS as capabilities and, you know, in the areas of machine learning and analytics, but then Andy's also touched on it bringing in ecosystem partners, right? I mean, one of the most exciting wins we had this year, and this year of COVID is looking at the universe, looking at Massachusetts, the COVID track and trace solution that we put in place is a partnership between Accenture, AWS, and Salesforce, right? So again, bringing together three really leading partners who can deliver value for our customers. I think we're going to see a lot more of that as customers look to partnerships like this, to help them figure out how to bring together the best of the ecosystem to drive solutions. So I think we're going to see more of that as well. >>All right, Andy final word, your take >>Thinks of innovation is, is picking up, um, dismiss things are just going faster and faster. I'm just super excited and looking forward to the next five years as, as you know, the technology invention, um, comes out and continues to sort of set new standards from AWS. Um, and as we, as Accenture wringing, our industry capabilities, we marry the two. We, we go and help our customers super exciting time. >>Well, congratulations on the partnership. I want to say thank you to you guys, because I've reported a few times some stories around real successes around this COVID pandemic that you guys worked together on with Amazon that really changed people's lives. Uh, so congratulations on that too as well. I want to call that out. Thanks for coming >>Up. Thank you. Thanks for coming on. >>Okay. This is the cubes coverage, essentially. AWS partnership, part of a century executive summit at Atrius reinvent 2020 I'm John for your host. Thanks. >>You're watching from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Hello, and welcome back to the cubes coverage of AWS reinvent 2020. This is special programming for the century executive summit, where all the thought leaders going to extract the signal from the nose to share with you their perspective of this year's reinvent conference, as it respects the customers' digital transformation. Brian Bohan is the director and head of a center. ADA was business group at Amazon web services. Brian, great to see you. And Chris Wegman is the, uh, center, uh, Amazon business group technology lead at Accenture. Um, guys, this is about technology vision, this, this conversation, um, Chris, I want to start with you because you, Andy Jackson's keynote, you heard about the strategy of digital transformation, how you gotta lean into it. You gotta have the guts to go for it, and you got to decompose. He went everywhere. So what, what did you hear? What was striking about the keynote? Because he covered a lot of topics. Yeah. You know, it >>Was Epic, uh, as always for Mandy, a lot of topics, a lot to cover in the three hours. Uh, there was a couple of things that stood out for me, first of all, hybrid, uh, the concept, the new concept of hybrid and how Andy talked about it, you know, uh, bringing the compute and the power to all parts of the enterprise, uh, whether it be at the edge or are in the big public cloud, uh, whether it be in an outpost or wherever it might be right with containerization now, uh, you know, being able to do, uh, Amazon containerization in my data center and that that's, that's awesome. I think that's gonna make a big difference, all that being underneath the Amazon, uh, console and billing and things like that, which is great. Uh, I'll also say the, the chips, right. And I know compute is always something that, you know, we always kind of take for granted, but I think again, this year, uh, Amazon and Andy really focused on what they're doing with the chips and PR and compute, and the compute is still at the heart of everything in cloud. And that continued advancement is, is making an impact and will make a continue to make a big impact. >>Yeah, I would agree. I think one of the things that really, I mean, the container thing was, I think really kind of a nuanced point when you got Deepak sing on the opening day with Andy Jassy and he's, he runs a container group over there, you know, small little team he's on the front and front stage. That really is the key to the hybrid. And I think this showcases this new layer and taking advantage of the graviton two chips that, which I thought was huge. Brian, this is really a key part of the platform change, not change, but the continuation of AWS higher level servers building blocks that provide more capabilities, heavy lifting as they say, but the new services that are coming on top really speaks to hybrid and speaks to the edge. >>It does. Yeah. And it, it, you know, I think like Andy talks about, and we talk about, I, you know, we really want to provide choice to our customers, uh, first and foremost, and you can see that and they re uh, services. We have, we can see it in the, the hybrid options that Chris talked about, being able to run your containers through ECS or EKS anywhere I just get to the customer's choice. And one of the things that I'm excited about as you talk about going up the stack and on the edge are things will certainly outpost. Um, right. So now I'll post those launched last year, but then with the new form factors, uh, and then you look at services like Panorama, right? Being able to take computer vision and embed machine learning and computer vision, and do that as a managed capability at the edge, um, for customers. >>And so we see this across a number of industries. And so what we're really thinking about is customers no longer have to make trade-offs and have to think about those, those choices that they can really deploy, uh, natively in the cloud. And then they can take those capabilities, train those models, and then deploy them where they need to, whether that's on premises or at the edge, you know, whether it be in a factory or retail environment. When we start, I think we're really well positioned when, um, you know, hopefully next year we started seeing the travel industry rebound, um, and the, the need, you know, more than ever really to, uh, to kind of rethink about how we kind of monitor and make those environments safe. Having this kind of capability at the edge is really going to help our customers as, as we come out of this year and hopefully rebound next year. >>Yeah. Chris, I want to go back to you for a second. It's hard to hard to pick your favorite innovation from the keynote, because, you know, just reminded me that Brian just reminded me of some things I forgot happened. It was like a buffet of innovation. Some keynotes have one or two, it was like 20, you got the industrial piece that was huge. Computer vision machine learning. That's just a game changer. The connect thing came out of nowhere, in my opinion, I mean, it's a call center technology. This is boring as hell. What are you gonna do with that? It turns out it's a game changer. It's not about the calls with the contact and that's discern intermediating, um, in the stack as well. So again, a feature that looks old is actually new and relevant. What's your, what was your favorite, um, innovation? >>Uh, it it's, it's, it's hard to say. I will say my personal favorite was the, the maca last. I, I just, I think that is a phenomenal, um, uh, just addition, right? And the fact that AWS is, has worked with Apple to integrate the Nitra chip into, into, uh, you know, the iMac and offer that out. Um, you know, a lot of people are doing development, uh, on for ILS and that stuff. And that there's just gonna be a huge benefit, uh, for the development teams. But, you know, I will say, I'll come back to connect you. You mentioned it. Um, you know, but you're right. It was a, it's a boring area, but it's an area that we've seen huge success with since, since connect was launched and the additional features and the Amazon continues to bring, you know, um, obviously with, with the pandemic and now that, you know, customer engagement through the phone, uh, through omni-channel has just been critical for companies, right. >>And to be able to have those agents at home, working from home versus being in the office, it was a huge, huge advantage for, for several customers that are using connect. You know, we, we did some great stuff with some different customers, but the continue technology, like you said, the, you know, the call translation and during a call to be able to pop up those key words and have a, have a supervisor, listen is awesome. And a lot of that was some of that was already being done, but we were stitching multiple services together. Now that's right out of the box. Um, and that Google's location is only going to make that go faster and make us to be able to innovate faster for that piece of the business. >>It's interesting, you know, not to get all nerdy and, and business school life, but you've got systems of records, systems of engagement. If you look at the call center and the connect thing, what got my attention was not only the model of disintermediating, that part of the engagement in the stack, but what actually cloud does to something that's a feature or something that could be an element, like say, call center, you old days of, you know, calling an 800 number, getting some support you got in chip, you have machine learning, you actually have stuff in the, in the stack that actually makes that different now. So you w you know, the thing that impressed me was Andy was saying, you could have machine learning, detect pauses, voice inflections. So now you have technology making that more relevant and better and different. So a lot going on, this is just one example of many things that are happening from a disruption innovation standpoint. W what do you guys, what do you guys think about that? And is that like getting it right? Can you share it? >>I think, I think, I think you are right. And I think what's implied there and what you're saying, and even in the, you know, the macro S example is the ability if we're talking about features, right. Which by themselves, you're saying, Oh, wow, what's, what's so unique about that, but because it's on AWS and now, because whether you're a developer working on, you know, w with Mac iOS and you have access to the 175 plus services, that you can then weave into your new applications, talk about the connect scenario. Now we're embedding that kind of inference and machine learning to do what you say, but then your data Lake is also most likely running in AWS, right? And then the other channels, whether they be mobile channels or web channels, or in store physical channels, that data can be captured in that same machine learning could be applied there to get that full picture across the spectrum. Right? So that's the, that's the power of bringing together on AWS to access to all those different capabilities of services, and then also the where the data is, and pulling all that together, that for that end to end view, okay, >>You guys give some examples of work you've done together. I know this stuff we've reported on. Um, in the last session we talked about some of the connect stuff, but that kind of encapsulates where this, where this is all going with respect to the tech. >>Yeah. I think one of the, you know, it was called out on Doug's partner summit was, you know, is there a, uh, an SAP data Lake accelerator, right? Almost every enterprise has SAP, right. And SAP getting data out of SAP has always been a challenge, right. Um, whether it be through, you know, data warehouses and AWS, sorry, SAP BW, you know, what we've focused on is, is getting that data when you're on have SAP on AWS getting that data into the data Lake, right. And getting it into, into a model that you can pull the value out of the customers can pull the value out, use those AI models. Um, so that was one thing we worked on in the last 12 months, super excited about seeing great success with customers. Um, you know, a lot of customers had ideas. They want to do this. They had different models. What we've done is, is made it very, uh, simplified, uh, framework that allows customers to do it very quickly, get the data out there and start getting value out of it and iterating on that data. Um, we saw customers are spending way too much time trying to stitch it all together and trying to get it to work technically. Uh, and we've now cut all that out and they can immediately start getting down to, to the data and taking advantage of those, those different, um, services are out there by AWS. >>Brian, you want to weigh in as things you see as relevant, um, builds that you guys done together that kind of tease out the future and connect the dots to what's coming. >>Uh, I, you know, I'm going to use a customer example. Uh, we worked with, um, and it just came out with, with Unilever around their blue air connected, smart air purifier. And what I think is interesting about that, I think it touches on some of the themes we're talking about, as well as some of the themes we talked about in the last session, which is we started that program before the pandemic. Um, and, but, you know, Unilever recognized that they needed to differentiate their product in the marketplace, move to more of a services oriented business, which we're seeing as a trend. We, uh, we enabled this capability. So now it's a smart air purifier that can be remote manage. And now in the pandemic head, they are in a really good position, obviously with a very relevant product and capability, um, to be used. And so that data then, as we were talking about is going to reside on the cloud. And so the learning that can now happen about usage and about, you know, filter changes, et cetera, can find its way back into future iterations of that valve, that product. And I think that's, that's keeping with, you know, uh, Chris was talking about where we might be systems of record, like in SAP, how do we bring those in and then start learning from that data so that we can get better on our future iterations? >>Hey, Chris, on the last segment we did on the business mission, um, session, Andy Taylor from your team, uh, talked about partnerships within a century and working with other folks. I want to take that now on the technical side, because one of the things that we heard from, um, Doug's, um, keynote and that during the partner day was integrations and data were two big themes. When you're in the cloud, technically the integrations are different. You're going to get unique things in the public cloud that you're just not going to get on premise access to other cloud native technologies and companies. How has that, how do you see the partnering of Accenture with people within your ecosystem and how the data and the integration play together? What's your vision? >>Yeah, I think there's two parts of it. You know, one there's from a commercial standpoint, right? So marketplace, you know, you, you heard Dave talk about that in the, in the partner summit, right? That marketplace is now bringing together this ecosystem, uh, in a very easy way to consume by the customers, uh, and by the users and bringing multiple partners together. And we're working with our ecosystem to put more products out in the marketplace that are integrated together, uh, already. Um, you know, I think one from a technical perspective though, you know, if you look at Salesforce, you know, we talked a little earlier about connect another good example, technically underneath the covers, how we've integrated connect and Salesforce, some of it being prebuilt by AWS and Salesforce, other things that we've added on top of it, um, I think are good examples. And I think as these ecosystems, these IFCs put their products out there and start exposing more and more API APIs, uh, on the Amazon platform, make opening it up, having those, those prebuilt network connections there between, you know, the different VPCs and the different areas within, within a customer's network. >>Um, and having them, having that all opened up and connected and having all that networking done underneath the covers. You know, it's one thing to call the API APIs. It's one thing to have access to those. And that's been a big focus of a lot of, you know, ISBNs and customers to build those API APIs and expose them, but having that network infrastructure and being able to stay within the cloud within AWS to make those connections, the past that data, we always talk about scale, right? It's one thing if I just need to pass like a, you know, a simple user ID back and forth, right? That's, that's fine. We're not talking massive data sets, whether it be seismic data or whatever it be passing those of those large, those large data sets between customers across the Amazon network is going to, is going to open up the world. >>Yeah. I see huge possibilities there and love to keep on this story. I think it's going to be important and something to keep track of. I'm sure you guys will be on top of it. You know, one of the things I want to, um, dig into with you guys now is Andy had kind of this philosophy philosophical thing in his keynote, talk about societal change and how tough the pandemic is. Everything's on full display. Um, and this kind of brings out kind of like where we are and the truth. You look at the truth, it's a virtual event. I mean, it's a website and you got some sessions out there with doing remote best weekend. Um, and you've got software and you've got technology and, you know, the concept of a mechanism it's software, it does something, it does a purpose. Essentially. You guys have a concept called living systems where growth strategy powered by technology. How do you take the concept of a, of a living organism or a system and replace the mechanism, staleness of computing and software. And this is kind of an interesting, because we're on the cusp of a, of a major inflection point post COVID. I get the digital transformation being slow that's yes, that's happening. There's other things going on in society. What do you guys think about this living systems concept? >>Yeah, so I, you know, I'll start, but, you know, I think the living system concept, um, you know, it started out very much thinking about how do you rapidly change the system, right? And, and because of cloud, because of, of dev ops, because of, you know, all these software technologies and processes that we've created, you know, that's where it started it, making it much easier to make it a much faster being able to change rapidly, but you're right. I think as you now bring in more technologies, the AI technology self-healing technologies, again, you're hurting Indian in his keynote, talk about, you know, the, the systems and services they're building to the tech problems and, and, and, and give, uh, resolve those problems. Right. Obviously automation is a big part of that living systems, you know, being able to bring that all together and to be able to react in real time to either what a customer, you know, asks, um, you know, either through the AI models that have been generated and turning those AI models around much faster, um, and being able to get all the information that came came in in the last 20 minutes, right. >>You know, society's moving fast and changing fast. And, you know, even in one part of the world, if, um, something, you know, in 10 minutes can change and being able to have systems to react to that, learn from that and be able to pass that on to the next country, especially in this world with COVID and, you know, things changing very quickly with quickly and, and, and, um, diagnosis and, and, um, medical response, all that so quickly to be able to react to that and have systems pass that information learned from that information is going to be critical. >>That's awesome. Brian, one of the things that comes up every year is, Oh, the cloud scalable this year. I think, you know, we've, we've talked on the cube before, uh, years ago, certainly with the censure and Amazon, I think it was like three or four years ago. Yeah. The clouds horizontally scalable, but vertically specialized at the application layer. But if you look at the data Lake stuff that you guys have been doing, where you have machine learning, the data's horizontally scalable, and then you got the specialization in the app changes that changes the whole vertical thing. Like you don't need to have a whole vertical solution or do you, so how has this year's um, cloud news impacted vertical industries because it used to be, Oh, the oil and gas financial services. They've got a team for that. We've got a stack for that. Not anymore. Is it going away? What's changing. Wow. >>I, you know, I think it's a really good question. And I don't think, I think what we're saying, and I was just on a call this morning talking about banking and capital markets. And I do think the, you know, the, the challenges are still pretty sector specific. Um, but what we do see is the, the kind of commonality, when we start looking at the, and we talked about it as the industry solutions that we're building as a partnership, most of them follow the pattern of ingesting data, analyzing that data, and then being able to, uh, provide insights and an actions. Right. So if you think about creating that yeah. That kind of common chassis of that ingest the data Lake and then the machine learning, can you talk about, you know, the announces around SageMaker and being able to manage these models, what changes then really are the very specific industries algorithms that you're, you're, you're writing right within that framework. And so we're doing a lot in connect is a good example of this too, where you look at it. Yeah. Customer service is a horizontal capability that we're building out, but then when you stop it into insurance or retail banking or utilities, there are nuances then that we then extend and build so that we meet the unique needs of those, those industries. And that's usually around those, those models. >>Yeah. And I think this year was the first reinvented. I saw real products coming out that actually solve that problem. And that was their last year SageMaker was kinda moving up the stack, but now you have apps embedding machine learning directly in, and users don't even know it's in there. I mean, Christmas is kind of where it's going. Right. I mean, >>Yeah. Announcements. Right. How many, how many announcements where machine learning is just embedded in? I mean, so, you know, code guru, uh, dev ops guru Panorama, we talked about, it's just, it's just there. >>Yeah. I mean, having that knowledge about the linguistics and the metadata, knowing the, the business logic, those are important specific use cases for the vertical and you can get to it faster. Right. Chris, how is this changing on the tech side, your perspective? Yeah. >>You know, I keep coming back to, you know, AWS and cloud makes it easier, right? None of this stuff, you know, all of this stuff can be done, uh, and has some of it has been, but you know, what Amazon continues to do is make it easier to consume by the developer, by the, by the customer and to actually embedded into applications much easier than it would be if I had to go set up the stack and build it all on that and, and, and, uh, embed it. Right. So it's, shortcutting that process. And again, as these products continue to mature, right. And some of the stuff is embedded, um, it makes that process so much faster. Uh, it makes it reduces the amount of work required by the developers, uh, the engineers to get there. So I I'm expecting, you're going to see more of this. >>Right. I think you're going to see more and more of these multi connected services by AWS that has a lot of the AIML, um, pre-configured data lakes, all that kind of stuff embedded in those services. So you don't have to do it yourself and continue to go up the stack. And we was talking about, Amazon's built for builders, right. But, you know, builders, you know, um, have been super specialized in, or we're becoming, you know, as engineers, we're being asked to be bigger and bigger and to be, you know, uh, be able to do more stuff. And I think, you know, these kinds of integrated services are gonna help us do that >>And certainly needed more. Now, when you have hybrid edge that are going to be operating with microservices on a cloud model, and with all those advantages that are going to come around the corner for being in the cloud, I mean, there's going to be, I think there's going to be a whole clarity around benefits in the cloud with all these capabilities and benefits cloud guru. Thanks my favorite this year, because it just points to why that could happen. I mean, that happens because of the cloud data. If you're on premise, you may not have a little cloud guru, you got to got to get more data. So, but they're all different edge certainly will come into your vision on the edge. Chris, how do you see that evolving for customers? Because that could be complex new stuff. How is it going to get easier? >>Yeah. It's super complex now, right? I mean, you gotta design for, you know, all the different, uh, edge 5g, uh, protocols are out there and, and, and solutions. Right. You know, Amazon's simplifying that again, to come back to simplification. Right. I can, I can build an app that, that works on any 5g network that's been integrated with AWS. Right. I don't have to set up all the different layers to get back to my cloud or back to my, my bigger data side. And I was kind of choking. I don't even know where to call the cloud anymore, big cloud, which is a central and I go down and then I've got a cloud at the edge. Right. So what do I call that? >>Exactly. So, you know, again, I think it is this next generation of technology with the edge comes, right. And we put more and more data at the edge. We're asking for more and more compute at the edge, right? Whether it be industrial or, you know, for personal use or consumer use, um, you know, that processing is gonna get more and more intense, uh, to be able to manage and under a single console, under a single platform and be able to move the code that I develop across that entire platform, whether I have to go all the way down to the, you know, to the very edge, uh, at the, at the 5g level, right? Or all the way into the bigger cloud and how that process, isn't there be able to do that. Seamlessly is going to be allow the speed of development that's needed. >>Well, you guys done a great job and no better time to be a techie or interested in technology or computer science or social science for that matter. This is a really perfect storm, a lot of problems to solve a lot of things, a lot of change happening, positive change opportunities, a lot of great stuff. Uh, final question guys, five years working together now on this partnership with AWS and Accenture, um, congratulations, you guys are in pole position for the next wave coming. Um, what's exciting. You guys, Chris, what's on your mind, Brian. What's, what's getting you guys pumped up >>Again. I come back to G you know, Andy mentioned it in his keynote, right? We're seeing customers move now, right. We're seeing, you know, five years ago we knew customers were going to get a new, this. We built a partnership to enable these enterprise customers to make that, that journey. Right. But now, you know, even more, we're seeing them move at such great speed. Right. Which is super excites me. Right. Because I can see, you know, being in this for a long time, now I can see the value on the other end. And I really, we've been wanting to push our customers as fast as they can through the journey. And now they're moving out of, they're getting, they're getting the religion, they're getting there. They see, they need to do it to change your business. So that's what excites me is just the excites me. >>It's just the speed at which we're, we're in a single movement. Yeah, yeah. I'd agree with, yeah, I'd agree with that. I mean, so, you know, obviously getting, getting customers to the cloud is super important work, and we're obviously doing that and helping accelerate that, it's it, it's what we've been talking about when we're there, all the possibilities that become available right. Through the common data capabilities, the access to the 175 some-odd AWS services. And I also think, and this is, this is kind of permeated through this week at re-invent is the opportunity, especially in those industries that do have an industrial aspect, a manufacturing aspect, or a really strong physical aspect of bringing together it and operational technology and the business with all these capabilities, then I think edge and pushing machine learning down to the edge and analytics at the edge is really going to help us do that. And so I'm super excited by all that possibility is I feel like we're just scratching the surface there, >>Great time to be building out. And you know, this is the time for re reconstruction. Re-invention big themes. So many storylines in the keynote, in the events. It's going to keep us busy here. It's looking at angle in the cube for the next year. Gentlemen, thank you for coming out. I really appreciate it. Thanks. Thank you. All right. Great conversation. You're getting technical. We could've go on another 30 minutes. Lot to talk about a lot of storylines here at AWS. Reinvent 2020 at the Centure executive summit. I'm John furrier. Thanks for watching.

Published Date : Dec 10 2020

SUMMARY :

It's the cube with digital coverage Welcome to cube three 60 fives coverage of the Accenture executive summit. Thanks for having me here. impact of the COVID-19 pandemic has been, what are you hearing from clients? you know, various facets, you know, um, first and foremost, to this reasonably okay, and are, you know, launching to many companies, even the ones who have adapted reasonably well, uh, all the changes the pandemic has brought to them. in the cloud that we are going to see. Can you tell us a little bit more about what this strategy entails? all the systems under which they attract need to be liberated so that you could drive now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's Talk a little bit about how this has changed, the way you support your clients and how That is their employees, uh, because you do, across every department, I'm the agent of this change is going to be the employee's weapon, So how are you helping your clients, And that is again, the power of cloud. And the power of cloud is to get all of these capabilities from outside that employee, the employee will be more engaged in his or her job and therefore And there's this, um, you know, no more true than how So at Accenture, you have long, long, deep Stan, sorry, And through that investment, we've also made several acquisitions that you would have seen in And, uh, they're seeing you actually made a statement that five years from now, Yeah, the future to me, and this is, uh, uh, a fundamental belief that we are entering a new And the evolution that is going to happen where, you know, the human grace of mankind, I genuinely believe that cloud first is going to be in the forefront of that change It's the cube with digital coverage I want to start by asking you what it is that we mean when we say green cloud, So the magnitude of the problem that is out there and how do we pursue a green you know, when companies begin their cloud journey and then they confront, uh, And, uh, you know, We know that in the COVID era, shifting to the cloud has really become a business imperative. uh, you know, from a few manufacturers hand sanitizers and to hand sanitizers, role there, uh, you know, from, in terms of our clients, you know, there are multiple steps And in the third year and another 3 million analytics costs that are saved through right-sizing So that's that instead of it, we practice what we preach, and that is something that we take it to heart. We know that conquering this pandemic is going to take a coordinated And it's about a group of global stakeholders cooperating to simultaneously manage the uh, in, in UK to build, uh, uh, you know, uh, Microsoft teams in What do you see as the different, the financial security or agility benefits to cloud. And obviously the ecosystem partnership that we have that We, what, what do you think the next 12 to 24 months? And we all along with Accenture clients will win. Thank you so much. It's the cube with digital coverage of AWS reinvent executive And what happens when you bring together the scientific And Brian bowhead, global director, and head of the Accenture AWS business group at Amazon Um, and I think that, you know, there's a, there's a need ultimately to, And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. And I think that, you know, that's going to help us make faster, better decisions. Um, and so I think with that, you know, there's a few different, How do we re-imagine that, you know, how do ideas go from getting tested So Arjun, I want to bring you into this conversation a little bit. It was, uh, something that, you know, we had all to do differently. And maybe the third thing I would say is this one team And what I think ultimately has enabled us to do is it allowed us to move And I think if you really think about what he's talking about, Because the old ways of thinking where you've got application people and infrastructure, How will their experience of work change and how are you helping re-imagine and And it's something that, you know, I think we all have to think a lot about, I mean, And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are very Uh, and so I think that that's, you know, one, one element that, uh, can be considered. or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently the customer obsession and this idea of innovating much more quickly. and Carl mentioned some of the things that, you know, partner like AWS can bring to the table is we talk a lot about builders, And it's not just the technical people or the it people who are you know, some decisions, what we call it at Amazon or two-way doors, meaning you can go through that door, And so we chose, you know, uh, with our focus on innovation Jen, I want you to close this out here. sort of been great for me to see is that when people think about cloud, you know, Well, thank you so much. Yeah, it's been fun. And thank you for tuning into the cube. It's the cube with digital coverage Matthew, thank you for joining us. and also what were some of the challenges that you were grappling with prior to this initiative? Um, so the reason we sort of embarked So what was the main motivation for, for doing, um, you know, certainly as a, as an it leader and some of my operational colleagues, What is the art of the possible, can you tell us a little bit about why you the public sector that, you know, there are many rules and regulations quite rightly as you would expect Matthew, I want to bring you into the conversation a little bit here. to bring in a number of the different teams that we have say, cloud teams, security teams, um, I mean, so much of this is about embracing comprehensive change to experiment and innovate and Um, rather than just, you know, trying to pick It's not always a one size fits all. Obviously, you know, today what we believe is critical is making sure that we're creating something that met the forces needs, So to give you a little bit of, of context, when we, um, started And the pilot was so successful. And I think just parallel to that is the quality of our, because we had a lot of data, Seen that kind of return on investment, because what you were just describing with all the steps that we needed Um, but all the, you know, the minutes here and that certainly add up Have you seen any changes Um, but you can see the step change that is making in each aspect to the organization, And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain You know, we had lots of workshops and seminars where we all talk about, you know, see, you know, to see the stat change, you know, and, and if we, if we have any issues now it's literally, when you are trying to get everyone on board for this kind of thing? The solution itself is, um, you know, extremely large and, um, I want to hear, where do you go from here? But so, because it's apparently not that simple, but, um, you know, And I see now that we have good at embedded in operational policing for me, this is the start of our journey, in particular has brought it together because you know, COVID has been the accelerant So a number of years back, we, we looked at kind of our infrastructure in our landscape trying to figure uh, you know, start to deliver bit by bit incremental progress, uh, to get to the, of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually I want to just real quick, a redirect to you and say, you know, if all the people said, Oh yeah, And, um, you know, Australia, we had to live through Bush fires You know, we're going to get the city, you get a minute on specifically, but from your perspective, uh, Douglas, to hours and days, and, and truly allowed us to, we had to, you know, VJ things, And what specifically did you guys do at Accenture and how did it all come one of the key things that, uh, you know, we learned along this journey was that, uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment How did you address your approach to the cloud and what was your experience? And then building upon it, and then, you know, partnering with Accenture allows because the kind of, uh, you know, digital transformation, cloud transformation, learnings, um, that might different from the expectation we all been there, Hey, you know, It's, it's getting that last bit over the line and making sure that you haven't been invested in the future hundred percent of the time, they will say yes until you start to lay out to them, okay, You know, the old expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, Um, you know, that's all stood up on AWS and is a significant portion of And I think our next big step is going to be obviously, So, um, you know, having a lot of that legwork done for us and an AWS gives you that, And obviously our, our CEO globally is just spending, you know, announcement about a huge investment that we're making in cloud. a lot of people kind of going through the same process, knowing what you guys know now, And we had all of our people working remotely, um, within, uh, you know, effectively one business day. So, um, you know, one example where you're able to scale and, uh, And this is really about you guys when they're actually set up for growth, um, and actually allows, you know, a line to achievements I really appreciate you coming. to figure out how we unlock that value, um, you know, drive our costs down efficiency, to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with There's got to say like e-learning squares, right, for me around, you know, It is tough, but, uh, uh, you know, you got to get started on it. It's the cube with digital coverage of Thank you so much for coming on the show, Johan you're welcome. their proper date, not just a day, but also the date you really needed that we did probably talked about So storing the data we should do as efficiently possibly can. Or if you started working with lots of large companies, you need to have some legal framework around some framework around What were some of the things you were trying to achieve with the OSU? So the first thing we did is really breaking the link between the application, And then you can export the data like small companies, last company, standpoint in terms of what you were trying to achieve with this? a lot of goods when we started rolling out and put in production, the old you are three and bug because we are So one of the other things that we talk a lot about here on the cube is sustainability. I was, you know, also do an alternative I don't mean to move away from that, but with sustainability, in addition to the benefits purchases for 51 found that AWS performs the same task with an So that customers benefit from the only commercial cloud that's hat hits service offerings and the whole industry, if you look it over, look at our companies are all moving in. objective is really in the next five years, you will become the key backbone It's the cube with digital coverage And obviously, you know, we have in the cloud, uh, you know, with and exhibition of digital transformation, you know, we are seeing the transformation or I want to go to you now trust and tell us a little bit about how mine nav works and how it helps One of the big focus now is to accelerate. having to collaborate, uh, not in real life. They realize that now the cloud is what is going to become important for them to differentiate. Keisha, I want to talk with you now about my navs multiple capabilities, And one of the things that we did a lot of research we found out is that there's an ability to influence So Tristan, tell us a little bit about how this capability helps clients make greener on renewable energy, some incredibly creative constructs on the how to do that. Would you say that it's catching on in the United States? And we have seen case studies and all Keisha, I want to bring you back into the conversation. And with the digital transformation requiring cloud at scale, you know, we're seeing that in And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need This enabled the client to get started, knowing that there is a business Have you found that at all? What man I gives the ability is to navigate through those, to start quickly. Kishor I want to give you the final word here. and we are, you know, achieving client's static business objectives while Any platform that can take some of the guesswork out of the future. It's the cube with digital coverage of And Andy T a B G the M is essentially Amazon business group lead managing the different pieces so I can move more quickly, uh, you know, And then, you know, that broadens our capability from just a technical discussion to It's not like it's new to you guys. the cloud, um, you know, that leaves 96 percentile now for him. And so I think, I think, you know, when you, when you think of companies out there faced with these challenges, have you seen for the folks who have done that? And at the end you can buy a lawn. it along with the talent and change pieces, which are also so important as you make What's the success factors that you see, a key success factor for these end to end transformations is not just the leaders, but you And so that takes me to perhaps the second point, which is the culture, um, it's important, Because I think, you know, as you work backwards from the customers, to the, you know, speed to insights, how'd you get them decomposing, uh, their application set and the top line is how do you harden that and protect that with, um, You know, the business model side, obviously the enablement is what Amazon has. And that we, if you think of that from the partnership, And if you hear Christophe Weber from Takeda talk, that need to get built and build that library by doing that, we can really help these insurance companies strategy you guys have to attract and attain the best and retain the people. Um, you know, it's, it's, um, it's an interesting one. I just say, you guys have a great team over there. um, uh, you know, capability set that will help enable him to and transformations as Brian And then number four is really about, you know, how do we, um, extend We got to get to the final question for you guys to weigh in on, and that's going to have the industry, um, you know, focus. Consume the latest and greatest of AWS as capabilities and, you know, in the areas of machine learning and analytics, as you know, the technology invention, um, comes out and continues to sort of I want to say thank you to you guys, because I've reported a few times some stories Thanks for coming on. at Atrius reinvent 2020 I'm John for your host. It's the cube with digital coverage of the century executive summit, where all the thought leaders going to extract the signal from the nose to share with you their perspective And I know compute is always something that, you know, over there, you know, small little team he's on the front and front stage. And one of the things that I'm excited about as you talk about going up the stack and on the edge are things will um, and the, the need, you know, more than ever really to, uh, to kind of rethink about because, you know, just reminded me that Brian just reminded me of some things I forgot happened. uh, you know, the iMac and offer that out. And a lot of that was some of that was already being done, but we were stitching multiple services It's interesting, you know, not to get all nerdy and, and business school life, but you've got systems of records, and even in the, you know, the macro S example is the ability if we're talking about features, Um, in the last session we talked And getting it into, into a model that you can pull the value out of the customers can pull the value out, that kind of tease out the future and connect the dots to what's coming. And I think that's, that's keeping with, you know, uh, Chris was talking about where we might be systems of record, Hey, Chris, on the last segment we did on the business mission, um, session, Andy Taylor from your team, So marketplace, you know, you, you heard Dave talk about that in the, in the partner summit, It's one thing if I just need to pass like a, you know, a simple user ID back and forth, You know, one of the things I want to, um, dig into with you guys now is in real time to either what a customer, you know, asks, um, you know, of the world, if, um, something, you know, in 10 minutes can change and being able to have the data's horizontally scalable, and then you got the specialization in the app changes And so we're doing a lot in connect is a good example of this too, where you look at it. And that was their last year SageMaker was kinda moving up the stack, but now you have apps embedding machine learning I mean, so, you know, code guru, uh, dev ops guru Panorama, those are important specific use cases for the vertical and you can get None of this stuff, you know, all of this stuff can be done, uh, and has some of it has been, And I think, you know, these kinds of integrated services are gonna help us do that I mean, that happens because of the cloud data. I mean, you gotta design for, you know, all the different, um, you know, that processing is gonna get more and more intense, uh, um, congratulations, you guys are in pole position for the next wave coming. I come back to G you know, Andy mentioned it in his keynote, right? I mean, so, you know, obviously getting, getting customers to the cloud is super important work, And you know, this is the time for re reconstruction.

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Ed Walsh, ChaosSearch | AWS re:Invent 2020 Partner Network Day


 

>> Narrator: From around the globe it's theCUBE, with digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS Global Partner Network. >> Hello and welcome to theCUBE Virtual and our coverage of AWS re:Invent 2020 with special coverage of APN partner experience. We are theCUBE Virtual and I'm your host, Justin Warren. And today I'm joined by Ed Walsh, CEO of ChaosSearch. Ed, welcome to theCUBE. >> Well thank you for having me, I really appreciate it. >> Now, this is not your first time here on theCUBE. You're a regular here and I've loved it to have you back. >> I love the platform you guys are great. >> So let's start off by just reminding people about what ChaosSearch is and what do you do there? >> Sure, the best way to say is so ChaosSearch helps our clients know better. We don't do that by a special wizard or a widget that you give to your, you know, SecOp teams. What we do is a hard work to give you a data platform to get insights at scale. And we do that also by achieving the promise of data lakes. So what we have is a Chaos data platform, connects and indexes data in a customer's S3 or glacier accounts. So inside your data lake, not our data lake but renders that data fully searchable and available for analysis using your existing tools today 'cause what we do is index it and publish open API, it's like API like Elasticsearch API, and soon SQL. So give you an example. So based upon those capabilities were an ideal replacement for a commonly deployed, either Elasticsearch or ELK Stack deployments, if you're hitting scale issues. So we talk about scalable log analytics, and more and more people are hitting these scale issues. So let's say if you're using Elasticsearch ELK or Amazon Elasticsearch, and you're hitting scale issues, what I mean by that is like, you can't keep enough retention. You want longer retention, or it's getting very expensive to keep that retention, or because the scale you hit where you have availability, where the cluster is hard to keep up running or is crashing. That's what we mean by the issues at scale. And what we do is simply we allow you, because we're publishing the open API of Elasticsearch use all your tools, but we save you about 80% off your monthly bill. We also give you an, and it's an and statement and give you unlimited retention. And as much as you want to keep on S3 or into Glacier but we also take care of all the hassles and management and the time to manage these clusters, which ends up being on a database server called leucine. And we take care of that as a managed service. And probably the biggest thing is all of this without changing anything your end users are using. So we include Kibana, but imagine it's an Elastic API. So if you're using API or Kibana, it's just easy to use the exact same tools used today, but you get the benefits of a true data lake. In fact, we're running now Elasticsearch on top of S3 natively. If that makes it sense. >> Right and natively is pretty cool. And look, 80% savings, is a dramatic number, particularly this year. I think there's a lot of people who are looking to save a few quid. So it'd be very nice to be able to save up to 80%. I am curious as to how you're able to achieve that kind of saving though. >> Yeah, you won't be the first person to ask me that. So listen, Elastic came around, it was, you know we had Splunk and we also have a lot of Splunk clients, but Elastic was a more cost effective solution open source to go after it. But what happens is, especially at scale, if it's fall it's actually very cost-effective. But underneath last six tech ELK Stack is a leucine database, it's a database technology. And that sits on our servers that are heavy memory count CPU count in and SSDs. So you can do on-prem or even in the clouds, so if you do an Amazon, basically you're spinning up a server and it stays up, it doesn't spin up, spin down. So those clusters are not one server, it's a cluster of those servers. And typically if you have any scale you're actually having multiple clusters because you don't dare put it on one, for different use cases. So our savings are actually you no longer need those servers to spin up and you don't need to pay for those seen underneath. You can still use Kibana under API but literally it's $80 off your bill that you're paying for your service now, and it's hard dollars. So it's not... And we typically see clients between 70 and 80%. It's up to 80, but it's literally right within a 10% margin that you're saving a lot of money, but more importantly, saving money is a great thing. But now you have one unified data lake that you can have. You used to go across some of the data or all the data through the role-based access. You can give different people. Like we've seen people who say, hey give that, help that person 40 days of this data. But the SecOp up team gets to see across all the different law. You know, all the machine generated data they have. And we can give you a couple of examples of that and walk you through how people deploy if you want. >> I'm always keen to hear specific examples of how customers are doing things. And it's nice that you've thought of drawn that comparison there around what what cloud is good for and what it isn't is. I'll often like to say that AWS is cheap to fail in, but expensive to succeed. So when people are actually succeeding with this and using this, this broad amount of data so what you're saying there with that savings I've actually got access to a lot more data that I can do things with. So yeah, if you could walk through a couple of examples of what people are doing with this increased amount of data that they have access to in EKL Search, what are some of the things that people are now able to unlock with that data? >> Well, literally it's always good for a customer size so we can go through and we go through it however it might want, Kleiner, Blackboard, Alert Logic, Armor Security, HubSpot. Maybe I'll start with HubSpot. One of our good clients, they were doing some Cloud Flare data that was one of their clusters they were using a lot to search for. But they were looking at to look at a denial service. And they were, we find everyone kind of at scale, they get limited. So they were down to five days retention. Why? Well, it's not that they meant to but basically they couldn't cost-effectively handle that in the scale. And also they're having scale issues with the environment, how they set the cluster and sharding. And when they also denial service tech, what happened that's when the influx of data that is one thing about scale is how fast it comes out, yet another one is how much data you have. But this is as the data was coming after them at denial service, that's when the cluster would actually go down believe it or not, you know right. When you need your log analysis tools. So what we did is because they're just using Kibana, it was easy swap. They ran in parallel because we published the open API but we took them from five days to nine days. They could keep as much as they want but nine days for denial services is what they wanted. And then we did save them in over $4 million a year in hard dollars, What they're paying in their environment from really is the savings on the server farm and a little bit on the Elasticsearch Stack. But more importantly, they had no outages since. Now here's the thing. Are you talking about the use case? They also had other clusters and you find everyone does it. They don't dare put it on one cluster, even though these are not one server, they're multiple servers. So the next use case for CloudFlare was one, the next QS and it was a 10 terabyte a day influx kept it for 90 days. So it's about a petabyte. They brought another use case on which was NetMon, again, Network Monitoring. And again, I'm having the same scale issue, retention area. And what they're able to do is easily roll that on. So that's one data platform. Now they're adding the next one. They have about four different use cases and it's just different clusters able to bring together. But now what they're able to do give you use cases either they getting more cost effective, more stability and freedom. We say saves you a lot of time, cost and complexity. Just the time they manage that get the data in the complexities around it. And then the cost is easy to kind of quantify but they've got better but more importantly now for particular teams they only need their access to one data but the SecOP team wants to see across all the data. And it's very easy for them to see across all the data where before it was impossible to do. So now they have multiple large use cases streaming at them. And what I love about that particular case is at one point they were just trying to test our scale. So they started tossing more things at it, right. To see if they could kind of break us. So they spiked us up to 30 terabytes a day which is for Elastic would even 10 terabytes a day makes things fall over. Now, if you think of what they just did, what were doing is literally three steps, put your data in S3 and as fast as you can, don't modify, just put it there. Once it's there three steps connect to us, you give us readability access to those buckets and a place to write the indexy. All of that stuff is in your S3, it never comes out. And then basically you set up, do you want to do live or do you want to do real time analysis? Or do you want to go after old data? We do the rest, we ingest, we normalize the schema. And basically we give you our back and the refinery to give the right people access. So what they did is they basically throw a whole bunch of stuff at it. They were trying to outrun S3. So, you know, we're on shoulders of giants. You know, if you think about our platform for clients what's a better dental like than S3. You're not going to get a better cross curve, right? You're not going to get a better parallelism. And so, or security it's in your, you know a virtual environment. But if you... And also you can keep data in the right location. So Blackboard's a good example. They need to keep that in all the different regions and because it's personal data, they, you know, GDPR they got to keep data in that location. It's easy, we just put compute in each one of the different areas they are. But the net net is if you think that architecture is shoulders of giants if you think you can outrun by just sheer volume or you can put in more cost-effective place to keep long-term or you think you can out store you have so much data that S3 and glacier can't possibly do it. Then you got me at your bigger scale at me but that's the scale we'r&e talking about. So if you think about the spiked our throughput what they really did is they try to outrun S3. And we didn't pick up. Now, the next thing is they tossed a bunch of users at us which were just spinning up in our data fabric different ways to do the indexing, to keep up with it. And new use cases in case they're going after everyone gets their own worker nodes which are all expected to fail in place. So again, they did some of that but really they're like you guys handled all the influx. And if you think about it, it's the shoulders of giants being on top of an Amazon platform, which is amazing. You're not going to get a more cost effective data lake in the world, and it's continuing to fall in price. And it's a cost curve, like no other, but also all that resiliency, all that security and the parallelism you can get, out of an S3 Glacier is just a bar none is the most scalable environment, you can build an environment. And what we do is a thin layer. It's a data platform that allows you to have your data now fully searchable and queryable using your tools >> Right and you, you mentioned there that, I mean you're running in AWS, which has broad experience in doing these sorts of things at scale but on that operational management side of things. As you mentioned, you actually take that off, off the hands of customers so that you run it on their behalf. What are some of the areas that you see people making in trying to do this themselves, when you've gone into customers, and brought it into the EKL Search platform? >> Yeah, so either people are just trying their best to build out clusters of Elasticsearch or they're going to services like Logz.io, Sumo Logic or Amazon Elasticsearch services. And those are all basically on the same ELK Stack. So they have the exact same limits as the same bits. Then we see people trying to say, well I really want to go to a data lake. I want to get away from these database servers and which have their limits. I want to use a data Lake. And then we see a lot of people putting data into environments before they, instead of using Elasticsearch, they want to use SQL type tools. And what they do is they put it into a Parquet or Presto form. It's a Presto dialect, but it into Parquet and structure it. And they go a lot of other way to, Hey it's in the data lake, but they end up building these little islands inside their data lake. And it's a lot of time to transform the data, to get it in a format that you can go after our tools. And then what we do is we don't make you do that. Just literally put the data there. And then what we do is we do the index and a polish API. So right now it's Elasticsearch in a very short time we'll publish Presto or the SQL dialect. You can use the same tool. So we do see people, either brute forcing and trying their best with a bunch of physical servers. We do see another group that says, you know, I want to go use an Athena use cases, or I want to use a there's a whole bunch of different startups saying, I do data lake or data lake houses. But they are, what they really do is force you to put things in the structure before you get insight. True data lake economics is literally just put it there, and use your tools natively to go after it. And that's where we're unique compared to what we see from our competition. >> Hmm, so with people who have moved into ChaosSearch, what's, let's say pick one, if you can, the most interesting example of what people have started to do with, with their data. What's new? >> That's good. Well, I'll give you another one. And so Armor Security is a good one. So Armor Security is a security service company. You know, thousands of clients doing great I mean a beautiful platform, beautiful business. And they won Rackspace as a partner. So now imagine thousand clients, but now, you know massive scale that to keep up with. So that would be an example but another example where we were able to come in and they were facing a major upgrade of their environment just to keep up, and they expose actually to their customers is how their customers do logging analytics. What we're able to do is literally simply because they didn't go below the API they use the exact same tools that are on top and in 30 days replaced that use case, save them tremendous amount of dollars. But now they're able to go back and have unlimited retention. They used to restrict their clients to 14 days. Now they have an opportunity to do a bunch of different things, and possible revenue opportunities and other. But allow them to look at their business differently and free up their team to do other things. And now they're, they're putting billing and other things into the same environment with us because one is easy it's scale but also freed up their team. No one has enough team to do things. And then the biggest thing is what people do interesting with our product is actually in their own tools. So, you know, we talk about Kibana when we do SQL again we talk about Looker and Tableau and Power BI, you know, the really interesting thing, and we think we did the hard work on the data layer which you can say is, you know I can about all the ways you consolidate the performance. Now, what becomes really interesting is what they're doing at the visibility level, either Kibana or the API or Tableau or Looker. And the key thing for us is we just say, just use the tools you're used to. Now that might be a boring statement, but to me, a great value proposition is not changing what your end users have to use. And they're doing amazing things. They're doing the exact same things they did before. They're just doing it with more data at bigger scale. And also they're able to see across their different machine learning data compared to being limited going at one thing at a time. And that getting the correlation from a unified data lake is really what we, you know we get very excited about. What's most exciting to our clients is they don't have to tell the users they have to use a different tool, which, you know, we'll decide if that's really interesting in this conversation. But again, I always say we didn't build a new algorithm that you going to give the SecOp team or a new pipeline cool widget that going to help the machine learning team which is another API we'll publish. But basically what we do is a hard work of making the data platform scalable, but more importantly give you the APIs that you're used to. So it's the platform that you don't have to change what your end users are doing, which is a... So we're kind of invisible behind the scenes. >> Well, that's certainly a pretty strong proposition there and I'm sure that there's plenty of scope for customers to come and and talk to you because no one's creating any less data. So Ed, thanks for coming out of theCUBE. It's always great to see you here. >> Know, thank you. >> You've been watching theCUBE Virtual and our coverage of AWS re:Invent 2020 with special coverage of APN partner experience. Make sure you check out all our coverage online, either on your desktop, mobile on your phone, wherever you are. I've been your host, Justin Warren. And I look forward to seeing you again soon. (soft music)

Published Date : Dec 3 2020

SUMMARY :

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Tomer Levy, Logz.io | AWS re:Invent 2020


 

>> Narrator: From around the globe it's theCUBE with digital coverage of AWS reinvent 2020. Sponsored by Intel, AWS and our community partners. >> All right, you're continuing coverage of AWS reinvent 2020 virtual event. We get the pleasure of covering this show like no other AWS reinvent. We are pulling in from the other side of the world Tomer Levy, CEO of Logz.io. First time Cuber so we're going to ease them into it but it's going to be a great conversation. I'm Keith Townsend at CTO advisor. Tomer, welcome to the show. >> Keith, thank you for having me. I'm super excited to be here. >> You know what? We love having founders here on theCUBE. We have a long history of having deep conversations with builders and we're probably the show for builders. AWS reinvent is virtual. However, I think the spirit of re-invent is highlighted in companies like this. We've seen a lot of observability companies sprout up around the industry. AWS is a big, big magnet for these types of solutions. What's the assets Logz.io and how are you guys differentiating yourselves in this crowded space? >> Yeah, absolutely Keith you see observability is so fundamental to building applications on AWS that as companies develop more applications, they have to have solid observability. And we have a mission and our mission is to enable develop engineers and any engineer out there to use open source to run their observability. So when we were developers we wanted to use open source but we had to compromise on a proprietary solution. We decided to build the company so engineers can use the observability tools they're already using for logging, for metrics, for tracing, Whatever they're already using we want to enable them to use that at scale on AWS. So it's easy to use, it's super smart and the data is coordinated. And I think fundamentally it's what we're doing very differently in the market. There is no other company in the market today that takes the best open sources and bring them together as one super strong platform and we're proud to be that company. >> Well, when you say there's no other company doing open source the way that you guys are doing it, that really intrigues me especially as we look at this from the angle of Cooper Netties, the CEO of the leading virtualization company called Kubernetes, the doubts home of the internet. How do you see the intersection of opensource observability in kubernetes especially in the public cloud? >> Yeah, for sure. People say that kubernetes is almost the operating system of the future and why do people use kubernetes? They use it to make sure they can run multiple microservices. They can take their application which used to be a monolith and put it in a distributed way. So it becomes so much harder to monitor or to troubleshoot even to secure applications. So the way we built Logz.io was really designed for companies that are moving into the cloud, companies moving into kubernetes, into microservices and by having logs and metrics and traces all work together through the best open sources. I think we can help customers really get the visibility and just accelerate the software delivery. Just provide better service to their customers. >> So Levy, walk me through that journey. What is it like for a developer to come from their traditional open source roots and enter the cloud where they're melding public cloud services in AWS alongside their tools that they're using in observability. How do you help ease that transition? >> Yeah, absolutely Keith because one of the main drivers for companies adopting tools like Logz.io is actually the migration to AWS. So imagine now migration to a new ground, what do you have to think about first? Do I have the glasses? Can I see what's going on? Like when I see what's going on, I feel more confident. So if I'm now using, let's call it elk or using the open-source Grafana or using tools like Jaeger, which are all open sources too that we offer as part of our platform. So when I use these tools I'm using them to get visibility into my own application, my own infrastructure. So Logz.io faster transition to Logz.io is super easy. This is the whole notion of having an open source compatible platform. So I want to move to Loz.io, everything that worked with my open source currently still works with Logz.io but now when you move to the cloud Logz.io on AWS, we have a very strong relationship so all the services are automatically monitored. You have pre-configured dashboard, everything is interconnected so just when I jump into the AWS platform I immediately get visibility of my existing apps and of the AWS infrastructure. And that eventually helped me become confident, grow and deliver faster on AWS. >> So again this is a conference full of builders but you used the term devOps. We're starting to see a bleeding of DevOps and builders or operations and builders come together. One of the big trans and DevOps and observability is AI and machine learning. What are some of the features of AI and Machine Learning you guys are bringing to bear to this market? >> Yeah, listen I'm a big believer in AI. You know, the amount of data that companies like Logz.io have to ingest and our customers have to process. It's just something a human being cannot possibly understand. It's like billions and millions of lines of data. So this is where we bring machines to help humans. I'll give you one example, right? If you're a DevOps engineer and you see an issue in your logs, what do you do? You usually copy that and putting it into Google and you'll end up on stack overflow, maybe on GitHub, maybe on another website. What we have done is we've scraped the web and we have learned from any user on our platform. So we actually know which log line is important and which one is not. So when companies send a log line, our AI automatically scans it and says, "Hey, here are the billion log lines. No one cares about but here is one that you should really look at right now because either you know half a million people that were searching for it. There are 7,000 alerts on this and it just happened to you. Keith look, maybe you should jump in and look at that". This is where AI makes us just better operate or better DevOp people and not kind of try to replace us. >> So I'm a technical founder, you're a technical founder, theCUBE loves supporting founders. One of the advantages of being the CEO of your company is that you get to decide the culture and the mission of your company. Talk to me about the people side of your organization and how you're making a change for the better. >> Yeah, absolutely. You know, it is a privilege and to the privilege to start and come with a mission that you want to change something in the world and we were just two developers, a staff, my co-founder and myself having to use a product we didn't want to use and you know still really wanted to use an open source product. So we said let's build the company around that and this is kind of set the mission for the company as the company evolved, so is our mission. It evolves from logging to monitoring, to tracing and we also added a cloud SIEM solution all based on open source. So we're going to DevOps engineers and any engineers and we tag any engineer we tell them, "Hey, you can use the best open source tools in the cloud is one platform without compromising". And that's something that really is very differentiated today and I'm very humbled and excited to be part of this journey and I think the team at Logz.io is as well. >> You know I'm always intrigued about this journey to the cloud. Security is one of these things that intrigues me especially as we look at something as mature in the way open source. We often associate open source with public cloud, cloud native but open source is as old as technology itself. So there is a lot of practices that we bring from legacy, traditional infrastructures into the public cloud. So talk to me about that transition of security and security models? How does observability help to either take our existing tools and migrate them to the public cloud or adopt all new cloud native tools in the public cloud? >> Yeah, for sure. I think security is probably together with observability. One of the top priority that when you think about CTOs and VP of Engineering and CSOs, they're concerned about. So we've taken the observability path and bringing better glasses to our users and then on the security side there's a whole market called the SIEM market where companies look at detecting threats, investigating them and most of these tools were that companies use our legacy, incumbents and for design on their own premises world. And are not really a fit for the dynamic world of kubernetes and the cloud. And this is when we decided a couple of years ago to launch a product in that space and today this product is extremely successful. We have customers protecting their AWS environments across the board. So basically with one product for observability, you can with a single checkbox enable security and then you can detect threats. You can look at kind of the common pitfalls of AWS environment and how you can avoid them. And eventually when you see a threat, you can use our tool to investigate and find the root cause in a tool which was designed on AWS for AWS. And it's really designed for the kind of the native cloud environment rather than the on-premise as well. >> Now, is there an integration between the AI ML law of management and the threat management solutions from our observability perspective? >> Yeah, for sure. This is the beauty, it's all one data platform. So customers ship their data, loads, metrics and traces into one place and then we start to look at how can we provide more value on the data, right? How can we look at the logs from an operational perspective and tell you, "Hey, your production might be going down because of a production risks or maybe we can provide you threat intelligence". We can enrich the data and tell you, "Hey, we think you're undergoing an attack right now". So this is all done by users and it is all enraged by AI that provides more visibility, more enrichment of the data and just advice on where to look. >> So Tomer levy, CEO, founder of Logz.io. You're now a few belong. Thank you for joining the show. I hope you have a very successful AWS reinvent. Speaking of AWS reinvent, theCUBE's nonstop coverage of AWS reinvent continues. Watch some of the world's greatest builders, innovators get challenged on their vision and for us to understand and appreciate the work that's been done in this dynamic community. Continue to watch this coverage and more. Talk to you next interview on the CUBE's coverage, of AWS reinvent 2020. (soft music)

Published Date : Dec 2 2020

SUMMARY :

the globe it's theCUBE We are pulling in from the I'm super excited to be here. around the industry. differently in the market. doing open source the way So the way we built Logz.io and enter the cloud where is actually the migration to AWS. One of the big trans and You know, the amount of data One of the advantages of in the world and we were in the way open source. One of the top priority that more enrichment of the data on the CUBE's coverage,

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Liz Dennett, AWS and Johan Krebbers, Shell | AWS Executive Summit 2020


 

>> Narrator: From around the globe, it's theCUBE. With digital coverage of AWS Reinvent Executive Summit 2020. Sponsored by Accenture and AWS. >> Welcome everyone to theCUBE virtual coverage of the Accenture Executive Summit part of AWS Re-invent 2020. I'm your host, Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First, we have Johan Krebbers. He is the GM Digital Emerging Technologies and VP of IT Innovation at Shell. Thank you so much for coming on the show, Johan. >> You're welcome. >> Rebecca: And next we have Liz Dennett. She is the Lead Solution Architect for OSDU on AWS. Thank you so much Liz. >> Happy to be here. >> So I want to start our conversation by talking about OSDU. Like so many great innovations, it started with a problem. Johann, what was the problem you were trying to solve at Shell? >> Yeah, let's go back a couple of the years. We started summer 2017, where we had a meeting with the guys from exploration in Shell. And the main problem they had of course they got lots and lots of data, but aren't unable to find the right data they need to work from. Well the data was scattered and is scattered, it was scattered it's all over the place. And so the real problem trying to solve is how that person working in exploration could find their proper data, not just the data also the data really needed. That's what we probably talked about in summer 2017. And we said, "Okay, the only way we see this moving forward is to start pulling that data into a single data platform." And that was at the time that we called it OSDU, the Open Subsurface Data Universe, and that was what the Shell name was. So, in January 2018, we start a project with Amazon to start creating and confronting the building that OSDU environment, that subservient the universe. So that single data platform to put all your exploration and wealth data into a single environment that was the intent. And then we said, already in March of that same year, we said, 'Well, from a Shell point of view, we would be far better off if we could make this an industry solution and not just a Shell solution." Because Shell will be, if you can make this an industry solution, but people start developing applications for it also, it's far better than for Shell to say, we have it Shell special solution. Because we don't make money out of how we store the data we can make money out of we have access to the data, we can exploit the data. So storing the data, we should do as efficiently possibly can. So in March we reached out to about eight or nine other large oil and gas operators, like the ECONOS, like the Totals, like the Chevrons of this world they said, "Hey, we in Shell are doing this, do you want to join this effort?" And to our surprise, they all said yes. And then in September 2018 we had our kick-off meeting with the open group, where we said, "Okay, if you want to work together with lots of other companies, we also need to look a bit at how we organize that." Because if you start working with lots of large companies you need to have some legal framework around it. So that's why, we went to the open group and said," Okay, let's form the OSDU forum." As we call it at the time. So in September, 2018 where I had a Galleria in Houston we had a kick off meeting for the OSDU forum with about 10 members at the time. So there's, just over two years ago, we started to exercise formally we called it OSDU, we kicked it off. And so that's really where we coming from and how we got there also. >> The origin story. >> Yes. >> What, so what, digging a little deeper there, what were some of the things you were trying to achieve with the OSDU? >> Well, a couple of things we've tried to achieve with OSDU. First is really separating data from applications. But what is the biggest problem we have in the subsurface space that the data and applications are all interlinked. They are all tied together and if you have then a new company coming along and say, "I have this new application, and needs access to the data." That is not possible because the data often interlinked with the application. The first thing we did is, really breaking the link between the application and the data. So that was the first thing we did. Secondly, put all the data to a single data platform, take the silos out because what was happening in the subsurface space I mean, they got all the data in what we call silos, in small little islands out there. So we try to do is, first, break the link. Two, create, put the data in a single data platform. And then third part, put a standard layer on top of that the same API layer on top of the created platform so we could create an ecosystem out of companies to start developing software applications on top of that data platform. Because you might have a data platform, but you aren't successful if you have a rich ecosystem of people start developing applications on top of that. And then you can exploit the data like small companies, large companies, universities, you name it. But you have to create an ecosystem out of there. So the three things was, first break the link between the application data, just break it and put data at the center. And also make sure that data, this data structure would not be managed by one company. But it would be managed the data structures, by the OSDU forum. Secondly then, put the data, single data platform. Thirdly then, have an API layer on top and then create an ecosystem, really go for people, say, "Please start developing applications." Because now you have access to the data, because the data is no longer linked to somebody's application was all freely available for an API layer. That was all September, 2018, more or less. >> Liz I want to bring you, in here a little bit. >> Yeah. >> Can you talk a little bit some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? >> Yeah, absolutely. And this whole thing is Johan said, started with a challenge that was really brought out at Shell. The challenges that geoscientists spend up to 70% of their time looking for data. I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out, how we could address that one problem, we worked together to really understand the root cause of these challenges. And working backwards from that use case, OSDU and OSDU on AWS has really enabled customers to create solutions that span not just this in particular problem. But can really scale to be inclusive of the entire energy value chain and deliver value from these used cases to the energy industry and beyond. >> Thank you. Johan, so talk a little bit about Accenture's Cloud First approach and how it has helped Shell work faster and better with speed. >> Well, of course Accenture Cloud First approach, really works together with Amazon environment, AWS environment. So we really look at Accenture and Amazon together, helping Shell in this space. Now the combination of the two is what we're really looking at where access of course can bring business knowledge to that environment, operate support knowledge to an environment and of course Amazon will be bring that to this environment, that underpinning services, et cetera. So we would expect of that combination, a lot of goods when we started rolling out in production, the other two or three environment. And probably our aim is, when a release fee comes to the market, in Q1 next year of OSDU have already started going out in production inside Shell. But as the first OSDU release which is ready for prime time production across an enterprise. Well we have released our one just before Christmas, last year, released two in May of this year. But release three is the first release we want to use for full scale production and deployment inside Shell and also all the operators around the world. And there is what Amazon, sorry and there when Accenture can play a role in the ongoing, in the deployment building up, but also support environment. >> So one of the other things that we talk a lot about here on theCUBE is sustainability and this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSDU, help organizations become how is this a greener solution for companies? >> Well, first we make, it's a great solution because you start making a much more efficient use of your resources, which is a really important one. The second thing we're doing is also we started with OSDU in very much in the oil and gas space, within the export development space. We've grown OSDU but in our strategy, we've grown OSDU now also to an alternative energy source. So obviously we'll all start supporting next year things like solar farms, wind farms, the geothermal environment, hydrogen. So it becomes an open energy data platform not just for the oil and gas industry, but for any type of industry, any type of energy industry. So our focus is to create, bring the data of all those various energy data sources together into a single data platform. You're going to use AI and other technology on top of that, to exploit the data to be together into a single data platform. >> Liz, I want to ask you about security, because security is such a big concern when it comes to data. How secure is the data on OSDU? >> Actually, can I talk, can I do a follow-up on the sustainability talking? >> Absolutely by all means. >> I mean, I want to interject, though security is absolutely our top priority I don't mean to move away from that but with sustainability, in addition to the benefits of the OSDU data platform. When a company moves from on-prem to the cloud they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical on-prem data center. Now, a recent study by 451 research found that, AWS's infrastructure, is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to a higher server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases 451 found that, AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSDU are working to support our customers as they seek to better understand their workflows and make their legacy businesses less carbon intensive. >> That's, those statistics are incredible. Do you want to talk a little bit now about security? >> Absolutely yeah. Security will always be AWS's top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy the security requirements for the military, global banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build and operate each of our regions. So that customers benefit from the only commercial cloud that's had hit service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features. As well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. >> Johann, I want you to talk a little bit about how OSDU you can be used today. Does it only handle subsurface data? >> Today is 100 subsets of wells data we go to add that to that production around the middle of next year. That means that the whole upstream business we got included every piece goes from exploration all the way to production, you bring it together into a single data platform. So production will be added around Q3 of next year. Then in principle, we have a typical elder data, a single environment and we're going to extend them to other data sources or energy sources like solar farms, wind farms, hydrogen, hydro, et cetera. So we're going to add a whole list of other day energy source to that and bring all the data together into a single data platform. So we move from an oil and gas data platform to an energy data platform. That's really what our objective is because the whole industry if you look at our companies all moving in that same direction of course are very strong in oil and gas but also increasingly go into other energy sources like solar, like wind, like hydrogen et cetera. So we move exactly with the same method, that the whole OSDU, can really support that whole energy spectrum of energy sources, of course. >> And Liz and Johan, I want you to close us out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSDU. We'll start with you, Liz. What do you see as the future holding for this platform? >> Honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers wherever their OSDU journeys, take them whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges. >> Johan. >> Yeah, first nobody can look that far ahead anymore nowadays, especially 10 years. I mean, who knows what happens in 10 years? But if you look what our objective is that really in the next five years, OSDU will become the key backbone for energy companies for storing your data, new artificial intelligence and optimize the whole supply, the energy supply chain in this world out here. >> Johan Krebbers, Liz Dennett thank you so much for coming on theCUBE virtual. >> Thank you. >> Thank you. >> I'm Rebecca Knight stay tuned for more of our coverage of the Accenture Executive Summit. (tranquil music).

Published Date : Dec 1 2020

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AWS Executive Summit 2020


 

>>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to cube three 60 fives coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight. Today we are joined by a cube alum, Karthik, Lorraine. He is Accenture senior managing director and lead Accenture cloud. First, welcome back to the show Karthik. >>Thank you. Thanks for having me here. >>Always a pleasure. So I want to talk to you. You are an industry veteran, you've been in Silicon Valley for decades. Um, I want to hear from your perspective what the impact of the COVID-19 pandemic has been, what are you hearing from clients? What are they struggling with? What are their challenges that they're facing day to day? >>I think, um, COVID-19 is being a eye-opener from, you know, various facets, you know, um, first and foremost, it's a, it's a hell, um, situation that everybody's facing, which is not just, uh, highest economic bearings to it. It has enterprise, um, an organization with bedding to it. And most importantly, it's very personal to people, um, because they themselves and their friends, family near and dear ones are going through this challenge, uh, from various different dimension. But putting that aside, when you come to it from an organization enterprise standpoint, it has changed everything well, the behavior of organizations coming together, working in their campuses, working with each other as friends, family, and, uh, um, near and dear colleagues, all of them are operating differently. So that's what big change to get things done in a completely different way, from how they used to get things done. >>Number two, a lot of things that were planned for normal scenarios, like their global supply chain, how they interact with their client customers, how they go innovate with their partners on how that employees contribute to the success of an organization at all changed. And there are no data models that give them a hint of something like this for them to be prepared for this. So we are seeing organizations, um, that have adapted to this reasonably okay, and are, you know, launching to innovate faster in this. And there are organizations that have started with struggling, but are continuing to struggle. And the gap between the leaders and legs are widening. So this is creating opportunities in a different way for the leaders, um, with a lot of pivot their business, but it's also creating significant challenge for the lag guides, uh, as we defined in our future systems research that we did a year ago, uh, and those organizations are struggling further. So the gap is actually widening. >>So you just talked about the widening gap. I've talked about the tremendous uncertainty that so many companies, even the ones who have adapted reasonably well, uh, in this, in this time, talk a little bit about Accenture cloud first and why, why now? >>I think it's a great question. Um, we believe that for many of our clients COVID-19 has turned, uh, cloud from an experimentation aspiration to an origin mandate. What I mean by that is everybody has been doing something on the other end cloud. There's no company that says we don't believe in cloud are, we don't want to do cloud. It was how much they did in cloud. And they were experimenting. They were doing the new things in cloud, but they were operating a lot of their core business outside the cloud or not in the cloud. Those organizations have struggled to operate in this new normal, in a remote fashion, as well as, uh, their ability to pivot to all the changes the pandemic has brought to them. But on the other hand, the organizations that had a solid foundation in cloud were able to collect faster and not actually gone into the stage of innovating faster and driving a new behavior in the market, new behavior within their organization. >>So we are seeing that spend to make is actually fast-forwarded something that we always believed was going to happen. This, uh, uh, moving to cloud over the next decade is fast forward it to happen in the next three to five years. And it's created this moment where it's a once in an era, really replatforming of businesses in the cloud that we are going to see. And we see this moment as a cloud first moment where organizations will use cloud as the, the, the canvas and the foundation with which they're going to reimagine their business after they were born in the cloud. Uh, and this requires a whole new strategy. Uh, and as Accenture, we are getting a lot in cloud, but we thought that this is the moment where we bring all of that, gave him a piece together because we need a strategy for addressing, moving to cloud are embracing cloud in a holistic fashion. And that's what Accenture cloud first brings together a holistic strategy, a team that's 70,000 plus people that's coming together with rich cloud skills, but investing to tie in all the various capabilities of cloud to Delaware, that holistic strategy to our clients. So I want you to >>Delve into a little bit more about what this strategy actually entails. I mean, it's clearly about embracing change and being willing to experiment and having capabilities to innovate. Can you tell us a little bit more about what this strategy entails? >>Yeah. The reason why we say that as a need for strategy is like I said, cloud is not new. There's almost every customer client is doing something with the cloud, but all of them have taken different approaches to cloud and different boundaries to cloud. Some organizations say, I just need to consolidate my multiple data centers to a small data center footprint and move the nest to cloud. Certain other organizations say that well, I'm going to move certain workloads to cloud. Certain other organizations said, well, I'm going to build this Greenfield application or workload in cloud. Certain other said, um, I'm going to use the power of AI ML in the cloud to analyze my data and drive insights. But a cloud first strategy is all of this tied with the corporate strategy of the organization with an industry specific cloud journey to say, if in this current industry, if I were to be reborn in the cloud, would I do it in the exact same passion that I did in the past, which means that the products and services that they offer need to be the matching, how they interact with that customers and partners need to be revisited, how they bird and operate their IP systems need to be the, imagine how they unearthed the data from all of the systems under which they attract need to be liberated so that you could drive insights of cloud. >>First strategy hands is a corporate wide strategy, and it's a C-suite responsibility. It doesn't take the ownership away from the CIO or CIO, but the CIO is, and CDI was felt that it was just their problem and they were to solve it. And everyone as being a customer, now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's agenda, where probably the CDI is the instrument to execute that that's a holistic cloud-first strategy >>And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, as you were saying, this idea of being reborn in the cloud. So now how do I think about things? How do I communicate? How do I collaborate? How do I get done? What I need to get done. Talk a little bit about how this has changed, the way you support your clients and how Accenture cloud first is changing your approach to cloud services. >>Wonderful. Um, you know, I did not color one very important aspect in my previous question, but that's exactly what you just asked me now, which is to do all of this. I talked about all of the variables, uh, an organization or an enterprise is going to go through, but the good part is they have one constant. And what is that? That is their employees, uh, because you do, the employees are able to embrace this change. If they are able to, uh, change them, says, pivot them says retool and train themselves to be able to operate in this new cloud. First one, the ability to reimagine every function of the business would be happening at speed. And cloud first approach is to do all of this at speed, because innovation is deadly proposed there, do the rate of probability on experimentation. You need to experiment a lot for any kind of experimentation. >>There's a probability of success. Organizations need to have an ability and a mechanism for them to be able to innovate faster for which they need to experiment a lot, the more the experiment and the lower cost at which they experiment is going to help them experiment a lot. And they experiment demic speed, fail fast, succeed more. And hence, they're going to be able to operate this at speed. So the cloud-first mindset is all about speed. I'm helping the clients fast track that innovation journey, and this is going to happen. Like I said, across the enterprise and every function across every department, I'm the agent of this change is going to be the employees or weapon, race, this change through new skills and new grueling and new mindset that they need to adapt to. >>So Karthik what you're describing it, it sounds so exciting. And yet for a pandemic wary workforce, that's been working remotely that may be dealing with uncertainty if for their kid's school and for so many other aspects of their life, it sounds hard. So how are you helping your clients, employees get onboard with this? And because the change management is, is often the hardest part. >>Yeah, I think it's, again, a great question. A bottle has only so much capacity. Something got to come off for something else to go in. That's what you're saying is absolutely right. And that is again, the power of cloud. The reason why cloud is such a fundamental breakthrough technology and capability for us to succeed in this era, because it helps in various forms. What we talked so far is the power of innovation that can create, but cloud can also simplify the life of the employees in an enterprise. There are several activities and tasks that people do in managing that complex infrastructure, complex ID landscape. They used to do certain jobs and activities in a very difficult underground about with cloud has simplified. And democratised a lot of these activities. So that things which had to be done in the past, like managing the complexity of the infrastructure, keeping them up all the time, managing the, um, the obsolescence of the capabilities and technologies and infrastructure, all of that could be offloaded to the cloud. >>So that the time that is available for all of these employees can be used to further innovate. Every organization is going to spend almost the same amount of money, but rather than spending activities, by looking at the rear view mirror on keeping the lights on, they're going to spend more money, more time, more energy, and spend their skills on things that are going to add value to their organization. Because you, every innovation that an enterprise can give to their end customer need not come from that enterprise. The word of platform economy is about democratising innovation. And the power of cloud is to get all of these capabilities from outside the four walls of the enterprise, >>It will add value to the organization, but I would imagine also add value to that employee's life because that employee, the employee will be more engaged in his or her job and therefore bring more excitement and energy into her, his or her day-to-day activities too. >>Absolutely. Absolutely. And this is, this is a normal evolution we would have seen everybody would have seen in their lives, that they keep moving up the value chain of what activities that, uh, gets performed buying by those individuals. And this is, um, you know, no more true than how the United States, uh, as an economy has operated where, um, this is the power of a powerhouse of innovation, where the work that's done inside the country keeps moving up to value chain. And, um, us leverage is the global economy for a lot of things that is required to power the United States and that global economic, uh, phenomenon is very proof for an enterprise as well. There are things that an enterprise needs to do them soon. There are things an employee needs to do themselves. Um, but there are things that they could leverage from the external innovation and the power of innovation that is coming from technologies like cloud. >>So at Accenture, you have long, long, deep Stan, sorry, you have deep and long-standing relationships with many cloud service providers, including AWS. How does the Accenture cloud first strategy, how does it affect your relationships with those providers? >>Yeah, we have great relationships with cloud providers like AWS. And in fact, in the cloud world, it was one of the first, um, capability that we started about years ago, uh, when we started developing these capabilities. But five years ago, we hit a very important milestone where the two organizations came together and said that we are forging a pharma partnership with joint investments to build this partnership. And we named that as a Accenture, AWS business group ABG, uh, where we co-invest and brought skills together and develop solutions. And we will continue to do that. And through that investment, we've also made several acquisitions that you would have seen in the recent times, like, uh, an invoice and gecko that we made acquisitions in in Europe. But now we're taking this to the next level. What we are saying is two cloud first and the $3 billion investment that we are bringing in, uh, through cloud-first. >>We are going to make specific investment to create unique joint solution and landing zones foundation, um, cloud packs with which clients can accelerate their innovation or their journey to cloud first. And one great example is what we are doing with Takeda, uh, billable, pharmaceutical giant, um, between we've signed a five-year partnership. And it was out in the media just a month ago or so, where we are, the two organizations are coming together. We have created a partnership as a power of three partnership, where the three organizations are jointly hoarding hats and taking responsibility for the innovation and the leadership position that Takeda wants to get to with this. We are going to simplify their operating model and organization by providing and flexibility. We're going to provide a lot more insights. Tequila has a 230 year old organization. Imagine the amount of trapped data and intelligence that is there. >>How about bringing all of that together with the power of AWS and Accenture and Takeda to drive more customer insights, um, come up with breakthrough R and D uh, accelerate clinical trials and improve the patient experience using AI ML and edge technologies. So all of these things that we will do through this partnership with joined investment from Accenture cloud first, as well as partner like AWS, so that Takeda can realize their gain. And, uh, their senior actually made a statement that five years from now, every ticket an employee will have an AI assistant. That's going to make that beginner employee move up the value chain on how they contribute and add value to the future of tequila with the AI assistant, making them even more equipped and smarter than what they could be otherwise. >>So, one last question to close this out here. What is your future vision for, for Accenture cloud first? What are we going to be talking about at next year's Accenture executive summit? Yeah, the future >>Is going to be, um, evolving, but the part that is exciting to me, and this is, uh, uh, a fundamental belief that we are entering a new era of industrial revolution from industry first, second, and third industry. The third happened probably 20 years ago with the advent of Silicon and computers and all of that stuff that happened here in the Silicon Valley. I think the fourth industrial revolution is going to be in the cross section of, uh, physical, digital and biological boundaries. And there's a great article, um, in one economic forum that people, uh, your audience can Google and read about it. Uh, but the reason why this is very, very important is we are seeing a disturbing phenomenon that over the last 10 years are seeing a Blackwing of the, um, labor productivity and innovation, which has dropped to about 2.1%. When you see that kind of phenomenon over that longer period of time, there has to be breakthrough innovation that needs to happen to come out of this barrier and get to the next, you know, base camp, as I would call it to further this productivity, um, lack that we are seeing, and that is going to happen in the intersection of the physical, digital and biological boundaries. >>And I think cloud is going to be the connective tissue between all of these three, to be able to provide that where it's the edge, especially is good to come closer to the human lives. It's going to come from cloud. Yeah. Pick totally in your mind, you can think about cloud as central, either in a private cloud, in a data center or in a public cloud, you know, everywhere. But when you think about edge, it's going to be far reaching and coming close to where we live and maybe work and very, um, get entertained and so on and so forth. And there's good to be, uh, intervention in a positive way in the field of medicine, in the field of entertainment, in the field of, um, manufacturing in the field of, um, you know, mobility. When I say mobility, human mobility, people, transportation, and so on and so forth with all of this stuff, cloud is going to be the connective tissue and the vision of cloud first is going to be, uh, you know, blowing through this big change that is going to happen. And the evolution that is going to happen where, you know, the human grace of mankind, um, our person kind of being very gender neutral in today's world. Um, go first needs to be that beacon of, uh, creating the next generation vision for enterprises to take advantage of that kind of an exciting future. And that's why it, Accenture, are we saying that there'll be change as our, as our purpose? >>I genuinely believe that cloud first is going to be in the forefront of that change agenda, both for Accenture as well as for the rest of the work. Excellent. Let there be change, indeed. Thank you so much for joining us Karthik. A pleasure I'm Rebecca nights stay tuned for more of Q3 60 fives coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS >>Welcome everyone to the Q virtual and our coverage of the Accenture executive summit, which is part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the green cloud and joining me is Kishor Dirk. He is Accenture senior managing director cloud first global services lead. Thank you so much for coming on the show. Kishor nice to meet you. So I want to start by asking you what it is that we mean when we say green cloud, we know the sustainability is a business imperative. So many organizations around the world are committing to responsible innovation, lowering carbon emissions. But what is this? What is it? What does it mean when they talk about cloud from a sustainability perspective? I think it's about responsible innovation being cloud is a cloud first approach that has benefit the clients by helping reduce carbon emissions. Think about it this way. >>You have a large number of data centers. Each of these data centers are increasing by 14% every year. And this double digit growth. What you're seeing is these data centers and the consumption is nearly coolant to the kind of them should have a country like Spain. So the magnitude of the problem that is out there and how do we pursue a green approach. If you look at this, our Accenture analysis, in terms of the migration to public cloud, we've seen that we can reduce that by 59 million tons of CO2 per year with just the 5.9% reduction in total emissions and equates this to 22 million cars off the road. And the magnitude of reduction can go a long way in meeting climate change commitments, particularly for data sensitive. Wow, that's incredible. The numbers that you're putting forward are, are absolutely mind blowing. So how does it work? Is it a simple cloud migration? So, you know, when companies begin their cloud journey and then they confront, uh, with >>Them a lot of questions, the decision to make, uh, this particular, uh, element sustainable in the solution and benefits they drive and they have to make wise choices, and then they will gain unprecedented level of innovation leading to both a greener planet, as well as, uh, a greener balance sheet, I would say, uh, so effectively it's all about ambition, data ambition, greater the reduction in carbon emissions. So from a cloud migration perspective, we look at it as a, as a simple solution with approaches and sustainability benefits, uh, that vary based on things it's about selecting the right cloud provider, a very carbon thoughtful provider and the first step towards a sustainable cloud journey. And here we're looking at cloud operators know, obviously they have different corporate commitments towards sustainability, and that determines how they plan, how they build, uh, their, uh, uh, the data centers, how they are consumed and assumptions that operate there and how they, or they retire their data centers. >>Then, uh, the next element that you want to do is how do you build it ambition, you know, for some of the companies, uh, and average on-prem, uh, drives about 65% energy reduction and the carbon emission reduction number was 84%, which is kind of good, I would say. But then if you could go up to 98% by configuring applications to the cloud, that is significant benefit for, uh, for the board. And obviously it's a, a greener cloud that we're talking about. And then the question is, how far can you go? And, uh, you know, the, obviously the companies have to unlock greater financial societal environmental benefits, and Accenture has this cloud based circular operations and sustainable products and services that we bring into play. So it's a, it's a very thoughtful, broader approach that w bringing in, in terms of, uh, just a simple concept of cloud migration. >>So we know that in the COVID era, shifting to the cloud has really become a business imperative. How is Accenture working with its clients at a time when all of this movement has been accelerated? How do you partner and what is your approach in terms of helping them with their migrations? >>Yeah, I mean, let, let me talk a little bit about the pandemic and the crisis that is that today. And if you really look at that in terms of how we partnered with a lot of our clients in terms of the cloud first approach, I'll give you a couple of examples. We worked with rolls, Royce, MacLaren, DHL, and others, as part of the ventilator, a UK challenge consortium, again, to, uh, coordinate production of medical ventilator surgically needed for the UK health service. Many of these farms I've taken similar initiatives in, in terms of, uh, you know, from a few manufacturers hand sanitizers, and to answer it as us and again, leading passionate labels, making PPE, and again, at the UN general assembly, we launched the end-to-end integration guide that helps company is essentially to have a sustainable development goals. And that's how we are parking at a very large scale. >>Uh, and, and if you really look at how we work with our clients and what is Accenture's role there, uh, you know, from, in terms of our clients, you know, there are multiple steps that we look at. One is about planning, building, deploying, and managing an optimal green cloud solution. And Accenture has this concept of, uh, helping clients with a platform to kind of achieve that goal. And here we are having, we are having a platform or a mine app, which has a module called BGR advisor. And this is a capability that helps you provide optimal green cloud, uh, you know, a business case, and obviously a blueprint for each of our clients and right from the start in terms of how do we complete cloud migration recommendation to an improved solution, accurate accuracy to obviously bringing in the end to end perspective, uh, you know, with this green card advisor capability, we're helping our clients capture what we call as a carbon footprint for existing data centers and provide, uh, I would say the current cloud CO2 emission score that, you know, obviously helps them, uh, with carbon credits that can further that green agenda. >>So essentially this is about recommending a green index score, reducing carbon footprint for migration migrating for green cloud. And if we look at how Accenture itself is practicing what we preach, 95% of our applications are in the cloud. And this migration has helped us, uh, to lead to about $14.5 million in benefit. And in the third year and another 3 million analytics costs that are saved through right-sizing a service consumption. So it's a very broad umbrella and a footprint in terms of how we engage societaly with the UN or our clients. And what is it that we exactly bring to our clients in solving a specific problem? >>Accenture isn't is walking the walk, as you say, >>Instead of it, we practice what we preach, and that is something that we take it to heart. We want to have a responsible business and we want to practice it. And we want to advise our clients around that >>You are your own use case. And so they can, they know they can take your advice. So talk a little bit about, um, the global, the cooperation that's needed. We know that conquering this pandemic is going to take a coordinated global effort and talk a little bit about the great reset initiative. First of all, what is that? Why don't we, why don't we start there and then we can delve into it a little bit more. >>Okay. So before we get to how we are cooperating, the great reset, uh, initiative is about improving the state of the world. And it's about a group of global stakeholders cooperating to simultaneously manage the direct consequences of their COVID-19 crisis. Uh, and in spirit of this cooperation that we're seeing during COVID-19, uh, which will obviously either to post pandemic, to tackle the world's pressing issues. As I say, uh, we are increasing companies to realize a combined potential of technology and sustainable impact to use enterprise solutions, to address with urgency and scale, and, um, obviously, uh, multiple challenges that are facing our world. One of the ways that are increasing, uh, companies to reach their readiness cloud with Accenture's cloud strategy is to build a solid foundation that is resilient and will be able to faster to the current, as well as future times. Now, when you think of cloud as the foundation, uh, that drives the digital transformation, it's about scale speed, streamlining your operations, and obviously reducing costs. >>And as these businesses seize the construct of cloud first, they must remain obviously responsible and trusted. Now think about this, right, as part of our analysis, uh, that profitability can co-exist with responsible and sustainable practices. Let's say that all the data centers, uh, migrated from on-prem to cloud based, we estimate that would reduce carbon emissions globally by 60 million tons per year. Uh, and think about it this way, right? Easier metric would be taking out 22 million cars off the road. Um, the other examples that you've seen, right, in terms of the NHS work that they're doing, uh, in, in UK to build, uh, uh, you know, uh, Microsoft teams in based integration. And, uh, the platform rolled out for 1.2 million users, uh, and got 16,000 users that we were able to secure, uh, instant messages, obviously complete audio video calls and host virtual meetings across India. So, uh, this, this work that we did with NHS is, is something that we have, we are collaborating with a lot of tools and powering businesses. >>Well, you're vividly describing the business case for sustainability. What do you see as the future of cloud when thinking about it from this lens of sustainability, and also going back to what you were talking about in terms of how you are helping your, your fostering cooperation within these organizations. >>Yeah, that's a very good question. So if you look at today, right, businesses are obviously environmentally aware and they are expanding efforts to decrease power consumption, carbon emissions, and they want to run a sustainable operational efficiency across all elements of their business. And this is an increasing trend, and there is that option of energy efficient infrastructure in the global market. And this trend is the cloud first thinking. And with the right cloud migration that we've been discussing is about unlocking new opportunity, like clean energy foundations enable enabled by cloud based geographic analysis, material, waste reductions, and better data insights. And this is something that, uh, uh, will drive, uh, with obviously faster analytics platform that is out there. Now, the sustainability is actually the future of business, which is companies that are historically different, the financial security or agility benefits to cloud. Now sustainability becomes an imperative for them. And I would own experience Accenture's experience with cloud migrations. We have seen 30 to 40% total cost of ownership savings, and it's driving a greater workload, flexibility, better service, your obligation, and obviously more energy efficient, uh, public clouds that cost, uh, we'll see that, that drive a lot of these enterprise own data centers. So in our view, what we are seeing is that this, this, uh, sustainable cloud position helps, uh, helps companies to, uh, drive a lot of the goals in addition to their financial and other goods. >>So what should organizations who are, who are watching this interview and saying, Hey, I need to know more, what, what do you recommend to them? And what, where should they go to get more information on Greenplum? >>Yeah. If you wanna, if you are a business leader and you're thinking about which cloud provider is good, or how, how should applications be modernized to meet our day-to-day needs, which cloud driven innovations should be priorities. Uh, you know, that's why Accenture, uh, formed up the cloud first organization and essentially to provide the full stack of cloud services to help our clients become a cloud first business. Um, you know, it's all about excavation, uh, the digital transformation innovating faster, creating differentiated, uh, and sustainable value for our clients. And we are powering it up at 70,000 cloud professionals, $3 billion investment, and, uh, bringing together and services for our clients in terms of cloud solutions. And obviously the ecosystem partnership that we have that we are seeing today, uh, and, and the assets that help our clients realize their goals. Um, and again, to do reach out to us, uh, we can help them determine obviously, an optimal, sustainable cloud for solution that meets the business needs and being unprecedented levels of innovation. Our experience, uh, will be our advantage. And, uh, now more than ever Rebecca, >>Just closing us out here. Do you have any advice for these companies who are navigating a great deal of uncertainty? We, what, what do you think the next 12 to 24 months? What do you think that should be on the minds of CEOs as they go through? >>So, as CEO's are thinking about rapidly leveraging cloud, migrating to cloud, uh, one of the elements that we want them to be thoughtful about is can they do that, uh, with unprecedent level of innovation, but also build a greener planet and a greener balance sheet, if we can achieve this balance and kind of, uh, have a, have a world which is greener, I think the world will win. And we all along with Accenture clients will win. That's what I would say, uh, >>Optimistic outlook, and I will take it. Thank you so much. Kishor for coming on the show >>That was >>Accenture's Kishor Dirk, I'm Rebecca Knight stay tuned for more of the cube virtuals coverage of the Accenture executive summit >>Around the globe. >>It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtual and our coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the power of three. And what happens when you bring together the scientific know-how of a global bias biopharmaceutical powerhouse in Takeda, a leading cloud services provider in AWS, and Accenture's ability to innovate, execute, and deliver innovation. Joining me to talk about these things. We have Aaron, sorry, Arjun, baby. He is the senior managing director and chairman of Accenture's diamond leadership council. Welcome Arjun, Karl hick. He is the chief digital and information officer at Takeda. What is your bigger, thank you, Rebecca and Brian bowhead, global director, and head of the Accenture AWS business group at Amazon web services. Thanks so much for coming up. So, as I said, we're talking today about this relationship between, uh, your three organizations. Carl, I want to talk with you. I know you're at the beginning of your cloud journey. What was the compelling reason? What w why, why move to the cloud and why now? >>Yeah, no, thank you for the question. So, you know, as a biopharmaceutical leader, we're committed to bringing better health and a brighter future to our patients. We're doing that by translating science into some really innovative and life transporting therapies, but throughout, you know, we believe that there's a responsible use of technology, of data and of innovation. And those three ingredients are really key to helping us deliver on that promise. And so, you know, while I think, uh, I'll call it, this cloud journey is already always been a part of our strategy. Um, and we've made some pretty steady progress over the last years with a number of I'll call it diverse approaches to the digital and AI. We just weren't seeing the impact at scale that we wanted to see. Um, and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and, uh, broaden that shift. >>And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. One of those has been certainly a number of the large acquisitions we've made Shire, uh, being the most pressing example, uh, but also the global pandemic, both of those highlight the need for us to move faster, um, at the speed of cloud, ultimately. Uh, and so we started thinking outside of the box because it was taking us too long and we decided to leverage the strategic partner model. Uh, and it's giving us a chance to think about our challenges very differently. We call this the power of three, uh, and ultimately our focus is singularly on our patients. I mean, they're waiting for us. We need to get there faster. It can take years. And so I think that there is a focus on innovation, um, at a rapid speed, so we can move ultimately from treating conditions to keeping people healthy. >>So, as you are embarking on this journey, what are some of the insights you want to share about, about what you're seeing so far? >>Yeah, no, it's a great question. So, I mean, look, maybe right before I highlight some of the key insights, uh, I would say that, you know, with cloud now as the, as the launchpad for innovation, you know, our vision all along has been that in less than 10 years, we want every single to kid, uh, associate we're employed to be empowered by an AI assistant. And I think that, you know, that's going to help us make faster, better decisions. It'll help us, uh, fundamentally deliver transformative therapies and better experiences to, to that ecosystem, to our patients, to physicians, to payers, et cetera, much faster than we previously thought possible. Um, and I think that technologies like cloud and edge computing together with a very powerful I'll call it data fabric is going to help us to create this, this real-time, uh, I'll call it the digital ecosystem. >>The data has to flow ultimately seamlessly between our patients and providers or partners or researchers, et cetera. Uh, and so we've been thinking about this, uh, I'll call it, we call it sort of this pyramid, um, that helps us describe our vision. Uh, and a lot of it has to do with ultimately modernizing the foundation, modernizing and rearchitecting, the platforms that drive the company, uh, heightening our focus on data, which means that there's an accelerated shift towards, uh, enterprise data platforms and digital products. And then ultimately, uh, uh, P you know, really an engine for innovation sitting at the very top. Um, and so I think with that, you know, there's a few different, I'll call it insights that, you know, are quickly kind of come zooming into focus. I would say one is this need to collaborate very differently. Um, you know, not only internally, but you know, how do we define ultimately, and build a connected digital ecosystem with the right partners and technologies externally? >>I think the second component that maybe people don't think as much about, but, you know, I find critically important is for us to find ways of really transforming our culture. We have to unlock talent and shift the culture certainly as a large biopharmaceutical very differently. And then lastly, you've touched on it already, which is, you know, innovation at the speed of cloud. How do we re-imagine that, you know, how do ideas go from getting tested and months to kind of getting tested in days? You know, how do we collaborate very differently? Uh, and so I think those are three, uh, perhaps of the larger I'll call it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. >>So Arjun, I want to bring you into this conversation a little bit, let let's delve into those a bit. Talk first about the collaboration, uh, that Carl was referencing there. How, how have you seen that? It is enabling, uh, colleagues and teams to communicate differently and interact in new and different ways? Uh, both internally and externally, as Carl said, >>No, th thank you for that. And, um, I've got to give call a lot of credit, because as we started to think about this journey, it was clear, it was a bold ambition. It was, uh, something that, you know, we had all to do differently. And so the, the concept of the power of three that Carl has constructed has become a label for us as a way to think about what are we going to do to collectively drive this journey forward. And to me, the unique ways of collaboration means three things. The first one is that, um, what is expected is that the three parties are going to come together and it's more than just the sum of our resources. And by that, I mean that we have to bring all of ourselves, all of our collective capabilities, as an example, Amazon has amazing supply chain capabilities. >>They're one of the best at supply chain. So in addition to resources, when we have supply chain innovations, uh, that's something that they're bringing in addition to just, uh, talent and assets, similarly for Accenture, right? We do a lot, uh, in the talent space. So how do we bring our thinking as to how we apply best practices for talent to this partnership? So, um, as we think about this, so that's, that's the first one, the second one is about shared success very early on in this partnership, we started to build some foundations and actually develop seven principles that all of us would look at as the basis for this success shared success model. And we continue to hold that sort of in the forefront, as we think about this collaboration. And maybe the third thing I would say is this one team mindset. So whether it's the three of our CEOs that get together every couple of months to think about, uh, this partnership, or it is the governance model that Carl has put together, which has all three parties in the governance and every level of leadership. We always think about this as a collective group, so that we can keep that front and center. And what I think ultimately has enabled us to do is it allowed us to move at speed, be more flexible. And ultimately all we're looking at the target the same way, the North side, the same way. >>Brian, what about you? What have you observed? And are you thinking about in terms of how this is helping teams collaborate differently, >>Lillian and Arjun made some, some great points there. And I think if you really think about what he's talking about, it's that, that diversity of talent, diversity of scale and viewpoint and even culture, right? And so we see that in the power of three. And then I think if we drill down into what we see at Takeda, and frankly, Takeda was, was really, I think, pretty visionary and on their way here, right? And taking this kind of cross functional approach and applying it to how they operate day to day. So moving from a more functional view of the world to more of a product oriented view of the world, right? So when you think about we're going to be organized around a product or a service or a capability that we're going to provide to our customers or our patients or donors in this case, it implies a different structure, although altogether, and a different way of thinking, right? >>Because now you've got technical people and business experts and marketing experts, all working together in this is sort of cross collaboration. And what's great about that is it's really the only way to succeed with cloud, right? Because the old ways of thinking where you've got application people and infrastructure, people in business, people is suboptimal, right? Because we can all access this tool as these capabilities and the best way to do that. Isn't across kind of a cross-collaborative way. And so this is product oriented mindset. It's a keto was already on. I think it's allowed us to move faster in those areas. >>Carl, I want to go back to this idea of unlocking talent and culture. And this is something that both Brian and Arjun have talked about too. People are an essential part of their, at the heart of your organization. How will their experience of work change and how are you helping re-imagine and reinforce a strong organizational culture, particularly at this time when so many people are working remotely. >>Yeah. It's a great question. And it's something that, you know, I think we all have to think a lot about, I mean, I think, um, you know, driving this, this call it, this, this digital and data kind of capability building, uh, takes a lot of, a lot of thinking. So, I mean, there's a few different elements in terms of how we're tackling this one is we're recognizing, and it's not just for the technology organization or for those actors that, that we're innovating with, but it's really across all of the Cato where we're working through ways of raising what I'll call the overall digital leaders literacy of the organization, you know, what are the, you know, what are the skills that are needed almost at a baseline level, even for a global bio-pharmaceutical company and how do we deploy, I'll call it those learning resources very broadly. >>And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are very specialized skills that are needed. Uh, my organization is one of those. And so, you know, we're fostering ways in which, you know, we're very kind of quickly kind of creating, uh, avenues excitement for, for associates in that space. So one example specifically, as we use, you know, during these very much sort of remote, uh, sort of days, we, we use what we call global it meet days, and we set a day aside every single month and this last Friday, um, you know, we, we create during that time, it's time for personal development. Um, and we provide active seminars and training on things like, you know, robotic process automation, data analytics cloud, uh, in this last month we've been doing this for months and months now, but in his last month, more than 50% of my organization participated, and there's this huge positive shift, both in terms of access and excitement about really harnessing those new skills and being able to apply them. >>Uh, and so I think that that's, you know, one, one element that, uh, can be considered. And then thirdly, um, of course, every organization to work on, how do you prioritize talent, acquisition and management and competencies that you can't rescale? I mean, there are just some new capabilities that we don't have. And so there's a large focus that I have with our executive team and our CEO and thinking through those critical roles that we need to activate in order to kind of, to, to build on this, uh, this business led cloud transformation. And lastly, probably the hardest one, but the one that I'm most jazzed about is really this focus on changing the mindsets and behaviors. Um, and I think there, you know, this is where the power of three is, is really, uh, kind of coming together nicely. I mean, we're working on things like, you know, how do we create this patient obsessed curiosity, um, and really kind of unlock innovation with a real, kind of a growth mindset. >>Uh, and the level of curiosity that's needed, not to just continue to do the same things, but to really challenge the status quo. So that's one big area of focus we're having the agility to act just faster. I mean, to worry less, I guess I would say about kind of the standard chain of command, but how do you make more speedy, more courageous decisions? And this is places where we can emulate the way that a partner like AWS works, or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently to a number of partnerships that we can build. So we can break down some of these barriers and use these networks, um, whether it's within our own internal ecosystem or externally to help, to create value faster. So a lot of energy around ways of working and we'll have to check back in, but I mean, we're early in on this mindset and behavioral shift, um, but a lot of good early momentum. >>Carl you've given me a good segue to talk to Brian about innovation, because you said a lot of the things that I was the customer obsession and this idea of innovating much more quickly. Obviously now the world has its eyes on drug development, and we've all learned a lot about it, uh, in the past few months and accelerating drug development is all, uh, is of great interest to all of us. Brian, how does a transformation like this help a company's, uh, ability to become more agile and more innovative and add a quicker speed to, >>Yeah, no, absolutely. And I think some of the things that Carl talked about just now are critical to that, right? I think where sometimes folks fall short is they think, you know, we're going to roll out the technology and the technology is going to be the silver bullet where in fact it is the culture, it is, is the talent. And it's the focus on that. That's going to be, you know, the determinant of success. And I will say, you know, in this power of three arrangement and Carl talked a little bit about the pyramid, um, talent and culture and that change, and that kind of thinking about that has been a first-class citizen since the very beginning, right. That absolutely is critical for, for being there. Um, and, and so that's been, that's been key. And so we think about innovation at Amazon and AWS, and Carl mentioned some of the things that, you know, partner like AWS can bring to the table is we talk a lot about builders, right? >>So kind of obsessive about builders. Um, and, and we meet what we mean by that is we at Amazon, we hire for builders, we cultivate builders and we like to talk to our customers about it as well. And it also implies a different mindset, right? When you're a builder, you have that, that curiosity, you have that ownership, you have that stake and whatever I'm creating, I'm going to be a co-owner of this product or this service, right. Getting back to that kind of product oriented mindset. And it's not just the technical people or the it people who are builders. It is also the business people as, as Carl talked about. Right. So when we start thinking about, um, innovation again, where we see folks kind of get into a little bit of a innovation pilot paralysis, is that you can focus on the technology, but if you're not focusing on the talent and the culture and the processes and the mechanisms, you're going to be putting out technology, but you're not going to have an organization that's ready to take it and scale it and accelerate it. >>Right. And so that's, that's been absolutely critical. So just a couple of things we've been doing with, with Takeda and Decatur has really been leading the way is, think about a mechanism and a process. And it's really been working backward from the customer, right? In this case, again, the patient and the donor. And that was an easy one because the key value of Decatur is to be a patient focused bio-pharmaceutical right. So that was embedded in their DNA. So that working back from that, that patient, that donor was a key part of that process. And that's really deep in our DNA as well. And Accenture's, and so we were able to bring that together. The other one is, is, is getting used to experimenting and even perhaps failing, right. And being able to iterate and fail fast and experiment and understanding that, you know, some decisions, what we call it at Amazon are two two-way doors, meaning you can go through that door, not like what you see and turn around and go back. And cloud really helps there because the costs of experimenting and the cost of failure is so much lower than it's ever been. You can do it much faster and the implications are so much less. So just a couple of things that we've been really driving, uh, with the cadence around innovation, that's been really critical. Carl, where are you already seeing signs of success? >>Yeah, no, it's a great question. And so we chose, you know, uh, with our focus on innovation to try to unleash maybe the power of data digital in, uh, in focusing on what I call sort of a nave. And so we chose our, our, our plasma derived therapy business, um, and you know, the plasma-derived therapy business unit, it develops critical life-saving therapies for patients with rare and complex diseases. Um, but what we're doing is by bringing kind of our energy together, we're focusing on creating, I'll call it state of the art digitally connected donation centers. And we're really modernizing, you know, the, the, the donor experience right now, we're trying to, uh, improve also I'll call it the overall plasma collection process. And so we've, uh, selected a number of alcohol at a very high speed pilots that we're working through right now, specifically in this, in this area. And we're seeing >>Really great results already. Um, and so that's, that's one specific area of focus are Jen, I want you to close this out here. Any ideas, any best practices advice you would have for other pharmaceutical companies that are, that are at the early stage of their cloud journey? Sorry. Was that for me? Yes. Sorry. Origin. Yeah, no, I was breaking up a bit. No, I think they, um, the key is what's sort of been great for me to see is that when people think about cloud, you know, you always think about infrastructure technology. The reality is that the cloud is really the true enabler for innovation and innovating at scale. And, and if you think about that, right, and all the components that you need, ultimately, that's where the value is for the company, right? Because yes, you're going to get some cost synergies and that's great, but the true value is in how do we transform the organization in the case of the Qaeda and our life sciences clients, right. >>We're trying to take a 14 year process of research and development that takes billions of dollars and compress that right. Tremendous amounts of innovation opportunity. You think about the commercial aspect, lots of innovation can come there. The plasma derived therapy is a great example of how we're going to really innovate to change the trajectory of that business. So I think innovation is at the heart of what most organizations need to do. And the formula, the cocktail that the Qaeda has constructed with this footie program really has all the ingredients, um, that are required for that success. Great. Well, thank you so much. Arjun, Brian and Carl was really an enlightening conversation. Thank you. It's been a lot of, thank you. Yeah, it's been fun. Thanks Rebecca. And thank you for tuning into the cube. Virtual has coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of Accenture executive summit here at AWS reinvent. I'm your host Rebecca Knight for this segment? We have two guests. First. We have Helen Davis. She is the senior director of cloud platform services, assistant director for it and digital for the West Midlands police. Thanks so much for coming on the show, Helen, and we also have Matthew pound. He is Accenture health and public service associate director and West Midlands police account lead. Thanks so much for coming on the show. Matthew, thank you for having us. So we are going to be talking about delivering data-driven insights to the West Midlands police force. Helen, I want to start with >>You. Can you tell us a little bit about the West Midlands police force? How big is the force and also what were some of the challenges that you were grappling with prior to this initiative? >>Yeah, certainly. So Westerners police is the second largest police force in the UK, outside of the metropolitan police in London. Um, we have an excessive, um, 11,000 people work at Westman ins police serving communities, um, through, across the Midlands region. So geographically, we're quite a big area as well, as well as, um, being population, um, density, having that as a, at a high level. Um, so the reason we sort of embarked on the data-driven insights platform and it, which was a huge change for us was for a number of reasons. Um, namely we had a lot of disparate data, um, which was spread across a range of legacy systems that were many, many years old, um, with some duplication of what was being captured and no single view for offices or, um, support staff. Um, some of the access was limited. You have to be in a, in an actual police building on a desktop computer to access it. Um, other information could only reach the offices on the frontline through a telephone call back to one of our enabling services where they would do a manual checkup, um, look at the information, then call the offices back, um, and tell them what they needed to know. So it was a very long laborious, um, process and not very efficient. Um, and we certainly weren't exploiting the data that we had in a very productive way. >>So it sounds like as you're describing and an old clunky system that needed a technological, uh, reimagination, so what was the main motivation for, for doing, for making this shift? >>It was really, um, about making us more efficient and more effective in how we do how we do business. So, um, you know, certainly as a, as an it leader and sort of my operational colleagues, we recognize the benefits, um, that data and analytics could bring in, uh, in a policing environment, not something that was, um, really done in the UK at the time. You know, we have a lot of data, so we're very data rich and the information that we have, but we needed to turn it into information that was actionable. So that's where we started looking for, um, technology partners and suppliers to help us and sort of help us really with what's the art of the possible, you know, this hasn't been done before. So what could we do in this space that's appropriate for policing? >>I love that idea. What is the art of the possible, can you tell us a little bit about why you chose AWS? >>I think really, you know, as with all things and when we're procuring a partner in the public sector that, you know, there are many rules and regulations, uh, quite rightly as you would expect that to be because we're spending public money. So we have to be very, very careful and, um, it's, it's a long process and we have to be open to public scrutiny. So, um, we sort of look to everything, everything that was available as part of that process, but we recognize the benefits that Clyde would provide in this space because, you know, without moving to a cloud environment, we would literally be replacing something that was legacy with something that was a bit more modern. Um, that's not what we wanted to do. Our ambition was far greater than that. So I think, um, in terms of AWS, really, it was around the scalability, interoperability, you know, disaster things like the disaster recovery service, the fact that we can scale up and down quickly, we call it dialing up and dialing back. Um, you know, it's it's page go. So it just sort of ticked all the boxes for us. And then we went through the full procurement process, fortunately, um, it came out on top for us. So we were, we were able to move forward, but it just sort of had everything that we were looking for in that space. >>Matthew, I want to bring you into the conversation a little bit here. How are you working with a wet with the West Midlands police, sorry. And helping them implement this cloud-first journey? >>Yeah, so I guess, um, by January the West Midlands police started, um, favorite five years ago now. So, um, we set up a partnership with the force. I wanted to operate in a way that it was very different to a traditional supplier relationship. Um, secretary that the data difference insights program is, is one of many that we've been working with last nights on, um, over the last five years. Um, as having said already, um, cloud gave a number of, uh, advantages certainly from a big data perspective and the things that that enabled us today, um, I'm from an Accenture perspective that allowed us to bring in a number of the different themes that we have say, cloud teams, security teams, um, and drafted from an insurance perspective, as well as more traditional services that people would associate with the country. >>I mean, so much of this is about embracing comprehensive change to experiment and innovate and try different things. Matthew, how, how do you help, uh, an entity like West Midlands police think differently when they are, there are these ways of doing things that people are used to, how do you help them think about what is the art of the possible, as Helen said, >>There's a few things to that enable those being critical is trying to co-create solutions together. Yeah. There's no point just turning up with, um, what we think is the right answer, try and say, um, collectively work three, um, the issues that the fullest is seeing and the outcomes they're looking to achieve rather than simply focusing on a long list of requirements, I think was critical and then being really open to working together to create the right solution. Um, rather than just, you know, trying to pick something off the shelf that maybe doesn't fit the forces requirements in the way that it should too, >>Right. It's not always a one size fits all. >>Absolutely not. You know, what we believe is critical is making sure that we're creating something that met the forces needs, um, in terms of the outcomes they're looking to achieve the financial envelopes that were available, um, and how we can deliver those in a, uh, iterative agile way, um, rather than spending years and years, um, working towards an outcome, um, that is gonna update before you even get that. >>So Helen, how, how are things different? What kinds of business functions and processes have been re-imagined in, in light of this change and this shift >>It's, it's actually unrecognizable now, um, in certain areas of the business as it was before. So to give you a little bit of, of context, when we, um, started working with essentially in AWS on the data driven insights program, it was very much around providing, um, what was called locally, a wizzy tool for our intelligence analysts to interrogate data, look at data, you know, decide whether they could do anything predictive with it. And it was very much sort of a back office function to sort of tidy things up for us and make us a bit better in that, in that area or a lot better in that area. And it was rolled out to a number of offices, a small number on the front line. Um, I'm really, it was, um, in line with a mobility strategy that we, hardware officers were getting new smartphones for the first time, um, to do sort of a lot of things on, on, um, policing apps and things like that to again, to avoid them, having to keep driving back to police stations, et cetera. >>And the pilot was so successful. Every officer now has access to this data, um, on their mobile devices. So it literally went from a handful of people in an office somewhere using it to do sort of clever bang things to, um, every officer in the force, being able to access that level of data at their fingertips. Literally. So what they were touched with done before is if they needed to check and address or check details of an individual, um, just as one example, they would either have to, in many cases, go back to a police station to look it up themselves on a desktop computer. Well, they would have to make a call back to a centralized function and speak to an operator, relay the questions, either, wait for the answer or wait for a call back with the answer when those people are doing the data interrogation manually. >>So the biggest change for us is the self-service nature of the data we now have available. So officers can do it themselves on their phone, wherever they might be. So the efficiency savings from that point of view are immense. And I think just parallel to that is the quality of our, because we had a lot of data, but just because you've got a lot of data and a lot of information doesn't mean it's big data and it's valuable necessarily. Um, so again, it was having the single source of truth as we, as we call it. So you know that when you are completing those safe searches and getting the responses back, that it is the most accurate information we hold. And also you're getting it back within minutes, as opposed to, you know, half an hour, an hour or a drive back to a station. So it's making officers more efficient and it's also making them safer. The more efficient they are, the more time they have to spend out with the public doing what they, you know, we all should be doing >>That kind of return on investment because what you were just describing with all the steps that we needed to be taken in prior to this, to verify an address say, and those are precious seconds when someone's life is on the line in, in sort of in the course of everyday police work. >>Absolutely. Yeah, absolutely. It's difficult to put a price on it. It's difficult to quantify. Um, but all the, you know, the minutes here and there certainly add up to a significant amount of efficiency savings, and we've certainly been able to demonstrate the officers are spending less time up police stations as a result or more time out on the front line. Also they're safer because they can get information about what may or may not be and address what may or may not have occurred in an area before very, very quickly without having to wait. >>I do, I want to hear your observations of working so closely with this West Midlands police. Have you noticed anything about changes in its culture and its operating model in how police officers interact with one another? Have you seen any changes since this technology change? >>What's unique about the Western displaces, the buy-in from the top down, the chief and his exact team and Helen as the leader from an IOT perspective, um, the entire force is bought in. So what is a significant change program? Uh, I'm not trickles three. Um, everyone in the organization, um, change is difficult. Um, and there's a lot of time effort that's been put in to bake the technical delivery and the business change and adoption aspects around each of the projects. Um, but you can see the step change that is making in each aspect to the organization, uh, and where that's putting West Midlands police as a leader in, um, technology I'm policing in the UK. And I think globally, >>And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain intransigence in workplaces about this is just the way we've always done things and we're used to this and don't try us to get us. Don't try to get us to do anything new here. It works. How do you get the buy-in that you need to do this kind of digital transformation? >>I think it would be wrong to say it was easy. Um, um, we also have to bear in mind that this was one program in a five-year program. So there was a lot of change going on, um, both internally for some of our back office functions, as well as front tie, uh, frontline offices. So with DDI in particular, I think the stack change occurred when people could see what it could do for them. You know, we had lots of workshops and seminars where we all talk about, you know, big data and it's going to be great and it's data analytics and it's transformational, you know, and quite rightly people that are very busy doing a day job, but not necessarily technologists in the main and, you know, are particularly interested quite rightly so in what we are not dealing with the cloud, you know? And it was like, yeah, okay. >>It's one more thing. And then when they started to see on that, on their phones and what teams could do, that's when it started to sell itself. And I think that's when we started to see, you know, to see the stat change, you know, and, and if we, if we have any issues now it's literally, you know, our help desks in meltdown. Cause everyone's like, well, we call it manage without this anymore. And I think that speaks for itself. So it doesn't happen overnight. It's sort of incremental changes and then that's a step change in attitude. And when they see it working and they see the benefits, they want to use it more. And that's how it's become fundamental to all policing by itself, really, without much selling >>You, Helen just made a compelling case for how to get buy in. Have you discovered any other best practices when you are trying to get everyone on board for this kind of thing? >>We've um, we've used a lot of the traditional techniques, things around comms and engagement. We've also used things like, um, the 30 day challenge and nudge theory around how can we gradually encourage people to use things? Um, I think there's a point where all of this around, how do we just keep it simple and keep it user centric from an end user perspective? I think DDI is a great example of where the, the technology is incredibly complex. The solution itself is, um, you know, extremely large and, um, has been very difficult to, um, get delivered. But at the heart of it is a very simple front end for the user to encourage it and take that complexity away from them. Uh, I think that's been critical through the whole piece of DDR. >>One final word from Helen. I want to hear, where do you go from here? What is the longterm vision? I know that this has made productivity, um, productivity savings equivalent to 154 full-time officers. Uh, what's next, >>I think really it's around, um, exploiting what we've got. Um, I use the phrase quite a lot, dialing it up, which drives my technical architects crazy, but because it's apparently not that simple, but, um, you know, we've, we've been through significant change in the last five years and we are still continuing to batch all of those changes into everyday, um, operational policing. But what we need to see is we need to exploit and build on the investments that we've made in terms of data and claims specifically, the next step really is about expanding our pool of data and our functions. Um, so that, you know, we keep getting better and better at this. Um, the more we do, the more data we have, the more refined we can be, the more precise we are with all of our actions. Um, you know, we're always being expected to, again, look after the public purse and do more for less. And I think this is certainly an and our cloud journey and cloud first by design, which is where we are now, um, is helping us to be future-proofed. So for us, it's very much an investment. And I see now that we have good at embedded in operational policing for me, this is the start of our journey, not the end. So it's really exciting to see where we can go from here. >>Exciting times. Indeed. Thank you so much. Lily, Helen and Matthew for joining us. I really appreciate it. Thank you. And you are watching the cube stay tuned for more of the cubes coverage of the AWS reinvent Accenture executive summit. I'm Rebecca Knight from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Hi, everyone. Welcome to the cube virtual coverage of the executive summit at AWS reinvent 2020 virtual. This is the cube virtual. We can't be there in person like we are every year we have to be remote. This executive summit is with special programming supported by Accenture where the cube virtual I'm your host John for a year, we had a great panel here called uncloud first digital transformation from some experts, Stuart driver, the director of it and infrastructure and operates at lion Australia, Douglas Regan, managing director, client account lead at lion for Accenture as a deep Islam associate director application development lead for Accenture gentlemen, thanks for coming on the cube virtual that's a mouthful, all that digital, but the bottom line it's cloud transformation. This is a journey that you guys have been on together for over 10 years to be really a digital company. Now, some things have happened in the past year that kind of brings all this together. This is about the next generation organization. So I want to ask Stuart you first, if you can talk about this transformation at lion has undertaken some of the challenges and opportunities and how this year in particular has brought it together because you know, COVID has been the accelerant of digital transformation. Well, if you're 10 years in, I'm sure you're there. You're in the, uh, on that wave right now. Take a minute to explain this transformation journey. >>Yeah, sure. So number of years back, we looked at kind of our infrastructure and our landscape trying to figure out where we >>Wanted to go next. And we were very analog based and stuck in the old it groove of, you know, Capitol reef rash, um, struggling to transform, struggling to get to a digital platform and we needed to change it up so that we could become very different business to the one that we were back then obviously cloud is an accelerant to that. And we had a number of initiatives that needed a platform to build on. And a cloud infrastructure was the way that we started to do that. So we went through a number of transformation programs that we didn't want to do that in the old world. We wanted to do it in a new world. So for us, it was partnering up with a dried organizations that can take you on the journey and, uh, you know, start to deliver bit by bit incremental progress, uh, to get to the, uh, I guess the promise land. >>Um, we're not, not all the way there, but to where we're on the way along. And then when you get to some of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually change pretty quickly, um, provide capacity and, uh, and increase your environments and, you know, do the things that you need to do in a much more dynamic way than we would have been able to previously where we might've been waiting for the hardware vendors, et cetera, to deliver capacity. So for us this year, it's been a pretty strong year from an it perspective and delivering for the business needs >>Before I hit the Douglas. I want to just real quick, a redirect to you and say, you know, if all the people said, Oh yeah, you got to jump on cloud, get in early, you know, a lot of naysayers like, well, wait till to mature a little bit, really, if you got in early and you, you know, paying your dues, if you will taking that medicine with the cloud, you're really kind of peaking at the right time. Is that true? Is that one of the benefits that comes out of this getting in the cloud? Yeah, >>John, this has been an unprecedented year, right. And, um, you know, Australia, we had to live through Bush fires and then we had covert and, and then we actually had to deliver a, um, a project on very large transformational project, completely remote. And then we also had had some, some cyber challenges, which is public as well. And I don't think if we weren't moved into and enabled through the cloud, we would have been able to achieve that this year. It would have been much different, would have been very difficult to do the backing. We're able to work and partner with Amazon through this year, which is unprecedented and actually come out the other end. Then we've delivered a brand new digital capability across the entire business. Um, in many, you know, wouldn't have been impossible if we could, I guess, state in the old world, the fact that we were moved into the new Naval by the new allowed us to work in this unprecedented year. >>Just quick, what's your personal view on this? Because I've been saying on the Cuban reporting necessity is the mother of all invention and the word agility has been kicked around as kind of a cliche, Oh, it'd be agile. You know, we're going to get the city, you get a minute on specifically, but from your perspective, uh, Douglas, what does that mean to you? Because there is benefits there for being agile. And >>I mean, I think as Stuart mentioned, right, in a lot of these things we try to do and, you know, typically, you know, hardware and of the last >>To be told and, and, and always on the critical path to be done, we really didn't have that in this case, what we were doing with our projects in our deployments, right. We were able to move quickly able to make decisions in line with the business and really get things going. Right. So you see a lot of times in a traditional world, you have these inhibitors, you have these critical path, it takes weeks and months to get things done as opposed to hours and days, and truly allowed us to, we had to, you know, VJ things, move things. And, you know, we were able to do that in this environment with AWS support and the fact that we can kind of turn things off and on as quickly as we need it. >>Yeah. Cloud-scale is great for speed. So DECA, Gardez get your thoughts on this cloud first mission, you know, it, you know, the dev ops world, they saw this early that jumping in there, they saw the, the, the agility. Now the theme this year is modern applications with the COVID pandemic pressure, there's real business pressure to make that happen. How did you guys learn to get there fast? And what specifically did you guys do at Accenture and how did it all come together? Can you take us inside kind of how it played out? >>Oh, right. So yeah, we started off with, as we do in most cases with a much more bigger group, and we worked with lions functional experts and, uh, the lost knowledge that allowed the infrastructure being had. Um, we then applied our journey to cloud strategy, which basically revolves around the seminars and, and, uh, you know, the deep three steps from our perspective, uh, assessing the current environment, setting up the new cloud environment. And as we go modernizing and, and migrating these applications to the cloud now, you know, one of the key things that, uh, you know, we learned along this journey was that, you know, you can have the best plans, but bottom line that we were dealing with, we often than not have to make changes. Uh, what a lot of agility and also work with a lot of collaboration with the, uh, Lyon team, as well as, uh, uh, AWS. I think the key thing for me was being able to really bring it all together. It's not just, uh, you know, essentially mobilize it's all of us working together to make this happen. >>What were some of the learnings real quick journeys? >>So I think so the perspective of the key learnings that, you know, uh, you know, when you look back at, uh, the, the infrastructure that was that we were trying to migrate over to the cloud, a lot of the documentation, et cetera, was not available. We were having to, uh, figure out a lot of things on the fly. Now that really required us to have, uh, uh, people with deep expertise who could go into those environments and, and work out, uh, you know, the best ways to, to migrate the workloads to the cloud. Uh, I think, you know, the, the biggest thing for me was making sure all the had on that real SMEs across the board globally, that we could leverage across the various technologies, uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment with line. >>Let's do what I got to ask you. How did you address your approach to the cloud and what was your experience? >>Yeah, for me, it's around getting the foundations right. To start with and then building on them. Um, so, you know, you've gotta have your, your, your process and you've got to have your, your kind of your infrastructure there and your blueprints ready. Um, AWS do a great job of that, right. Getting the foundations right. And then building upon it, and then, you know, partnering with Accenture allows you to do that very successfully. Um, I think, um, you know, the one thing that was probably surprising to us when we started down this journey and kind of after we got a long way down the track and looking backwards is actually how much you can just turn off. Right? So a lot of stuff that you, uh, you get left with a legacy in your environment, and when you start to work through it with the types of people that civic just mentioned, you know, the technical expertise working with the business, um, you can really rationalize your environment and, uh, you know, cloud is a good opportunity to do that, to drive that legacy out. >>Um, so you know, a few things there, the other thing is, um, you've got to try and figure out the benefits that you're going to get out of moving here. So there's no point just taking something that is not delivering a huge amount of value in the traditional world, moving it into the cloud, and guess what is going to deliver the same limited amount of value. So you've got to transform it, and you've got to make sure that you build it for the future and understand exactly what you're trying to gain out of it. So again, you need a strong collaboration. You need a good partners to work with, and you need good engagement from the business as well, because the kind of, uh, you know, digital transformation, cloud transformation, isn't really an it project, I guess, fundamentally it is at the core, but it's a business project that you've got to get the whole business aligned on. You've got to make sure that your investment streams are appropriate and that you're able to understand the benefits and the value that, so you're going to drive back towards the business. >>Let's do it. If you don't mind me asking, what was some of the obstacles you encountered or learnings, um, that might different from the expectation we all been there, Hey, you know, we're going to change the world. Here's the sales pitch, here's the outcome. And then obviously things happen, you know, you learn legacy, okay. Let's put some containerization around that cloud native, um, all that rational. You're talking about what are, and you're going to have obstacles. That's how you learn. That's how perfection has developed. How, what obstacles did you come up with and how are they different from your expectations going in? >>Yeah, they're probably no different from other people that have gone down the same journey. If I'm totally honest, the, you know, 70 or 80% of what you do is relatively easy of the known quantity. It's relatively modern architectures and infrastructures, and you can upgrade, migrate, move them into the cloud, whatever it is, rehost, replatform, rearchitect, whatever it is you want to do, it's the other stuff, right? It's the stuff that always gets left behind. And that's the challenge. It's, it's getting that last bit over the line and making sure that you haven't invested in the future while still carrying all of your legacy costs and complexity within your environment. So, um, to be quite honest, that's probably taken longer and has been more of a challenge than we thought it would be. Um, the other piece I touched on earlier on in terms of what was surprising was actually how much of, uh, your environment is actually not needed anymore. >>When you start to put a critical eye across it and understand, um, uh, ask the tough questions and start to understand exactly what, what it is you're trying to achieve. So if you ask a part of a business, do they still need this application or this service a hundred percent of the time, they will say yes until you start to lay out to them, okay, now I'm going to cost you this to migrate it or this, to run it in the future. And, you know, here's your ongoing costs and, you know, et cetera, et cetera. And then, uh, for a significant amount of those answers, you get a different response when you start to layer on the true value of it. So you start to flush out those hidden costs within the business, and you start to make some critical decisions as a company based on, uh, based on that. So that was a little tougher than we first thought and probably broader than we thought there was more of that than we anticipated, um, which actually results in a much cleaner environment post and post migration. >>You know, the old expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value Stuart and Sadiq. Mainly if you can weigh in on this love to know the percentage of total cloud that you have now, versus when you started, because as you start to uncover whether it's by design for purpose, or you discover opportunities to innovate, like you guys have, I'm sure it kind of, you took on some territory inside Lyon, what percentage of cloud now versus stark? >>Yeah. At the start, it was minimal, right. You know, close to zero, right. Single and single digits. Right. It was mainly SAS environments that we had, uh, sitting in clouds when we, uh, when we started, um, Doug mentioned earlier on a really significant transformation project, um, that we've undertaken and recently gone live on a multi-year one. Um, you know, that's all stood up on AWS and is a significant portion of our environment, um, in terms of what we can move to cloud. Uh, we're probably at about 80 or 90% now. And the balanced bit is, um, legacy infrastructure that is just gonna retire as we go through the cycle rather than migrate to the cloud. Um, so we are significantly cloud-based and, uh, you know, we're reaping the benefits of it. I know you like 20, 20, I'm actually glad that you did all the hard yards in the previous years when you started that business challenges thrown out as, >>So do you any common reaction to the cloud percentage penetration? >>I mean, guys don't, but I was going to say was, I think it's like the 80 20 rule, right? We, we, we worked really hard in the, you know, I think 2018, 19 to get any person off, uh, after getting a loan, the cloud and, or the last year is the 20% that we have been migrating. And Stuart said like, uh, not that is also, that's going to be a good diet. And I think our next big step is going to be obviously, you know, the icing on the tape, which is to decommission all these apps as well. Right. So, you know, to get the real benefits out of, uh, the whole conservation program from a, uh, from a >>Douglas and Stewart, can you guys talk about the decision around the cloud because you guys have had success with AWS, why AWS how's that decision made? Can you guys give some insight into some of those thoughts? >>I can stop, start off. I think back when the decision was made and it was, it was a while back, um, you know, there's some clear advantages of moving relay, Ws, a lot of alignment with some of the significant projects and, uh, the trend, that particular one big transformation project that we've alluded to as well. Um, you know, we needed some, uh, some very robust and, um, just future proof and, um, proven technology. And they Ws gave that to us. We needed a lot of those blueprints to help us move down the path. We didn't want to reinvent everything. So, um, you know, having a lot of that legwork done for us and AWS gives you that, right. And, and particularly when you partner up with, uh, with a company like Accenture as well, you get combinations of the technology and the skills and the knowledge to, to move you forward in that direction. >>So, um, you know, for us, it was a, uh, uh, it was a decision based on, you know, best of breed, um, you know, looking forward and, and trying to predict the future needs and, and, and kind of the environmental that we might need. Um, and, you know, partnering up with organizations that can then take you on the journey. Yeah. And just to build on it. So obviously, you know, lion's like an AWS, but, you know, we knew it was a very good choice given that, um, uh, the skills and the capability that we had, as well as the assets and tools we had to get the most out of, um, AWS and obviously our, our CEO globally, you know, announcement about a huge investment that we're making in cloud. Um, but you know, we've, we've worked very well DWS, we've done some joint workshops and joint investments, um, some joint POC. So yeah, w we have a very good working relationship, AWS, and I think, um, one incident to reflect upon whether it's cyber it's and again, where we actually jointly, you know, dove in with, um, with Amazon and some of their security experts and our experts. And we're able to actually work through that with mine quite successfully. So, um, you know, really good behaviors as an organization, but also really good capabilities. >>Yeah. As you guys, you're essential cloud outcomes, research shown, it's the cycle of innovation with the cloud. That's creating a lot of benefits, knowing what you guys know now, looking back certainly COVID is impacted a lot of people kind of going through the same process, knowing what you guys know now, would you advocate people to jump on this transformation journey? If so, how, and what tweaks they make, which changes, what would you advise? >>Uh, I might take that one to start with. Um, I hate to think where we would have been when, uh, COVID kicked off here in Australia and, you know, we were all sent home, literally were at work on the Friday, and then over the weekend. And then Monday, we were told not to come back into the office and all of a sudden, um, our capacity in terms of remote access and I quadrupled, or more four, five X, uh, what we had on the Friday we needed on the Monday. And we were able to stand that up during the day Monday and into Tuesday, because we were cloud-based. And, uh, you know, we just found up your instances and, uh, you know, sort of our licensing, et cetera. And we had all of our people working remotely, um, within, uh, you know, effectively one business day. >>Um, I know peers of mine in other organizations and industries that are relying on kind of a traditional wise and getting hardware, et cetera, that were weeks and months before they could get their, the right hardware to be able to deliver to their user base. So, um, you know, one example where you're able to scale and, uh, uh, get, uh, get value out of this platform beyond probably what was anticipated at the time you talk about, um, you know, less the, in all of these kinds of things. And you can also think of a few scenarios, but real world ones where you're getting your business back up and running in that period of time is, is just phenomenal. There's other stuff, right? There's these programs that we've rolled out, you do your sizing, um, and in the traditional world, you would just go out and buy more servers than you need. >>And, you know, probably never realize the full value of those, you know, the capability of those servers over the life cycle of them. Whereas you're in a cloud world, you put in what you think is right. And if it's not right, you pump it up a little bit when, when all of your metrics and so on, tell you that you need to bump it up. And conversely you scale it down at the same rate. So for us, with the types of challenges and programs and, uh, uh, and just business need, that's come at as this year, uh, we wouldn't have been able to do it without a strong cloud base, uh, to, uh, to move forward >>Know Douglas. One of the things that I talked to, a lot of people on the right side of history who have been on the right wave with cloud, with the pandemic, and they're happy, they're like, and they're humble. Like, well, we're just lucky, you know, luck is preparation meets opportunity. And this is really about you guys getting in early and being prepared and readiness. This is kind of important as people realize, then you gotta be ready. I mean, it's not just, you don't get lucky by being in the right place, the right time. And there were a lot of companies were on the wrong side of history here who might get washed away. This is a super important, I think, >>To echo and kind of build on what Stewart said. I think that the reason that we've had success and I guess the momentum is we, we didn't just do it in isolation within it and technology. It was actually linked to broader business changes, you know, creating basically a digital platform for the entire business, moving the business, where are they going to be able to come back stronger after COVID, when they're actually set up for growth, um, and actually allows, you know, lying to achievements growth objectives, and also its ambitions as far as what it wants to do, uh, with growth in whatever they make, do with acquiring other companies and moving into different markets and launching new products. So we've actually done it in a way that is, you know, real and direct business benefit, uh, that actually enables line to grow >>General. I really appreciate you coming. I have one final question. If you can wrap up here, uh, Stuart and Douglas, you don't mind weighing in what's the priorities for the future. What's next for lion in a century >>Christmas holidays, I'll start Christmas holidays been a big deal and then a, and then a reset, obviously, right? So, um, you know, it's, it's figuring out, uh, transform what we've already transformed, if that makes sense. So God, a huge proportion of our services sitting in the cloud. Um, but we know we're not done even with the stuff that is in there. We need to take those next steps. We need more and more automation and orchestration. We need to, um, our environment, there's more future growth. We need to be able to work with the business and understand what's coming at them so that we can, um, you know, build that into, into our environment. So again, it's really transformation on top of transformation is the way that I'll describe it. And it's really an open book, right? Once you get it in and you've got the capabilities and the evolving tool sets that, uh, AWS continue to bring to the market, um, you know, working with the partners to, to figure out how we unlock that value, um, you know, drive our costs down efficiency, uh, all of those kind of, you know, standard metrics. >>Um, but you know, we're looking for the next things to transform and show value back out to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with and understand how we can better meet their needs. Yeah, I think just to echo that, I think it's really leveraging this and then did you capability they have and getting the most out of that investment. And then I think it's also moving to, uh, and adopting more new ways of working as far as, you know, the speed of the business, um, is getting up the speed of the market is changing. So being able to launch and do things quickly and also, um, competitive and efficient operating costs, uh, now that they're in the cloud, right? So I think it's really leveraging the most out of the platform and then, you know, being efficient in launching things. So putting them with the business, >>Any word from you on your priorities by you see this year in folding, >>There's got to say like e-learning squares, right, for me around, you know, just journey. This is a journey to the cloud, right. >>And, uh, you know, as well, the sort of Saturday, it's getting all, you know, different parts of the organization along the journey business to it, to your, uh, product lenders, et cetera. Right. And it takes time. It is tough, but, uh, uh, you know, you got to get started on it. And, you know, once we, once we finish off, uh, it's the realization of the benefits now that, you know, looking forward, I think for, from Alliance perspective, it is, uh, you know, once we migrate all the workloads to the cloud, it is leveraging, uh, all staff, right. And as I think students said earlier, uh, with, uh, you know, the latest and greatest stuff that AWS is basically working to see how we can really, uh, achieve more better operational excellence, uh, from a, uh, from a cloud perspective. >>Well, Stewart, thanks for coming on with a and sharing your environment and what's going on and your journey you're on the right wave. Did the work you're in, it's all coming together with faster, congratulations for your success, and, uh, really appreciate Douglas with Steve for coming on as well from Accenture. Thank you for coming on. Thanks, John. Okay. Just the cubes coverage of executive summit at AWS reinvent. This is where all the thought leaders share their best practices, their journeys, and of course, special programming with Accenture and the cube. I'm Sean ferry, your host, thanks for watching from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtuals coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First. We have Johan Krebbers. He is the GM digital emerging technologies and VP of it. Innovation at shell. Thank you so much for coming on the show, Johan you're welcome. And next we have Liz Dennett. She is the lead solution architect for O S D U on AWS. Thank you so much Liz to be here. So I want to start our conversation by talking about OSD. You like so many great innovations. It started with a problem Johan. What was the problem you were trying to solve at shell? >>Yeah, the ethical back a couple of years, we started shoving 2017 where we had a meeting with the deg, the gas exploration in shell, and the main problem they had. Of course, they got lots of lots of data, but are unable to find the right data. They need to work from all over the place. And totally >>Went to real, probably tried to solve is how that person working exploration could find their proper date, not just a day, but also the date you really needed that we did probably talked about his summer 2017. And we said, okay, they don't maybe see this moving forward is to start pulling that data into a single data platform. And that, that was at the time that we called it as the, you, the subsurface data universe in there was about the shell name was so in, in January, 2018, we started a project with Amazon to start grating a co fricking that building, that Stu environment that subserve the universe, so that single data level to put all your exploration and Wells data into that single environment that was intent. And every cent, um, already in March of that same year, we said, well, from Michelle point of view, we will be far better off if we could make this an industry solution and not just a shelf sluice, because Shelby, Shelby, if you can make an industry solution where people are developing applications for it, it also is far better than for shell to say we haven't shell special solution because we don't make money out of how we start a day that we can make money out of it. >>We have access to the data, we can explore the data. So storing the data we should do as efficiently possibly can. So we monitor, we reach out to about eight or nine other large, uh, or I guess operators like the economics, like the tutorials, like the chefs of this world and say, Hey, we inshallah doing this. Do you want to join this effort? And to our surprise, they all said, yes. And then in September, 2018, we had our kickoff meeting with your open group where we said, we said, okay, if you want to work together with lots of other companies, we also need to look at okay, how, how we organize that. Or if you started working with lots of large companies, you need to have some legal framework around some framework around it. So that's why we went to the open group and say, okay, let's, let's form the old forum as we call it at the time. So it's September, 2080, where I did a Galleria in Houston, but the kickoff meeting for the OT four with about 10 members at the time. So there's just over two years ago, we started an exercise for me called ODU, uh, kicked it off. Uh, and so that's really them will be coming from and how we've got there. Also >>The origin story. Um, what, so what digging a little deeper there? What were some of the things you were trying to achieve with the OSU? >>Well, a couple of things we've tried to achieve with you, um, first is really separating data from applications for what is, what is the biggest problem we have in the subsurface space that the data and applications are all interlinked tied together. And if, if you have them and a new company coming along and say, I have this new application and is access to the data that is not possible because the data often interlinked with the application. So the first thing we did is really breaking the link between the application, the data out as those levels, the first thing we did, secondly, put all the data to a single data platform, take the silos out what was happening in the sub-service space and know they got all the data in what we call silos in small little islands out there. So what we're trying to do is first break the link to great, great. >>They put the data single day, the bathroom, and the third part, put a standard layer on top of that, it's an API layer on top to create a platform. So we could create an ecosystem out of companies to start a valving shop application on top of dev data platform across you might have a data platform, but you're only successful. If you have a rich ecosystem of people start developing applications on top of that. And then you can export the data like small companies, last company, university, you name it, we're getting after create an ecosystem out there. So the three things were as was first break, the link between application data, just break it and put data at the center and also make sure that data, this data structure would not be managed by one company. It would only be met. It will be managed the data structures by the ODI forum. Secondly, then put a data, a single data platform certainly then has an API layer on top and then create an ecosystem. Really go for people, say, please start developing applications because now you have access to the data or the data no longer linked to somebody whose application was all freely available, but an API layer that was, that was all September, 2018, more or less >>To hear a little bit. Can you talk a little bit about some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? Yeah, absolutely. And this whole thing is Johann said started with a challenge that was really brought out at shell. The challenges that geoscientists spend up to 70% of their time looking for data. I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out how we could address that one problem, we worked together to really understand the root cause of these challenges and working backwards from that use case OSU and OSU on AWS has really enabled customers to create solutions that span, not just this in particular problem, but can really scale to be inclusive of the entire energy value chain and deliver value from these use cases to the energy industry and beyond. >>Thank you, Lee, >>Uh, Johann. So talk a little bit about Accenture's cloud first approach and how it has, uh, helped shell work faster and better with it. >>Well, of course, access a cloud first approach only works together. It's been an Amazon environment, AWS environment. So we really look at, uh, at, at Accenture and others up together helping shell in this space. Now the combination of the two is where we're really looking at, uh, where access of course can be increased knowledge student to that environment operates support knowledge to do an environment. And of course, Amazon will be doing that to this environment that underpinning their services, et cetera. So, uh, we would expect a combination, a lot of goods when we started rolling out and put in production, the old you are three and four because we are anus. Then when release feed comes to the market in Q1 next year of ODU, when he started going to Audi production inside shell, but as the first release, which is ready for prime time production across an enterprise will be released just before Christmas, last year when he's still in may of this year. But really three is the first release we want to use for full scale production deployment inside shell, and also all the operators around the world. And there is one Amazon, sorry, at that one. Um, extensive can play a role in the ongoing, in the, in deployment building up, but also support environment. >>So one of the other things that we talk a lot about here on the cube is sustainability. And this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSD you, uh, help organizations become, how is this a greener solution for companies? >>Well, first he make it's a greatest solution because you start making a much more efficient use of your resources. is already an important one. The second thing we're doing is also, we started with ODU in framers, in the oil and gas space in the expert development space. We've grown, uh, OTU in our strategy, we've grown. I was, you know, also do an alternative energy sociology. We'll all start supporting next year. Things like solar farms, wind farms, uh, the, the dermatomal environment hydration. So it becomes an and, and an open energy data platform, not just what I want to get into steep that's for new industry, any type of energy industry. So our focus is to create, bring the data of all those various energy data sources to get me to a single data platform you can to use AI and other technology on top of that, to exploit the data, to beat again into a single data platform. >>Liz, I want to ask you about security because security is, is, is such a big concern when it comes to data. How secure is the data on OSD? You, um, actually, can I talk, can I do a follow up on this sustainability talking? Oh, absolutely. By all means. I mean, I want to interject though security is absolutely our top priority. I don't mean to move away from that, but with sustainability, in addition to the benefits of the OSU data platform, when a company moves from on-prem to the cloud, they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical data center. Now, a recent study by four 51 research found that AWS is infrastructure is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to higher, um, server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases for 51 found that AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSU are working to support our customers is they seek to better understand their workflows and make their legacy businesses less carbon intensive. >>That's that's incorrect. Those are those statistics are incredible. Do you want to talk a little bit now about security? Absolutely. Security will always be AWS is top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy. There are the security requirements for the military global banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build an operate each of our regions. So that customers benefit from the only commercial cloud that's hat hits service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features as well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. Johann, I want you to talk a little bit about how OSD you can be used today. Does it only handle subsurface data? >>Uh, today it's Honda's subserves or Wells data. We got to add to that production around the middle of next year. That means that the whole upstate business. So we've got goes from exploration all the way to production. You've made it together into a single data platform. So production will be added around Q3 of next year. Then a principal. We have a difficult, the elder data that single environment, and we want to extend it then to other data sources or energy sources like solar farms, wind farms, uh, hydrogen, hydro, et cetera. So we're going to add a whore, a whole list of audit day energy source to them and be all the data together into a single data club. So we move from an all in guest data platform to an entity data platform. That's really what our objective is because the whole industry, if you look it over, look at our competition or moving in that same two acts of quantity of course, are very strong in oil and gas, but also increased the, got into other energy sources like, like solar, like wind, like th like highly attended, et cetera. So we would be moving exactly what it's saying, method that, that, that, that the whole OSU can't really support at home. And as a spectrum of energy sources, >>Of course, and Liz and Johan. I want you to close this out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSD. We'll start with you, Liz, what do you, what do you see as the future holding for this platform? Um, honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers, wherever their OSU journeys, take them, whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond, but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges, Johann first, nobody can look at any more nowadays, especially 10 years, but our objective is really in the next five years, you will become the key backbone for energy companies for store your data intelligence and optimize the whole supply energy supply chain, uh, in this world Johan Krebbers Liz Dennett. Thank you so much for coming on the cube virtual. Thank you. I'm Rebecca Knight stay tuned for more of our coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight today we're welcoming back to Cuba alum. We have Kishor Dirk. He is the Accenture senior managing director cloud first global services lead. Welcome back to the show Kishore. Thank you very much. Nice to meet again. And, uh, Tristan moral horse set. He is the managing director, Accenture cloud first North American growth. Welcome back to you to Tristin. Great to be back in grapes here again, Rebecca. Exactly. Even in this virtual format, it is good to see your faces. Um, today we're going to be talking about my NAB and green cloud advisor capability. Kishor I want to start with you. So my NAB is a platform that is really celebrating its first year in existence. Uh, November, 2019 is when Accenture introduced it. Uh, but it's, it has new relevance in light of this global pandemic that we are all enduring and suffering through. Tell us a little bit about the lineup platform, what it is that cloud platform to help our clients navigate the complexity of cloud and cloud decisions and to make it faster. And obviously, you know, we have in the cloud, uh, you know, with >>The increased relevance and all the, especially over the last few months with the impact of COVID crisis and exhibition of digital transformation, you know, we are seeing the transformation of the exhibition to cloud much faster. This platform that you're talking about has enabled hardened 40 clients globally across different industries. You identify the right cloud solution, navigate the complexity, provide a cloud specific solution simulate for our clients to meet that strategy business needs. And the clients are loving it. >>I want to go to you now trust and tell us a little bit about how my nav works and how it helps companies make good cloud choice. >>Yeah, so Rebecca, we we've talked about cloud is, is more than just infrastructure and that's what mine app tries to solve for it. It really looks at a variety of variables, including infrastructure operating model and fundamentally what clients' business outcomes, um, uh, our clients are, are looking for and, and identifies the optimal solution for what they need. And we assign this to accelerate. And we mentioned that the pandemic, one of the big focus now is to accelerate. And so we worked through a three-step process. The first is scanning and assessing our client's infrastructure, their data landscape, their application. Second, we use our automated artificial intelligence engine to interact with. We have a wide variety and library of, uh, collective plot expertise. And we look to recommend what is the enterprise architecture and solution. And then third, before we live with our clients, we look to simulate and test this scaled up model. And the simulation gives our clients a way to see what cloud is going to look like, feel like and how it's going to transform their business before they go there. >>Tell us a little bit about that in real life. Now as a company, so many of people are working remotely having to collaborate, uh, not in real life. How is that helping them right now? >>So, um, the, the pandemic has put a tremendous strain on systems, uh, because of the demand on those systems. And so we talk about resiliency. We also now need to collaborate across data across people. Um, I think all of us are calling from a variety of different places where our last year we were all at the VA cube itself. Um, and, and cloud technologies such as teams, zoom that we're we're leveraging now has fundamentally accelerated and clients are looking to onboard this for their capabilities. They're trying to accelerate their journey. They realize that now the cloud is what is going to become important for them to differentiate. Once we come out of the pandemic and the ability to collaborate with their employees, their partners, and their clients through these systems is becoming a true business differentiator for our clients. >>Keisha, I want to talk with you now about my navs multiple capabilities, um, and helping clients design and navigate their cloud journeys. Tell us a little bit about the green cloud advisor capability and its significance, particularly as so many companies are thinking more deeply and thoughtfully about sustainability. >>Yes. So since the launch of my NAB, we continue to enhance capabilities for our clients. One of the significant, uh, capabilities that we have enabled is the being or advisor today. You know, Rebecca, a lot of the businesses are more environmentally aware and are expanding efforts to decrease power consumption, uh, and obviously carbon emissions and, uh, and run a sustainable operations across every aspect of the enterprise. Uh, as a result, you're seeing an increasing trend in adoption of energy, efficient infrastructure in the global market. And one of the things that we did, a lot of research we found out is that there's an ability to influence our client's carbon footprint through a better cloud solution. And that's what we internalize, uh, brings to us, uh, in, in terms of a lot of the client connotation that you're seeing in Europe, North America and others. Lot of our clients are accelerating to a green cloud strategy to unlock greater financial societal and environmental benefit, uh, through obviously cloud-based circular, operational, sustainable products and services. That is something that we are enhancing my now, and we are having active client discussions at this point of time. >>So Tristan, tell us a little bit about how this capability helps clients make greener decisions. >>Yeah. Um, well, let's start about the investments from the cloud providers in renewable and sustainable energy. Um, they have most of the hyperscalers today, um, have been investing significantly on data centers that are run on renewable energy, some incredibly creative constructs on the, how, how to do that. And sustainability is there for a key, um, key item of importance for the hyperscalers and also for our clients who now are looking for sustainable energy. And it turns out this marriage is now possible. I can, we marry the, the green capabilities of the cloud providers with a sustainability agenda of our clients. And so what we look into the way the mind works is it looks at industry benchmarks and evaluates our current clients, um, capabilities and carpet footprint leveraging their existing data centers. We then look to model from an end-to-end perspective, how the, their journey to the cloud leveraging sustainable and, um, and data centers with renewable energy. We look at how their solution will look like and, and quantify carbon tax credits, um, improve a green index score and provide quantifiable, um, green cloud capabilities and measurable outcomes to our clients, shareholders, stakeholders, clients, and customers. Um, and our green plot advisers sustainability solutions already been implemented at three clients. And in many cases in two cases has helped them reduce the carbon footprint by up to 400% through migration from their existing data center to green cloud. Very, very, >>That is remarkable. Now tell us a little bit about the kinds of clients. Is this, is this more interesting to clients in Europe? Would you say that it's catching on in the United States? Where, what is the breakdown that you're seeing right now? >>Sustainability is becoming such a global agenda and we're seeing our clients, um, uh, tie this and put this at board level, um, uh, agenda and requirements across the globe. Um, Europe has specific constraints around data sovereignty, right, where they need their data in country, but from a green, a sustainability agenda, we see clients across all our markets, North America, Europe in our growth markets adopt this. And we have seen case studies and all three months, >>Kesha. I want to bring you back into the conversation. Talk a little bit about how MindUP ties into Accenture's cloud first strategy, your Accenture's CEO, Julie Sweet, um, has talked about post COVID leadership, requiring every business to become a cloud first business. Tell us a little bit about how this ethos is in Accenture and how you're sort of looking outward with it too. >>So Rebecca mine is the launch pad, uh, to a cloud first transformation for our clients. Uh, Accenture, see your jewelry suite, uh, shared the Accenture cloud first and our substantial investment demonstrate our commitment and is delivering greater value for our clients when they need it the most. And with the digital transformation requiring cloud at scale, you know, we're seeing that in the post COVID leadership, it requires that every business should become a cloud business. And my nap helps them get there by evaluating the cloud landscape, navigating the complexity, modeling architecting and simulating an optimal cloud solution for our clients. And as Justin was sharing a greener cloud. >>So Tristan, talk a little bit more about some of the real life use cases in terms of what are we, what are clients seeing? What are the results that they're having? >>Yes. Thank you, Rebecca. I would say two key things right around my notes. The first is the iterative process. Clients don't want to wait, um, until they get started, they want to get started and see what their journey is going to look like. And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need to move to cloud very quickly. And my nav is there to do that. So how do we do that? First is generating the business cases. Clients need to know in many cases that they have a business case by business case, we talk about the financial benefits, as well as the business outcomes, the green, green clot impact sustainability impacts with minus. We can build initial recommendations using a basic understanding of their environment and benchmarks in weeks versus months with indicative value savings in the millions of dollars arranges. >>So for example, very recently, we worked with a global oil and gas company, and in only two weeks, we're able to provide an indicative savings where $27 million over five years, this enabled the client to get started, knowing that there is a business case benefit and then iterate on it. And this iteration is, I would say the second point that is particularly important with my nav that we've seen in bank of clients, which is, um, any journey starts with an understanding of what is the application landscape and what are we trying to do with those, these initial assessments that used to take six to eight weeks are now taking anywhere from two to four weeks. So we're seeing a 40 to 50% reduction in the initial assessment, which gets clients started in their journey. And then finally we've had discussions with all of the hyperscalers to help partner with Accenture and leverage mine after prepared their detailed business case module as they're going to clients. And as they're accelerating the client's journey, so real results, real acceleration. And is there a journey? Do I have a business case and furthermore accelerating the journey once we are by giving the ability to work in iterative approach. >>I mean, it sounds as though that the company that clients and and employees are sort of saying, this is an amazing time savings look at what I can do here in, in so much in a condensed amount of time, but in terms of getting everyone on board, one of the things we talked about last time we met, uh, Tristin was just how much, uh, how one of the obstacles is getting people to sign on and the new technologies and new platforms. Those are often the obstacles and struggles that companies face. Have you found that at all? Or what is sort of the feedback that you're getting? >>Yeah, sorry. Yes. We clearly, there are always obstacles to a cloud journey. If there were an obstacles, all our clients would be, uh, already fully in the cloud. What man I gives the ability is to navigate through those, to start quickly. And then as we identify obstacles, we can simulate what things are going to look like. We can continue with certain parts of the journey while we deal with that obstacle. And it's a fundamental accelerator. Whereas in the past one, obstacle would prevent a class from starting. We can now start to address the obstacles one at a time while continuing and accelerating the contrary. That is the fundamental difference. >>Kishor I want to give you the final word here. Tell us a little bit about what is next for Accenture might have and what we'll be discussing next year at the Accenture executive summit, >>Rebecca, we are continuously evolving with our client needs and reinventing reinventing for the future. Well, mine has been toward advisor. Our plan is to help our clients reduce carbon footprint and again, migrate to a green cloud. Uh, and additionally, we're looking at, you know, two capabilities, uh, which include sovereign cloud advisor, uh, with clients, especially in, in Europe and others are under pressure to meet, uh, stringent data norms that Kristen was talking about. And the sovereign cloud advisor helps organization to create an architecture cloud architecture that complies with the green. Uh, I would say the data sovereignty norms that is out there. The other element is around data to cloud. We are seeing massive migration, uh, for, uh, for a lot of the data to cloud. And there's a lot of migration hurdles that come within that. Uh, we have expanded mine app to support assessment capabilities, uh, for, uh, assessing applications, infrastructure, but also covering the entire state, including data and the code level to determine the right cloud solution. So we are, we are pushing the boundaries on what mine app can do with mine. Have you created the ability to take the guesswork out of cloud, navigate the complexity? We are rolling risks costs, and we are, you know, achieving client's static business objectives while building a sustainable alerts with being cloud, >>Any platform that can take some of the guesswork out of the future. I am I'm on board with thank you so much, Tristin and Kishore. This has been a great conversation. Stay tuned for more of the cubes coverage of the Accenture executive summit. I'm Rebecca Knight.

Published Date : Dec 1 2020

SUMMARY :

It's the cube with digital coverage Welcome to cube three 60 fives coverage of the Accenture executive summit. Thanks for having me here. impact of the COVID-19 pandemic has been, what are you hearing from clients? you know, various facets, you know, um, first and foremost, to this reasonably okay, and are, you know, launching to So you just talked about the widening gap. all the changes the pandemic has brought to them. in the cloud that we are going to see. Can you tell us a little bit more about what this strategy entails? all of the systems under which they attract need to be liberated so that you could drive now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, That is their employees, uh, because you do, across every department, I'm the agent of this change is going to be the employees or weapon, So how are you helping your clients, And that is again, the power of cloud. And the power of cloud is to get all of these capabilities from outside that employee, the employee will be more engaged in his or her job and therefore And this is, um, you know, no more true than how So at Accenture, you have long, long, deep Stan, sorry, And in fact, in the cloud world, it was one of the first, um, And one great example is what we are doing with Takeda, uh, billable, So all of these things that we will do Yeah, the future to the next, you know, base camp, as I would call it to further this productivity, And the evolution that is going to happen where, you know, the human grace of mankind, I genuinely believe that cloud first is going to be in the forefront of that change It's the cube with digital coverage I want to start by asking you what it is that we mean when we say green cloud, magnitude of the problem that is out there and how do we pursue a green approach. Them a lot of questions, the decision to make, uh, this particular, And, uh, you know, the, obviously the companies have to unlock greater financial How do you partner and what is your approach in terms of helping them with their migrations? uh, you know, from a few manufacturers hand sanitizers, and to answer it role there, uh, you know, from, in terms of our clients, you know, there are multiple steps And in the third year and another 3 million analytics costs that are saved through right-sizing Instead of it, we practice what we preach, and that is something that we take it to heart. We know that conquering this pandemic is going to take a coordinated And it's about a group of global stakeholders cooperating to simultaneously manage the uh, in, in UK to build, uh, uh, you know, uh, Microsoft teams in What do you see as the different, the financial security or agility benefits to cloud. And obviously the ecosystem partnership that we have that We, what, what do you think the next 12 to 24 months? And we all along with Accenture clients will win. Thank you so much. It's the cube with digital coverage of AWS reinvent executive And what happens when you bring together the scientific and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and, And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. And I think that, you know, that's going to help us make faster, better decisions. Um, and so I think with that, you know, there's a few different, How do we re-imagine that, you know, how do ideas go from getting tested So Arjun, I want to bring you into this conversation a little bit, let let's delve into those a bit. It was, uh, something that, you know, we had all to do differently. And maybe the third thing I would say is this one team And I think if you really think about what he's talking about, Because the old ways of thinking where you've got application people and infrastructure, How will their experience of work change and how are you helping re-imagine and And it's something that, you know, I think we all have to think a lot about, I mean, And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are Uh, and so I think that that's, you know, one, one element that, uh, can be considered. or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently the customer obsession and this idea of innovating much more quickly. and Carl mentioned some of the things that, you know, partner like AWS can bring to the table is we talk a lot about builders, And it's not just the technical people or the it people who are And Accenture's, and so we were able to bring that together. And so we chose, you know, uh, with our focus on innovation that when people think about cloud, you know, you always think about infrastructure technology. And thank you for tuning into the cube. It's the cube with digital coverage So we are going to be talking and also what were some of the challenges that you were grappling with prior to this initiative? Um, so the reason we sort of embarked um, you know, certainly as a, as an it leader and sort of my operational colleagues, What is the art of the possible, can you tell us a little bit about why you chose the public sector that, you know, there are many rules and regulations, uh, quite rightly as you would expect Matthew, I want to bring you into the conversation a little bit here. to bring in a number of the different themes that we have say, cloud teams, security teams, um, I mean, so much of this is about embracing comprehensive change to experiment and innovate and and the outcomes they're looking to achieve rather than simply focusing on a long list of requirements, It's not always a one size fits all. um, that is gonna update before you even get that. So to give you a little bit of, of context, when we, um, started And the pilot was so successful. And I think just parallel to that is the quality of our, because we had a lot of data, That kind of return on investment because what you were just describing with all the steps that we needed Um, but all the, you know, the minutes here and there certainly add up Have you seen any changes Um, but you can see the step change that is making in each aspect to the organization, And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain You know, we had lots of workshops and seminars where we all talk about, you know, you know, to see the stat change, you know, and, and if we, if we have any issues now it's literally, when you are trying to get everyone on board for this kind of thing? The solution itself is, um, you know, extremely large and, um, I want to hear, where do you go from here? crazy, but because it's apparently not that simple, but, um, you know, And you are watching the cube stay tuned for more of the cubes coverage of the AWS in particular has brought it together because you know, COVID has been the accelerant So number of years back, we looked at kind of our infrastructure and our landscape trying to figure uh, you know, start to deliver bit by bit incremental progress, uh, to get to the, of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually I want to just real quick, a redirect to you and say, you know, if all the people said, Oh yeah, And, um, you know, Australia, we had to live through Bush fires You know, we're going to get the city, you get a minute on specifically, but from your perspective, uh, Douglas, to hours and days, and truly allowed us to, we had to, you know, VJ things, And what specifically did you guys do at Accenture and how did it all come together? the seminars and, and, uh, you know, the deep three steps from uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment How did you address your approach to the cloud and what was your experience? And then building upon it, and then, you know, partnering with Accenture allows because the kind of, uh, you know, digital transformation, cloud transformation, learnings, um, that might different from the expectation we all been there, Hey, you know, It's, it's getting that last bit over the line and making sure that you haven't invested in the future hundred percent of the time, they will say yes until you start to lay out to them, okay, You know, the old expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, Um, you know, that's all stood up on AWS and is a significant portion of And I think our next big step is going to be obviously, uh, with a company like Accenture as well, you get combinations of the technology and the skills and the So obviously, you know, lion's like an AWS, but, you know, a lot of people kind of going through the same process, knowing what you guys know now, And we had all of our people working remotely, um, within, uh, you know, effectively one business day. and in the traditional world, you would just go out and buy more servers than you need. And if it's not right, you pump it up a little bit when, when all of your metrics and so on, And this is really about you guys when they're actually set up for growth, um, and actually allows, you know, lying to achievements I really appreciate you coming. to figure out how we unlock that value, um, you know, drive our costs down efficiency, to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with There's got to say like e-learning squares, right, for me around, you know, It is tough, but, uh, uh, you know, you got to get started on it. It's the cube with digital coverage of Thank you so much for coming on the show, Johan you're welcome. Yeah, the ethical back a couple of years, we started shoving 2017 where we it also is far better than for shell to say we haven't shell special solution because we don't So storing the data we should do What were some of the things you were trying to achieve with the OSU? So the first thing we did is really breaking the link between the application, And then you can export the data like small companies, last company, standpoint in terms of what you were trying to achieve with this? uh, helped shell work faster and better with it. a lot of goods when we started rolling out and put in production, the old you are three and four because we are So one of the other things that we talk a lot about here on the cube is sustainability. I was, you know, also do an alternative energy sociology. found that AWS performs the same task with an 88% lower So that customers benefit from the only commercial cloud that's hat hits service offerings and the whole industry, if you look it over, look at our competition or moving in that same two acts of quantity of course, our objective is really in the next five years, you will become the key It's the cube with digital coverage And obviously, you know, we have in the cloud, uh, you know, with and exhibition of digital transformation, you know, we are seeing the transformation of I want to go to you now trust and tell us a little bit about how my nav works and how it helps And then third, before we live with our clients, having to collaborate, uh, not in real life. They realize that now the cloud is what is going to become important for them to differentiate. Keisha, I want to talk with you now about my navs multiple capabilities, And one of the things that we did, a lot of research we found out is that there's an ability to influence So Tristan, tell us a little bit about how this capability helps clients make greener And so what we look into the way the Would you say that it's catching on in the United States? And we have seen case studies and all I want to bring you back into the conversation. And with the digital transformation requiring cloud at scale, you know, we're seeing that in And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need So for example, very recently, we worked with a global oil and gas company, Have you found that at all? What man I gives the ability is to navigate through those, to start quickly. Kishor I want to give you the final word here. and we are, you know, achieving client's static business objectives while I am I'm on board with thank you so much,

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AWS Executive Summit 2020


 

>>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to cube three 60 fives coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight. Today we are joined by a cube alum, Karthik, Lorraine. He is Accenture senior managing director and lead Accenture cloud. First, welcome back to the show Karthik. >>Thank you. Thanks for having me here. >>Always a pleasure. So I want to talk to you. You are an industry veteran, you've been in Silicon Valley for decades. Um, I want to hear from your perspective what the impact of the COVID-19 pandemic has been, what are you hearing from clients? What are they struggling with? What are their challenges that they're facing day to day? >>I think, um, COVID-19 is being a eye-opener from, you know, various facets, you know, um, first and foremost, it's a, it's a hell, um, situation that everybody's facing, which is not just, uh, highest economic bearings to it. It has enterprise, um, an organization with bedding to it. And most importantly, it's very personal to people, um, because they themselves and their friends, family near and dear ones are going through this challenge, uh, from various different dimension. But putting that aside, when you come to it from an organization enterprise standpoint, it has changed everything well, the behavior of organizations coming together, working in their campuses, working with each other as friends, family, and, uh, um, near and dear colleagues, all of them are operating differently. So that's what big change to get things done in a completely different way, from how they used to get things done. >>Number two, a lot of things that were planned for normal scenarios, like their global supply chain, how they interact with their client customers, how they go innovate with their partners on how that employees contribute to the success of an organization at all changed. And there are no data models that give them a hint of something like this for them to be prepared for this. So we are seeing organizations, um, that have adapted to this reasonably okay, and are, you know, launching to innovate faster in this. And there are organizations that have started with struggling, but are continuing to struggle. And the gap between the leaders and legs are widening. So this is creating opportunities in a different way for the leaders, um, with a lot of pivot their business, but it's also creating significant challenge for the lag guides, uh, as we defined in our future systems research that we did a year ago, uh, and those organizations are struggling further. So the gap is actually widening. >>So you just talked about the widening gap. I've talked about the tremendous uncertainty that so many companies, even the ones who have adapted reasonably well, uh, in this, in this time, talk a little bit about Accenture cloud first and why, why now? >>I think it's a great question. Um, we believe that for many of our clients COVID-19 has turned, uh, cloud from an experimentation aspiration to an origin mandate. What I mean by that is everybody has been doing something on the other end cloud. There's no company that says we don't believe in cloud are, we don't want to do cloud. It was how much they did in cloud. And they were experimenting. They were doing the new things in cloud, but they were operating a lot of their core business outside the cloud or not in the cloud. Those organizations have struggled to operate in this new normal, in a remote fashion, as well as, uh, their ability to pivot to all the changes the pandemic has brought to them. But on the other hand, the organizations that had a solid foundation in cloud were able to collect faster and not actually gone into the stage of innovating faster and driving a new behavior in the market, new behavior within their organization. >>So we are seeing that spend to make is actually fast-forwarded something that we always believed was going to happen. This, uh, uh, moving to cloud over the next decade is fast forward it to happen in the next three to five years. And it's created this moment where it's a once in an era, really replatforming of businesses in the cloud that we are going to see. And we see this moment as a cloud first moment where organizations will use cloud as the, the, the canvas and the foundation with which they're going to reimagine their business after they were born in the cloud. Uh, and this requires a whole new strategy. Uh, and as Accenture, we are getting a lot in cloud, but we thought that this is the moment where we bring all of that, gave him a piece together because we need a strategy for addressing, moving to cloud are embracing cloud in a holistic fashion. And that's what Accenture cloud first brings together a holistic strategy, a team that's 70,000 plus people that's coming together with rich cloud skills, but investing to tie in all the various capabilities of cloud to Delaware, that holistic strategy to our clients. So I want you to >>Delve into a little bit more about what this strategy actually entails. I mean, it's clearly about embracing change and being willing to experiment and having capabilities to innovate. Can you tell us a little bit more about what this strategy entails? >>Yeah. The reason why we say that as a need for strategy is like I said, cloud is not new. There's almost every customer client is doing something with the cloud, but all of them have taken different approaches to cloud and different boundaries to cloud. Some organizations say, I just need to consolidate my multiple data centers to a small data center footprint and move the nest to cloud. Certain other organizations say that well, I'm going to move certain workloads to cloud. Certain other organizations said, well, I'm going to build this Greenfield application or workload in cloud. Certain other said, um, I'm going to use the power of AI ML in the cloud to analyze my data and drive insights. But a cloud first strategy is all of this tied with the corporate strategy of the organization with an industry specific cloud journey to say, if in this current industry, if I were to be reborn in the cloud, would I do it in the exact same passion that I did in the past, which means that the products and services that they offer need to be the matching, how they interact with that customers and partners need to be revisited, how they bird and operate their IP systems need to be the, imagine how they unearthed the data from all of the systems under which they attract need to be liberated so that you could drive insights of cloud. >>First strategy hands is a corporate wide strategy, and it's a C-suite responsibility. It doesn't take the ownership away from the CIO or CIO, but the CIO is, and CDI was felt that it was just their problem and they were to solve it. And everyone as being a customer, now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's agenda, where probably the CDI is the instrument to execute that that's a holistic cloud-first strategy >>And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, as you were saying, this idea of being reborn in the cloud. So now how do I think about things? How do I communicate? How do I collaborate? How do I get done? What I need to get done. Talk a little bit about how this has changed, the way you support your clients and how Accenture cloud first is changing your approach to cloud services. >>Wonderful. Um, you know, I did not color one very important aspect in my previous question, but that's exactly what you just asked me now, which is to do all of this. I talked about all of the variables, uh, an organization or an enterprise is going to go through, but the good part is they have one constant. And what is that? That is their employees, uh, because you do, the employees are able to embrace this change. If they are able to, uh, change them, says, pivot them says retool and train themselves to be able to operate in this new cloud. First one, the ability to reimagine every function of the business would be happening at speed. And cloud first approach is to do all of this at speed, because innovation is deadly proposed there, do the rate of probability on experimentation. You need to experiment a lot for any kind of experimentation. >>There's a probability of success. Organizations need to have an ability and a mechanism for them to be able to innovate faster for which they need to experiment a lot, the more the experiment and the lower cost at which they experiment is going to help them experiment a lot. And they experiment demic speed, fail fast, succeed more. And hence, they're going to be able to operate this at speed. So the cloud-first mindset is all about speed. I'm helping the clients fast track that innovation journey, and this is going to happen. Like I said, across the enterprise and every function across every department, I'm the agent of this change is going to be the employees or weapon, race, this change through new skills and new grueling and new mindset that they need to adapt to. >>So Karthik what you're describing it, it sounds so exciting. And yet for a pandemic wary workforce, that's been working remotely that may be dealing with uncertainty if for their kid's school and for so many other aspects of their life, it sounds hard. So how are you helping your clients, employees get onboard with this? And because the change management is, is often the hardest part. >>Yeah, I think it's, again, a great question. A bottle has only so much capacity. Something got to come off for something else to go in. That's what you're saying is absolutely right. And that is again, the power of cloud. The reason why cloud is such a fundamental breakthrough technology and capability for us to succeed in this era, because it helps in various forms. What we talked so far is the power of innovation that can create, but cloud can also simplify the life of the employees in an enterprise. There are several activities and tasks that people do in managing that complex infrastructure, complex ID landscape. They used to do certain jobs and activities in a very difficult underground about with cloud has simplified. And democratised a lot of these activities. So that things which had to be done in the past, like managing the complexity of the infrastructure, keeping them up all the time, managing the, um, the obsolescence of the capabilities and technologies and infrastructure, all of that could be offloaded to the cloud. >>So that the time that is available for all of these employees can be used to further innovate. Every organization is going to spend almost the same amount of money, but rather than spending activities, by looking at the rear view mirror on keeping the lights on, they're going to spend more money, more time, more energy, and spend their skills on things that are going to add value to their organization. Because you, every innovation that an enterprise can give to their end customer need not come from that enterprise. The word of platform economy is about democratising innovation. And the power of cloud is to get all of these capabilities from outside the four walls of the enterprise, >>It will add value to the organization, but I would imagine also add value to that employee's life because that employee, the employee will be more engaged in his or her job and therefore bring more excitement and energy into her, his or her day-to-day activities too. >>Absolutely. Absolutely. And this is, this is a normal evolution we would have seen everybody would have seen in their lives, that they keep moving up the value chain of what activities that, uh, gets performed buying by those individuals. And this is, um, you know, no more true than how the United States, uh, as an economy has operated where, um, this is the power of a powerhouse of innovation, where the work that's done inside the country keeps moving up to value chain. And, um, us leverage is the global economy for a lot of things that is required to power the United States and that global economic, uh, phenomenon is very proof for an enterprise as well. There are things that an enterprise needs to do them soon. There are things an employee needs to do themselves. Um, but there are things that they could leverage from the external innovation and the power of innovation that is coming from technologies like cloud. >>So at Accenture, you have long, long, deep Stan, sorry, you have deep and long-standing relationships with many cloud service providers, including AWS. How does the Accenture cloud first strategy, how does it affect your relationships with those providers? >>Yeah, we have great relationships with cloud providers like AWS. And in fact, in the cloud world, it was one of the first, um, capability that we started about years ago, uh, when we started developing these capabilities. But five years ago, we hit a very important milestone where the two organizations came together and said that we are forging a pharma partnership with joint investments to build this partnership. And we named that as a Accenture, AWS business group ABG, uh, where we co-invest and brought skills together and develop solutions. And we will continue to do that. And through that investment, we've also made several acquisitions that you would have seen in the recent times, like, uh, an invoice and gecko that we made acquisitions in in Europe. But now we're taking this to the next level. What we are saying is two cloud first and the $3 billion investment that we are bringing in, uh, through cloud-first. >>We are going to make specific investment to create unique joint solution and landing zones foundation, um, cloud packs with which clients can accelerate their innovation or their journey to cloud first. And one great example is what we are doing with Takeda, uh, billable, pharmaceutical giant, um, between we've signed a five-year partnership. And it was out in the media just a month ago or so, where we are, the two organizations are coming together. We have created a partnership as a power of three partnership, where the three organizations are jointly hoarding hats and taking responsibility for the innovation and the leadership position that Takeda wants to get to with this. We are going to simplify their operating model and organization by providing and flexibility. We're going to provide a lot more insights. Tequila has a 230 year old organization. Imagine the amount of trapped data and intelligence that is there. >>How about bringing all of that together with the power of AWS and Accenture and Takeda to drive more customer insights, um, come up with breakthrough R and D uh, accelerate clinical trials and improve the patient experience using AI ML and edge technologies. So all of these things that we will do through this partnership with joined investment from Accenture cloud first, as well as partner like AWS, so that Takeda can realize their gain. And, uh, their senior actually made a statement that five years from now, every ticket an employee will have an AI assistant. That's going to make that beginner employee move up the value chain on how they contribute and add value to the future of tequila with the AI assistant, making them even more equipped and smarter than what they could be otherwise. >>So, one last question to close this out here. What is your future vision for, for Accenture cloud first? What are we going to be talking about at next year's Accenture executive summit? Yeah, the future >>Is going to be, um, evolving, but the part that is exciting to me, and this is, uh, uh, a fundamental belief that we are entering a new era of industrial revolution from industry first, second, and third industry. The third happened probably 20 years ago with the advent of Silicon and computers and all of that stuff that happened here in the Silicon Valley. I think the fourth industrial revolution is going to be in the cross section of, uh, physical, digital and biological boundaries. And there's a great article, um, in one economic forum that people, uh, your audience can Google and read about it. Uh, but the reason why this is very, very important is we are seeing a disturbing phenomenon that over the last 10 years are seeing a Blackwing of the, um, labor productivity and innovation, which has dropped to about 2.1%. When you see that kind of phenomenon over that longer period of time, there has to be breakthrough innovation that needs to happen to come out of this barrier and get to the next, you know, base camp, as I would call it to further this productivity, um, lack that we are seeing, and that is going to happen in the intersection of the physical, digital and biological boundaries. >>And I think cloud is going to be the connective tissue between all of these three, to be able to provide that where it's the edge, especially is good to come closer to the human lives. It's going to come from cloud. Yeah. Pick totally in your mind, you can think about cloud as central, either in a private cloud, in a data center or in a public cloud, you know, everywhere. But when you think about edge, it's going to be far reaching and coming close to where we live and maybe work and very, um, get entertained and so on and so forth. And there's good to be, uh, intervention in a positive way in the field of medicine, in the field of entertainment, in the field of, um, manufacturing in the field of, um, you know, mobility. When I say mobility, human mobility, people, transportation, and so on and so forth with all of this stuff, cloud is going to be the connective tissue and the vision of cloud first is going to be, uh, you know, blowing through this big change that is going to happen. And the evolution that is going to happen where, you know, the human grace of mankind, um, our person kind of being very gender neutral in today's world. Um, go first needs to be that beacon of, uh, creating the next generation vision for enterprises to take advantage of that kind of an exciting future. And that's why it, Accenture, are we saying that there'll be change as our, as our purpose? >>I genuinely believe that cloud first is going to be the forefront of that change agenda, both for Accenture as well as for the rest of the work. >>Excellent. Let there be changed. Indeed. Thank you so much for joining us Karthik. A pleasure I'm Rebecca Knight stay tuned for more of Q3 60 fives coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtual and our coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the power of three. And what happens when you bring together the scientific, how of a global bias biopharmaceutical powerhouse in Takeda, a leading cloud services provider in AWS, and Accenture's ability to innovate, execute, and deliver innovation. Joining me to talk about these things. We have Aaron, sorry. Arjan Beatty. He is the senior managing director and chairman of Accenture's diamonds leadership council. Welcome Arjun. Thank you, Karl hick. He is the chief digital and information officer at Takeda. >>What is your bigger, thank you, Rebecca >>And Brian Beau Han global director and head of the Accenture AWS business group at Amazon web services. Thanks so much for coming on. Thank you. So, as I said, we're talking today about this relationship between, uh, your three organizations. Carl, I want to talk with you. I know you're at the beginning of your cloud journey. What was the compelling reason? Why w why, why move to the cloud and why now? >>Yeah, no, thank you for the question. So, you know, as a biopharmaceutical leader, we're committed to bringing better health and a brighter future to our patients. We're doing that by translating science into some really innovative and life transporting therapies, but throughout, you know, we believe that there's a responsible use of technology, of data and of innovation. And those three ingredients are really key to helping us deliver on that promise. And so, you know, while I think a I'll call it, this cloud journey is already always been a part of our strategy. Um, and we've made some pretty steady progress over the last years with a number of I'll call it diverse approaches to the digital and AI. We just weren't seeing the impact at scale that we wanted to see. Um, and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and broaden that shift. >>And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. One of those has been certainly a number of the acquisitions we've made Shire, uh, being the most pressing example, uh, but also the global pandemic, both of those highlight the need for us to move faster, um, at the speed of cloud, ultimately. Uh, and so we started thinking outside of the box because it was taking us too long and we decided to leverage the strategic partner model. Uh, and it's giving us a chance to think about our challenges very differently. We call this the power of three, uh, and ultimately our focus is singularly on our patients. I mean, they're waiting for us. We need to get there faster. It can take years. And so I think that there is a focus on innovation at a rapid speed, so we can move ultimately from treating conditions to keeping people healthy. >>So as you are embarking on this journey, what are some of the insights you want to share about, about what you're seeing so far? >>Yeah, no, it's a great question. So, I mean, look, maybe right before I highlight some of the key insights, uh, I would say that, you know, with cloud now as the, as a launchpad for innovation, you know, our vision all along has been that in less than 10 years, we want every single to kid, uh, the associate or employee to be empowered by an AI assistant. And I think that, you know, that's going to help us make faster, better decisions. That'll help us, uh, fundamentally deliver transformative therapies and better experiences to, to that ecosystem, to our patients, to physicians, to payers, et cetera, much faster than we previously thought possible. Um, and I think that technologies like cloud and edge computing together with a very powerful I'll call it data fabric is going to help us to create this, this real-time, uh, I'll call it the digital ecosystem. >>The data has to flow ultimately seamlessly between our patients and providers or partners or researchers, et cetera. Uh, and so we've been thinking about this, uh, I'll call it weekly, call up sort of this pyramid, um, that helps us describe our vision. Uh, and a lot of it has to do with ultimately modernizing the foundation, modernizing and rearchitecting, the platforms that drive the company, uh, heightening our focus on data, which means that there's an accelerated shift towards, uh, enterprise data platforms and digital products. And then ultimately, uh, uh, uh, you know, really an engine for innovation sitting at the very top. Um, and so I think with that, you know, there's a few different, I'll call it insights that, you know, are quickly kind of come zooming into focus. I would say one is this need to collaborate very differently. Um, you know, not only internally, but you know, how do we define ultimately, and build a connected digital ecosystem with the right partners and technologies externally? >>I think the second component that maybe people don't think as much about, but, you know, I find critically important is for us to find ways of really transforming our culture. We have to unlock talent and shift the culture certainly as a large biopharmaceutical very differently. And then lastly, you've touched on it already, which is, you know, innovation at the speed of cloud. How do we re-imagine that? You know, how do ideas go from getting tested in months to kind of getting tested in days? You know, how do we collaborate very differently? Uh, and so I think those are three, uh, perhaps of the larger I'll call it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. >>So Arjun, I want to bring you into this conversation a little bit. Let's, let's delve into those a bit. Talk first about the collaboration, uh, that Carl was referencing there. How, how have you seen that? It is enabling, uh, colleagues and teams to communicate differently and interact in new and different ways? Uh, both internally and externally, as Carl said, >>No, thank you for that. And, um, I've got to give call a lot of credit because as we started to think about this journey, it was clear. It was a bold ambition was, uh, something that, you know, we had all to do differently. And so the concept of the power of three that Carl has constructed has become a label for us as a way to think about what are we going to do to collectively drive this journey forward. And to me, the unique ways of collaboration means three things. The first one is that, um, what is expected is that the three parties are going to come together and it's more than just the sum of our resources. And by that, I mean that we have to bring all of ourselves, all of our collective capabilities, as an example, Amazon has amazing supply chain capabilities. They're one of the best at supply chain. >>So in addition to resources, when we have supply chain innovations, uh, that's something that they're bringing in addition to just, uh, talent and assets, similarly for Accenture, right? We do a lot, uh, in the talent space. So how do we bring our thinking as to how we apply best practices for talent to this partnership? So, um, as we think about this, so that's, that's the first one, the second one is about shared success very early on in this partnership, we started to build some foundations and actually develop seven principles that all of us would look at as the basis for this success shared success model. And we continue to hold that sort of in the forefront, as we think about this collaboration. And maybe the third thing I would say is this one team mindset. So whether it's the three of our CEOs that get together every couple of months to think about, uh, this partnership, or it is the governance model that Carl has put together, which has all three parties in the governance and every level of leadership, we always think about this as a collective group so that we can keep that front and center. >>And what I think ultimately has enabled us to do is it's allowed us to move at speed, be more flexible. And ultimately all we're looking at the target the same way, the North side, the same way, >>Brian, about you, what have you observed and what are you thinking about in terms of how this is helping teams collaborate differently? Yeah, >>Absolutely. And RJ made some, some great points there. And I think if you really think about what he's talking about, it's that, that diversity of talent, diversity of skill and viewpoint and even culture, right? And so we see that in the power of three. And then I think if we drill down into what we see at Takeda and frankly Takeda was, was really, I think, pretty visionary and on their way here, right. And taking this kind of cross-functional approach and applying it to how they operate day to day. So moving from a more functional view of the world to more of a product oriented view of the world, right? So when you think about we're going to be organized around a product or a service or a capability that we're going to provide to our customers or our patients or donors in this case, it implies a different structure all to altogether and a different way of thinking, right? >>Because now you've got technical people and business experts and marketing experts all working together in this is sort of cross collaboration. And what's great about that is it's really the only way to succeed with cloud, right? Because the old ways of thinking where you've got application people and infrastructure, people in business, people is suboptimal, right? Because we can all access this tool as these capabilities and the best way to do that. Isn't across kind of a cross collaborative way. And so this is product oriented mindset. It's a keto was already on. I think it's allowed us to move faster. >>Carl, I want to go back to this idea of unlocking talent and culture. And this is something that both Brian and Arjun have talked about too. People are an essential part of their, at the heart of your organization. How will their experience of work change and how are you helping re-imagine and reinforce a strong organizational culture, particularly at this time when so many people are working remotely. >>Yeah. It's a great question. And it's something that, you know, I think we all have to think a lot about, I mean, I think, um, you know, driving this, this color, this, this digital and data kind of capability building, uh, it takes a lot of, a lot of thinking. So, I mean, there's a few different elements in terms of how we're tackling this one is we're recognizing, and it's not just for the technology organization or for those actors that, that we're innovating with, but it's really across all of the Qaeda where we're working through ways of raising what I'll call the overall digital leaders literacy of the organization, you know, what are the, you know, what are the skills that are needed almost at a baseline level, even for a global bio-pharmaceutical company and how do we deploy, I'll call it those learning resources very broadly. >>And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are very specialized skills that are needed. Uh, my organization is one of those. And so, you know, we're fostering ways in which, you know, we're very kind of quickly kind of creating, uh, avenues excitement for, for associates in that space. So one example specifically, as we use, you know, during these, uh, very much sort of remote, uh, sort of days, we, we use what we call global it meet days, and we set a day aside every single month and this last Friday, um, you know, we, we create during that time, it's time for personal development. Um, and we provide active seminars and training on things like, you know, robotic process automation, data analytics cloud, uh, in this last month we've been doing this for months and months now, but in his last month, more than 50% of my organization participated, and there's this huge positive shift, both in terms of access and excitement about really harnessing those new skills and being able to apply them. >>Uh, and so I think that that's, you know, one, one element that can be considered. And then thirdly, um, of course every organization has to work on how do you prioritize talent, acquisition and management and competencies that you can't rescale? I mean, there are just some new capabilities that we don't have. And so there's a large focus that I have with our executive team and our CEO and thinking through those critical roles that we need to activate in order to kind of, to, to build on this, uh, this business led cloud transformation. And lastly, probably the hardest one, but the one that I'm most jazzed about is really this focus on changing the mindsets and behaviors. Um, and I think there, you know, this is where the power of three is, is really, uh, kind of coming together nicely. I mean, we're working on things like, you know, how do we create this patient obsessed curiosity, um, and really kind of unlock innovation with a real, kind of a growth mindset. >>Uh, and the level of curiosity that's needed, not to just continue to do the same things, but to really challenge the status quo. So that's one big area of focus we're having the agility to act just faster. I mean, to worry less, I guess I would say about kind of the standard chain of command, but how do you make more speedy, more courageous decisions? And this is places where we can emulate the way that a partner like AWS works, or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently to a number of partnerships that we can build. So we can break down some of these barriers and use these networks, um, whether it's within our own internal ecosystem or externally to help, to create value faster. So a lot of energy around ways of working and we'll have to check back in, but I mean, we're early in on this mindset and behavioral shift, um, but a lot of good early momentum. >>Carl you've given me a good segue to talk to Brian about innovation, because you said a lot of the things that I was the customer obsession and this idea of innovating much more quickly. Obviously now the world has its eyes on drug development, and we've all learned a lot about it, uh, in the past few months and accelerating drug development is all, uh, is of great interest to all of us. Brian, how does a transformation like this help a company's ability to become more agile and more innovative and at a quicker speed to, >>Yeah, no, absolutely. And I think some of the things that Carl talked about just now are critical to that, right? I think where sometimes folks fall short is they think, you know, we're going to roll out the technology and the is going to be the silver bullet where in fact it is the culture, it is, is the talent. And it's the focus on that. That's going to be, you know, the determinant of success. And I will say, you know, in this power of three arrangement and Carl talked a little bit about the pyramid, um, talent and culture and that change, and that kind of thinking about that has been a first-class citizen since the very beginning, right. That absolutely is critical for, for being there. Um, and so that's been, that's been key. And so we think about innovation at Amazon and AWS and Chrome mentioned some of the things that, you know, a partner like AWS brings to the table is we talk a lot about builders, right? >>So we're kind of obsessive about builders. Um, and, and we meet what we mean by that is we, we, at Amazon, we hire for builders, we cultivate builders and we like to talk to our customers about it as well. And it also implies a different mindset, right? When you're a builder, you have that, that curiosity, you have that ownership, you have that stake and whatever I'm creating, I'm going to be a co-owner of this product or this service, right. Getting back to that kind of product oriented mindset. And it's not just the technical people or the it people who are builders. It is also the business people as, as Carl talked about. Right. So when we start thinking about, um, innovation again, where we see folks kind of get into a little bit of, uh, innovation, pilot paralysis, is that you can focus on the technology, but if you're not focusing on the talent and the culture and the processes and the mechanisms, you're going to be putting out technology, but you're not going to have an organization that's ready to take it and scale it and accelerate it. >>Right. And so that's, that's been absolutely critical. So just a couple of things we've been doing with, with the Qaeda and Decatur has really been leading the way is, think about a mechanism and a process. And it's really been working backward from the customer, right? In this case, again, the patient and the donor. And that was an easy one because the key value of Decatur is to be a patient focused bio-pharmaceutical right. So that was embedded in their DNA. So that working back from that, that patient, that donor was a key part of that process. And that's really deep in our DNA as well and Accentures. And so we were able to bring that together. The other one is, is, is getting used to experimenting and even perhaps failing, right. And being able to iterate and fail fast and experiment and understanding that, you know, some decisions, what we call it at Amazon are two two-way doors, meaning you can go through that door, not like what you see and turn around and go back. And cloud really helps there because the costs of experimenting and the cost of failure is so much lower than it's ever been. You can do it much faster and the implications are so much less. So just a couple of things that we've been really driving, uh, with Decatur around innovation, that's been really critical. >>Carl, where are you already seeing signs of success? Yeah, no, it's a great question. And so we chose, you know, uh, with our focus on, on innovation to try to unleash maybe the power of data digital in, uh, in focusing on what I call sort of a nave. And so we chose our, our, our plasma derived therapy business, um, and you know, the plasma-derived therapy business unit, it develops critical life-saving therapies for patients with rare and complex diseases. Um, but what we're doing is by bringing kind of our energy together, we're focusing on creating, I'll call it state of the art digitally connected donation centers. And we're really modernizing, you know, the, the, the donor experience right now, we're trying to, uh, improve also I'll call it the overall plasma collection process. And so we've, uh, selected a number of alcohol at a very high-speed pilots that we're working through right now, specifically in this, in this area. And we're seeing really great results already. Um, and so that's, that's one specific area of focus >>Arjun. I want you to close this out here. Any ideas, any best practices advice you would have for other pharmaceutical companies that are, that are at the early stage of their cloud journey for me? Yes. >>Yeah, no, I was breaking up a bit. No, I think they, um, the key is what's sort of been great for me to see is that when people think about cloud, you know, you always think about infrastructure technology. The reality is that the cloud is really the true enabler for innovation and innovating at scale. And, and if you think about that, right, in all the components that you need, that ultimately that's where the value is for the company, right? Because yes, you're going to get some cost synergies and that's great, but the true value is in how do we transform the organization in the case of the Qaeda and the life sciences clients, right. We're trying to take a 14 year process of research and development that takes billions of dollars and compress that, right. Tremendous amounts of innovation opportunity. You think about the commercial aspect, lots of innovation can come there. The plasma derived therapy is a great example of how we're going to really innovate to change the trajectory of that business. So I think innovation is at the heart of what most organizations need to do. And the formula, the cocktail that the Qaeda has constructed with this Fuji program really has all the ingredients, um, that are required for that success. >>Great. Well, thank you so much. Arjun, Brian and Carl was really an enlightening conversation. >>Yeah, it's been fun. Thanks Rebecca. >>Thank you for tuning into the cube virtuals coverage of the Accenture executive summit from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. Welcome everyone to the cubes of Accenture >>Executive summit here at AWS reinvent. I'm your host Rebecca Knight for this segment? We have two guests. First. We have Helen Davis. She is the senior director of cloud platform services, assistant director for it and digital for the West Midlands police. Thanks so much for coming on the show, Helen, And we also have Matthew lb. He is Accenture health and public service associate director and West Midlands police account lead. Thanks so much for coming on the show. Matthew, thank you for having us. So we are going to be talking about delivering data-driven insights to the West Midlands police force. Helen, I want to start with you. Can you tell us a little bit about the West Midlands police force? How big is the force and also what were some of the challenges that you were grappling with prior to this initiative? >>Yes, certainly. So Westerners police is the second largest police force in the UK, outside of the metropolitan police in London. Um, we have an excessive, um, 11,000 people work at Westminster police serving communities, um, through, across the Midlands region. So geographically, we're quite a big area as well, as well as, um, being population, um, density, having that as a, at a high level. Um, so the reason we sort of embarked on the data-driven insights platform and it, which was a huge change for us was for a number of reasons. Um, namely we had a lot of disparate data, um, which was spread across a range of legacy systems that were many, many years old, um, with some duplication of, um, what was being captured and no single view for offices or, um, support staff. Um, some of the access was limited. You have to be in a, in an actual police building on a desktop computer to access it. Um, other information could only reach officers on the frontline through a telephone call back to one of our enabling services where they would do a manual checkup, um, look at the information, then call the offices back, um, and tell them what they needed to know. So it was a very long laborious process and not very efficient. Um, and we certainly weren't exploiting the data that we had in a very productive way. >>So it sounds like as you're describing and an old clunky system that needed a technological, uh, reimagination, so what was the main motivation for, for doing, for making this shift? >>It was really, um, about making us more efficient and more effective in how we do how we do business. So, um, you know, certainly as a, as an it leader and sort of my operational colleagues, we recognize the benefits, um, that data analytics could bring in, uh, in a policing environment, not something that was, um, really done in the UK at time. You know, we have a lot of data, so we're very data rich and the information that we have, but we needed to turn it into information that was actionable. So that's where we started looking for, um, technology partners and, um, suppliers to help us and sort of help us really with what's the art of the possible, you know, this hasn't been done before. So what could we do in this space that's appropriate for policing >>Helen? I love that idea. What is the art of the possible, can you tell us a little bit about why you chose AWS? >>I think really, you know, as with all things and when we're procuring a partner in the public sector that, you know, there are many rules and regulations quite rightly as you would expect that to be because we're spending public money. So we have to be very, very careful and, um, it's, it's a long process and we have to be open to public scrutiny. So, um, we sort of look to everything, everything that was available as part of that process, but we recognize the benefits that tide would provide in this space because, you know, without moving to a cloud environment, we would literally be replacing something that was legacy with something that was a bit more modern. Um, that's not what we wanted to do. Our ambition was far greater than that. So I think, um, in terms of AWS, really, it was around scalability, interoperability, you know, disaster things like the disaster recovery service, the fact that we can scale up and down quickly, we call it dialing up and dialing back. Um, you know, it's it's page go. So it just sort of ticked all the boxes for us. And then we went through the full procurement process, fortunately, um, it came out on top for us. So we were, we were able to move forward, but it just sort of had everything that we were looking for in that space. >>Matthew, I want to bring you into the conversation a little bit here. How are you working with the wet with the West Midlands police, sorry, and helping them implement this cloud first journey? >>Yeah, so I guess, um, by January the West Midlands police started, um, pay for five years ago now. So, um, we set up a partnership with the force I, and you to operate operation the way that was very different to a traditional supplier relationship. Um, secretary that the data difference insights program is, is one of many that we've been working with less neutral on, um, over the last five years. Um, as having said already, um, cloud gave a number of, uh, advantages certainly from a big data perspective and the things that that enabled us today, um, I'm from an Accenture perspective that allowed us to bring in a number of the different themes that we have say cloud themes, security teams, um, interacted from a design perspective, as well as more traditional services that people would associate with the country. >>So much of this is about embracing comprehensive change to experiment, innovate, and try different things. Matthew, how, how do you help an entity like West Midlands police think differently when they are, there are these ways of doing things that people are used to, how do you help them think about what is the art of the possible, as Helen said, >>There's a few things for that, you know, what's being critical is trying to co-create solutions together. Yeah. There's no point just turning up with, um, what we think is the right answer, try and say, um, collectively work through, um, the issues that the forest are seeing the outcomes they're looking to achieve rather than simply focusing on the long list of requirements I think was critical and then being really open to working together to create the right solution. Um, rather than just, you know, trying to pick something off the shelf that maybe doesn't fit the forces requirements in the way that it should to, right. It's not always a one size fits all. Obviously, you know, today what we thought was critical is making sure that we're creating something that met the forces needs, um, in terms of the outcomes they're looking to achieve the financial envelopes that were available, um, and how we can deliver those in a, uh, iterative agile way, um, rather than spending years and years, um, working towards an outcome, um, that is going to outdate before you even get that. >>How, how are things different? What kinds of business functions and processes have been re-imagined in, in light of this change and this shift >>It's, it's actually unrecognizable now, um, in certain areas of the business as it was before. So to give you a little bit of context, when we, um, started working with essentially century AWS on the data driven insights program, it was very much around providing, um, what was called locally, a wizzy tool for our intelligence analysts to interrogate data, look at data, you know, decide whether they could do anything predictive with it. And it was very much sort of a back office function to sort of tidy things up for us and make us a bit better in that, in that area or a lot better in that area. And it was rolled out to a number of offices, a small number on the front line. Um, I'm really, it was, um, in line with a mobility strategy that we, hardware officers were getting new smartphones for the first time, um, to do sort of a lot of things on, on, um, policing apps and things like that to again, to avoid them, having to keep driving back to police stations, et cetera. >>And the pilot was so successful. Every officer now has access to this data, um, on their mobile devices. So it literally went from a handful of people in an office somewhere using it to do sort of clever whizzbang things to, um, every officer in the force, being able to access that level of data at their fingertips literally. So what they would touch we've done before is if they needed to check and address or check, uh, details of an individual, um, just as one example, they would either have to, in many cases, go back to a police station to look it up themselves on a desktop computer. Well, they would have to make a call back to, um, a centralized function and speak to an operator, relay the questions either, wait for the answer or wait for a call back with the answer when those people are doing the data interrogation manually. >>So the biggest change for us is the self-service nature of the data we now have available. So officers can do it themselves on their phone, wherever they might be. So the efficiency savings, um, from that point of view are immense. And I think just parallel to that is the quality of our data because we had a lot of data, but just because you've got a lot of data and a lot of information doesn't mean it's big data and it's valuable necessarily. Um, so again, it was having the single source of truth as we, as we call it. So you know, that when you are completing those safe searches and getting the responses back, that it is the most accurate information we hold. And also you're getting it back within minutes as opposed to, you know, half an hour, an hour or a drive back to the station. So it's making officers more efficient and it's also making them safer. The more efficient they are, the more time they have to spend, um, out with the public doing what they, you know, we all should be doing. >>And have you seen that kind of return on investment because what you were just describing with all the steps that we'd needed to be taken in prior to this to verify and address say, and those are precious seconds when someone's life is on the line in, in sort of in the course of everyday police work. >>Absolutely. Yeah, absolutely. It's difficult to put a price on it. It's difficult to quantify. Um, but all the, you know, the minutes here and that certainly add up to a significant amount of efficiency savings, and we've certainly been able to demonstrate the officers are spending less time up police stations as a result and more time out on the front line. Also they're safer because they can get information about what may or may not be and address what may or may not have occurred in an area before very, very quickly without having to wait. >>Matthew, I want to hear your observations of working so closely with this West Midlands police. Have you noticed anything about changes in its culture and its operating model in how police officers interact with one another? Have you seen any changes since this technology change, >>Um, unique about the West new misplaces, the buy-in from the top, it depend on the chief and his exact team. And Helen is the leader from an IOT perspective. Um, the entire force is bought in. So what is a significant change program? Uh, uh, not trickles three. Um, everyone in the organization, um, change is difficult. Um, and there's a lot of time effort. That's been put into bake, the technical delivery and the business change and adoption aspects around each of the projects. Um, but you can see the step change that it's making in each aspect to the organization, uh, and where that's putting West Midlands police as a leader in, um, technology I'm policing in the UK. And I think globally, >>And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain intransigence in workplaces about this is just the way we've always done things and we're used to this and don't try to get us, don't try to get us to do anything new here. It works. How do you get the buy-in that you need to, to do this kind of digital transformation? >>I think it, it would be wrong to say it was easy. Um, um, we also have to bear in mind that this was one program in a five year program. So there was a lot of change going on, um, both internally for some of our back office functions, as well as front tie, uh, frontline offices. So with DDI in particular, I think the stat change occurred when people could see what it could do for them. You know, we had lots of workshops and seminars where we all talk about, you know, big data and it's going to be great and it's data analytics and it's transformational, you know, and quite rightly people that are very busy doing a day job that not necessarily technologists in the main and, you know, are particularly interested quite rightly so in what we are not dealing with the cloud, you know? >>And it was like, yeah, okay. It's one more thing. And then when they started to see on that, on their phones and what teams could do, that's when it started to sell itself. And I think that's when we started to see, you know, to see the stack change, you know, and, and if we, if we have any issues now it's literally, you know, our help desks in meltdown. Cause everyone's like, well, we call it manage without this anymore. And I think that speaks for itself. So it doesn't happen overnight. It's sort of incremental changes and then that's a step change in attitude. And when they see it working and they see the benefits, they want to use it more. And that's how it's become fundamental to our policing by itself, really without much selling >>Matthew, Helen just made a compelling case for how to get buy in. Have you discovered any other best practices when you are trying to get everyone on board for this kind of thing? >>So we've, um, we've used a lot of the traditional techniques, things around comms and engagement. We've also used things like, um, the 30 day challenge and nudge theory around how can we gradually encourage people to use things? Um, I think there's a point where all of this around, how do we just keep it simple and keep it user centric from an end user perspective? I think DDI is a great example of where the, the technology is incredibly complex. The solution itself is, um, you know, extremely large and, um, has been very difficult to, um, get delivered. But at the heart of it is a very simple front end for the user to encourage it and take that complexity away from them. Uh, I think that's been critical through the whole piece of video. >>One final word from Helen. I want to hear, where do you go from here? What is the longterm vision? I know that this made productivity, >>Um, productivity savings equivalent to 154 full-time officers. Uh, what's next, I think really it's around, um, exploiting what we've got. Um, I use the phrase quite a lot, dialing it up, which drives my technical architects crazy, but because it's apparently not that simple, but, um, you know, we've, we've been through significant change in the last five years and we are still continuing to batch all of those changes into everyday, um, operational policing. But what we need to see now is we need to exploit and build on the investments that we've made, um, in terms of data and claims specifically, the next step really is about expanding our pool of data and our functions. Um, so that, you know, we keep getting better and better, um, at this, um, the more we do, the more data we have, the more refined we can be, the more precise we are with all of our actions. >>Um, you know, we're always being expected to, again, look after the public purse and do more for less. And I think this is certainly an and our cloud journey and cloud first by design, which is where we are now, um, is helping us to be future-proofed. So for us, it's very much an investment. And I see now that we have good at embedded in operational policing for me, this is the start of our journey, not the end. So it's really exciting to see where we can go from here. Exciting times. Indeed. Thank you so much. And Matthew for joining us, I really appreciate it. And you are watching the cube stay tuned for more of the cubes coverage of the AWS reinvent Accenture executive summit. I'm Rebecca Knight from around the globe with digital coverage, >>AWS reinvent executive summit, 2020, sponsored by Accenture and AWS. Everyone. Welcome to the cube virtual coverage of the executive summit at AWS reinvent 2020 virtual. This is the cube virtual. We can't be there in person like we are every year we have to be remote. This executive summit is with special programming supported by Accenture where the cube virtual I'm your host John for a year, we had a great panel here called uncloud first digital transformation from some experts, Stuart driver, the director of it and infrastructure and operates at lion Australia, Douglas Regan, managing director, client account lead at lion for Accenture as a deep Islam associate director application development lead for Accenture gentlemen, thanks for coming on the cube virtual that's a mouthful, all that digital, but the bottom line it's cloud transformation. This is a journey that you guys have been on together for over 10 years to be really a digital company. Now, some things have happened in the past year that kind of brings all this together. This is about the next generation organization. So I want to ask Stuart you first, if you can talk about this transformation at lion has undertaken some of the challenges and opportunities and how this year in particular has brought it together because you, you know, COVID has been the accelerant of digital transformation. Well, if you're 10 years in, I'm sure you're there. You're in the, uh, uh, on that wave right now. Take a minute to explain this transformation journey. >>Yeah, sure. So number of years back, we, we looked at kind of our infrastructure and our landscape. I'm trying to figure out where we wanted to go next. And we were very analog based, um, and stuck in the old it groove of, you know, capital refresh, um, struggling to transform, struggling to get to a digital platform and we needed to change it up so that we could, uh, become very different business to the one that we were back then. Um, obviously cloud is an accelerant to that and we had a number of initiatives that needed a platform to build on. And a cloud infrastructure was the way that we started to do that. So we went through a number of transformation programs that we didn't want to do that in the old world. We wanted to do it in a new world. So for us, it was partnering up with a, you know, great organizations that can take you on the journey and, uh, you know, start to deliver a bit by bit incremental progress, uh, to get to the, uh, I guess the promise land. >>Um, we're not, uh, not all the way there, but to where we're a long way along. And then when you get to some of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually change pretty quickly, um, provide capacity and, uh, and increase your environments and, you know, do the things that you need to do in a much more dynamic way than we would have been able to previously where we might've been waiting for the hardware vendors, et cetera, to deliver capacity for us this year, it's been a pretty strong year from an it perspective and delivering for the business needs, >>Forget the Douglas. I want to just real quick and redirect to you and say, you know, for all the people who said, Oh yeah, you got to jump on cloud, get in early, you know, a lot of naysayers like, well, wait till to mature a little bit. Really, if you got in early and you paying your dues, if you will taking that medicine with the cloud, you're really kind of peaking at the right time. Is that true? Is that one of the benefits that comes out of this getting in the cloud, >>John, this has been an unprecedented year, right. And, um, you know, Australia, we had to live through Bush fires and then we had covert and, and then we actually had to deliver a, um, a project I'm very know transformational product project, completely remote. And then we also had had some, some cyber challenges, which is public as well. And I don't think if we weren't moved into and enabled through the cloud would have been able to achieve that this year. It would have been much different. It would have been very difficult to do the fact that we were able to work and partner with Amazon through this year, which is unprecedented and actually come out the other end and we've delivered a brand new digital capability across the entire business. Um, it wouldn't >>Have been impossible if we could, I guess, stayed in the old world. The fact that we moved into the new Naval by the Navy allowed us to work in this unprecedented gear >>Just quick. What's your personal view on this? Because I've been saying on the Cuban reporting, necessity's the mother of all invention and the word agility has been kicked around as kind of a cliche, Oh, it'd be agile. You know, we're gonna get to Sydney. You get a minute on specifically, but from your perspective, uh, Douglas, what does that mean to you? Because there is benefits there for being agile. And >>I mean, I think as Stuart mentioned writing, and a lot of these things we try to do and, you know, typically, you know, hardware capabilities of the last to be told and, and always the only critical path to be done. You know, we really didn't have that in this case, what we were doing with our projects in our deployments, right. We were able to move quickly able to make decisions in line with the business and really get things going, right. So you, a lot of times in a traditional world, you have these inhibitors, you have these critical path, it takes weeks and months to get things done as opposed to hours and days. And it truly allowed us to, we had to VJ things, move things. And, you know, we were able to do that in this environment with AWS to support and the fact that we can kind of turn things off and on as quickly as we need it. Yeah. >>Cloud-scale is great for speed. So DECA got, Gardez get your thoughts on this cloud first mission, you know, it, you know, the dev ops worlds, they saw this early, that jumping in there, they saw the, the, the agility. Now the theme this year is modern applications with the COVID pandemic pressure, there's real business pressure to make that happen. How did you guys learn to get there fast? And what specifically did you guys do at Accenture and how did it all come together? Can you take us inside kind of how it played out? >>All right. So we started off with us and we work with lions experts and, uh, the lost knowledge that allowed reconstructive being had. Um, we then applied our journey group cloud strategy basically revolves around the seven Oz and, and, uh, you know, the deep peaking steps from our perspective, uh, assessing the current bottom, setting up the new cloud in modern. And as we go modernizing and, and migrating these applications to the cloud now, you know, one of the things that, uh, no we did not along this journey was that, you know, you can have the best plans, but bottom of that, we were dealing with, we often than not have to make changes. Uh, what a lot of agility and also work with a lot of collaboration with the, uh, Lyon team, as well as, uh, uh, AWS. I think the key thing for me was being able to really bring it all together. It's not just, uh, you know, essentially mobilize all of us. >>What were some of the learnings real quick, your journey there? >>So I think perspective the key learnings around that, you know, uh, you know, what, when we look back at, uh, the, the infrastructure that was that we were trying to migrate over to the cloud, a lot of the documentation, et cetera, was not, uh, available. We were having to, uh, figure out a lot of things on the fly. Now that really required us to have, uh, uh, people with deep expertise who could go into those environments and, and work out, uh, you know, the best ways to, to migrate the workloads to the cloud. Uh, I think, you know, the, the biggest thing for me was making Jovi had on that real SMEs across the board globally, that we could leverage across various technologies, uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment would line >>Just do what I got to ask you. How did you address your approach to the cloud and what was your experience? >>Yeah, for me, it's around getting the foundations right. To start with and then building on them. Um, so, you know, you've got to have your, your process and you're going to have your, your kind of your infrastructure there and your blueprints ready. Um, AWS do a great job of that, right. Getting the foundations right. And then building upon it, and then, you know, partnering with Accenture allows you to do that very successfully. Um, I think, um, you know, the one thing that was probably surprising to us when we started down this journey and kind of, after we got a long way down, the track of looking backwards is actually how much you can just turn off. Right? So a lot of stuff that you, uh, you get left with a legacy in your environment, and when you start to work through it with the types of people that civic just mentioned, you know, the technical expertise working with the business, um, you can really rationalize your environment and, uh, um, you know, cloud is a good opportunity to do that, to drive that legacy out. >>Um, so you know, a few things there, the other thing is, um, you've got to try and figure out the benefits that you're going to get out of moving here. So there's no point just taking something that is not delivering a huge amount of value in the traditional world, moving it into the cloud, and guess what it's going to deliver the same limited amount of value. So you've got to transform it, and you've got to make sure that you build it for the future and understand exactly what you're trying to gain out of it. So again, you need a strong collaboration. You need a good partners to work with, and you need good engagement from the business as well, because the kind of, uh, you know, digital transformation, cloud transformation, isn't really an it project, I guess, fundamentally it is at the core, but it's a business project that you've got to get the whole business aligned on. You've got to make sure that your investment streams are appropriate and that you're able to understand the benefits and the value that you're going to drive back towards the business. >>Let's do it. If you don't mind me asking what was some of the obstacles encountered or learnings, um, that might've differed from the expectation we all been there, Hey, you know, we're going to change the world. Here's the sales pitch, here's the outcome. And then obviously things happen, you know, you learn legacy, okay. Let's put some containerization around that cloud native, um, all that rational. You're talking about what are, and you're going to have obstacles. That's how you learn. That's how perfection has developed. How, what obstacles did you come up with and how are they different from your expectations going in? >>Yeah, they're probably no different from other people that have gone down the same journey. If I'm totally honest, the, you know, 70 or 80% of what you do is relative music, because they're a known quantity, it's relatively modern architectures and infrastructures, and you can, you know, upgrade, migrate, move them into the cloud, whatever it is, rehost, replatform, rearchitect, whatever it is you want to do, it's the other stuff, right? It's the stuff that always gets left behind. And that's the challenge. It's, it's getting that last bit over the line and making sure that you haven't invested in the future while still carrying all of your legacy costs and complexity within your environment. So, um, to be quite honest, that's probably taken longer and, and has been more of a challenge than we thought it would be. Um, the other piece I touched on earlier on in terms of what was surprising was actually how much of your environment is actually not needed anymore. >>When you start to put a critical eye across it and understand, um, uh, ask the tough questions and start to understand exactly what, what it is you're trying to achieve. So if you ask a part of a business, do they still need this application or this service a hundred percent of the time, they'll say yes, until you start to lay out to them, okay, now I'm going to cost you this to migrate it or this, to run it in the future. And, you know, here's your ongoing costs and, you know, et cetera, et cetera. And then, uh, for a significant amount of those answers, you get a different response when you start to layer on the true value of it. So you start to flush out those hidden costs within the business, and you start to make some critical decisions as a company based on, uh, based on that. So that was a little tougher than we first thought and probably broader than we thought there was more of that than we anticipated, which actually resulted in a much cleaner environment post and post migration. Yeah. >>Well, expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value, uh, Stuart and Siddique. Mainly if you can weigh in on this love to know the percentage of total cloud that you have now, versus when you started, because as you start to uncover whether it's by design for purpose, or you discover opportunities to innovate, like you guys have, I'm sure it kind of, you took on some territory inside Lyon, what percentage of cloud now versus >>Yeah. At the start, it was minimal, right. You know, close to zero, right. Single and single digits. Right. It was mainly SAS environments that we had, uh, sitting in cloud when we, uh, when we started, um, Doug mentioned earlier a really significant transformation project that we've undertaken recently gone live on a multi-year one. Um, you know, that's all stood up on AWS and is a significant portion of our environment, um, in terms of what we can move to cloud. Uh, we're probably at about 80 or 90% now. And the balanced bit is, um, legacy infrastructure that is just gonna retire as we go through the cycle rather than migrate to the cloud. Um, so we are significantly cloud-based and, uh, you know, we're reaping the benefits of it in a year, like 2020, and makes you glad that you did all of the hard yards in the previous years when you start business challenges, trying out as, >>So do you get any common reaction to the cloud percentage penetration? >>Sorry, I didn't, I didn't catch that, but I, all I was going to say was, I think it's like the typical 80 20 rule, right? We, we, we worked really hard in the, you know, I think 2018, 19 to get 80% off the, uh, application onto the cloud. And over the last year is the 20% that we have been migrating. And Stuart said, right. A lot of it is also, that's going to be your diet. And I think our next big step is going to be obviously, you know, the icing on the cake, which is to decommission all of these apps as well. Right. So, you know, to get the real benefits out of, uh, out of the whole conservation program from a, uh, from a reduction of CapEx, OPEX perspective, >>Douglas and Stuart, can you guys talk about the decision around the clouds because you guys have had success with AWS? Why AWS how's that decision made? Can you guys give some insight into some of those things? >>I can, I can start, start off. I think back when the decision was made and it was, it was a while back, um, you know, there was some clear advantages of moving relay, Ws, a lot of alignment with some of the significant projects and, uh, the trend, that particular one big transformation project that we've alluded to as well. Um, you know, we needed some, um, some very robust and, um, just future proof and, and proven technology. And AWS gave that to us. We needed a lot of those blueprints to help us move down the path. We didn't want to reinvent everything. So, um, you know, having a lot of that legwork done for us and AWS gives you that, right. And particularly when you partner up with, uh, with a company like Accenture as well, you get combinations of technology and the, the skills and the knowledge to, to move you forward in that direction side. Um, you know, for us, it was a, uh, uh, it was a decision based on, you know, best of breed, um, you know, looking forward and, and trying to predict the future needs and, and, and kind of the environmental that we might need. Um, and, you know, partnering up with organizations that can then take you on the journey >>Just to build on that. So obviously, you know, lines like an antivirus, but, you know, we knew it was a very good choice given the, um, >>Uh, skills and the capability that we had, as well as the assets and tools we had to get the most out of an AWS. And obviously our CEO globally just made an announcement about a huge investment that we're making in cloud. Um, but you know, we've, we've worked very well with AWS. We've done some joint workshops and joint investments, um, some joint POC. So yeah, w we have a very good working relationship, AWS, and I think, um, one incident to reflect upon whether it's cyber it's and again, where we actually jointly, you know, dove in with, um, with Amazon and some of their security experts and our experts. And we're able to actually work through that with mine quite successful. So, um, you know, really good behaviors as an organization, but also really good capabilities. >>Yeah. As you guys, your essential cloud outcomes, research shown, it's the cycle of innovation with the cloud, that's creating a lot of benefits, knowing what you guys know now, looking back certainly COVID has impacted a lot of people kind of going through the same process, knowing what you guys know now, would you advocate people to jump on this transformation journey? If so, how, and what tweaks they make, which changes, what would you advise? >>I might take that one to start with. Um, I hate to think where we would have been when, uh, COVID kicked off here in Australia and, you know, we were all sent home, literally were at work on the Friday, and then over the weekend. And then Monday, we were told not to come back into the office and all of a sudden, um, our capacity in terms of remote access and I quadrupled, or more four, five X, what we had on the Friday we needed on the Monday. And we were able to stand that up during the day Monday into Tuesday, because we were cloud-based and, uh, you know, we just spun up your instances and, uh, you know, sort of our licensing, et cetera. And, and we had all of our people working remotely, um, within, uh, you know, effectively one business day. Um, I know peers of mine in other organizations and industries that are relying on kind of a traditional wise and getting hardware, et cetera, that were weeks and months before they could get the right hardware to be able to deliver to their user base. >>So, um, you know, one example where you're able to scale and, uh, uh, get, uh, get value out of this platform beyond probably what was anticipated at the time you talk about, um, you know, less this, the, and all of these kinds of things. And you can also think of a few scenarios, but real world ones where you're getting your business back up and running in that period of time is, is just phenomenal. There's other stuff, right? There's these programs that we've rolled out, you do your sizing, um, and in the traditional world, you would just go out and buy more servers than you need. And, you know, probably never realize the full value of those, you know, the capability of those servers over the life cycle of them. Whereas, you know, in a cloud world, you put in what you think is right. And if it's not right, you pump it up a little bit when, when all of your metrics and so on telling you that you need to bump it up and conversely Scarlett down at the same rate. So for us with the types of challenges and programs and, uh, uh, and just business need, that's come at as this year, uh, we wouldn't have been able to do it without a strong cloud base, uh, to, uh, to move forward with >>Yeah, Douglas, one of the things that I talked to, a lot of people on the right side of history who have been on the right wave with cloud, with the pandemic, and they're happy, they're like, and they're humble. Like, well, we're just lucky, you know, luck is preparation meets opportunity. And this is really about you guys getting in early and being prepared and readiness. This is kind of important as people realize, then you gotta be ready. I mean, it's not just, you don't get lucky by being in the right place, the right time. And there were a lot of companies were on the wrong side of history here who might get washed away. This is a second >>I think, to echo and kind of build on what Stewart said. I think that the reason that we've had success and I guess the momentum is we, we didn't just do it in isolation within it and technology. It was actually linked to broader business changes, you know, creating basically a digital platform for the entire business, moving the business, where are they going to be able to come back stronger after COVID, when they're actually set up for growth, um, and actually allows, you know, a line new achievements, growth objectives, and also its ambitions as far as what he wants to do, uh, with growth in whatever they may do as acquiring other companies and moving into different markets and launching new product. So we've actually done it in a way that there's, you know, real and direct business benefit, uh, that actually enables line to grow >>General. I really appreciate you coming. I have one final question. If you can wrap up here, uh, Stuart and Douglas, you don't mind waiting, and what's the priorities for the future. What's next for lion and a century >>Christmas holidays, I'll start Christmas holidays. And I spent a third year and then a, and then a reset, obviously, right? So, um, you know, it's, it's figuring out, uh, transform what we've already transformed, if that makes sense. So God, a huge proportion of our services sitting in the cloud. Um, but we know we're not done even with the stuff that is in there. We need to take those next steps. We need more and more automation and orchestration. We need to, um, our environment, there's more future growth. We need to be able to work with the business and understand what's coming at them so that we can, um, you know, build that into, into our environment. So again, it's really transformation on top of transformation is the way that I'll describe it. And it's really an open book, right? Once you get it in and you've got the capabilities and the evolving tool sets that AWS continue to bring to the market base, um, you know, working with the partners to, to figure out how we unlock that value, um, you know, drive our costs down our efficiency, uh, all of those kind of, you know, standard metrics. >>Um, but you know, we're looking for the next things to transform and show value back out to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with and understand how we can better meet their needs. Yeah, I think just to echo that, I think it's really leveraging this and then digital capability they have and getting the most out of that investment. And then I think it's also moving to, >>Uh, and adopting more new ways of working as far as, you know, the state of the business. Um, it's getting up the speed of the market is changing. So being able to launch and do things quickly and also, um, competitive and efficient operating costs, uh, now that they're in the cloud, right. So I think it's really leveraging the most out of a platform and then, you know, being efficient in launching things. So putting the, with the business, >>Cedric, any word from you on your priorities by UC this year and folding. >>Yeah. So, uh, just going to say like e-learning squares, right for me were around, you know, just journey. This is a journey to the cloud, right. And, uh, you know, as well dug into sort of Saturday, it's getting all, you know, different parts of the organization along the journey business to ID to your, uh, product windows, et cetera. Right. And it takes time with this stuff, but, uh, uh, you know, you gotta get started on it and, you know, once we, once we finish off, uh, it's the realization of the benefits now that, you know, I'm looking forward? I think for, from Alliance perspective, it's, it is, uh, you know, once we migrate all the workloads to the cloud, it is leveraging, uh, all stack drive. And as I think Stewart said earlier, uh, with, uh, you know, the latest and greatest stuff that AWS it's basically working to see how we can really, uh, achieve more better operational excellence, uh, from a, uh, from a cloud perspective. >>Well, Stewart, thanks for coming on with a century and sharing your environment and what's going on and your journey you're on the right wave. Did the work you were in that it's all coming together with faster, congratulations for your success, and really appreciate Douglas with Steve for coming on as well from Accenture. Thank you for coming on. Thanks, John. Okay. Just the cubes coverage of executive summit at AWS reinvent. This is where all the thought leaders share their best practices, their journeys, and of course, special programming with the center and the cube. I'm Sean ferry, your host, thanks for watching From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtuals coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First. We have Johan Krebbers. He is the GM digital emerging technologies and VP of it. Innovation at shell. Thank you so much for coming on the show. Johan you're welcome. And next we have Liz Dennett. She is the lead solution architect for O S D U on AWS. Thank you so much, Liz. You'll be. So I want to start our conversation by talking about OSD. You like so many great innovations. It started with a problem Johan. What was the problem you were trying to solve at shell? >>Yeah, the ethical back a couple of years, we started summer 2017, where we had a meeting with the deg, the gas exploration in shell, and the main problem they had. Of course, they got lots of lots of data, but are unable to find the right data. They need to work from once the day, this was scattered in is scattered my boss kind of Emirates all over the place and turned them into real, probably tried to solve is how that person working exploration could find their proper date, not just a day of loss of date. You really needed that we did probably talked about is summer 2017. We said, okay. The only way ABC is moving forward is to start pulling that data into a single data platform. And that, that was at the time that we called it as the, you, the subsurface data universe in there was about the shell name was so in, in January, 2018, we started a project with Amazon to start grating a freaking that building, that Stu environment that the, that universe, so that single data level to put all your exploration and Wells data into that single environment that was intent and every cent, um, already in March of that same year, we said, well, from Michele point of view, we will be far better off if we could make this an industry solution and not just a shelf solution, because Shelby, Shelby, if you can make this industry solution, but people are developing applications for it. >>It also is far better than for shell to say we haven't shell special solution because we don't make money out of how we start a day that we can make money out of, if you have access to the data, we can explore the data. So storing the data we should do as efficiently possibly can. So in March, we reached out to about eight or nine other large, uh, I gas operators, like the economics, like the totals, like the chefs of this world and say, Hey, we inshallah doing this. Do you want to join this effort? And to our surprise, they all said, yes. And then in September, 2018, we had our kickoff meeting with your open group where we said, we said, okay, if you want to work together, lots of other companies, we also need to look at, okay, how, how we organize that, or is that if you started working with lots of large companies, you need to have some legal framework around some framework around it. So that's why we went to the open group and said, okay, let's, let's form the ODU forum as we call it the time. So it's September, 2080, where I did a Galleria in Houston, but the kick off meeting for the OT four with about 10 members at the time. So there's just over two years ago, we started an exercise for me called ODU, kicked it off. Uh, and so that's really then we'll be coming from and how we got there. Also >>The origin story. Um, well, so what digging a little deeper there? What were some of the things you were trying to achieve with the OSD? >>Well, a couple of things we've tried to achieve with OSU, um, first is really separating data from applications. And what is the, what is the biggest problem we have in the subsurface space that the data and applications are all interlinked or tied together. And if you have them and a new company coming along and say, I have this new application and has access to the data that is not possible because the data often interlinked with the application. So the first thing we did is really breaking the link between the application, the data as those levels, the first thing we did, secondly, put all the data to a single data platform, take the silos out what was happening in the subsurface space. And they got all the data in what we call silos in small little islands out there. So we're trying to do is first break the link to great, great. >>They put the data in a single data bathroom, and a third part who does standard layer. On top of that, it's an API layer on top of the, a platform. So we could create an ecosystem out of companies to start developing soft applications on top of dev data platform across you might have a data platform, but you're only successful. If you have a rich ecosystem of people start developing applications on top of that. And then you can explore today, like small companies, last company, university, you name it, we're getting after create an ecosystem out here. So the three things, whereas was first break the link between application data, just break it and put data at the center and also make sure that data, this data structure would not be managed by one company. It would only be met. It will be managed the data structures by the OT forum. Secondly, then the data of single data platform certainly has an API layer on top and then create an ecosystem. Really go for people, say, please start developing applications because now you have access to the data. I've got the data no longer linked to somebody whose application was all freely available for an API layer. That was, that was all September, 2018, more or less. >>And to bring you in here a little bit, can you talk a little bit about some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? Yeah, absolutely. And this whole thing is Johan said started with a challenge that was really brought out at shell. The challenges that geo-scientists spend up to 70% of their time looking for data, I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out how we could address that one problem, we worked together to really understand the root cause of these challenges and working backwards from that use case OSU and OSU on AWS has really enabled customers to create solutions that span, not just this in particular problem, but can really scale to be inclusive of the entire energy chain and deliver value from these use cases to the energy industry and beyond. Thank you, Lee, uh, Johann. So talk a little bit about Accenture's cloud first approach and how it has, uh, helped shell work faster and better with speed. >>Well, of course, access a cloud first approach only works together in an Amazon environment, AWS environment. So we really look at, at, at, at Accenture and others altogether helping shell in this space. Now the combination of the two is what we're really looking at, uh, where access of course can be, this is not a student who that environment operates, support knowledge to an environment. And of course, Amazon would be doing that to today's environment that underpinning, uh, services, et cetera. So, uh, we would expect a combination, a lot of goods when we started rolling out and put in production, the old you are three and bubble because we are anus. Then when the release feed comes to the market in Q1 next year of ODU, when he started going to Audi production inside shell, but as the first release, which is ready for prime time production across an enterprise will be released one just before Christmas, last year when he's still in may of this year. But release three is the first release we want to use for full scale production deployment inside shell, and also all the operators around the world. And there is what Amazon, sorry. Um, extensive can play a role in the ongoing, in the, in deployment building up, but also support environment. >>So one of the other things that we talk a lot about here on the cube is sustainability. And this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSD you, uh, help organizations become, how is this a greener solution for companies? >>Well, firstly make it, it's a great solution because you start making a much more efficient use of your resources, which is, which is already an important one. The second thing they're doing is also, we started with ODU in the oil and gas space with the expert development space. We've grown, uh OTU but in our strategy of growth, OSU now also do an alternative energy sociology. We'll all start supporting next year. Things like solar farms, wind farms, uh, the, the dermatomal environment hydration. So it becomes an and, and an open energy data platform, not just for the, for the, I want to get into steam that's for new industry, any type of energy industry. So our focus is to create, bring that data of all those various energy data sources together into a single data platform. You're going to use AI and other technology on top of that to exploit the data, to meet again in a single data platform. >>Liz, I want to ask you about security because security is, is, is such a big concern when it comes to how secure is the data on OSD you, um, actually, can I talk, can I do a follow up on the sustainability talking? Oh, absolutely. By all means. I mean, I want to interject though security is absolutely our top priority. I don't mean to move away from that, but with sustainability, in addition to the benefits of the OSU data platform, when a company moves from on-prem to the cloud, they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical on-prem data center. Now, a recent study by four 51 research found that AWS is infrastructure is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to higher server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases, four 51 found that AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSU are working to support our customers is they seek to better understand their workflows and make their legacy businesses less carbon intensive. >>That's that's those are those statistics are incredible. Do you want to talk a little bit now about security? Absolutely. And security will always be AWS is top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy. There are the security requirements for the military global banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build and operate each of our regions. So that customers benefit from the only commercial cloud that's had hits service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features as well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. Johann, I want you to talk a little bit about how OSD you can be used today. Does it only handle subsurface data >>And today it's hundreds of servers or Wells data. We got to add to that production around the middle of next year. That means that the whole upstate business. So we've got, if you look at MC, obviously this goes from exploration all the way to production. You've been at the into to a single data platform. So production will be added the round Q3 of next year. Then it principal, we have a difficult, the elder data that single environment, and we want to extended them to other data sources or energy sources like solar farms, wheat farms, uh, hydrogen hydro at San Francisco. We want to add a whore or a list of other day. >>And he saw a student and B all the data together into a single data club. So we move from an fallen guest, a data platform to an energy data platform. That's really what our objective is because the whole industry we've looked at, I've looked at our company companies all moving in that same direction of quantity, of course are very strong at all, I guess, but also increase the, got into all the other energy sources like, like solar, like wind, like, like the hydrogen, et cetera. So we, we move exactly the same method that, that, that the whole OSU can really support at home. And as a spectrum of energy sources, of course, >>And Liz and Johan. I want you to close us out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSD. You we'll start with you, Liz. What do you, what do you see as the future holding for this platform? Um, honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers, wherever their OSU journeys, take them, whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond, but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges. >>Yeah. First, nobody can look that far ahead, any more nowadays, especially 10 years mean now, who knows what happens in 10 years, but if you look what our whole objective is that really in the next five years owes you will become the key backbone for energy companies for storing your data. You are efficient intelligence and optimize the whole supply energy supply chain in this world out there. >>Rubbers Liz Dennett. Thank you so much for coming on the cube virtual, >>Thank you, >>Rebecca nights, stay tuned for more of our coverage of the Accenture executive summit >>Around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight today we're welcoming back to Kubila. We have Kishor Dirk. He is the Accenture senior managing director cloud first global services lead. Welcome back to the show >>Kishore. Thank you very much. >>Nice to meet again. And, uh, Tristin moral horse set. He is the managing director, Accenture cloud first North American growth. Welcome back to YouTube. >>Great to be back in. Great to see you again, Rebecca. >>Exactly. Even in this virtual format, it is good to see your faces. Um, today we're going to be talking about my nav and green cloud advisor >>Capability. Kishor I want to start with you. So my NAB is a platform that is really celebrating its first year in existence. Uh, November, 2019 is when Accenture introduced it. Uh, but it's, it has new relevance in light of this global pandemic that we are all enduring and suffering through. Tell us a little bit about the miner platform, what it is. >>Sure, Rebecca, you know, we lost it and now 2019 and, uh, you know, it is a cloud platform to help our clients navigate the complexity of cloud and cloud decisions and to make it faster and obviously innovate in the cloud, uh, you know, with the increased relevance and all the, especially over the last few months with the impact of COVID crisis and exhibition of digital transformation, you know, we are seeing the transformation of the acceleration to cloud much faster. This platform that you're talking about has enabled hundred and 40 clients globally across different industries. You identify the right cloud solution, navigate the complexity, provide a cloud specific solution simulate for our clients to meet the strategy business needs and the clients are loving it. >>I want to go to you now trust and tell us a little bit about how my nav works and how it helps companies make good cloud choices. >>Yeah. So Rebecca we've talked about cloud is, is more than just infrastructure and that's what mine app tries to solve for. It really looks at a variety of variables, including infrastructure operating model and fundamentally what clients business outcomes, um, uh, our clients are, are looking for and, and identify as the optimal solution for what they need. And we design this to accelerate and we mentioned the pandemic. One of the big focus now is to accelerate. And so we worked through a three-step process. The first is scanning and assessing our client's infrastructure, their data landscape, their application. Second, we use our automated artificial intelligence engine to interact with. We have a wide variety and library of, uh, collective plot expertise. And we look to recommend what is the enterprise architecture and solution. And then third, before we aligned with our clients, we look to simulate and test this scaled up model. And the simulation gives our clients a wait to see what cloud is going to look like, feel like and how it's going to transform their business before they go there. >>Tell us a little bit about that in real life. Now as a company, so many of people are working remotely having to collaborate, uh, not in real life. How is that helping them right now? >>So, um, the, the pandemic has put a tremendous strain on systems, uh, because of the demand on those systems. And so we talk about resiliency. We also now need to collaborate across data across people. Um, I think all of us are calling from a variety of different places where our last year we were all at the cube itself. Um, and, and cloud technologies such as teams, zoom that we're we're leveraging now has fundamentally accelerated and clients are looking to onboard this for their capabilities. They're trying to accelerate their journey. They realize that now the cloud is what is going to become important for them to differentiate. Once we come out of the pandemic and the ability to collaborate with their employees, their partners, and their clients through these systems is becoming a true business differentiator for our clients. >>Sure. I want to talk with you now about my NABS multiple capabilities, um, and helping clients design and navigate their cloud journeys. Tell us a little bit about the green cloud advisor capability and its significance, particularly as so many companies are thinking more deeply and thoughtfully about sustainability. >>Yes. So since the launch of my NAB, we continue to enhance capabilities for our clients. One of the significant, uh, capabilities that we have enabled is the brain trust advisor today. You know, Rebecca, a lot of the businesses are more environmentally aware and are expanding efforts to decrease power consumption, uh, and obviously carbon emissions and, uh, and run a sustainable operations across every aspect of the enterprise. Uh, as a result, you're seeing an increasing trend in adoption of energy, efficient infrastructure in the global market. And one of the things that we did, a lot of research we found out is that there's an ability to influence our client's carbon footprint through a better cloud solution. And that's what we entered by brings to us, uh, in, in terms of a lot of the client connotation that you're seeing in Europe, North America and others, lot of our clients are accelerating to a green cloud strategy to unlock beta financial, societal and environmental benefit, uh, through obviously cloud-based circular, operational and sustainable products and services. That is something that, uh, we are enhancing my now and we are having active client discussions at this point of time. >>So Tristan, tell us a little bit about how this capability helps clients make greener. >>Yeah. Um, well, let's start about the investments from the cloud providers in renewable and sustainable energy. Um, they have most of the hyperscalers today, um, have been investing significantly on data centers that are run or renewable energy, some incredibly creative constructs on the how to do that. And sustainability is therefore a key, um, key item of importance for the hyperscalers and also for our clients who now are looking for sustainable energy. And it turns out this marriage is now possible. I can, we marry the, the green capabilities of the cloud providers with a sustainability agenda of our clients. And so what we look into way the mine EF works is it looks at industry benchmarks and evaluates our current clients, um, capabilities and carpet footprint leveraging their existing data centers. We then look to model from an end-to-end perspective, how the, their journey to the cloud leveraging sustainable and, um, and data centers with renewable energy. We look at how their solution will look like and, and quantify carbon tax credits, um, improve a green index score and provide quantifiable, um, green cloud capabilities and measurable outcomes to our clients, shareholders, stakeholders, clients, and customers, um, and our green plot advisors, sustainability solutions already been implemented at three clients. And in many cases in two cases has helped them reduce the carbon footprint by up to 400% through migration from their existing data center to green club. Very, very important. Yeah, >>That is remarkable. Now tell us a little bit about the kinds of clients. Is this, is this more interesting to clients in Europe? Would you say that it's catching on in the United States where we're at? What is the breakdown that you're seeing right now? >>Sustainability is becoming such a global agenda and we're seeing our clients, um, uh, tie this and put this at board level, um, uh, agenda and requirements across the globe. Um, Europe has specific constraints around data sovereignty, right, where they need their data in country, but from a green, a sustainability agenda, we see clients across all our markets, North America, Europe, and our growth markets adopt this. And we have seen case studies in all three markets >>Kisha. I want to bring you back into the conversation. Talk a little bit about how mine up ties into Accenture's cloud first strategy, your Accenture's CEO, Julie Sweet has talked about post COVID leadership requiring every business to become a cloud first business. Tell us a little bit about how this ethos is in Accenture and how you're sort of looking outward with it too. >>So Rebecca mine is the launch pad, uh, to a cloud first transformation for our clients. Uh, Accenture, see you, uh, Julie Sweet, uh, shared the Accenture cloud first and our substantial investment demonstrate our commitment and is delivering data value for our clients when they need it the most. And with the district transformation requiring cloud at scale, you know, we're seeing that in the post COVID leadership, it requires that every business should become a cloud business. And my nap helps them get there by evaluating the cloud landscape, navigating the complexity, modeling architecting and simulating an optimal cloud solution for our clients. And as Justin was sharing a greener cloud, Tristan, talk a little >>Bit more about some of the real life use cases in terms of what are we, what are clients seeing? What are the results? >>Yes, thank you, Rebecca. I would say two key things right around my now the first is the iterative process. Clients don't want to wait, um, until they get started, they want to get started and see what their journey is going to look like. And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need to move to cloud very quickly. And my nav is there to do that. So how do we do that? First is generating the business cases. Clients need to know in many cases that they have a business case by business case, we talk about the financial benefits, as well as the business outcomes, the green green cloud impact sustainability impacts with minus we can build initial recommendations using a basic understanding of their environment and benchmarks in weeks versus months with indicative value savings in the millions of dollars arranges. >>So for example, very recently, we worked with a global oil and gas company, and in only two weeks, we're able to provide an indicative savings for $27 million over five years. This enabled the client to get started, knowing that there is a business case benefit and then iterate on it. And this iteration is, I would say the second point that is particularly important with my nav that we've seen in bank, the clients, which is, um, any journey starts with an understanding of what is the application landscape and what are we trying to do with those, these initial assessments that used to take six to eight weeks are now taking anywhere from two to four weeks. So we're seeing a 40 to 50% reduction in the initial assessment, which gets clients started in their journey. And then finally we've had discussions with all of the hyperscalers to help partner with Accenture and leverage mine after prepared their detailed business case module as they're going to clients. And as they're accelerating the client's journey, so real results, real acceleration. And is there a journey? Do I have a business case and furthermore accelerating the journey once we are by giving the ability to work in an iterative approach, >>It sounds as though that the company that clients and and employees are sort of saying, this is an amazing time savings look at what I can do here in, in so much in a condensed amount of time, but in terms of getting everyone on board, one of the things we talked about last time we met, uh, Tristin was just how much, uh, how one of the obstacles is getting people to sign on and the new technologies and new platforms. Those are often the obstacles and struggles that companies face. Have you found that at all? Or what is sort of the feedback that you're getting from? >>Yeah. Sorry. Yes. We clearly, there are always obstacles to a con journey. If there weren't obstacles, all our clients would be already fully in the cloud. What man I gives the ability is to navigate through those, to start quickly. And then as we identify obstacles, we can simulate what things are going to look like. We can continue with certain parts of the journey while we deal with that obstacle. And it's a fundamental accelerator. Whereas in the past one, obstacle would prevent a class from starting. We can now start to address the obstacles one at a time while continuing and accelerating the contrary. That is the fundamental difference. Kishor I want to give you the final word here. Tell us a little bit about what is next for Accenture might have and what we'll be discussing next year at the Accenture executive summit >>Sort of echo, we are continuously evolving with our client needs and reinventing, reinventing for the future. For my advisor, our plan is to help our clients reduce carbon footprint and again, migrate to a green cloud. Uh, and additionally, we're looking at, you know, two capabilities, uh, which include sovereign cloud advisor, uh, with clients, especially in, in Europe and others are under pressure to meet stringent data norms that Kristen was talking about. And the sovereign cloud advisor health organization to create an architecture cloud architecture that complies with the green. Uh, I would say the data sound-bitey norms that is out there. The other element is around data to cloud. We are seeing massive migration, uh, for, uh, for a lot of the data to cloud. And there's a lot of migration hurdles that come within that. Uh, we have expanded mine app to support assessment capabilities, uh, for, uh, assessing applications, infrastructure, but also covering the entire state, including data and the code level to determine the right cloud solution. So we are, we are pushing the boundaries on what might have can do with mine. And we have created the ability to take the guesswork out of cloud, navigate the complexity. We are rolling risks costs, and we are achieving clients strategy, business objectives, while building a sustainable lots with being cloud, >>Any platform that can take some of the guesswork out of the future. I'm I'm on board with. Thank you so much, Kristin and Kishore. This has been a great conversation. Thank you, Rebecca. Thank you, Rebecca. Stay tuned for more of the cubes coverage of the Accenture executive summit. I'm Rebecca Knight. >>Yeah, Yeah.

Published Date : Dec 1 2020

SUMMARY :

It's the cube with digital coverage Welcome to cube three 60 fives coverage of the Accenture executive summit. Thanks for having me here. impact of the COVID-19 pandemic has been, what are you hearing from clients? you know, various facets, you know, um, first and foremost, to this reasonably okay, and are, you know, launching to So you just talked about the widening gap. all the changes the pandemic has brought to them. in the cloud that we are going to see. Can you tell us a little bit more about what this strategy entails? all of the systems under which they attract need to be liberated so that you could drive now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, the employees are able to embrace this change. across every department, I'm the agent of this change is going to be the employees or weapon, And because the change management is, is often the hardest And that is again, the power of cloud. And the power of cloud is to get all of these capabilities from outside that employee, the employee will be more engaged in his or her job and therefore And this is, um, you know, no more true than how So at Accenture, you have long, long, deep Stan, sorry, And in fact, in the cloud world, it was one of the first, um, And one great example is what we are doing with Takeda, uh, billable, to drive more customer insights, um, come up with breakthrough Yeah, the future to the next, you know, base camp, as I would call it to further this productivity, And the evolution that is going to happen where, you know, the human grace of mankind, I genuinely believe that cloud first is going to be the forefront of that change Thank you so much for joining us Karthik. It's the cube with digital coverage And what happens when you bring together the scientific, And Brian Beau Han global director and head of the Accenture AWS business group at Amazon Um, and I think that, you know, there's a, there's a need ultimately to, And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. And I think that, you know, that's going to help us make faster, better decisions. Um, and so I think with that, you know, there's a few different, it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. So Arjun, I want to bring you into this conversation a little bit. uh, something that, you know, we had all to do differently. in the governance and every level of leadership, we always think about this as a collective the same way, the North side, the same way, And I think if you really think about what he's talking about, Because the old ways of thinking where you've got application people and infrastructure, How will their experience of work change and how are you helping re-imagine and And it's something that, you know, I think we all have to think a lot about, I mean, And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are Uh, and so I think that that's, you know, one, one element that can be considered. or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently the customer obsession and this idea of innovating much more quickly. of the things that, you know, a partner like AWS brings to the table is we talk a lot about builders, And it's not just the technical people or the it people who are you know, some decisions, what we call it at Amazon are two two-way doors, meaning you can go through that door, And so we chose, you know, uh, with our focus on, I want you to close this out here. sort of been great for me to see is that when people think about cloud, you know, Well, thank you so much. Yeah, it's been fun. It's the cube with digital coverage of How big is the force and also what were some of the challenges that you were grappling with Um, so the reason we sort of embarked um, you know, certainly as a, as an it leader and sort of my operational colleagues, What is the art of the possible, can you tell us a little bit about why you the public sector that, you know, there are many rules and regulations quite rightly as you would expect Matthew, I want to bring you into the conversation a little bit here. to bring in a number of the different themes that we have say cloud themes, security teams, um, So much of this is about embracing comprehensive change to experiment, the outcomes they're looking to achieve rather than simply focusing on the long list of requirements I think was critical So to give you a little bit of context, when we, um, started And the pilot was so successful. And I think just parallel to that is the quality of our data because we had a lot of data, And have you seen that kind of return on investment because what you were just describing with all the steps Um, but all the, you know, the minutes here and that certainly add up Have you seen any changes And Helen is the leader from an IOT perspective. And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain You know, we had lots of workshops and seminars where we all talk about, you know, see, you know, to see the stack change, you know, and, and if we, if we have any issues now it's literally, when you are trying to get everyone on board for this kind of thing? the 30 day challenge and nudge theory around how can we gradually encourage people to use things? I want to hear, where do you go from here? not that simple, but, um, you know, we've, we've been through significant change in the last And I see now that we have good at embedded in operational So I want to ask Stuart you first, if you can talk about this transformation and stuck in the old it groove of, you know, capital refresh, um, of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually I want to just real quick and redirect to you and say, you know, for all the people who said, Oh yeah, And, um, you know, Australia, we had to live through Bush fires by the Navy allowed us to work in this unprecedented gear Because I've been saying on the Cuban reporting, necessity's the mother of all and always the only critical path to be done. And what specifically did you guys do at Accenture and how did it all come applications to the cloud now, you know, one of the things that, uh, no we did not along uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment How did you address your approach to the cloud and what was your experience? And then building upon it, and then, you know, partnering with Accenture allows because the kind of, uh, you know, digital transformation, cloud transformation, learnings, um, that might've differed from the expectation we all been there, Hey, you know, It's, it's getting that last bit over the line and making sure that you haven't invested in the future hundred percent of the time, they'll say yes, until you start to lay out to them, okay, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value, Um, you know, that's all stood up on AWS and is a significant portion of And I think our next big step is going to be obviously, So, um, you know, having a lot of that legwork done for us and AWS gives you that, So obviously, you know, lines like an antivirus, but, you know, we knew it was a very good So, um, you know, really good behaviors as an a lot of people kind of going through the same process, knowing what you guys know now, And, and we had all of our people working remotely, um, within, uh, you know, effectively one business day. the time you talk about, um, you know, less this, the, and all of these kinds of things. And this is really about you guys getting It was actually linked to broader business changes, you know, creating basically a digital platform Stuart and Douglas, you don't mind waiting, and what's the priorities for the future. to figure out how we unlock that value, um, you know, drive our costs down our efficiency, our customer base, um, that, uh, that we continue to, you know, sell our products to and work with Uh, and adopting more new ways of working as far as, you know, the state of the business. And it takes time with this stuff, but, uh, uh, you know, Did the work you were in that it's all coming together with faster, What was the problem you were trying to solve at shell? And that, that was at the time that we called it as the, make money out of how we start a day that we can make money out of, if you have access to the data, we can explore the data. What were some of the things you were trying to achieve with the OSD? So the first thing we did is really breaking the link between the application, I've got the data no longer linked to somebody whose application was all freely available for an API layer. And to bring you in here a little bit, can you talk a little bit about some of the imperatives from the a lot of goods when we started rolling out and put in production, the old you are three and bubble because we are So one of the other things that we talk a lot about here on the cube is sustainability. of that to exploit the data, to meet again in a single data platform. purchases, four 51 found that AWS performs the same task with an So that customers benefit from the only commercial cloud that's had hits service offerings and You've been at the into to a single data platform. And he saw a student and B all the data together into a single data club. Um, honestly, the incredibly cool thing about working at AWS is you who knows what happens in 10 years, but if you look what our whole objective is that really in the next five Thank you so much for coming on the cube virtual, It's the cube with digital coverage of He is the Accenture senior managing director cloud first global services Thank you very much. He is the managing director, Great to see you again, Rebecca. Even in this virtual format, it is good to see your faces. So my NAB is a platform that is really celebrating to make it faster and obviously innovate in the cloud, uh, you know, with the increased relevance I want to go to you now trust and tell us a little bit about how my nav works and how it helps One of the big focus now is to accelerate. having to collaborate, uh, not in real life. They realize that now the cloud is what is going to become important for them to differentiate. about the green cloud advisor capability and its significance, particularly as so many companies And one of the things that we did, a lot of research we found out is that there's an ability to influence or renewable energy, some incredibly creative constructs on the how to do that. What is the breakdown that you're seeing right now? And we have seen case studies in all I want to bring you back into the conversation. And with the district transformation requiring cloud at scale, you know, we're seeing that in And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need This enabled the client to get started, knowing that there is a business is getting people to sign on and the new technologies and new platforms. What man I gives the ability is to navigate through those, to start quickly. And the sovereign cloud advisor health organization to create an Any platform that can take some of the guesswork out of the future.

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Rob Thomas Afterthought


 

>> (vocalizing) >> Narrator: From theCube studios in Palo Alto and Boston, it's theCube. Covering IBM Think, brought to you by IBM. >> Hi everybody, this is Dave Vallante and this is our continuing coverage of Think 2020, the digital event experience. This is the post-thing, the sort of halo effect, the afterthoughts, and joining me is Rob Thomas, he's back. The Senior Vice president of Cloud and Data Platform. Rob, thanks for taking some time to debrief on Think. >> Absolutely Dave, great to be here, good to see you again. >> Yeah, so you have a great event, you guys put it together in record time. I want to talk about sort of your innovation agenda. I mean, you are at the heart of innovation. You're talking cloud, data, AI, really the pillars of innovation, I could probably add in edge to extend the cloud. But I wonder if you could talk about your vision for the innovation agenda and how you're bringing that to customers. I mean, we heard from PayPal, you talked about Royal Bank of Scotland, Credit Mutual, a number of customer examples. How are you bringing innovation forward with the customer? >> I wouldn't describe innovation, maybe I'd give it two different categories. One is, I think the classic term would be consumerization, and you're innovating by making interiorized technology really easy to use. That's why we built out a huge design capability, it's why we've been able to get products like Watson Assistant to get companies live in 24 hours. That's the consumerization aspect, just making enterprise products really easy to use. The second aspect is even harder, which is, how do you tap into an institution like IBM Research, where we're doing fundamental invention. So, one of our now strengths in the last couple of months was around taking technology out of IBM Debater, project Debater, the AI system that could debate humans and then putting that into enterprised products. And, you saw companies like PayPal that are using Watson Assistant and now they have access to that kind of language capability. There's only two aspects here, there's the consumerization and then there's about fundamental technology that really changes how businesses can operate. >> I mean, the point you made about speed and implementation in your key note was critical, I mean really, within 24 hours, very important during this pandemic. Talk about automation, you know, you would think by now right, everything's automation. But, now you're seeing a real boom in automation and it really is driven by AI, all this data, so there's seems to be a next wave, almost a renaissance, if you will, in automation. >> There is and I think automation, when people hear first of the term, it's sometimes a scary term. Because people are like hey, is this going to take my job? Gain a lot of momentum for automation is a difficult, repetitive tasks that nobody really wanted to do in the first place. Whether it's things like data matching, containerizing an application. All these are really hard things and the output's great, but nobody really wants to do that work, they just want the outcome. And, as we've started to demonstrate different use cases for automation that are in that realm, a lot of momentum has taken off, that we're seeing. >> I want to come back to this idea of consumerization and simplification. I mean, when you think about what's been happening over the last several years. And, you and I have talked about this a lot, AI for consumer versus AI for business and enterprise. And really, one of the challenges for the encumbrance, if you will, is to really become data driven, put data at the core and apply machine intelligence to that, just to that data. Now the good news is, they don't have to invent all this stuff, because guys like you are doing that and talk about how you're making that simple. I mean, cloud packs is an example of that, simplification, but talk about how customers are going to be able to tap into AI without having to be AI inventors. >> Well, the classic AI problem actually is a data problem, and the classic data problem is data slide over, which is a company has got a lot of data but it's spread across a hundred or a thousand or tens of thousands different repositories or locations. Our strategy when we say a hybrid cloud is about how do we unify those data storage. So, it's called PaaS, on red hat open shift. We do a lot of things like data virtualization, really high performance. So, we take what is thousands of different data sources and we have that packed like a single fluid item. So then, when you're training models, you can train your models in one place and connect to all your data. That is the big change that's happening and that's how you take something like hybrid cloud, and it actually starts to impact your data architecture. And once you're doing that, then AI becomes a lot easier, because the biggest AI challenge that I described is, where's the data? Is the data in a usable form? >> A lot of times in this industry, you know, we go whale hunting, there are a lot of big companies out there, a lot of times they take priority. You know, at the same time though, a lot of the innovations are coming from companies, you know, we've never even heard of that could be multi-billion dollar companies by the end of the decade. So, how can, you know, small companies and mid-sized companies tap into this trend? Is it just for the big whales or could the small guys participate? >> The thing that's pretty amazing about modern cloud and data technology, I'll call it, is it's accessible to companies of any size. When we talked about, you know, the hundred or so clients that have adopted Watson Assistant since COVID-19 started, many of those are very small institutions with no IT staff or very limited IT staff. Though, we're making this technology very accessible. when you look at something like data, now a small company may not have a hundred different repositories, which is fine, but what they do have is they do want to make better predictions, they do want to automate, they do want to optimize the business processes that they're running in their business. And, the way that we've transformed our model consumption base starting small, it's really making technology available to, you know, from anywhere from the local deli to the Fortune 50 Company. >> So, last question is, What are your big takeaways from Think? I would ask that question normally when we're in a live event. It's a little different with the digital event, but there are still takeaways. What was your reaction and what do to leave people with? >> Even as we get back to doing physical events, which I'm positive will happen at some point. What we learned is there is something great about an immersive digital experience. So, I think the future of events is probably higher than this. Meaning, a big digital experience, to complement the physical experience. That's one big takeaway because the reaction was so positive to the content and how people could access it. Second one is the, all the labs that we did. So, for developers, builders, those were at capacity, meaning we didn't even take any more. So, there's definitively a thirst in the market for developing new applications, developing new data products, developing new security products. That's clear just by the attendance that we saw, that's exciting. Now, I'd say third, that is that AI is now moving into the mainstream, that was clear from the customer examples, whether it was with Tansa or UPS or PayPal that I mentioned before, that was talking with me. AI is becoming accessible to every company, that's pretty exciting. >> Well, the world is hybrid, oh you know the lab, the point you're making about labs is really important. I've talked to a number of individuals saying, "Hey I'm using this time to update my skills. I'm working longer hours, maybe different times of the day, but I'm going to skill up." And you know, the point about AI, 37 years ago, when I started in this business AI was all the buzz and it didn't happen. It's real this time and I'm really excited Rob, that you're at the heart of all this innovation, so really, I appreciate you taking the time. And, best of luck, stay safe, and hopefully we'll see you face to face. >> Offscreen Man: Sure. >> Thanks Dave, same to you and the whole team at theCube, take care. >> Thank you Rob, and thank you for watching everybody, this is Dave Vellante for theCube and our coverage of IBM Think 2020, the digital event experience and the post-event. We'll see you next time. (music)

Published Date : May 13 2020

SUMMARY :

Covering IBM Think, brought to you by IBM. This is the post-thing, be here, good to see you again. I mean, you are at the in the last couple of months I mean, the point you made is this going to take my job? I mean, when you think and the classic data this industry, you know, is it's accessible to What was your reaction and the labs that we did. and hopefully we'll see you face to face. you and the whole team and the post-event.

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Lynn Lucas, Cohesity | AWS re:Invent 2018


 

>> Live from Las Vegas, it's theCUBE covering AWS re:Invent 2018, brought to your by Amazon Web Services, Intel, and their ecosystem partners. (techy music) >> Hey, welcome back, everyone. It's theCUBE live here in Las Vegas for Amazon Web Services, AWS re:Invent 2018, I'm John Furrier with Lauren Cooney, the cohost of theCUBE on this set. There's two sets, and we're getting all the great interviews from the smartest people here in the ecosystem. AWS re:Invent is the industry conference that makes it all happen in the cloud. We're excited to have Lynn Lucas here, CMO of Cohesity, back on theCUBE, CUBE alumni, also the architect of the greatest party of all time. The Cohesity parties, you guys had a great party last night. I tweeted some live footage of it. Got a little bit of backlash on Twitter, but it's okay, you know. >> We don't want that. >> A lot of FOMO. >> Hopefully also the architect of some great marketing here. We're here to get the word out about Cohesity and our news with Amazon, so glad to have you here. Thanks for having me on the set again. >> You guys really hit the formula for parties at events because normally they can be kind of boring. You bring artists in, you have a great venue. You glam it up with green, the color of Cohesity. How's that working out for you guys, what's been the feedback? I was going to say people last night were jamming, great crowd. Tell us what's going on, what's the success look like, what's the vibe? >> Yeah, well it certainly is about appreciating our partners and customers that are here, but really it's all about getting the word out about Cohesity, and you know, I think you know the numbers here were somewhere between 50 and 60,000 people here, crazy, at re:Invent, and we want people to know what Cohesity can do for them in terms of their use of Amazon and making that investment even better and smarter for them, for what we call secondary data, so that was the purpose of the party, thank our customers and partners and get the word out about what we can do. >> As they say in the old marketing cliche, if you've got the sizzle you've got to have the steak. >> Absolutely. >> So, tell me, you've got some great sizzle, great marketing, congratulations, doing a great job. Love working with you and love going to your events. What is the action on the products, like where's the meat on the bone? >> Sure thing, so we had a really important announcement here yesterday extending our partnership with Amazon. We had an extension to some already great, killer features that we have. Three things, so three things you got to know. One, integration without agents to do backup of your cloud native, AWS applications, full failover and fail back to the Amazon cloud and back again for DR, and we also are now offering integration with Snowball, so a lot of customers looking at how they can get more of their data into Amazon, and now we facilitate that and of course give you the indexing that allows that to become searchable and usable for the longer term. >> I want to ask you a question. I saw a presentation this morning at Teresa Carlson's public sector breakfast, packed house, again. She's really doing an amazing job, so shout out to her and her team, but the presentation was from the deputy of the FBI counter terrorism, she talked about all the bad things that have happened and how they tried to catch up and find the bad guys, or gals, and the problem they have is that they have a data crisis, and she said that: "The FBI has a data crisis," and they can't put the puzzle together fast enough because although the data's there, they can't get it out of the databases and there are all these different fragmented systems. This is a problem, how are you guys helping clients fix this fragmentation problem? Is that an area you're solving? What's your vision, or Cohesity's vision, around this notion of how does cloudification solve this speeding up of value around data that's kind of spread out everywhere? >> Yeah, so you hit the nail on the head. We call this mass data fragmentation, and that's the problem that she's talking about. In fact, we just completed a global study of secondary data, and nine out of ten, not surprisingly, of IT organizations around the globe think that this is going to cost them somewhere between 50% and 100% more than what they're currently spending to manage their data, because it's in silos, it's in silos on-premise, but it's also then started to silo inside the cloud, and how Cohesity helps is creating a unified platform, what we call the Data Platform, and spanning the on-premise and the cloud, the multicloud environment, and providing some really unique capabilities to help organizations take that fragmentation and now remove it, bust those silos, put it in one place, give you global search, indexing, and then compression, because we all know how many copies... Excuse me, deduplication, save storage, but then also the removal of copies, because we all know how many copies there are out there. >> So, Cohesity's brand message is you guys keep pounding the frequency, get the brand message out there, is what, what's the brand promise for Cohesity? >> Great question, the brand promise is we are going to end your mass data fragmentation problems and give you web scale simplicity, right? So, why are so many organizations here, right? They love what they see with AWS and that web scale and that hyper scale simplicity, but many companies, right, still have a lot of on-premise systems, and so they're struggling with it. Well, our founder, Mohit Aron, was one of the original developers of the Google file system, knows a little bit about building distributed file systems, and so he's brought that into an affordable platform for the enterprise to give you that scalability across your on-premise, your public cloud, private cloud edge sites. >> And I think that is critical across multiple environments, especially as people are trying to develop across those multiple environments, there really needs to be that consistency for them. Some of the things that I've picked up that I hear about you guys, it's really about user experience. It seems like you care a lot about that. You've got one graphical, you know, interface that you actually use, and it makes, I think, data less scary to folks. I would say the ecosystem, I don't know... You know, I looked at your architecture and I don't know who's not in those boxes, but you make it very clear, you know, in particular, and I think also saving people money, you know, that's going to be critical because everyone is scaling out and they're spending more and more and more, and what they're spending more on is, you know, this vast amount of data that they can't control anymore, and it's, you know, just kind of churning. >> Yeah. >> And we just had this great guy on here and he was talking about, you know, the movie that he did, and he's the one-stop shop, like, IT guy at this company, and he's the... He thinks, he's like, "They saved my life," was what he told us-- >> Yeah. >> About you guys, so-- >> So, I think you hit the nail on the head, it's all about simplicity. I mean, again, in our new study, and I don't think this is going to surprise anyone, but bringing it up to date for 2018, you still have, on average, five to six systems just for backup, up to 15 if you count all secondary, which is files and objects, analytics, test dev, and think about IT trying to manage all of that complexity from a user interface, a procurement, a training enablement. So, we give them that one-stop dashboard simplicity-- >> Yeah. >> And then on top of that build a foundation for the test dev organization, analytics organization to now do more with the data, because it's not enough to just bring, bust those silos and bring the data into one place. We need to do something with that data, right? >> Absolutely, and you know, you guys were talking, before we came on camera, about storytelling, and you know, I look at the story of the cloud. I want to get your perspective on this, and Lauren, feel free to chime in because I think you've got a good input on this. If you look at what the cloud is doing to changing the game, this narrative is changing. Andy Jassy calls it the old guard, other people call it legacy systems. We've all been in a tech industry. We've kind of seen where it's been and where it's going now. More visibility now in where it's going, AI and more automation, all this greatness. The narrative's changing, who's ready, who's prepared, what is the story of the modern cloud era? What is that narrative and how should companies be talking to themselves? What's their self-talk, how do they... What's your thoughts on the story of the modern era? What's actually happening in your mind? >> Well, I think, you know, the narrative is around if you are not cloud-forward, I don't like to call it cloud native because I think that really doesn't speak to so many organizations, so it's about being cloud-forward, and having that mindset, right, that you are going to be thinking about what are the advantages of the AWS cloud for me and my business. How can I use that to gain efficiencies, and that is something that I think really does separate the old guard from the new guard. You know, if I think about Cohesity in that vein, compared to some of the legacy solutions out there, that is what Mohit Aron built in. We're cloud native from the beginning with an S3 interface, but with those interfaces back into the enterprise world so that we can help customers bring that forward, data portability and app portability. >> That's Amazon's mission, they're just forward, forward, forward progress. They're not even looking in the rear view. Although, Andy does look at Oracle, but we have to Oracle, Lauren, what's your take on the storytelling, because I'd love to get your perspective on this, too. I hate to go on a little tangent here, but I think it ties to the Cohesity brand promise. You got developers changing, you got IT experts being devops kind of, you know, culture change there, and you've got the role of opensource communities. This is a new mosh pit of action. What's your-- >> Yeah, I think it's a mosh pit of action, but it's more of a mosh pit of opportunity-- >> Yeah, absolutely. (chuckling) >> If you really want to look at it. You know, you have developers, so you know, in 2003 I was at BEA building developer communities around web servers, and then I actually went, you know, in 2008 I was at Microsoft building the web platform, which was the precursor to Azure, and you know, then skip ahead, you know, 10 years, and this is where we are and this is what we're looking at, and I think that what we've gotten to along that, you know, kind of timeline, is it has to be easy for users. Development has to be easy, it doesn't matter where in the stack people are working, it has to be accessible, people have to be able to learn it or up skill to it very, very quickly, and it's really a new, you know, shape and form that's kind of coming to the table, and as people look to study computer science and things along those lines it will be important, but it will become less important as more companies start to look at the Salesforce model where you literally can become a developer in a week, and things along those lines. >> Right. >> That's what I think the cloud is really bringing to the table. >> It's the new software methodology. Clearly Amazon announcing this cool ground station, satellite as a service, spin up, fly your own drones, whatever you want to do. You don't have to provision a satellite anymore, just turn it on. It's going to empower the edge, because the edge is where conductivity stops. So, if you've got conductivity everywhere, that now means that all data will be coming in even probably more exponentially. This is kind of in your wheelhouse. As you look forward, as you go cloud-forward and IoT edge forward more data's coming. Are you ready for that, what's the vision for you guys, how do you handle all that? >> Well, you know, I think the story about more data, with respect, is old. We all know that, right, you know. What people haven't been able to solve is as it's coming in, how are you going to keep track of it, and is it even feasible to try to put it all in one place, and I think the answer's not really, right? I mean, think about IoT-- >> Yeah. >> And all these edge sites-- >> Yeah. >> And the promise of what's going on, so this vision, which I love, is of a spanning system that gives you that operating model of one platform, but not trying to do the impossible of continually trying to put data all in physically one place, coupled with, I so agree with you, this API-first economy. If you aren't building systems that way, you know, then it really isn't built for the future because who can imagine all of the things that we do with our smartphones, and we like to think of what the Cohesity Data Platform is is the analogy to the smartphone, right? We used to carry the flip phone, the GPS, the music player, the flashlight, that device changed the world, and then we changed it again by using APIs to build new apps on it. Cohesity Data Platform is that same vision. We're going to create that unified operating environment, and then through APIs let companies build on it. >> So, it's a data platform is not so much a category of backup and recovery. It's a benefit, a lot of value there, get a magic quadrant, maybe, written up someday, but you're a data platform. >> Yeah, well I go back to that analogy of the smartphone, right? You know, so we solve, and want to solve and be the world's best at solving some of the toughest problems, and data protection is one of them. Like, I'll speak to one of our other AWS customers that's here, which is Dolby, and Dolby had a massive challenge with their on-premise data center moving their workloads to AWS since 2016, had a fire in their data center and started realizing, "Hey, there's a lot of benefits "to doing more backup in the cloud, "but also doing more archive to the cloud," both from a protection point of a view, as well as a cost saving point of view, and that is, you know, the kind of thing where we're going to solve each of those use cases. Your phone is still great as a phone, but it's also great to order your Uber here, and maybe get you a meal. >> And there's data in there, too, okay. >> Yeah. >> Question, final question for you is competition, a lot of heat in the kitchen with competition. You don't shy away from it, I love that about you. You guys are loud and proud at Cohesity, love that brand. >> Super green. >> Yeah, super green, green light, go, green is money, too. How are you different from competition, why are you winning, what's the advantage? >> Well, let me go back to, I think, a phrase, old guard, new guard. So, I think there's an old guard, and we would clearly separate ourselves from the old legacy solutions that are not hyperconverged and are not web scale, and are not web-first or cloud-forward. There's another group that are looking at, and even some of the old players now, trying to move into the new world, but I think what differentiates Cohesity is three things: A true spanning file system, web scale, that is not focused on just being a better backup. So, you just touched on backup, it's an important workload, but our vision is to consolidate all secondary workloads, so that's backup, yes, but it's also files and objects. It's also then making that data productive for test dev and analytics, and doing that across, again, the edge, the cloud, and on-premise, and that's what makes us different. >> Final, final question, because I always do this because one pops into my head when you're talking, Andy Jassy's going to talk a lot about this tomorrow, because I got a little preview on Monday last week, net new workloads, latency, all these new things. Got some of the announcements trickling out. He's seeing, and a lot of people are, we included agree with him, when you have the kind of compute that's available and the kind of data platforms and the horizontal scalability to cloud, these new net workload will be enabled. AIs been enabled by great compute. AIs been around for decades-- >> Mm-hm. >> And it's got a renaissance with compute. What new net work, net new workloads do you envision Cohesity bumping into or pioneering in the future? >> Well, actually we're going to look to the developer community, honestly, right. I think we have a strong ethos and belief that, you know, we're not the smartest people in the room, so to speak, so let's bring that out to the developers and let them in their companies or in the third parties, the great community that's here, figure out what is the next thing that we can do. When we don't have these fragmented silos of data and we can actually see in its entirety what is available to us, what might be possible? I think it could change the world. >> Developer community's a very key part of it, I would agree. Again, there's hardcore new developers emerging, IT expert developers, opensource community contributors all coming together, all here on theCUBE covering, that's our audience, that's you guys out there. Bringing the best action here at re:Invent. I'm John Furrier with Lauren Cooney, here with Lynn Lucas with Cohesity. We'll be back with more live coverage here from the two sets, double barrel shotgun of theCUBE, we call it theCUBE canons. Stay with us for more coverage after this short break. (techy music)

Published Date : Nov 27 2018

SUMMARY :

brought to your by Amazon that makes it all happen in the cloud. so glad to have you here. How's that working out for you guys, and you know, I think if you've got the sizzle What is the action on the products, that allows that to become and the problem they have is and that's the problem and give you web scale simplicity, right? and it's, you know, just kind of churning. and he's the one-stop shop, like, and I don't think this is because it's not enough to just bring, and you know, I look at and that is something that I think really but I think it ties to the Yeah, absolutely. and it's really a new, you know, is really bringing to the table. for you guys, how do you handle all that? and is it even feasible to try is the analogy to the smartphone, right? It's a benefit, a lot of value there, and that is, you know, the kind of thing in the kitchen with competition. How are you different from competition, and even some of the old players now, and the horizontal scalability to cloud, do you envision Cohesity bumping into in the room, so to speak, so let's audience, that's you guys out there.

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Steve Wooledge, Arcadia Data & Satya Ramachandran, Neustar | DataWorks Summit 2018


 

(upbeat electronic music) >> Live from San Jose, in the heart of Silicon Valley, it's theCUBE. Covering Dataworks Summit 2018, brought to you by Hortonworks. (electronic whooshing) >> Welcome back to theCUBE's live coverage of Dataworks, here in San Jose, California. I'm your host, Rebecca Knight, along with my co-host, James Kobielus. We have two guests in this segment, we have Steve Wooledge, he is the VP of Product Marketing at Arcadia Data, and Satya Ramachandran, who is the VP of Engineering at Neustar. Thanks so much for coming on theCUBE. >> Our pleasure and thank you. >> So let's start out by setting the scene for our viewers. Tell us a little bit about what Arcadia Data does. >> Arcadia Data is focused on getting business value from these modern scale-out architectures, like Hadoop, and the Cloud. We started in 2012 to solve the problem of how do we get value into the hands of the business analysts that understand a little bit more about the business, in addition to empowering the data scientists to deploy their models and value to a much broader audience. So I think that's been, in some ways, the last mile of value that people need to get out of Hadoop and data lakes, is to get it into the hands of the business. So that's what we're focused on. >> And start seeing the value, as you said. >> Yeah, seeing is believing, a picture is a thousand words, all those good things. And what's really emerging, I think, is companies are realizing that traditional BI technology won't solve the scale and user concurrency issues, because architecturally, big data's different, right? We're on the scale-out, MPP architectures now, like Hadoop, the data complexity and variety has changed, but the BI tools are still the same, and you pull the data out of the system to put it into some little micro cube to do some analysis. Companies want to go after all the data, and view the analysis across a much broader set, and that's really what we enable. >> I want to hear about the relationship between your two companies, but Satya, tell us a little about Neustar, what you do. >> Neustar is an information services company, we are built around identity. We are the premiere identity provider, the most authoritative identity provider for the US. And we built a whole bunch of services around that identity platform. I am part of the marketing solutions group, and I head the analytics engineering for marketing solutions. The product that I work on helps marketers do their annual planning, as well as their campaign or tactical planning, so that they can fine tune their campaigns on an ongoing basis. >> So how do you use Arcadia Data's primary product? >> So we are a predictive analytics platform, the reporting solution, we use Arcadia for the reporting part of it. So we have multi terabytes of advertising data in our values, and so we use Arcadia to provide fast taxes to our customers, and also very granular and explorative analysis of this data. High (mumbles) and explorative analysis of this data. >> So you say you help your customers with their marketing campaigns, so are you doing predictive analytics? And are you during churn analysis and so forth? And how does Arcadia fit into all of that? >> So we get data and then they build an activation model, which tells how the marketing spent corresponds to the revenue. We not only do historical analysis, we also do predictive, in the sense that the marketers frequently done what-if analysis, saying that, what if I moved my budget from page search to TV? And how does it affect the revenue? So all of this modeling is built by Neustar, the modeling platform is built by the Neustar, but the last mile of taking these reports and providing this explorative analysis of the results, that is provided by the reporting solution, which is Arcadia. >> Well, I mean, the thing about data analytics, is that it really is going to revolutionize marketing. That famous marketing adage of, I know my advertising works, I just don't know which half, and now we're really going to be able to figure out which half. Can you talk a little bit about return on investment and what your clients see? >> Sure, we've got some major Fortune 500 companies that have said publicly that they've realized over a billion dollars of incremental value. And that could be across both marketing analytics, and how we better treat our messaging, our brand, to reach our intended audience. There's things like supply chain and being able to more realtime analyze what-if analysis for different routes, it's things like cyber security and stopping fraud and waste and things like that at a much grander scale than what was really possible in the past. >> So we're here at Dataworks and it's the Hortonworks show. Give us a sense of the degree of your engagement or partnership with Hortonworks and participation in their partner ecosystem. >> Yeah, absolutely. Hortonworks is one of our key partners, and what we did that's different architecturally, is we built our BI server directly into the data platforms. So what I mean by that is, we take the concept of a BI server, we install it and run it on the data nodes of Hortonworks Data Platform. We inherit the security directly out of systems like Apache Ranger, so that all that administration and scale is done at Hadoop economics, if you will, and it leverages the things that are already in place. So that has huge advantages both in terms of scale, but also simplicity, and then you get the performance, the concurrency that companies need to deploy out to like, 5,000 users directly on that Hadoop cluster. So, Hortonworks is a fantastic partner for us and a large number of our customers run on Hortonworks, as well as other platforms, such as Amazon Web Services, where Satya's got his system deployed. >> At the show they announced Hortonworks Data Platform 3.0. There's containerization there, there's updates to Hive to enable it to be more of a realtime analytics, and also a data warehousing engine. In Arcadia Data, do you follow their product enhancements, in terms of your own product roadmap with any specific, fixed cycle? Are you going to be leveraging the new features in HDP 3.0 going forward to add value to your customers' ability to do interactive analysis of this data in close to realtime? >> Sure, yeah, no, because we're a native-- >> 'Cause marketing campaigns are often in realtime increasingly, especially when you're using, you know, you got a completely digital business. >> Yeah, absolutely. So we benefit from the innovations happening within the Hortonworks Data Platform. So, because we're a native BI tool that runs directly within that system, you know, with changes in Hive, or different things within HDFS, in terms of performance or compression and things like that, our customers generally benefit from that directly, so yeah. >> Satya, going forward, what are some of the problems that you want to solve for your clients? What is their biggest pain points and where do you see Neustar? >> So, data is the new island, right? So, marketers, also for them now, data is the biggest, is what they're going after. They want faster analysis, they want to be able to get to insights as fast as they can, and they want to obviously get, work on as large amount of data as possible. The variety of sources is becoming higher and higher and higher, in terms of marketing. There used to be a few channels in '70s and '80s, and '90s kind of increased, now you have like, hundreds of channels, if not thousands of channels. And they want visibility across all of that. It's the ability to work across this variety of data, increasing volume at a very high speed. Those are high level challenges that we have at Neustar. >> Great. >> So the difference, marketing attribution analysis you say is one of the core applications of your solution portfolio. How is that more challenging now than it had been in the past? We have far more marketing channels, digital and so forth, then how does the state-of-the-art of marketing attribution analysis, how is it changing to address this multiplicity of channels and media for advertising and for influencing the customer on social media and so forth? And then, you know, can you give us a sense for then, what are the necessary analytical tools needed for that? We often hear about a social graph analysis or semantic analysis, or for behavioral analytics and so forth, all of this makes it very challenging. How can you determine exactly what influences a customer now in this day and age, where, you think, you know, Twitter is an influencer over the conversation. How can you nail that down to specific, you know, KPIs or specific things to track? >> So I think, from our, like you pointed out, the variety is increasing, right? And I think the marketers now have a lot more options than what they have, and that that's a blessing, and it's also a curse. Because then I don't know where I'm going to move my marketing spending to. So, attribution right now, is still sitting at the headquarters, it's kind of sitting at a very high level and it is answering questions. Like we said, with the Fortune 100 companies, it's still answering questions to the CMOs, right? Where attribution will take us, next step is to then lower down, where it's able to answer the regional headquarters on what needs to happen, and more importantly, on every store, I'm able to then answer and tailor my attribution model to a particular store. Let's take Ford for an example, right? Now, instead of the CMO suite, but, if I'm able to go to every dealer, and I'm able to personal my attribution to that particular dealer, then it becomes a lot more useful. The challenge there is it all needs to be connected. Whatever model we are working for the dealer, needs to be connected up to the headquarters. >> Yes, and that personalization, it very much leverages the kind of things that Steve was talking about at Arcadia. Being able to analyze all the data to find those micro, micro, micro segments that can be influenced to varying degrees, so yeah. I like where you're going with this, 'cause it very much relates to the power of distributing federated big data fabrics like Hortonworks' offers. >> And so it's streaming analytics is coming to forward, and it's been talked about for the past longest period of time, but we have real use cases for streaming analytics right now. Similarly, the large volumes of the data volumes is, indeed, becoming a lot more. So both of them are doing a lot more right now. >> Yes. >> Great. >> Well, Satya and Steve, thank you so much for coming on theCUBE, this was really, really fun talking to you. >> Excellent. >> Thanks, it was great to meet you. Thanks for having us. >> I love marketing talk. >> (laughs) It's fun. I'm Rebecca Knight, for James Kobielus, stay tuned to theCUBE, we will have more coming up from our live coverage of Dataworks, just after this. (upbeat electronic music)

Published Date : Jun 20 2018

SUMMARY :

brought to you by Hortonworks. the VP of Product Marketing the scene for our viewers. the data scientists to deploy their models the value, as you said. and you pull the data out of the system Neustar, what you do. and I head the analytics engineering the reporting solution, we use Arcadia analysis of the results, and what your clients see? and being able to more realtime and it's the Hortonworks show. and it leverages the things of this data in close to realtime? you got a completely digital business. So we benefit from the It's the ability to work to specific, you know, KPIs and I'm able to personal my attribution the data to find those micro, analytics is coming to forward, talking to you. Thanks, it was great to meet you. stay tuned to theCUBE, we

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Rob Bearden, Hortonworks | DataWorks Summit 2018


 

>> Live from San Jose in the heart of Silicon Valley, it's theCUBE covering DataWorks Summit 2018, brought to you by Hortonworks. >> Welcome back to theCUBE's live coverage of DataWorks Summit here in San Jose, California. I'm your host, Rebecca Knight, along with my co-host, James Kobielus. We're joined by Rob Bearden. He is the CEO of Hortonworks. So thanks so much for coming on theCUBE again, Rob. >> Thank you for having us. >> So you just got off of the keynote on the main stage. The big theme is really about modern data architecture. So we're going to have this modern data architecture. What is it all about? How do you think about it? What's your approach? And how do you walk customers through this process? >> Well, there's a lot of moving parts in enabling a modern data architecture. One of the first steps is what we're trying to do is unlock the siloed transactional applications, and to get that data into a central architecture so you can get real time insights around the inclusive dataset. But what we're really trying to accomplish then within that modern data architecture is to bring all types of data whether it be real time streaming data, whether it be sensor data, IoT data, whether it be data that's coming from a connected core across the network, and to be able to bring all that data together in real time, and give the enterprise the ability to be able to take best in class action so that you get a very prescriptive outcome of what you want. So if we bring that data under management from point of origination and out on the edge, and then have the platforms that move that through its entire lifecycle, and that's our HDF platform, it gives the customer the ability to, after they capture it at the edge, move it, and then have the ability to process it as an event happens, a condition changes, various conditions come together, have the ability to process and take the exact action that you want to see performed against that, and then bring it to rest, and that's where our HDP platform comes into play where then all that data can be aggregated so you can have a holistic insight, and have real time interactions on that data. But then it then becomes about deploying those datasets and workloads on the tier that's most economically and architecturally pragmatic. So if that's on-prem, we make sure that we are architected for that on-prem deployment or private cloud or even across multiple public clouds simultaneously, and give the enterprise the ability to support each of those native environments. And so we think hybrid cloud architecture is really where the vast majority of our customers today and in the future, are going to want to be able to run and deploy their applications and workloads. And that's where our DataPlane Service Offering gives them the ability to have that hybrid architecture and the architectural latitude to move workloads and datasets across each tier transparently to what storage file format that they did or where that application is, and we provide all the tooling to match the complexity from doing that, and then we ensured that it has one common security framework, one common governance through its entire lifecycle, and one management platform to handle that entire lifecycle data. And that's the modern data architecture is to be able to bring all data under management, all types of data under management, and manage that in real time through its lifecycle til it comes at rest and deploy that across whatever architecture tier is most appropriate financially and from a performance on-cloud or prem. >> Rob, this morning at the keynote here in day one at DataWorks San Jose, you presented this whole architecture that you described in the context of what you call hybrid clouds to enable connected communities and with HDP, Hortonworks Data Platform 3.0 is one of the prime announcements, you brought containerization into the story. Could you connect those dots, containerization, connected communities, and HDP 3.0? >> Well, HDP 3.0 is really the foundation for enabling that hybrid architecture natively, and what's it done is it separated the storage from the compute, and so now we have the ability to deploy those workloads via a container strategy across whichever tier makes the most sense, and to move those application and datasets around, and to be able to leverage each tier in the deployment architectures that are most pragmatic. And then what that lets us do then is be able to bring all of the different data types, whether it be customer data, supply chain data, product data. So imagine as an industrial piece of equipment is, an airplane is flying from Atlanta, Georgia to London, and you want to be able to make sure you really understand how well is that each component performing, so that that plane is going to need service when it gets there, it doesn't miss the turnaround and leave 300 passengers stranded or delayed, right? Now with our Connected platform, we have the ability to take every piece of data from every component that's generated and see that in real time, and let the airlines make that real time. >> Delineate essentially. >> And ensure that we know every person that touched it and looked at that data through its entire lifecycle from the ground crew to the pilots to the operations team to the service. Folks on the ground to the reservation agents, and we can prove that if somehow that data has been breached, that we know exactly at what point it was breached and who did or didn't get to see it, and can prevent that because of the security models that we put in place. >> And that relates to compliance and mandates such as the Global Data Protection Regulation GDPR in the EU. At DataWorks Berlin a few months ago, you laid out, Hortonworks laid out, announced a new product called the Data Steward Studio to enable GDPR compliance. Can you give our listeners now who may not have been following the Berlin event a bit of an update on Data Steward Studio, how it relates to the whole data lineage, or set of requirements that you're describing, and then going forward what does Hortonworks's roadmap for supporting the full governance lifecycle for the Connected community, from data lineage through like model governance and so forth. Can you just connect a few dots that will be helpful? >> Absolutely. What's important certainly, driven by GDPR, is the requirement to be able to prove that you understand who's touched that data and who has not had access to it, and that you ensure that you're in compliance with the GDPR regulations which are significant, but essentially what they say is you have to protect the personal data and attributes of that data of the individual. And so what's very important is that you've got to be able to have the systems that not just secure the data, but understand who has the accessibility at any point in time that you've ever maintained that individual's data. And so it's not just about when you've had a transaction with that individual, but it's the rest of the history that you've kept or the multiple datasets that you may try to correlate to try to expand relationship with that customer, and you need to make sure that you can ensure not only that you've secured their data, but then you're protecting and governing who has access to it and when. And as importantly that you can prove in the event of a breach that you had control of that, and who did or did not access it, because if you can't prove any breach, that it was secure, and that no one breached it, who has or access to this not supposed to, you can be opened up for hundreds of thousands of dollars or even multiple millions of dollars of fines just because you can't prove that it was not accessed, and that's what the variety of our platforms, you mentioned Data Studio, is part of. DataPlane is one of the capabilities that gives us the ability. The core engine that does that is Atlas, and that's the open source governance platform that we developed through the community that really drives all the capabilities for governance that moves through each of our products, HDP, HDF, then of course, and DataPlane and Data Studio takes advantage of that and how it moves and replicates data and manages that process for us. >> One of the things that we were talking about before the cameras were rolling was this idea of data driven business models, how they are disrupting current contenders, new rivals coming on the scene all the time. Can you talk a little bit about what you're seeing and what are some of the most exciting and maybe also some of the most threatening things that you're seeing? >> Sure, in the traditional legacy enterprise, it's very procedural driven. You think about classic Encore ERP. It's worked very hard to have a very rigid, very structural procedural order to cash cycle that has not a great deal of flexibility. And it takes through a design process, it builds product, that then you sell product to a customer, and then you service that customer, and then you learn from that transaction different ways to automate or improve efficiencies in their supply chain. But it's very procedural, very linear. And in the new world of connected data models, you want to bring transparency and real time understanding and connectivity between the enterprise, the customer, the product, and the supply chain, and that you can take real time best in practice action. So for example you understand how well your product is performing. Is your customer using it correctly? Are they frustrated with that? Are they using it in the patterns and the frequency that they should be if they are going to expand their use and buy more, and if they're not, how do we engage in that cycle? How do we understand if they're going through a re-review and another buying of something similar that may not be with you for a different reason. And when we have real time visibility to our customer's interaction, understand our product's performance through its entire lifecycle, then we can bring real time efficiency with linking those together with our supply chain into the various relationships we have with our customers. To do that, it requires the modern data architecture, bringing data under management from the point it originates, whether it's from the product or the customer interacting with the company, or the customer interacting potentially with our ecosystem partners, mutual partners, and then letting the best in practice supply chain techniques, make sure that we're bringing the highest level of service and support to that entire lifecycle. And when we bring data under management, manage it through its lifecycle and have the historical view at rest, and leverage that across every tier, that's when we get these high velocity, deep transparency, and connectivity between each of the constituents in the value chain, and that's what our platforms give them the ability to do. >> Not only your platform, you guys have been in business now for I think seven years or so, and you shifted from being in the minds of many and including your own strategy from being the premier data at rest company in terms of the a Hadoop platform to being one of the premier data in motion companies. Is that really where you're going? To be more of a completely streaming focus, solution provider in a multi-cloud environment? And I hear a lot of Kafka in your story now that it's like, oh yeah, that's right, Hortonworks is big on Kafka. Can you give us just a quick sense of how you're making that shift towards low latency real time streaming, big data, or small data for that matter, with embedded analytics and machine learning? >> So, we have evolved from certainly being the leader in global data platforms with all the work that we do collaboratively, and in through the community, to make Hadoop an enterprise viable data platform that has the ability to run mission critical workloads and apps at scale, ensuring that it has all the enterprise facilities from security and governance and management. But you're right, we have expanded our footprint aggressively. And we saw the opportunity to actually create more value for our customers by giving them the ability to not wait til they bring data under management to gain an insight, because in that case, they're happened to be reactive post event post transaction. We want to give them the ability to shift their business model to being interactive, pre-event, pre-conditioned. The way to do that we learned was to be able to bring the data under management from the point of origination, and that's what we used MiNiFi and NiFi for, and then HDF, to move it through its lifecycle, and your point, we have the intellect, we have the insight, and then we have the ability then to process the best in class outcome based on what we know the variables are we're trying to solve for as that's happening. >> And there's the word, the phrase asset which of course is a transactional data paradigm plan, I hear that all over your story now in streaming. So, what you're saying is it's a completely enterprise-grade streaming environment from n to n for the new era of edge computing. Would that be a fair way of-- >> It's very much so. And our model and strategy has always been bring the other best in class engines for what they do well for their particular dataset. A couple of examples of that, one, you brought up Kafka, another is Spark. And they do what they do really well. But what we do is make sure that they fit inside an overall data architecture that then embodies their access to a much broader central dataset that goes from point of origination to point of rest on a whole central architecture, and then benefit from our security, governance, and operations model, being able to manage those engines. So what we're trying to do is eliminate the silos for our customers, and having siloed datasets that just do particular functions. We give them the ability to have an enterprise modern data architecture, we manage the things that bring that forward for the enterprise to have the modern data driven business models by bringing the governance, the security, the operations management, ensure that those workflows go from beginning to end seamlessly. >> Do you, go ahead. >> So I was just going to ask about the customer concerns. So here you are, you've now given them this ability to make these real time changes, what's sort of next? What's on their mind now and what do you see as the future of what you want to deliver next? >> First and foremost we got to make sure we get this right, and we really bring this modern data architecture forward, and make sure that we truly have the governance correct, the security models correct. One pane of glass to manage this. And really enable that hybrid data architecture, and let them leverage the cloud tier where it's architecturally and financially pragmatic to do it, and give them the ability to leg into a cloud architecture without risk of either being locked in or misunderstanding where the lines of demarcation of workloads or datasets are, and not getting the economies or efficiencies they should. And we solved that with DataPlane. So we're working very hard with the community, with our ecosystem and strategic partners to make sure that we're enabling the ability to bring each type of data from any source and deploy it across any tier with a common security, governance, and management framework. So then what's next is now that we have this high velocity of data through its entire lifecycle on one common set of platforms, then we can start enabling the modern applications to function. And we can go look back into some of the legacy technologies that are very procedural based and are dependent on a transaction or an event happening before they can run their logic to get an outcome because that grinds the customer in post world activity. We want to make sure that we're bringing that kind of, for example, supply chain functionality, to the modern data architecture, so that we can put real time inventory allocation based on the patterns that our customers go in either how they're using the product, or frustrations they've had, or success they've had. And we know through artificial intelligence and machine learning that there's a high probability not only they will buy or use or expand their consumption of whatever that they have of our product or service, but it will probably to these other things as well if we do those things. >> Predict the logic as opposed to procedural, yes, AI. >> And very much so. And so it'll be bringing those what's next will be the modern applications on top of this that become very predictive and enabler versus very procedural post to that post transaction. We're little ways downstream. That's looking out. >> That's next year's conference. >> That's probably next year's conference. >> Well, Rob, thank you so much for coming on theCUBE, it's always a pleasure to have you. >> Thank you both for having us, and thank you for being here, and enjoy the summit. >> We're excited. >> Thank you. >> We'll do. >> I'm Rebecca Knight for Jim Kobielus. We will have more from DataWorks Summit just after this. (upbeat music)

Published Date : Jun 20 2018

SUMMARY :

in the heart of Silicon Valley, He is the CEO of Hortonworks. keynote on the main stage. and give the enterprise the ability in the context of what you call and let the airlines from the ground crew to the pilots And that relates to and that you ensure that and maybe also some of the most and that you can take real and you shifted from being that has the ability to run for the new era of edge computing. and then benefit from our security, and what do you see as the future and make sure that we truly have Predict the logic as the modern applications on top of this That's probably next year's it's always a pleasure to have you. and enjoy the summit. I'm Rebecca Knight for Jim Kobielus.

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Day Two Kickoff | DataWorks Summit 2018


 

>> Live from San Jose, in the heart of Silicon Valley, it's theCube. Covering DataWorks Summit 2018. Brought to you by Hortonworks. >> Welcome back to day two of theCube's live coverage of DataWorks here in San Jose, California. I'm your host, Rebecca Knight along with my co-host James Kobielus. James, it's great to be here with you in the hosting seat again. >> Day two, yes. >> Exactly. So here we are, this conference, 2,100 attendees from 32 countries, 23 industries. It's a relatively big show. They do three of them during the year. One of the things that I really-- >> It's a well-established show too. I think this is like the 11th year since Yahoo started up the first Hadoop summit in 2008. >> Right, right. >> So it's an established event, yeah go. >> Exactly, exactly. But I really want to talk about Hortonworks the company. This is something that you had brought up in an analyst report before the show started and that was talking about Hortonworks' cash flow positivity for the first time. >> Which is good. >> Which is good, which is a positive sign and yet what are the prospects for this company's financial health? We're still not seeing really clear signs of robust financial growth. >> I think the signs are good for the simple reason they're making significant investments now to prepare for the future that's almost inevitable. And the future that's almost inevitable, and when I say the future, the 2020s, the decade that's coming. Most of their customers will shift more of their workloads, maybe not entirely yet, to public cloud environments for everything they're doing, AI, machine learning, deep learning. And clearly the beneficiaries of that trend will be the public cloud providers, all of whom are Hortonworks' partners and established partners, AWS, Microsoft with Azure, Google with, you know, Google Cloud Platform, IBM with IBM Cloud. Hortonworks, and this is... You know, their partnerships with these cloud providers go back several years so it's not a new initiative for them. They've seen the writing on the wall practically from the start of Hortonworks' founding in 2011 and they now need to go deeper towards making their solution portfolio capable of being deployable on-prem, in cloud, public clouds, and in various and sundry funky combinations called hybrid multi-clouds. Okay, so, they've been making those investments in those partnerships and in public cloud enabling the Hortonworks Data Platform. Here at this show, DataWorks 2018 here in San Jose, they've released the latest major version, HDP 3.0 of their core platform with a lot of significant enhancements related to things that their customers are increasingly doing-- >> Well I want to ask you about those enhancements. >> But also they have partnership announcements, the deep ones of integration and, you know, lift and shift of the Hortonworks portfolio of HDP with Hortonworks DataFlow and DataPlane Services, so that those solutions can operate transparently on those public cloud environments as the customers, as and when the customers choose to shift their workloads. 'Cause Hortonworks really... You know, like Scott Gnau yesterday, I mean just laid it on the line, they know that the more of the public cloud workloads will predominate now in this space. They're just making these speculative investments that they absolutely have to now to prepare the way. So I think this cost that they're incurring now to prepare their entire portfolio for that inevitable future is the right thing to do and that's probably why they still have not attained massive rock and rollin' positive cash flow yet but I think that they're preparing the way for them to do so in the coming decade. >> So their financial future is looking brighter and they're doing the right things. >> Yeah, yes. >> So now let's talk tech. And this is really where you want to be, Jim, I know you. >> Oh I get sleep now and I don't think about tech constantly. >> So as you've said, they're really doing a lot of emphasis now on their public cloud partnerships. >> Yes. >> But they've also launched several new products and upgrades to existing products, what are you seeing that excites you and that you think really will be potential game changers? >> You know, this is geeky but this is important 'cause it's at the very heart of Hortonworks Data Platform 3.0, containerization of more... When you're a data scientist, and you're building a machine learning model using data that's maintained, and is persisted, and processed within Hortonworks Data Platform or any other big data platform, you want the ability increasingly for developing machine learning, deep learning, AI in general, to take that application you might build while you're using TensorFlow models, that you build on HDP, they will containerize it in Docker and, you know, orchestrate it all through Kubernetes and all that wonderful stuff, and deploy it out, those AI, out to increasingly edge computing, mobile computing, embedded computing environments where, you know, the real venture capital mania's happening, things like autonomous vehicles, and you know, drones, and you name it. So the fact is that Hortonworks has made that in many ways the premier new feature of HDP 3.0 announced here this week at the show. That very much harmonizes with what their partners, where their partners are going with containerization of AI. IBM, one of their premier partners, very recently, like last month, I think it was, announced the latest version of IBM, what do they call it, IBM Cloud Private, which has embedded as a core feature containerization within that environment which is a prem-based environment of AI and so forth. The fact that Hortonworks continues to maintain close alignment with the capabilities that its public cloud partners are building to their respective portfolios is important. But also Hortonworks with its, they call it, you know, a single pane of glass, the DataPlane Services for metadata and monitoring and governance and compliance across this sprawling hybrid multi-cloud, these scenarios. The fact that they're continuing to make, in fact, really focusing on deep investments in that portfolio, so that when an IBM introduces or, AWS, whoever, introduces some new feature in their respective platforms, Hortonworks has the ability to, as it were, abstract above and beyond all of that so that the customer, the developer, and the data administrator, all they need to do, if they're a Hortonworks customer, is stay within the DataPlane Services and environment to be able to deploy with harmonized metadata and harmonized policies, and harmonized schemas and so forth and so on, and query optimization across these sprawling environments. So Hortonworks, I think, knows where their bread is buttered and it needs to stay on the DPS, DataPlane Services, side which is why a couple months ago in Berlin, Hortonworks made a, I think, the most significant announcement of the year for them and really for the industry, was that they announced the Data Steward Studio in Berlin. Tech really clearly was who addressed the GDPR mandate that was coming up but really did a stewardship as an end-to-end workflow for lots of, you know, core enterprise applications, absolutely essential. Data Steward Studio is a DataPlane Service that can operate across multi-cloud environments. Hortonworks is going to keep on, you know... They didn't have a DPS, DataPlane Services, announcements here in San Jose this week but you can best believe that next year at this time at this show, and in the interim they'll probably have a number of significant announcements to deepen that portfolio. Once again it's to grease the wheels towards a more purely public cloud future in which there will be Hortonworks DNA inside most of their customers' environments going forward. >> I want to ask you about themes of this year's conference. The thing is is that you were in Berlin at the last big Hortonworks DataWorks Summit. >> (speaks in foreign language) >> And really GDPR dominated the conversations because the new rules and regulations hadn't yet taken effect and companies were sort of bracing for what life was going to be like under GDPR. Now the rules are here, they're here to stay, and companies are really grappling with it, trying to understand the changes and how they can exist in this new regime. What would you say are the biggest themes... We're still talking about GDPR, of course, but what would you say are the bigger themes that are this week's conference? Is it scalability, is it... I mean, what would you say we're going, what do you think has dominated the conversations here? >> Well scalability is not the big theme this week though there are significant scalability announcements this week in the context of HDP 3.0, the ability to persist in a scale-out fashion across multi-cloud, billions of files. Storage efficiency is an important piece of the overall announcement with support for erasure coding, blah blah blah. That's not, you know, that's... Already, Hortonworks, like all of their cloud providers and other big data providers, provide very scalable environments for storage, workload management. That was not the hugest, buzzy theme in terms of the announcements this week. The buzz of course was HDP 3.0. Containerization, that's important, but you know, we just came out of the day two keynote. AI is not a huge focus yet for a lot of the Hortonworks customers who are here, the developers. They're, you know, most of their customers are not yet that far along in their deep learning journeys and whatever but they're definitely going there. There's plenty of really cool keynote discussions including the guy with the autonomous vehicles or whatever that, the thing we just came out of. That was not the predominant theme this week here in terms of the HDP 3.0. I think what it comes down to is that with HDP 3.0... Hive, though you tend to take it for granted, it's been in Hadoop from the very start, practically, Hive is now a full enterprise database and that's the core, one of the cores, of HDP 3.0. Hive itself, Hive 3.0 now is its version, is ACID compliant and that may be totally geeky to the most of the world but that enables it to support transactional applications. So more big data in every environment is supporting more traditional enterprise application, transactional applications that require like two-phase commit and all that goodness. The fact is, you know, Hortonworks have, from what I can see, is the first of the big data vendors to incorporate those enhancements to Hive 3.0 because they're so completely tuned in to the Hive environment in terms of a committer. I think in many ways that is the predominant theme in terms of the new stuff that will actually resonate with the developers, their customers here at the show. And with the, you know, enterprises in general, they can put more of their traditional enterprise application workloads on big data environments and specifically, Hortonworks hopes, its HDP 3.0. >> Well I'm excited to learn more here at the on theCube with you today. We've got a lot of great interviews lined up and a lot of interesting content. We got a great crew too so this is a fun show to do. >> Sure is. >> We will have more from day two of the.

Published Date : Jun 20 2018

SUMMARY :

Live from San Jose, in the heart James, it's great to be here with you One of the things that I really-- I think this is like the So it's an This is something that you had brought up of robust financial growth. in public cloud enabling the Well I want to ask you is the right thing to do doing the right things. And this is really where you Oh I get sleep now and I don't think of emphasis now on their announcement of the year at the last big Hortonworks because the new rules of the announcements this week. this is a fun show to do.

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Eric Herzog, IBM | DataWorks Summit 2018


 

>> Live from San Jose in the heart of Silicon Valley, it's theCUBE, covering DataWorks Summit 2018, brought to you by Hortonworks. >> Welcome back to theCUBE's live coverage of DataWorks here in San Jose, California. I'm your host, Rebecca Knight, along with my co-host, James Kobielus. We have with us Eric Herzog. He is the Chief Marketing Officer and VP of Global Channels at the IBM Storage Division. Thanks so much for coming on theCUBE once again, Eric. >> Well, thank you. We always love to be on theCUBE and talk to all of theCUBE analysts about various topics, data, storage, multi-cloud, all the works. >> And before the cameras were rolling, we were talking about how you might be the biggest CUBE alum in the sense of you've been on theCUBE more times than anyone else. >> I know I'm in the top five, but I may be number one, I have to check with Dave Vellante and crew and see. >> Exactly and often wearing a Hawaiian shirt. >> Yes. >> Yes, I was on theCUBE last week from CISCO Live. I was not wearing a Hawaiian shirt. And Stu and John gave me a hard time about why was not I wearing a Hawaiian shirt? So I make sure I showed up to the DataWorks show- >> Stu, Dave, get a load. >> You're in California with a tan, so it fits, it's good. >> So we were talking a little bit before the cameras were rolling and you were saying one of the points that is sort of central to your professional life is it's not just about the storage, it's about the data. So riff on that a little bit. >> Sure, so at IBM we believe everything is data driven and in fact we would argue that data is more valuable than oil or diamonds or plutonium or platinum or silver to anything else. It is the most viable asset, whether you be a global Fortune 500, whether you be a midsize company or whether you be Herzogs Bar and Grill. So data is what you use with your suppliers, with your customers, with your partners. Literally everything around your company is really built around the data so most effectively managing it and make sure, A, it's always performant because when it's not performant they go away. As you probably know, Google did a survey that one, two, after one, two they go off your website, they click somewhere else so has to be performant. Obviously in today's 365, 7 by 24 company it needs to always be resilient and reliable and it always needs to be available, otherwise if the storage goes down, guess what? Your AI doesn't work, your Cloud doesn't work, whatever workload, if you're more traditional, your Oracle, Sequel, you know SAP, none of those workloads work if you don't have a solid storage foundation underneath your data driven enterprise. >> So with that ethos in mind, talk about the products that you are launching, that you newly launched and also your product roadmap going forward. >> Sure, so for us everything really is that storage is this critical foundation for the data driven, multi Cloud enterprise. And as I've said before on theCube, all of our storage software's now Cloud-ified so if you need to automatically tier out to IBM Cloud or Amazon or Azure, we automatically will move the data placement around from one premise out to a Cloud and for certain customers who may be multi Cloud, in this case using multiple private Cloud providers, which happens due to either legal reasons or procurement reasons or geographic reasons for the larger enterprises, we can handle that as well. That's part of it, second thing is we just announced earlier today an artificial intelligence, an AI reference architecture, that incorporates a full stack from the very bottom, both servers and storage, all the way up through the top layer, then the applications on top, so we just launched that today. >> AI for storage management or AI for run a range of applications? >> Regular AI, artificial intelligence from an application perspective. So we announced that reference architecture today. Basically think of the reference architecture as your recipe, your blueprint, of how to put it all together. Some of the components are from IBM, such as Spectrum Scale and Spectrum Computing from my division, our servers from our Cloud division. Some are opensource, Tensor, Caffe, things like that. Basic gives you what the stack needs to be, and what you need to do in various AI workloads, applications and use cases. >> I believe you have distributed deep learning as an IBM capability, that's part of that stack, is that correct? >> That is part of the stack, it's like in the middle of the stack. >> Is it, correct me if I'm wrong, that's containerization of AI functionality? >> Right. >> For distributed deployment? >> Right. >> In an orchestrated Kubernetes fabric, is that correct? >> Yeah, so when you look at it from an IBM perspective, while we clearly support the virtualized world, the VM wares, the hyper V's, the KVMs and the OVMs, and we will continue to do that, we're also heavily invested in the container environment. For example, one of our other divisions, the IBM Cloud Private division, has announced a solution that's all about private Clouds, you can either get it hosted at IBM or literally buy our stack- >> Rob Thomas in fact demoed it this morning, here. >> Right, exactly. And you could create- >> At DataWorks. >> Private Cloud initiative, and there are companies that, whether it be for security purposes or whether it be for legal reasons or other reasons, don't want to use public Cloud providers, be it IBM, Amazon, Azure, Google or any of the big public Cloud providers, they want a private Cloud and IBM either A, will host it or B, with IBM Cloud Private. All of that infrastructure is built around a containerized environment. We support the older world, the virtualized world, and the newer world, the container world. In fact, our storage, allows you to have persistent storage in a container's environment, Dockers and Kubernetes, and that works on all of our block storage and that's a freebie, by the way, we don't charge for that. >> You've worked in the data storage industry for a long time, can you talk a little bit about how the marketing message has changed and evolved since you first began in this industry and in terms of what customers want to hear and what assuages their fears? >> Sure, so nobody cares about speeds and feeds, okay? Except me, because I've been doing storage for 32 years. >> And him, he might care. (laughs) >> But when you look at it, the decision makers today, the CIOs, in 32 years, including seven start ups, IBM and EMC, I've never, ever, ever, met a CIO who used to be a storage guy, ever. So, they don't care. They know that they need storage and the other infrastructure, including servers and networking, but think about it, when the app is slow, who do they blame? Usually they blame the storage guy first, secondarily they blame the server guy, thirdly they blame the networking guy. They never look to see that their code stack is improperly done. Really what you have to do is talk applications, workloads and use cases which is what the AI reference architecture does. What my team does in non AI workloads, it's all about, again, data driven, multi Cloud infrastructure. They want to know how you're going to make a new workload fast AI. How you're going to make their Cloud resilient whether it's private or hybrid. In fact, IBM storage sells a ton of technology to large public Cloud providers that do not have the initials IBM. We sell gobs of storage to other public Cloud providers, both big, medium and small. It's really all about the applications, workloads and use cases, and that's what gets people excited. You basically need a position, just like I talked about with the AI foundations, storage is the critical foundation. We happen to be, knocking on wood, let's hope there's no earthquake, since I've lived here my whole life, and I've been in earthquakes, I was in the '89 quake. Literally fell down a bunch of stairs in the '89 quake. If there's an earthquake as great as IBM storage is, or any other storage or servers, it's crushed. Boom, you're done! Okay, well you need to make sure that your infrastructure, really your data, is covered by the right infrastructure and that it's always resilient, it's always performing and is always available. And that's what IBM drives is about, that's the message, not about how many gigabytes per second in bandwidth or what's the- Not that we can't spew that stuff when we talk to the right person but in general people don't care about it. What they want to know is, "Oh that SAP workload took 30 hours and now it takes 30 minutes?" We have public references that will say that. "Oh, you mean I can use eight to ten times less storage for the same money?" Yes, and we have public references that will say that. So that's what it's really about, so storage is really more from really a speeds and feeds Nuremberger sort of thing, and now all the Nurembergers are doing AI and Caffe and TensorFlow and all of that, they're all hackers, right? It used to be storage guys who used to do that and to a lesser extent server guys and definitely networking guys. That's all shifted to the software side so you got to talk the languages. What can we do with Hortonworks? By the way we were named in Q1 of 2018 as the Hortonworks infrastructure partner of the year. We work with Hortonworks all time, at all levels, whether it be with our channel partners, whether it be with our direct end users, however the customer wants to consume, we work with Hortonworks very closely and other providers as well in that big data analytics and the AI infrastructure world, that's what we do. >> So the containerizations side of the IBM AI stack, then the containerization capabilities in Hortonworks Data Platform 3.0, can you give us a sense for how you plan to, or do you plan at IBM, to work with Hortonworks to bring these capabilities, your reference architecture, into more, or bring their environment for that matter, into more of an alignment with what you're offering? >> So we haven't an exact decision of how we're going to do it, but we interface with Hortonworks on a continual basis. >> Yeah. >> We're working to figure out what's the right solution, whether that be an integrated solution of some type, whether that be something that we do through an adjunct to our reference architecture or some reference architecture that they have but we always make sure, again, we are their partner of the year for infrastructure named in Q1, and that's because we work very tightly with Hortonworks and make sure that what we do ties out with them, hits the right applications, workloads and use cases, the big data world, the analytic world and the AI world so that we're tied off, you know, together to make sure that we deliver the right solutions to the end user because that's what matters most is what gets the end users fired up, not what gets Hortonworks or IBM fired up, it's what gets the end users fired up. >> When you're trying to get into the head space of the CIO, and get your message out there, I mean what is it, what would you say is it that keeps them up at night? What are their biggest pain points and then how do you come in and solve them? >> I'd say the number one pain point for most CIOs is application delivery, okay? Whether that be to the line of business, put it this way, let's take an old workload, okay? Let's take that SAP example, that CIO was under pressure because they were trying, in this case it was a giant retailer who was shipping stuff every night, all over the world. Well guess what? The green undershirts in the wrong size, went to Paducah, Kentucky and then one of the other stores, in Singapore, which needed those green shirts, they ended up with shoes and the reason is, they couldn't run that SAP workload in a couple hours. Now they run it in 30 minutes. It used to take 30 hours. So since they're shipping every night, you're basically missing a cycle, essentially and you're not delivering the right thing from a retail infrastructure perspective to each of their nodes, if you will, to their retail locations. So they care about what do they need to do to deliver to the business the right applications, workloads and use cases on the right timeframe and they can't go down, people get fired for that at the CIO level, right? If something goes down, the CIO is gone and obviously for certain companies that are more in the modern mode, okay? People who are delivering stuff and their primary transactional vehicle is the internet, not retail, not through partners, not through people like IBM, but their primary transactional vehicle is a website, if that website is not resilient, performant and always reliable, then guess what? They are shut down and they're not selling anything to anybody, which is to true if you're Nordstroms, right? Someone can always go into the store and buy something, right, and figure it out? Almost all old retailers have not only a connection to core but they literally have a server and storage in every retail location so if the core goes down, guess what, they can transact. In the era of the internet, you don't do that anymore. Right? If you're shipping only on the internet, you're shipping on the internet so whether it be a new workload, okay? An old workload if you're doing the whole IOT thing. For example, I know a company that I was working with, it's a giant, private mining company. They have those giant, like three story dump trucks you see on the Discovery Channel. Those things cost them a hundred million dollars, so they have five thousand sensors on every dump truck. It's a fricking dump truck but guess what, they got five thousand sensors on there so they can monitor and make sure they take proactive action because if that goes down, whether these be diamond mines or these be Uranium mines or whatever it is, it costs them hundreds of millions of dollars to have a thing go down. That's, if you will, trying to take it out of the traditional, high tech area, which we all talk about, whether it be Apple or Google, or IBM, okay great, now let's put it to some other workload. In this case, this is the use of IOT, in a big data analytics environment with AI based infrastructure, to manage dump trucks. >> I think you're talking about what's called, "digital twins" in a networked environment for materials management, supply chain management and so forth. Are those requirements growing in terms of industrial IOT requirements of that sort and how does that effect the amount of data that needs to be stored, the sophistication of the AI and the stream competing that needs to be provisioned? Can you talk to that? >> The amount of data is growing exponentially. It's growing at yottabytes and zettabytes a year now, not at just exabytes anymore. In fact, everybody on their iPhone or their laptop, I've got a 10GB phone, okay? My laptop, which happens to be a Power Book, is two terabytes of flash, on a laptop. So just imagine how much data's being generated if you're doing in a giant factory, whether you be in the warehouse space, whether you be in healthcare, whether you be in government, whether you be in the financial sector and now all those additional regulations, such as GDPR in Europe and other regulations across the world about what you have to do with your healthcare data, what you have to do with your finance data, the amount of data being stored. And then on top of it, quite honestly, from an AI big data analytics perspective, the more data you have, the more valuable it is, the more you can mine it or the more oil, it's as if the world was just oil, forget the pollution side, let's assume oil didn't cause pollution. Okay, great, then guess what? You would be using oil everywhere and you wouldn't be using solar, you'd be using oil and by the way you need more and more and more, and how much oil you have and how you control that would be the power. That right now is the power of data and if anything it's getting more and more and more. So again, you always have to be able to be resilient with that data, you always have to interact with things, like we do with Hortonworks or other application workloads. Our AI reference architecture is another perfect example of the things you need to do to provide, you know, at the base infrastructure, the right foundation. If you have the wrong foundation to a building, it falls over. Whether it be your house, a hotel, this convention center, if it had the wrong foundation, it falls over. >> Actually to follow the oil analogy just a little bit further, the more of this data you have, the more PII there is and it usually, and the more the workloads need to scale up, especially for things like data masking. >> Right. >> When you have compliance requirements like GDPR, so you want to process the data but you need to mask it first, therefore you need clusters that conceivably are optimized for high volume, highly scalable masking in real time, to drive the downstream app, to feed the downstream applications and to feed the data scientist, you know, data lakes, whatever, and so forth and so on? >> That's why you need things like Incredible Compute which IBM offers with the Power Platform. And why you need storage that, again, can scale up. >> Yeah. >> Can get as big as you need it to be, for example in our reference architecture, we use both what we call Spectrum Scale, which is a big data analytics workload performance engine, it has multiple threaded, multi tasking. In fact one of the largest banks in the world, if you happen to bank with them, your credit card fraud is being done on our stuff, okay? But at the same time we have what's called IBM Cloud Object Storage which is an object store, you want to take every one of those searches for fraud and when they find out that no one stole my MasterCard or the Visa, you still want to put it in there because then you mine it later and see patterns of how people are trying to steal stuff because it's all being done digitally anyway. You want to be able to do that. So you A, want to handle it very quickly and resiliently but then you want to be able to mine it later, as you said, mining the data. >> Or do high value anomaly detection in the moment to be able to tag the more anomalous data that you can then sift through later or maybe in the moment for realtime litigation. >> Well that's highly compute intensive, it's AI intensive and it's highly storage intensive on a performance side and then what happens is you store it all for, lets say, further analysis so you can tell people, "When you get your Am Ex card, do this and they won't steal it." Well the only way to do that, is you use AI on this ocean of data, where you're analyzing all this fraud that has happened, to look at patterns and then you tell me, as a consumer, what to do. Whether it be in the financial business, in this case the credit card business, healthcare, government, manufacturing. One of our resellers actually developed an AI based tool that can scan boxes and cans for faults on an assembly line and actually have sold it to a beer company and to a soda company that instead of people looking at the cans, like you see on the Food Channel, to pull it off, guess what? It's all automatically done. There's no people pulling the can off, "Oh, that can is damaged" and they're looking at it and by the way, sometimes they slip through. Now, using cameras and this AI based infrastructure from IBM, with our storage underneath the hood, they're able to do this. >> Great. Well Eric thank you so much for coming on theCUBE. It's always been a lot of fun talking to you. >> Great, well thank you very much. We love being on theCUBE and appreciate it and hope everyone enjoys the DataWorks conference. >> We will have more from DataWorks just after this. (techno beat music)

Published Date : Jun 19 2018

SUMMARY :

in the heart of Silicon He is the Chief Marketing Officer and talk to all of theCUBE analysts in the sense of you've been on theCUBE I know I'm in the top five, Exactly and often And Stu and John gave me a hard time about You're in California with and you were saying one of the points and it always needs to be available, that you are launching, for the data driven, and what you need to do of the stack, it's like in in the container environment. Rob Thomas in fact demoed it And you could create- and that's a freebie, by the Sure, so nobody cares And him, he might care. and the AI infrastructure So the containerizations So we haven't an exact decision so that we're tied off, you know, together and the reason is, they of the AI and the stream competing and by the way you need more of this data you have, And why you need storage that, again, my MasterCard or the Visa, you still want anomaly detection in the moment at the cans, like you of fun talking to you. the DataWorks conference. We will have more from

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Joel Horwitz, IBM | IBM CDO Summit Sping 2018


 

(techno music) >> Announcer: Live, from downtown San Francisco, it's theCUBE. Covering IBM Chief Data Officer Strategy Summit 2018. Brought to you by IBM. >> Welcome back to San Francisco everybody, this is theCUBE, the leader in live tech coverage. We're here at the Parc 55 in San Francisco covering the IBM CDO Strategy Summit. I'm here with Joel Horwitz who's the Vice President of Digital Partnerships & Offerings at IBM. Good to see you again Joel. >> Thanks, great to be here, thanks for having me. >> So I was just, you're very welcome- It was just, let's see, was it last month, at Think? >> Yeah, it's hard to keep track, right. >> And we were talking about your new role- >> It's been a busy year. >> the importance of partnerships. One of the things I want to, well let's talk about your role, but I really want to get into, it's innovation. And we talked about this at Think, because it's so critical, in my opinion anyway, that you can attract partnerships, innovation partnerships, startups, established companies, et cetera. >> Joel: Yeah. >> To really help drive that innovation, it takes a team of people, IBM can't do it on its own. >> Yeah, I mean look, IBM is the leader in innovation, as we all know. We're the market leader for patents, that we put out each year, and how you get that technology in the hands of the real innovators, the developers, the longtail ISVs, our partners out there, that's the challenging part at times, and so what we've been up to is really looking at how we make it easier for partners to partner with IBM. How we make it easier for developers to work with IBM. So we have a number of areas that we've been adding, so for example, we've added a whole IBM Code portal, so if you go to developer.ibm.com/code you can actually see hundreds of code patterns that we've created to help really any client, any partner, get started using IBM's technology, and to innovate. >> Yeah, and that's critical, I mean you're right, because to me innovation is a combination of invention, which is what you guys do really, and then it's adoption, which is what your customers are all about. You come from the data science world. We're here at the Chief Data Officer Summit, what's the intersection between data science and CDOs? What are you seeing there? >> Yeah, so when I was here last, it was about two years ago in 2015, actually, maybe three years ago, man, time flies when you're having fun. >> Dave: Yeah, the Spark Summit- >> Yeah Spark Technology Center and the Spark Summit, and we were here, I was here at the Chief Data Officer Summit. And it was great, and at that time, I think a lot of the conversation was really not that different than what I'm seeing today. Which is, how do you manage all of your data assets? I think a big part of doing good data science, which is my kind of background, is really having a good understanding of what your data governance is, what your data catalog is, so, you know we introduced the Watson Studio at Think, and actually, what's nice about that, is it brings a lot of this together. So if you look in the market, in the data market, today, you know we used to segment it by a few things, like data gravity, data movement, data science, and data governance. And those are kind of the four themes that I continue to see. And so outside of IBM, I would contend that those are relatively separate kind of tools that are disconnected, in fact Dinesh Nirmal, who's our engineer on the analytic side, Head of Development there, he wrote a great blog just recently, about how you can have some great machine learning, you have some great data, but if you can't operationalize that, then really you can't put it to use. And so it's funny to me because we've been focused on this challenge, and IBM is making the right steps, in my, I'm obviously biased, but we're making some great strides toward unifying the, this tool chain. Which is data management, to data science, to operationalizing, you know, machine learning. So that's what we're starting to see with Watson Studio. >> Well, I always push Dinesh on this and like okay, you've got a collection of tools, but are you bringing those together? And he flat-out says no, we developed this, a lot of this from scratch. Yes, we bring in the best of the knowledge that we have there, but we're not trying to just cobble together a bunch of disparate tools with a UI layer. >> Right, right. >> It's really a fundamental foundation that you're trying to build. >> Well, what's really interesting about that, that piece, is that yeah, I think a lot of folks have cobbled together a UI layer, so we formed a partnership, coming back to the partnership view, with a company called Lightbend, who's based here in San Francisco, as well as in Europe, and the reason why we did that, wasn't just because of the fact that Reactive development, if you're not familiar with Reactive, it's essentially Scala, Akka, Play, this whole framework, that basically allows developers to write once, and it kind of scales up with demand. In fact, Verizon actually used our platform with Lightbend to launch the iPhone 10. And they show dramatic improvements. Now what's exciting about Lightbend, is the fact that application developers are developing with Reactive, but if you turn around, you'll also now be able to operationalize models with Reactive as well. Because it's basically a single platform to move between these two worlds. So what we've continued to see is data science kind of separate from the application world. Really kind of, AI and cloud as different universes. The reality is that for any enterprise, or any company, to really innovate, you have to find a way to bring those two worlds together, to get the most use out of it. >> Fourier always says "Data is the new development kit". He said this I think five or six years ago, and it's barely becoming true. You guys have tried to make an attempt, and have done a pretty good job, of trying to bring those worlds together in a single platform, what do you call it? The Watson Data Platform? >> Yeah, Watson Data Platform, now Watson Studio, and I think the other, so one side of it is, us trying to, not really trying, but us actually bringing together these disparate systems. I mean we are kind of a systems company, we're IT. But not only that, but bringing our trained algorithms, and our trained models to the developers. So for example, we also did a partnership with Unity, at the end of last year, that's now just reaching some pretty good growth, in terms of bringing the Watson SDK to game developers on the Unity platform. So again, it's this idea of bringing the game developer, the application developer, in closer contact with these trained models, and these trained algorithms. And that's where you're seeing incredible things happen. So for example, Star Trek Bridge Crew, which I don't know how many Trekkies we have here at the CDO Summit. >> A few over here probably. >> Yeah, a couple? They're using our SDK in Unity, to basically allow a gamer to use voice commands through the headset, through a VR headset, to talk to other players in the virtual game. So we're going to see more, I can't really disclose too much what we're doing there, but there's some cool stuff coming out of that partnership. >> Real immersive experience driving a lot of data. Now you're part of the Digital Business Group. I like the term digital business, because we talk about it all the time. Digital business, what's the difference between a digital business and a business? What's the, how they use data. >> Joel: Yeah. >> You're a data person, what does that mean? That you're part of the Digital Business Group? Is that an internal facing thing? An external facing thing? Both? >> It's really both. So our Chief Digital Officer, Bob Lord, he has a presentation that he'll give, where he starts out, and he goes, when I tell people I'm the Chief Digital Officer they usually think I just manage the website. You know, if I tell people I'm a Chief Data Officer, it means I manage our data, in governance over here. The reality is that I think these Chief Digital Officer, Chief Data Officer, they're really responsible for business transformation. And so, if you actually look at what we're doing, I think on both sides is we're using data, we're using marketing technology, martech, like Optimizely, like Segment, like some of these great partners of ours, to really look at how we can quickly A/B test, get user feedback, to look at how we actually test different offerings and market. And so really what we're doing is we're setting up a testing platform, to bring not only our traditional offers to market, like DB2, Mainframe, et cetera, but also bring new offers to market, like blockchain, and quantum, and others, and actually figure out how we get better product-market fit. What actually, one thing, one story that comes to mind, is if you've seen the movie Hidden Figures- >> Oh yeah. >> There's this scene where Kevin Costner, I know this is going to look not great for IBM, but I'm going to say it anyways, which is Kevin Costner has like a sledgehammer, and he's like trying to break down the wall to get the mainframe in the room. That's what it feels like sometimes, 'cause we create the best technology, but we forget sometimes about the last mile. You know like, we got to break down the wall. >> Where am I going to put it? >> You know, to get it in the room! So, honestly I think that's a lot of what we're doing. We're bridging that last mile, between these different audiences. So between developers, between ISVs, between commercial buyers. Like how do we actually make this technology, not just accessible to large enterprise, which are our main clients, but also to the other ecosystems, and other audiences out there. >> Well so that's interesting Joel, because as a potential partner of IBM, they want, obviously your go-to-market, your massive company, and great distribution channel. But at the same time, you want more than that. You know you want to have a closer, IBM always focuses on partnerships that have intrinsic value. So you talked about offerings, you talked about quantum, blockchain, off-camera talking about cloud containers. >> Joel: Yeah. >> I'd say cloud and containers may be a little closer than those others, but those others are going to take a lot of market development. So what are the offerings that you guys are bringing? How do they get into the hands of your partners? >> I mean, the commonality with all of these, all the emerging offerings, if you ask me, is the distributed nature of the offering. So if you look at blockchain, it's a distributed ledger. It's a distributed transaction chain that's secure. If you look at data, really and we can hark back to say, Hadoop, right before object storage, it's distributed storage, so it's not just storing on your hard drive locally, it's storing on a distributed network of servers that are all over the world and data centers. If you look at cloud, and containers, what you're really doing is not running your application on an individual server that can go down. You're using containers because you want to distribute that application over a large network of servers, so that if one server goes down, you're not going to be hosed. And so I think the fundamental shift that you're seeing is this distributed nature, which in essence is cloud. So I think cloud is just kind of a synonym, in my opinion, for distributed nature of our business. >> That's interesting and that brings up, you're right, cloud and Big Data/Hadoop, we don't talk about Hadoop much anymore, but it kind of got it all started, with that notion of leave the data where it is. And it's the same thing with cloud. You can't just stuff your business into the public cloud. You got to bring the cloud to your data. >> Joel: That's right. >> But that brings up a whole new set of challenges, which obviously, you're in a position just to help solve. Performance, latency, physics come into play. >> Physics is a rough one. It's kind of hard to avoid that one. >> I hear your best people are working on it though. Some other partnerships that you want to sort of, elucidate. >> Yeah, no, I mean we have some really great, so I think the key kind of partnership, I would say area, that I would allude to is, one of the things, and you kind of referenced this, is a lot of our partners, big or small, want to work with our top clients. So they want to work with our top banking clients. They want, 'cause these are, if you look at for example, MaRisk and what we're doing with them around blockchain, and frankly, talk about innovation, they're innovating containers for real, not virtual containers- >> And that's a joint venture right? >> Yeah, it is, and so it's exciting because, what we're bringing to market is, I also lead our startup programs, called the Global Entrepreneurship Program, and so what I'm focused on doing, and you'll probably see more to come this quarter, is how do we actually bridge that end-to-end? How do you, if you're startup or a small business, ultimately reach that kind of global business partner level? And so kind of bridging that, that end-to-end. So we're starting to bring out a number of different incentives for partners, like co-marketing, so I'll help startups when they're early, figure out product-market fit. We'll give you free credits to use our innovative technology, and we'll also bring you into a number of clients, to basically help you not burn all of your cash on creating your own marketing channel. God knows I did that when I was at a start-up. So I think we're doing a lot to kind of bridge that end-to-end, and help any partner kind of come in, and then grow with IBM. I think that's where we're headed. >> I think that's a critical part of your job. Because I mean, obviously IBM is known for its Global 2000, big enterprise presence, but startups, again, fuel that innovation fire. So being able to attract them, which you're proving you can, providing whatever it is, access, early access to cloud services, or like you say, these other offerings that you're producing, in addition to that go-to-market, 'cause it's funny, we always talk about how efficient, capital efficient, software is, but then you have these companies raising hundreds of millions of dollars, why? Because they got to do promotion, marketing, sales, you know, go-to-market. >> Yeah, it's really expensive. I mean, you look at most startups, like their biggest ticket item is usually marketing and sales. And building channels, and so yeah, if you're, you know we're talking to a number of partners who want to work with us because of the fact that, it's not just like, the direct kind of channel, it's also, as you kind of mentioned, there's other challenges that you have to overcome when you're working with a larger company. for example, security is a big one, GDPR compliance now, is a big one, and just making sure that things don't fall over, is a big one. And so a lot of partners work with us because ultimately, a number of the decision makers in these larger enterprises are going, well, I trust IBM, and if IBM says you're good, then I believe you. And so that's where we're kind of starting to pull partners in, and pull an ecosystem towards us. Because of the fact that we can take them through that level of certification. So we have a number of free online courses. So if you go to partners, excuse me, ibm.com/partners/learn there's a number of blockchain courses that you can learn today, and will actually give you a digital certificate, that's actually certified on our own blockchain, which we're actually a first of a kind to do that, which I think is pretty slick, and it's accredited at some of the universities. So I think that's where people are looking to IBM, and other leaders in this industry, is to help them become experts in their, in this technology, and especially in this emerging technology. >> I love that blockchain actually, because it's such a growing, and interesting, and innovative field. But it needs players like IBM, that can bring credibility, enterprise-grade, whether it's security, or just, as I say, credibility. 'Cause you know, this is, so much of negative connotations associated with blockchain and crypto, but companies like IBM coming to the table, enterprise companies, and building that ecosystem out is in my view, crucial. >> Yeah, no, it takes a village. I mean, there's a lot of folks, I mean that's a big reason why I came to IBM, three, four years ago, was because when I was in start-up land, I used to work for H20, I worked for Alpine Data Labs, Datameer, back in the Hadoop days, and what I realized was that, it's an opportunity cost. So you can't really drive true global innovation, transformation, in some of these bigger companies because there's only so much that you can really kind of bite off. And so you know at IBM it's been a really rewarding experience because we have done things like for example, we partnered with Girls Who Code, Treehouse, Udacity. So there's a number of early educators that we've partnered with, to bring code to, to bring technology to, that frankly, would never have access to some of this stuff. Some of this technology, if we didn't form these alliances, and if we didn't join these partnerships. So I'm very excited about the future of IBM, and I'm very excited about the future of what our partners are doing with IBM, because, geez, you know the cloud, and everything that we're doing to make this accessible, is bar none, I mean, it's great. >> I can tell you're excited. You know, spring in your step. Always a lot of energy Joel, really appreciate you coming onto theCUBE. >> Joel: My pleasure. >> Great to see you again. >> Yeah, thanks Dave. >> You're welcome. Alright keep it right there, everybody. We'll be back. We're at the IBM CDO Strategy Summit in San Francisco. You're watching theCUBE. (techno music) (touch-tone phone beeps)

Published Date : May 2 2018

SUMMARY :

Brought to you by IBM. Good to see you again Joel. that you can attract partnerships, To really help drive that innovation, and how you get that technology Yeah, and that's critical, I mean you're right, Yeah, so when I was here last, to operationalizing, you know, machine learning. that we have there, but we're not trying that you're trying to build. to really innovate, you have to find a way in a single platform, what do you call it? So for example, we also did a partnership with Unity, to basically allow a gamer to use voice commands I like the term digital business, to look at how we actually test different I know this is going to look not great for IBM, but also to the other ecosystems, But at the same time, you want more than that. So what are the offerings that you guys are bringing? So if you look at blockchain, it's a distributed ledger. You got to bring the cloud to your data. But that brings up a whole new set of challenges, It's kind of hard to avoid that one. Some other partnerships that you want to sort of, elucidate. and you kind of referenced this, to basically help you not burn all of your cash early access to cloud services, or like you say, that you can learn today, but companies like IBM coming to the table, that you can really kind of bite off. really appreciate you coming onto theCUBE. We're at the IBM CDO Strategy Summit in San Francisco.

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Sai Mukundan, Cohesity | AWS Summit SF 2018


 

>> Announcer: Live, from the Moscone Center, it's theCUBE covering AWS Summit San Francisco 2018. Brought to you by Amazon Web Services. (electronic music) >> Welcome back to theCUBE's coverage of AWS Summit here in San Francisco. I'm Stu Miniman, happy to welcome to the program a first time guest, Sai Mukundan, who's in product management at Cohesity, excuse me, Sai, thanks so much for joining us. >> Thanks, Stu, lovely to be here at AWS Summit. >> Okay, tell us a little bit about your background and really, what led you to come to Cohesity? >> Sure, so as you know, Cohesity is one of the private VC funded companies in the Bay Area. I was actually in Microsoft Azure prior to Cohesity. >> Can't mention Azure here, we're at the AWS event, Sai. >> It's okay, I mean, that's where I was, right? >> So, I've been in storage domain, in the industry for some time, prior to that at Veritas. Being in product management for a number of years, and I think what drew me to Cohesity was really two things, right. One is the fact that it was led by, it's led by Mohit Aron, one of the pioneers when it comes to distributed systems and building and scaling companies. And then, the second thing is to really be part of something where you can make a big difference in industry. I mean, you are making a sea change in the storage domain, of all things, to become hard again. And so to be part of that change was really what drew me to Cohesity. >> Yeah, (mumble), you talk about storage in Cloud. You know, when you think back, it's like, remember, Cloud was going to be simple, it's just this wonderful thing. We just turn it on, I don't have to worry about things like, definitely don't have to worry about storage. You know, they'll take care of all my security, your backup goes away, I don't have to worry about any of the things anymore. Oh, wait, maybe we do need to worry about those things, right? >> Yeah, absolutely, absolutely. So, what we see from customers is, a lot of them really want to adopt the Cloud and have been adopting it in their own way, right? But what they're faced with is, really, broadly, I would say from a storage perspective, three different challenges. One is the fact that they have, they continue to have their on-premises and now they're looking to leverage the Cloud, so that's number one in terms of how can I make it very seamless without any point products or point solutions. The second is, from a Cohesity perspective, we are really focused on what we call a secondary storage. Things that are outside what we call the primary, which is not your mission critical, high IOPS, low latency applications, but things like backup, test, dev, DR, right? And so, there's a lot of silos in there. So, how do I adopt the Cloud, at the same time reduce the silo infrastructure? And the third one is really around ease of use and management and simplicity around it. So that's really where the complexity comes in and Cohesity is trying to address that. >> Okay, Sai, when I look, some of the marketing material from Cohesity, I heard the term, it was hyper-converged, secondary storage. Isn't that some box that lives in my data center? How does that fit into, kind of, the Cloud discussion that we're having today? >> Yeah, so let me clarify that myth a little bit, right. So, in the data center, yeah, you have a lot of boxes, right. But, from Cohesity, the way we like to think about our solutions is it's completely software defined, right. Software defined, API-driven approach to doing things. So let me, kind of, set you up with what the challenge is from a customer standpoint. So when you have secondary storage, or the element of backup and test, dev, and DR. What customers typically have is a combination of media servers, massive servers, talking to storage, tape, and then Cloud becomes an afterthought. You typically have some kind of a Cloud gateway, talking to various different public Clouds, right. So you can see how this environment is pretty complicated in the fact you have different point products. So very scattered and inefficient. The second thing, from an inefficiency standpoint, is the fact that there is the same copy of data maintained across many different systems. And then, now, when you think about the Cloud, you're now trying to manage the on-premise with the Cloud, right, and managing it in two different environments is not very easy. That's the problem space and then with Cohesity, what we are trying to do is, we have what we call The Data Platform, again that's the software-defined aspect of it, which can run on hardware that we provide. Or it can run on hardware that the customers bring to the table. So, again that's where the software-defined nature comes in. And the same software, we call it the Cloud Edition can run on AWS or any of the other public Clouds as well. >> Okay, so paint a picture for me. Is the data center kind of the primary piece and the Cloud, is it kind of a back up archive, things like that? Or are they equal and they live, or there's some customers, can I just have Cohesity software only in public Clouds, or does there need to be some data center component of this? >> It's really all of the above, in the sense that we have customers who think of it, think of a hybrid approach to doing things. So they have their on-premises and the Cloud as well, right. And, in the hybrid approach, they're typically trying to do two things. One is, leverage just the storage in the Cloud as an extension of their on-premise, wherein you can archive the data for long-term retention or for tiering. And then the second use case is really around test, dev, and disaster recovery in the Cloud. Then we have a second set of customers which are born in the Cloud, Cloud only, right. And that's where our Cloud Edition product, the software-defined nature of it helps them run in the Cloud and so all the same main points. We don't want any silos now existing in the Cloud, right. And then, there is a third category wherein they are predominantly on-prem today, but heavily looking to leverage the Cloud, and Cohesity is that data continuum, so to speak, in terms of a single platform, a single fabric, that can manage both on-premise, as well as the Cloud environment. >> Great, so I heard, Cloud Edition, I could be only in The Cloud and can work with Cohesity. >> Absolutely. >> When I look at customers, you know, it's typically heterogy as an environment. It's great if I've got some brand new, born in the Cloud there, but most customers, they've got a heterogeneous environment, which means, I've got multiple different storage types in my data center. I'm probably using multiple Cloud services, and we'd think that'd be a good position for Cohesity, to be that secondary storage layer, to help manage all of that, no matter what we are. Am I getting that right? >> Yeah, absolutely. I would say, the more fragmentation, or the more point solutions a customer is using today, the greater the benefit they can realize from Cohesity. 'Cause we are really bringing all of that together, right. So, you mention storage, storage is a big part of it. But, you also see a lot of customers looking toward up more compute as well in The Cloud, right. That's where the likes of Amazon EC2 and The EBS really comes in to play as well, right. And in that case, really, the use cases are test, dev, disaster recovery, and then the fact that they can do more with the data, right? One of the other things that our platform offers is the ability to do analytics on it. The ability to find insights, as Mohit likes to call it, it's dark data today, but we can shed some light on it. So that's really where the direction is where we are headed in terms of innovation and where Cohesity is headed as a company. >> Sai, what do you find from customers? Are they aware of the challenge that they have in the Cloud? I think, in the data center, it's kind of well known that I need to be able to deal with these. Are there customers that are just unaware that they've got some of these challenges or falling into pitfalls and losing data or having issues that they then have to deal with? >> I would say there are two sets of customers in that space. One is the customer who is really wary about things, who's really security conscious, who's kind of just dabbling with The Cloud, maybe, here and there, but really conscious about adopting it on a broader perspective. Just because they're really concerned about whether it's PII information, or any other security aspects, right. So, for them, having a solution that spans both on-premise and the Cloud really is a great stepping stone, so to speak, in terms of now I can confidently move the data to the Cloud. It's encrypted both at rest and in flight, and I can continue to use the same solution in both cases. We have a second set of customers, I would say, who are more, have been more bullish about the Cloud in general. But now they are taking a step back and saying, hey, wait a minute, I'm continuing to face some of these same challenges that existed on-premise in the past, right. It's siloed again, I have various different storage. We have S3, EBS, you have potentially other things, And then, I'm running into the same pitfalls. So how can I take a step back, take a more holistic approach and solve the problem? So, again, they're with the software-defined nature of our solution really appeals to them because we come in and we can solve some of those problems as well. They then face the same sort of problems in the Cloud world as they did on-prem world and now they can say hey, let me look at Cohesity as a solution that can get me there. >> All right, you brought up PII, so I have to ask the big question that's in everybody's mind lately, what about GDPR? AWS said this morning, all their services, fully ready, 100%, how does this impact Cohesity and your customers? >> So, GDPR is a big thing for us and our customers and prospects, as well. So we are actively working on getting GDPR compliant. Today, our platform is FIPS compliant, so that's already a big stepping stone to getting there. So we look at GDPR in one of, in two ways again, right. One is the the solution that we provide to our customers, The Data Platform and The Data Protector, as we call it, being GDPR compliant. Meaning, the data that lands on that system, the ability to delete the data, the ability to say who has access to the data, road-based access, things like that. The second aspect is our support and the fact that we have access to a lot of customer information ourselves, right. The fact that we can look at their systems and make sure that everything that we do internally is also GDPR compliant, so that the customers and our support systems and our salesforce database is all GDPR as well. So both those elements come in to play and we are actively working on all of them. >> Well, I wouldn't expect that you'd be looking at the customers' data. (Stu chuckles) >> Well, when I say customers' information, what I mean is the fact that when we access their platform, let's say they file a support ticket. The fact that now we can access their platform, debug their systems, look at the logs and alerts. It's equally important to be compliant there as well, from a GDPR stand point. >> Totally understand, I just wanted to make sure there wasn't any ambiguity there. Great, Sai, I want to give you the final word. We look forward to 2018, what can we be looking for from Cohesity as a regards to the Cloud Marketplace? >> Yeah, I think a couple of things there. One thing that you will hear more about is Cohesity and Cloud. We are actively, we have been working on The Cloud elements, both from a storage perspective and a computer perspective. But looking here, I would say more on what we can do with Cloud Edition, especially with the fact that there are more Cloud native, born in the Cloud applications and providing the same data protection and platform abilities in the Cloud, that is number one. And then the second aspect, I would say, is continued reinforcement of our hybrid message. The fact that we can solve this pain point for our customers in the on-prem world and the Cloud world. Really, from a scalable standpoint, from an API different standpoint, and the ease of use in management. Those three themes are something that you will continue to hear from Cohesity. >> All right, Sai Mukundan with Cohesity, thanks so much for bringing us the update. We'll be back with lots more coverage here from AWS Summit San Francisco, I'm Stu Miniman, you're watching theCUBE. (electronic music)

Published Date : Apr 5 2018

SUMMARY :

Announcer: Live, from the Moscone Center, it's theCUBE I'm Stu Miniman, happy to welcome to the program private VC funded companies in the Bay Area. in the industry for some time, prior to that at Veritas. about any of the things anymore. One is the fact that they have, they continue to have How does that fit into, kind of, the Cloud the customers bring to the table. Is the data center kind of the primary piece and the Cloud, and Cohesity is that data continuum, so to speak, Great, so I heard, Cloud Edition, born in the Cloud there, but most customers, is the ability to do analytics on it. that I need to be able to deal with these. confidently move the data to the Cloud. and the fact that we have access be looking at the customers' data. The fact that now we can access their platform, We look forward to 2018, what can we be looking and platform abilities in the Cloud, that is number one. All right, Sai Mukundan with Cohesity,

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Vikram Murali, IBM | IBM Data Science For All


 

>> Narrator: Live from New York City, it's theCUBE. Covering IBM Data Science For All. Brought to you by IBM. >> Welcome back to New York here on theCUBE. Along with Dave Vellante, I'm John Walls. We're Data Science For All, IBM's two day event, and we'll be here all day long wrapping up again with that panel discussion from four to five here Eastern Time, so be sure to stick around all day here on theCUBE. Joining us now is Vikram Murali, who is a program director at IBM, and Vikram thank for joining us here on theCUBE. Good to see you. >> Good to see you too. Thanks for having me. >> You bet. So, among your primary responsibilities, The Data Science Experience. So first off, if you would, share with our viewers a little bit about that. You know, the primary mission. You've had two fairly significant announcements. Updates, if you will, here over the past month or so, so share some information about that too if you would. >> Sure, so my team, we build The Data Science Experience, and our goal is for us to enable data scientist, in their path, to gain insights into data using data science techniques, mission learning, the latest and greatest open source especially, and be able to do collaboration with fellow data scientist, with data engineers, business analyst, and it's all about freedom. Giving freedom to data scientist to pick the tool of their choice, and program and code in the language of their choice. So that's the mission of Data Science Experience, when we started this. The two releases, that you mentioned, that we had in the last 45 days. There was one in September and then there was one on October 30th. Both of these releases are very significant in the mission learning space especially. We now support Scikit-Learn, XGBoost, TensorFlow libraries in Data Science Experience. We have deep integration with Horton Data Platform, which is keymark of our partnership with Hortonworks. Something that we announced back in the summer, and this last release of Data Science Experience, two days back, specifically can do authentication with Technotes with Hadoop. So now our Hadoop customers, our Horton Data Platform customers, can leverage all the goodies that we have in Data Science Experience. It's more deeply integrated with our Hadoop based environments. >> A lot of people ask me, "Okay, when IBM announces a product like Data Science Experience... You know, IBM has a lot of products in its portfolio. Are they just sort of cobbling together? You know? So exulting older products, and putting a skin on them? Or are they developing them from scratch?" How can you help us understand that? >> That's a great question, and I hear that a lot from our customers as well. Data Science Experience started off as a design first methodology. And what I mean by that is we are using IBM design to lead the charge here along with the product and development. And we are actually talking to customers, to data scientist, to data engineers, to enterprises, and we are trying to find out what problems they have in data science today and how we can best address them. So it's not about taking older products and just re-skinning them, but Data Science Experience, for example, it started of as a brand new product: completely new slate with completely new code. Now, IBM has done data science and mission learning for a very long time. We have a lot of assets like SPSS Modeler and Stats, and digital optimization. And we are re-investing in those products, and we are investing in such a way, and doing product research in such a way, not to make the old fit with the new, but in a way where it fits into the realm of collaboration. How can data scientist leverage our existing products with open source, and how we can do collaboration. So it's not just re-skinning, but it's building ground up. >> So this is really important because you say architecturally it's built from the ground up. Because, you know, given enough time and enough money, you know, smart people, you can make anything work. So the reason why this is important is you mentioned, for instance, TensorFlow. You know that down the road there's going to be some other tooling, some other open source project that's going to take hold, and your customers are going to say, "I want that." You've got to then integrate that, or you have to choose whether or not to. If it's a super heavy lift, you might not be able to do it, or do it in time to hit the market. If you architected your system to be able to accommodate that. Future proof is the term everybody uses, so have you done? How have you done that? I'm sure API's are involved, but maybe you could add some color. >> Sure. So we are and our Data Science Experience and mission learning... It is a microservices based architecture, so we are completely dockerized, and we use Kubernetes under the covers for container dockerstration. And all these are tools that are used in The Valley, across different companies, and also in products across IBM as well. So some of these legacy products that you mentioned, we are actually using some of these newer methodologies to re-architect them, and we are dockerizing them, and the microservice architecture actually helps us address issues that we have today as well as be open to development and taking newer methodologies and frameworks into consideration that may not exist today. So the microservices architecture, for example, TensorFlow is something that you brought in. So we can just pin up a docker container just for TensorFlow and attach it to our existing Data Science Experience, and it just works. Same thing with other frameworks like XGBoost, and Kross, and Scikit-Learn, all these are frameworks and libraries that are coming up in open source within the last, I would say, a year, two years, three years timeframe. Previously, integrating them into our product would have been a nightmare. We would have had to re-architect our product every time something came, but now with the microservice architecture it is very easy for us to continue with those. >> We were just talking to Daniel Hernandez a little bit about the Hortonworks relationship at high level. One of the things that I've... I mean, I've been following Hortonworks since day one when Yahoo kind of spun them out. And know those guys pretty well. And they always make a big deal out of when they do partnerships, it's deep engineering integration. And so they're very proud of that, so I want to come on to test that a little bit. Can you share with our audience the kind of integrations you've done? What you've brought to the table? What Hortonworks brought to the table? >> Yes, so Data Science Experience today can work side by side with Horton Data Platform, HDP. And we could have actually made that work about two, three months back, but, as part of our partnership that was announced back in June, we set up drawing engineering teams. We have multiple touch points every day. We call it co-development, and they have put resources in. We have put resources in, and today, especially with the release that came out on October 30th, Data Science Experience can authenticate using secure notes. That I previously mentioned, and that was a direct example of our partnership with Hortonworks. So that is phase one. Phase two and phase three is going to be deeper integration, so we are planning on making Data Science Experience and a body management pact. And so a Hortonworks customer, if you have HDP already installed, you don't have to install DSX separately. It's going to be a management pack. You just spin it up. And the third phase is going to be... We're going to be using YARN for resource management. YARN is very good a resource management. And for infrastructure as a service for data scientist, we can actually delegate that work to YARN. So, Hortonworks, they are putting resources into YARN, doubling down actually. And they are making changes to YARN where it will act as the resource manager not only for the Hadoop and Spark workloads, but also for Data Science Experience workloads. So that is the level of deep engineering that we are engaged with Hortonworks. >> YARN stands for yet another resource negotiator. There you go for... >> John: Thank you. >> The trivia of the day. (laughing) Okay, so... But of course, Hortonworks are big on committers. And obviously a big committer to YARN. Probably wouldn't have YARN without Hortonworks. So you mentioned that's kind of what they're bringing to the table, and you guys primarily are focused on the integration as well as some other IBM IP? >> That is true as well as the notes piece that I mentioned. We have a notes commenter. We have multiple notes commenters on our side, and that helps us as well. So all the notes is part of the HDP package. We need knowledge on our side to work with Hortonworks developers to make sure that we are contributing and making end roads into Data Science Experience. That way the integration becomes a lot more easier. And from an IBM IP perspective... So Data Science Experience already comes with a lot of packages and libraries that are open source, but IBM research has worked on a lot of these libraries. I'll give you a few examples: Brunel and PixieDust is something that our developers love. These are visualization libraries that were actually cooked up by IBM research and the open sourced. And these are prepackaged into Data Science Experience, so there is IBM IP involved and there are a lot of algorithms, mission learning algorithms, that we put in there. So that comes right out of the package. >> And you guys, the development teams, are really both in The Valley? Is that right? Or are you really distributed around the world? >> Yeah, so we are. The Data Science Experience development team is in North America between The Valley and Toronto. The Hortonworks team, they are situated about eight miles from where we are in The Valley, so there's a lot of synergy. We work very closely with them, and that's what we see in the product. >> I mean, what impact does that have? Is it... You know, you hear today, "Oh, yeah. We're a virtual organization. We have people all over the world: Eastern Europe, Brazil." How much of an impact is that? To have people so physically proximate? >> I think it has major impact. I mean IBM is a global organization, so we do have teams around the world, and we work very well. With the invent of IP telephoning, and screen-shares, and so on, yes we work. But it really helps being in the same timezone, especially working with a partner just eight miles or ten miles a way. We have a lot of interaction with them and that really helps. >> Dave: Yeah. Body language? >> Yeah. >> Yeah. You talked about problems. You talked about issues. You know, customers. What are they now? Before it was like, "First off, I want to get more data." Now they've got more data. Is it figuring out what to do with it? Finding it? Having it available? Having it accessible? Making sense of it? I mean what's the barrier right now? >> The barrier, I think for data scientist... The number one barrier continues to be data. There's a lot of data out there. Lot of data being generated, and the data is dirty. It's not clean. So number one problem that data scientist have is how do I get to clean data, and how do I access data. There are so many data repositories, data lakes, and data swamps out there. Data scientist, they don't want to be in the business of finding out how do I access data. They want to have instant access to data, and-- >> Well if you would let me interrupt you. >> Yeah? >> You say it's dirty. Give me an example. >> So it's not structured data, so data scientist-- >> John: So unstructured versus structured? >> Unstructured versus structured. And if you look at all the social media feeds that are being generated, the amount of data that is being generated, it's all unstructured data. So we need to clean up the data, and the algorithms need structured data or data in a particular format. And data scientist don't want to spend too much time in cleaning up that data. And access to data, as I mentioned. And that's where Data Science Experience comes in. Out of the box we have so many connectors available. It's very easy for customers to bring in their own connectors as well, and you have instant access to data. And as part of our partnership with Hortonworks, you don't have to bring data into Data Science Experience. The data is becoming so big. You want to leave it where it is. Instead, push analytics down to where it is. And you can do that. We can connect to remote Spark. We can push analytics down through remote Spark. All of that is possible today with Data Science Experience. The second thing that I hear from data scientist is all the open source libraries. Every day there's a new one. It's a boon and a bane as well, and the problem with that is the open source community is very vibrant, and there a lot of data science competitions, mission learning competitions that are helping move this community forward. And it's a good thing. The bad thing is data scientist like to work in silos on their laptop. How do you, from an enterprise perspective... How do you take that, and how do you move it? Scale it to an enterprise level? And that's where Data Science Experience comes in because now we provide all the tools. The tools of your choice: open source or proprietary. You have it in here, and you can easily collaborate. You can do all the work that you need with open source packages, and libraries, bring your own, and as well as collaborate with other data scientist in the enterprise. >> So, you're talking about dirty data. I mean, with Hadoop and no schema on, right? We kind of knew this problem was coming. So technology sort of got us into this problem. Can technology help us get out of it? I mean, from an architectural standpoint. When you think about dirty data, can you architect things in to help? >> Yes. So, if you look at the mission learning pipeline, the pipeline starts with ingesting data and then cleansing or cleaning that data. And then you go into creating a model, training, picking a classifier, and so on. So we have tools built into Data Science Experience, and we're working on tools, that will be coming up and down our roadmap, which will help data scientist do that themselves. I mean, they don't have to be really in depth coders or developers to do that. Python is very powerful. You can do a lot of data wrangling in Python itself, so we are enabling data scientist to do that within the platform, within Data Science Experience. >> If I look at sort of the demographics of the development teams. We were talking about Hortonworks and you guys collaborating. What are they like? I mean people picture IBM, you know like this 100 plus year old company. What's the persona of the developers in your team? >> The persona? I would say we have a very young, agile development team, and by that I mean... So we've had six releases this year in Data Science Experience. Just for the on premises side of the product, and the cloud side of the product it's got huge delivery. We have releases coming out faster than we can code. And it's not just re-architecting it every time, but it's about adding features, giving features that our customers are asking for, and not making them wait for three months, six months, one year. So our releases are becoming a lot more frequent, and customers are loving it. And that is, in part, because of the team. The team is able to evolve. We are very agile, and we have an awesome team. That's all. It's an amazing team. >> But six releases in... >> Yes. We had immediate release in April, and since then we've had about five revisions of the release where we add lot more features to our existing releases. A lot more packages, libraries, functionality, and so on. >> So you know what monster you're creating now don't you? I mean, you know? (laughing) >> I know, we are setting expectation. >> You still have two months left in 2017. >> We do. >> We do not make frame release cycles. >> They are not, and that's the advantage of the microservices architecture. I mean, when you upgrade, a customer upgrades, right? They don't have to bring that entire system down to upgrade. You can target one particular part, one particular microservice. You componentize it, and just upgrade that particular microservice. It's become very simple, so... >> Well some of those microservices aren't so micro. >> Vikram: Yeah. Not. Yeah, so it's a balance. >> You're growing, but yeah. >> It's a balance you have to keep. Making sure that you componentize it in such a way that when you're doing an upgrade, it effects just one small piece of it, and you don't have to take everything down. >> Dave: Right. >> But, yeah, I agree with you. >> Well, it's been a busy year for you. To say the least, and I'm sure 2017-2018 is not going to slow down. So continue success. >> Vikram: Thank you. >> Wish you well with that. Vikram, thanks for being with us here on theCUBE. >> Thank you. Thanks for having me. >> You bet. >> Back with Data Science For All. Here in New York City, IBM. Coming up here on theCUBE right after this. >> Cameraman: You guys are clear. >> John: All right. That was great.

Published Date : Nov 1 2017

SUMMARY :

Brought to you by IBM. Good to see you. Good to see you too. about that too if you would. and be able to do collaboration How can you help us understand that? and we are investing in such a way, You know that down the and attach it to our existing One of the things that I've... And the third phase is going to be... There you go for... and you guys primarily are So that comes right out of the package. The Valley and Toronto. We have people all over the We have a lot of interaction with them Is it figuring out what to do with it? and the data is dirty. You say it's dirty. You can do all the work that you need with can you architect things in to help? I mean, they don't have to and you guys collaborating. And that is, in part, because of the team. and since then we've had about and that's the advantage of microservices aren't so micro. Yeah, so it's a balance. and you don't have to is not going to slow down. Wish you well with that. Thanks for having me. Back with Data Science For All. That was great.

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Carey James, Jason Schroedl, & Matt Maccaux | Big Data NYC 2017


 

>> Narrator: Live from Midtown Manhattan, it's theCUBE, covering BigData New York City 2017 Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Hey, welcome back everyone, live in New York, it's theCUBE coverage, day three of three days of wall-to-wall coverage of BigData at NYC, in conjunction with Strata Data right around the corner, separate event than ours, we've been covering. It's our eighth year. We're here expanding on our segment we just had with Matt from Deli EMC on, really on the front lines consultant, we've got Jason from BlueData, and Casey from BlueTalon, two separate companies but the blue in the name, team blue. And of course, Matt from Dell EMC, guys, welcome back to theCUBE and let's talk about the partnerships. I know you guys have a partnership, Dell EMC leads the front lines mostly with the customer base you guys come in with the secret sauce to help that solution which I want to get to in a minute, but the big theme here this week is partnerships. And before we get into the relationship that you guys have, I want you to talk about the changes in the ecosystem, because we're seeing a couple key things. Open source, one, and it's winning, continues to grow, but the Linux Foundation pointed out the open source that we cover that exponential growth is going to be in open-source software. You can see from 4 lines of code to billions in the next 10 years. So more onboarding, so clear development path. Ecosystems have work. Now they're coming into the enterprise with suppliers, whether it's consulting, it's front-end, or full stack developers coming together. How do you see ecosystems playing in both the supplier side and also the customer side? >> So we see from the supplier side, right, and from the customer side as well, and it kind of drives both of those conversations together is that you had the early days of I don't want vendor lock-in, right, I want to have a disparate virtual cornucopia of tools in the marketplace, and then they were, each individual shop was trying to develop those and implement those on their own. And what you're now seeing is that companies still want that diversity in the tools that they utilize, and that they work with, but they don't want that, the complication of having to deliver all those tools themselves, and so they're looking more for partners that can actually bring an ecosystem to the table where it's a loose coupling of events, but that one person actually has the forefront, has the customer's best interest in mind, and actually being able to drive through those pieces. And that's what we see from a partnership, why we're driving towards partnerships, 'cause we can be a point solution, we can solve a lot of pieces, but by bringing us as a part of an ecosystem and with a partner that can actually help deliver the customer and business value to the customer, that's where we're starting to see the traction and the movement and the wins for us as an organization. >> BlueData, you guys have had very big successes, big data as a service, docker containers, this is the programmer's nirvana. Infrastructure plus code, that's the DevOps ethos going mainstream. Your thoughts on partnering, 'cause you can't do it alone. >> Yeah, I mean, for us, speaking of DevOps, and we see our software platform provides a solution for bringing a DevOps approach to data science and big data analytics. And it's much more streamlined approached, an elastic and agile approach to big data analytics and data science, but to your point, we're partnered with Dell EMC because they bring together an entire solution that delivers an elastic platform for secure multi-tenant environments for data science teams and analytics teams for a variety of different open source tool sets. So there is a large ecosystem of open source tools out there from Hadoop to Spark to Kafka to a variety of different data science, machine learning and deep learning tool sets out there, and we provide through our platform the ability to dockerize all of those environments, make them available through self-service to the data science community so they can get up and running quickly and start building their models and running their algorithms. And for us, it's on any infrastructure. So, we work closely with Dell EMC to run it on Isilon and their infrastructure, Dell-powered servers, but also you can run it in a hybrid cloud architecture. So you could run it on Azure and now GCP, and AWS. >> So this is the agility piece for the developer. They get a lot of agility, they get their security. Dell EMC has all the infrastructure side, so you got to partner together. Matt, pull this together. The customer doesn't want, they want a single pane of glass, or however you want to look at it, they don't want to deal with the nuances. You guys got to bring it all together. They want it to work. Now the theme I hear at BigData New York is integration is everything, right, so, if it doesn't integrate, the plumbings not working. How important is it for the customer to have this smooth, seamless experience? >> It's critical for them to, they have to be able to believe that it's going to be a seamless experience, and these are just two partners in the ecosystem. When we talk to enterprise customers, they have other vendors. They have half a dozen or a dozen other vendors solving big data problems, right? The Hadoop analytic tools, on and on and on. And when they choose a partner like us, they want to see that we are bringing other partners to the table that are going to complement or enhance capabilities that they have, but they want to see two key things. And we need to see the same things as well when we look at our partnerships. We want to see APIs, we want to see open APIs that are well-documented so that we know these tools can play with each other, and two, these have to be organizations we can work with. At the end of the day, a customer does business with Dell EMC because they know we're going to stand behind whatever we put in front of them. >> John: They get a track record too, you're pretty solid. >> Yep, it is-- >> But I want to push on the ecosystem, not you guys, it's critical, but I mean one thing that I've seen over my 30 years in the enterprise is ecosystems, you see bullshit and you see real deal, right, so. A lot of customers are scared, now with all this FUD and new technology, it's hard to squint through what the BS is in an ecosystem. So how do you do ecosystems right in this new market? 'Cause like you said, it's not API, that's kind of technical, but philosophy-wise you can't do the barney deals, you got Pat Gelsinger standing up on stage at VMworld, basically flew down to stand in front of all the customers of VMworld's customers and said, we're not doing a barney deal. Now, he didn't say barney deals, that's our old term. He said, it's not an optical deal we're doing with VMware. We got your back. He didn't say that, but that's my interpretation, that's what he basically said. The CEO of AWS said that. That's a partner, you know what I'm saying? So, some deals are okay we got a deal on paper, what's the difference, how do you run an ecosystem, in your opinion? >> Yeah, it's not trivial. It's not an easy thing. It takes an executive, at that level, it takes a couple of executives coming together-- >> John: From the top, obviously. >> Committing, it's not just money, it's reputation, right? If you're at that level, it's about reputation which then trickles down to the company's reputation, and so within the ecosystem, we want to sort of crawl, walk, run. Let's do some projects-- >> So you're saying reputation in communities is the number one thing. >> I think so, people are not going to go, so you will always have the bleeding edge. Someone's going to go play with a tool, they're going to see if it works-- >> Wow, reputation's everything. >> Yeah. If it fails, they're going to tell, what is the saying, if something fails, if something bad happens you tell twelve people-- >> All right, so give them a compliment. What's BlueTalon do great for you guys? Explain their talent in the ecosystem. >> So BlueTalon's talent in the ecosystem, other than being just great people, we love Carey, is that they-- >> I'll get you to say something bad about him soon, but give him the compliment first. >> They have simplified the complexity of doing security, policy and role-based security for big data. So regardless of where your data lives, regardless of if it's Hadoop, Spark, Flink, Mongo, AWS, you define a policy once. And so if I am in front of the chief governance officer, my infrastructure doesn't have a value problem to them, but theirs does, right? The legal team, when we have to do proposals, this is what gets us through the legal and compliance for GDPR in this, it's that centralized control that is so critical to the capability we provide for big data. If you sprawl your data everywhere, and we know data sprawls everywhere-- >> So you can rely on them, these guys. >> Absolutely. >> All right, BlueData, give them a compliment, where do they fit? >> So they have solved the problem of deploying containers, big data environments, in any cloud. And the notion of ephemeral clusters for big data workloads is actually really, really hard to solve. We've seen a lot of organizations attempt to do this, we see frameworks out there, like Kupernetes, that people are trying to build on. These guys have fixed it. We have gone through the most rigorous security audits at the biggest banks in the world, and they have signed off because of the network segmentation and the data segmentation, it just works. >> I think I'm running a presidential debate, now you got to say something nice about him. No, I mean, Dell EMC we know what these guys do. But for you guys, I mean, how big is BlueTalon, company-wise? I mean, you guys are not small but you're not massive either. >> We're not small, but we're not massive, right. So, we're probably around 40 resources global, and so from our perspective, we're-- >> John: That's a great deal, working with a big gorilla in Dell EMC, they got a lot of market share, big muscle? >> Exactly, and so for us, like we talked about earlier, right, the big thing for us is ecosystem functions. We do what we do really well, right, we build software that does control unified access across multiple platforms as well as multiple distributions whether it be private cloud, on-prem, or public cloud, and for us, again, it's great that we have the software, it's great that we can do those things, but if we can't actually help customers use that software to deliver value, it's useless. >> Do you guys go to the market together, do you just hold hands in front of the customer, bundle products? >> No, we go to market together, so we actually, we work, a lot of our team in enablement is not enabling our customers, it is enabling Dell EMC on the use of our software and how to do that. So we actually work with Dell EMC to train and work-- >> So you're a tight partner. There's certification involved, close relationships, you're not mailing it in. >> And then we're also involved with the customer side as well, so it's not like we go, okay great, now it's sold, we throw up our hands and walk away. >> John: Well, they're counting on you that. >> They're counting on us for the specific pieces, but we're also working with Dell EMC so that we can get that breadth right in their reach, so that they can actually go confidently to their customers and actually understand where we fit and when we don't fit. Because we're not everything to everybody, right, and so they have to understand those pieces to be able to know when that works right and how the best practices are. And so again, we're 40 people, they're, I forget, there were 80,000 at one point? Maybe even more than that? But even in the services arm, there's several thousands of people in the-- >> What's the whole point of ecosystems you're getting at here? Point at the critical thing. You've got a big piece of the puzzle, it's not just they're bundling you in. You're an active part of that, and it's an integration world right, so he needs to rely on you to integrate with his systems. >> Yeah, we have to integrate with the other parts of the ecosystem too, so it really is a three-way integration on this perspective where they do what they do really well, we do what we do and they're complementary to each other, but without the services and the glue from Dell EMC-- >> So when you bring Dell EMC into the deals too? >> We do, so we bring Dell EMC into deals, and Dell EMC sells us through a reseller agreement with them so we actually help jointly either bring them to a deal we've already found, we'll bring services to them, or we'll actually go out and do joint development of customers. So we actually come out and help with the sales process and cycles to actually understand is there a fit or is there not a fit? So, it's not a one-size-fits-all, it's not just a, yes we got something on paper that we can sell you and we'll sell you every once in a while, it really is a way to develop an ecosystem to deliver value to the customer. >> All right, so let's talk about the customer mindset real quick. When you, are they, how far along on them, I really don't know much 'cause I'm really starting to probe in this area, how savvy are they to the partnership levels? I mean, you disclose it, you're transparent about it, but I mean, are customers getting that the partnering is very key? I mean, are they drilling, asking tough questions, are you kind of getting them educated one way, are they savvy about it? They may have been doing partners in house, but remember the enterprise had a generation of down-to-the-bone cutting, outsource everything, consolidation, and then you know, go back around 2010, the uplift on reinvestment hit, so we're kind of in this renaissance right now. So, thoughts? >> The partnership is actually the secret sauce that's part of our sales cycle. When we talk about big data outcomes and enabling self-service, customers assume oh, okay, you guys built some software, you've got some hardware, and then when we double-click into how we make this capable, we say oh, well we partner with BlueTalon and BlueData, and this other, and they go, wait a minute, that's not your software? No, no, we didn't build that. We have scoured the market and we've found partners that we work with and we trust, and all of a sudden you can see their shoulders relax and they realize that we're not just there to sell them more kit. We're actually there to help them solve their problems. And it is a game changer, because they deal with vendors every day. Software Vendor X, Software Vendor Y, Hardware Vendor Z, and so to have a company that they have good relationships with already bring more capabilities to them, the guard comes down and they say okay, let's talk about how we can make this work. >> All right, so let's get to the meat of the partnership, which I want to get to 'cause I think that's fundamental. Thanks for sharing perspective on the community piece. We're being on it, we've been doing, we're a community brand ourselves. We're not a close guard, we're not about restricting and censoring people at events, that's not what we're about. So you guys know that, so appreciate you commenting on the community there. The Elastic Data Platform you guys are talking about, it's a partnership deal. You provide an EPIC software, you guys providing some great security in there. What is it about, what's the benefit? So it's you're leading them to product, take a minute to explain the product and then the roles. >> Yeah, so the Elastic Data Platform is a capability, a set of capabilities that is meant to help our enterprise customers get to that next level of self-service. Data science as a service, and do that on any cloud with any tools in a security-controlled manner. That's what Elastic Data Platform is. And it's meant to plug in to the customer's existing investments and their existing tools and augment that, and through our services arm, we tie these technologies together using their open APIs, that's why that's so critical for us, and we bring that value back to our customers. >> And you guys are providing the EPIC software? What is EPIC software? I mean, I love epic software, that's an epic, I hope it's not an epic fail, so an epic name, but epic-- >> Elastic Private Instant Clusters, it's actually an acronym for what it stands for, that is what it provides for our customers. >> John: So you're saying that EPIC stands for-- >> Elastic Private Instant Clusters. So it can run in a private cloud environment on your on-prem infrastructure, but as I said before, it can run in a hybrid architecture on the public cloud as well. But yeah, I mean, we're working closely with the Dell EMC team, they're an investor, we work closely with their services organization, with their server organization, the storage organization, but they really are the glue that brings it all together. From services to software to hardware, and provides the complete solution to the customers. So, as I think Matt-- >> John: Multi-tenancy is a huge deal, multi-tenancy's a huge deal. >> Absolutely, yeah. Also the ability to have logical isolation between each of those different tenants for different data science teams, different analyst teams, you know, that's particularly at large financial services organizations like Barclays, you spoke yesterday, Matt alluded to earlier. They talked about the need to support a variety of different business units who each have their own unique use cases, whether it's batch processing with Hadoop or real-time streaming and fast data with Spark, Kafka, and NoSQL Database, or whether it's deep learning, machine learning. Each of those different tenants has different needs, and so you can spin up containers using our solution for each of those tenants. >> John: Yeah, that's been a big theme this week too, and so many little things, this one relates to this one, is the elastic nature of how people want to manage the provisioning of more resource. So, here's what we see. They're using collective intelligence, data, hey, they're data science guys, they figured it out! Whatever the usage is, they can do a virtual layer if you will, and then based upon the use they can then double down. So let the users drive this real collaborative, that seems to the a big theme, so this helps there. The other theme has been the centralized, this is the GDPR hanging over one's head, but the, even though that's more of threat and it's a gun to the head, it's the hammer or the guillotine, however you look at it, there's more of enablement around centralization, so it's not just the threat of that, it's other things that are benefiting. >> Right, it's more than just the threat of the GDPR and being compliant with those perspectives, right? The other big portion of this is, if you want to do, you do want to provide self-service. So the key to self-service is that's great, I can create an environment, but if it takes me a long time to get data to that environment to actually be able to utilize it or protect the data that's in that environment by having to rewrite policies from a different place, then you don't get the benefit right, the acceleration of the self-service. So having centralized policies of distributed enforcements gives you that elastic ability, right? Again, we can deploy the central engines again on-premises, but you can protect data that's in the cloud or protect data that's in a private cloud, so as companies move data for their different workloads, we can put the same protections with them and it goes immediately with them, so you don't have to manage it in multiple places. It's not like, oh, did I remember to put that rule over in this system? Oh, no I didn't, oh and guess what just happened to me? You know, I did get smacked with a big fine because I didn't, I wasn't compliant. So compliance-- >> How about Audit, too? I mean, are you checking the Audit side too? >> Yeah, so Audit's a great portion of that, and we do Audit for a couple of reasons. One is to make sure that you are compliant, but two is to make sure you actually have the right policies defined. Are people accessing the data the way you expect them to access that data? So that's another big portion of us and what we do from an audit perspective is that data usage lineage, and we actually tell you what the customer, what the user was trying to do. So if a customer's trying to access the data you see a large group trying to access a certain set of data but they're being denied access to it, now you can look and say, is that truly correct? Do I want them not being-- >> John: Well, Equifax, that thing was being phished out over months and months and months. Not just four, that thing has been phished over 10 times. In fact, state-sponsored actors were franchises of that organization. So, they were in the VPN, so it's not even, so you, so this is where the issues, okay, let's just say that happened again. You would have flagged it. >> We flag it. >> You would have seen the pattern access and said, okay, a lot of people cleaning us out. >> Yep, while it's happening. Right, so you get to see that usage, the lineage of the usage of the data, right, so you get to see that pattern as well. Not only who's trying to access, all right, 'cause protecting the perimeter is, as we all know, is no longer viable. So we actually get to watch the usage of the, the usage pattern so you can detect an anomaly in that type of system, as well as you can quickly change policies to shut down that gap, and then watch to see what happens, see who's continuing to try to hit it. >> Well, it's been a great conversation. Love that you guys are on and great to see the Elastic Data Platform come together through the partnerships, again. As you know, we're really passionate about highlighting and understanding more about the community dynamic as it becomes more than just socialization, it's a business model to the enterprise, as it was in open source. We'll be covering that. So I'd like to go around the panel here just to end this segment. Share something that someone might not know what's going on in industry that you want to point out, that's an observation, an anecdote that hasn't been covered, hasn't been serviced, it could be a haymaker, it could be something anecdotal, personal observation. In the big data world, BigData NYC this week or beyond, what should people know about that may or may not be covered out there that's happened that they should know about? >> Well, I think this one's, people pretty much should know about this one, right, but four or five years ago Hadoop was going to replace everything in the world. And two, three years ago the RDBMS's groups were like, Hadoop will never make it out of the science fair project. Right, we're in a world now where that's no longer true. It's somewhere in between. Hadoop is going to remain, and they're going to be continued, and the RDBMS is also going to continue. So you need to look at ecosystems that can actually allow you to cover both sides of that coin, which we're talking about here, is those types of tools are going to continue together forward. So you have to look at your entire ecosystem and move away from siloed functions to how you actually look at an entire data protection in data usage on environment. >> Matt? >> I would say that the technology adoption in the enterprise is outstripping the organization's ability to keep up with it. So as we deploy new technologies, tools, and techniques to do all sorts of really amazing things, we see the organization lagging in its ability to keep up. And so policies and procedures, operating models, whatever you want to call that, put it under the data governance umbrella, I suppose. If those don't keep up, you're going to end up with just an organization that is mismatched with the technology that is put into place, and ultimately you can end up in a massive compliance problem. Now, that's worst case. But even in best case, you're going to have a really inefficient use of your resources. My favorite question to ask organizations, so let's say you could put a timer on one of the data science sandboxes. So what happens when the timer goes off and the data science is not done? And you've got a line of people waiting for resources, what do you do? What is, how does the organization respond to that? It's a really simple question, but the answer's going to be very nuanced. So if that's the policy, that's the operating model stuff that we're talking about that we've got to think about when we enable self-service and self-security, those things have to come hand-in-hand. >> That's the operational thinking that needs to come through. >> Okay, Jason? >> Yeah, I think even for us, I mean this has been happening for some time now, but I think there still is this notion that the traditional way to deploy Hadoop and other big data workloads on prem is bare metal, and that's the way it's always been done. Or, you can run it in the cloud. But I think what we're seeing now, what we've seen evolve over the past couple of years is you can run your on-prem workloads using docker containers in a containerized environment. You can have this cloud-like experience on-prem but you can also provide the ability to be able to move those workloads, whether they're on-prem or in the cloud. So you can have this hybrid approach and multi-cloud approach. So I think that's fundamentally changing, it's a new dynamic, a new paradigm for big data, either on-prem or in the cloud. It doesn't have to be on bare metal anymore. And we get the same, we've been able to get-- >> It's on-prem, people want on-prem, that's where the action is, and cloud no doubt, but right now it's the transition. Hybrid cloud's definitely going to be there. I guess my observation is the tool shed problem. You know, I said earlier all day, you don't want to have a tool shed full of tools you don't use anymore or buy a hammer that wants to turn into a lawn mower 'cause the vendor changed, pivoted. You got to be careful what you buy, the tools, so don't think like a tool. Think like a platform. And I think having a platform mentality, understanding the system, or operating environment as you were getting to, I think really is a fundamental exercise that most decision makers think about. 'Cause again, your relationship with the Elastic Data Platform proves that this operating environment's evolving, it's not about the tool. The tool has to be enabled, and if the tool is enabled into the platform it should have a data model that falls into place, no one should have to think about it, you get the compliance, you get the docker container, so don't buy too many tools. If you do, make sure they're clean and in a clean tool shed! You got a lawnmower, I guess that's the platform. Bad analogy, but you know, I think tools has been the rage in this market, and now I think platforming it is something that we're seeing more of. So guys, thanks so much, appreciate it. Elastic Data Platform by Dell EMC, with the EPIC Platform from BlueData, and BlueTalon providing the data governance and compliance, great stuff, I'm certain the GDPR, BlueTalon, you guys got a bright future, congratulations. All right, more CUBE coverage after this short break, live from New York, it's theCUBE. 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Published Date : Sep 29 2017

SUMMARY :

Brought to you by SiliconANGLE Media And before we get into the relationship that you guys have, the complication of having to deliver all those tools that's the DevOps ethos going mainstream. the ability to dockerize all of those environments, so you got to partner together. that it's going to be a seamless experience, but philosophy-wise you can't do the barney deals, It takes an executive, at that level, and so within the ecosystem, is the number one thing. so you will always have the bleeding edge. If it fails, they're going to tell, what is the saying, What's BlueTalon do great for you guys? but give him the compliment first. critical to the capability we provide for big data. and the data segmentation, it just works. I mean, you guys are not small and so from our perspective, we're-- Exactly, and so for us, like we talked about earlier, on the use of our software and how to do that. So you're a tight partner. we throw up our hands and walk away. and so they have to understand those pieces right, so he needs to rely on you the sales process and cycles to actually understand but I mean, are customers getting that the partnering and all of a sudden you can see their shoulders relax All right, so let's get to the meat of the partnership, Yeah, so the Elastic Data Platform is that is what it provides for our customers. and provides the complete solution to the customers. John: Multi-tenancy is a huge deal, and so you can spin up containers or the guillotine, however you look at it, So the key to self-service is and we actually tell you what the customer, so this is where the issues, You would have seen the pattern access and said, the usage pattern so you can detect an anomaly Love that you guys are on and great to see and the RDBMS is also going to continue. but the answer's going to be very nuanced. that needs to come through. and that's the way it's always been done. You got to be careful what you buy, the tools,

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Jacque Istok, Pivotal | BigData NYC 2017


 

>> Announcer: Live from midtown Manhattan, it's the Cube, covering big data New York City 2017. Brought to you by Silicon Angle Media and its ecosystem sponsors. >> Welcome back everyone, we're here live in New York City for the week, three days of wall to wall coverage of big data NYC, it's big data week here in conjunction with Strata Adup, Strata Data which is an event running right around the corner, this is the Cube, I'm John Furrier with my cohost, Peter Burris, our next guest Jacque Istok who's the head of data at Pivotal. Welcome to the Cube, good to see you again. >> Likewise. >> You guys had big news we covered at VMware, obviously the Kubernetes craze is fantastic, you're starting to see cloud native platforms front and center even in some of these operational worlds like in cloud, data you guys have been here a while with Green Plum and Pivotal's been adding more to the data suite, so you guys are a player in this ecosystem. >> Correct. >> As it grows to be much more developer-centric and enterprise-centric and AI-centric, what's the update? >> I'd like to talk about a couple things, just three quick things here, one focused primarily on simplicity, first and foremost as you said, there's a lot of things going on on the cloud foundry side, a lot of things that we're doing with Kubernetes, etc., super exciting. I will say Tony Berge has written a nice piece about Green Plum in Zitinet, essentially calling Green Plum the best kept secret in the analytic database world. Why I think that's important is, what isn't really well known is that over the period of Pivotal's history, the last four and a half years, we focused really heavily on the cloud foundry side, on dev/ops, on getting users to actually be able to publish code. What we haven't talked about as much is what we're doing on the data side and I find it very interesting to repeatedly tell analysts and customers that the Green Plum business has been and continues to be a profitable business unit within Pivotal, so as we're growing on the cloud foundry side, we're continuing to grow a business that many of the organizations that I see here at Strata are still looking to get to, that ever forgotten profitability zone. >> There's a legacy around Green Plum, I'm not going to say they pivoted, pun intended, Pivotal. There's been added stuff around Green Plum, Green Plum might get lost in the messaging because it's been now one of many ingredients, right? >> It's true and when we formed Pivotal, I think there were 34 some different skews that we have now focused in on over the last two years or so. What's super exciting is again, over that time period, one of the things that we took to heart within the Green Plum side is this idea of extreme agile. As you guys know, Pivotal Labs being the core part of the Pivotal mission helps our customers figure out how to actually build software. We finally are drinking our own champagne and over the last year and a half of Green Plum R&D, we're shipping code, a complete data platform, we're shipping that on a cadence of about four to five weeks which again, a little bit unheard of in the industry, being able to move at that pace. We work through the backlog and what is also super exciting and I'm glad that you guys are able to help me tell the world, we released version five last week. Version five is actually the only parallel open source data platform that actually has native ANSI compliance SQL and I feel a little bit like I've rewound the clock 15 years where I have to actually throw in the ANSI compliance, but I think that in a lot of ways, there are SQL alternatives that are out there in the world. They are very much not ANSI compliant and that hurts. >> It's a nuance but it's table stakes in the enterprise. ANSI compliance is just, >> There's a reason you want to be ANSI compliant, because there's a whole swath of analytic applications mainly in the data warehouse world, that were built using ANSI compliant SQL, so why do this with version five? I presume it's got to have something to do with you want to start capturing some of those applications and helping customers modernize. >> That is correct. I think the SQL piece is one part of the data platform, of really a modern data platform. The other parts are again, becoming table stakes. Being able to do text analytics, we've backed Apache Solar within Green Plum, being able to do graph analytics or spatial analytics, anything from classifications, regressions, all of that, actually becomes table stakes and we feel that enterprises have suffered a little bit over the last five or six years. They've had this promise of having a new platform that they can leverage for doing interesting new things, machine learning, AI, etc. but the existing stuff that they were trying to do has been super, super hard. What we're trying to do is bridge those together and provide both in the same platform, out of the gate so that customers can actually use it immediately and I think one of the things we've seen is there's about 1000 to one SQL experienced individuals within the enterprise versus say Haduk experience in individuals. The other thing that I think is actually super important and almost bigger than everything else I talked about is we're the, a lot of the old school postgres deriviants of MBD databases forked their databases at some point in postgres's history, for a variety of reasons from licensing to when they started. Green Plum's no different. We forked right around eight dot too with this last release of version five, we've actually up leveled the postgres base within Green Plum's 8.3. Now in and of itself, it doesn't sound, >> What does that mean? >> We are now taking a 100% commitment both to open source and both to the postgres community. I think if you look at postgres today, in its latest versions, it is a full fledged, mission critical database that can be used anywhere. What we feel is that if we can bring our core engineering developments around parallelism, around analytics and combine that with postgres itself, then we don't have to implement all of the low level database things that a lot of our competitors have to do. What's unique about it is one, Green Plum continues to be open source, which again most of our competitors are not, two if you look at primarily what they're doing, nobody's got that level of commitment to the postgres community which means all of their resources are going to be stuck building core database technology, even building that ANSI SQL compliance in, which we'll get "for free" which will let us focus on things like machine learning, artificial intelligence. >> Just give a quick second and tell about the relevance of postgres because of the success, first of all it's massive, it's everywhere, but it's not going anywhere. Just give a quick, for the audience watching, what's the relevance of it. >> Sure like you said, it is everywhere. It is the most full featured, actual database in the open source community. Arguably my SQL has "more" market share, but my SQL projects that generally leverage them are not used for mission critical enterprise applications. Being able to have parity allows us not only to have that database technology baked into Green Plum, but it also gives us all of the community stuff with it. Everything from being able to leverage the most recent ODBC and JDBC libraries, but also integrations into everything from the post GIS travert for geospatial to being able to connect to other types of data sources, etc. >> It's a big community, shows that it's successful, but again, >> And it doesn't come in a red box. >> It does not come in a red box, that is correct. >> Which is not a bad thing. Look, postgres as a technology was developed a long time ago, largely in response to think about analytics and transaction, or analytics and operating applications might have actually come to and we're now living in a world where we can actually see the hardware and a lot of practices, etc. are beginning to find ways where this may start to happen. With Green Plum and postgres both MPP based, so your, by going to this, you're able to stay more modern, more up to date on all the new technology that's coming together to support these richer, more complex classes of applications. >> You're spot on, I suppose I would argue that postgres, I feel came up with as a response to Oracle in the past of, we need an open source alternative to Oracle, but other than that, 100% correct. >> There was always a difference between postgres and MySQL, MySQL always was okay, that's that, let's do that open source, postgres coming out of Berkeley and coming out of some other places, always had a slightly different notion of the types of problems it was going to take on. >> 100% correct, 100%. But to your question before, what does this all mean to customers, I think the one thing that version five really gives us the confidence to say is, and a lot of times I hate lobbing when the ball's out like this, but we welcome and embrace with open arms any terradata customers out there that are looking to save millions if not tens of millions of dollars on a modern platform that can actually run not only on premise, not only on bare metal, but virtually and off premise. We're truly the only MPP platform, the only open source MPP data platform that can allow you to build analytics and move those analytics from Amazon to Azure to back on prem. >> Talk about this, the terradata thing for a second, I want to get down and double click on that. Customers don't want to change code, so what specifically are you guys offering terradata customers specifically. With the release of version five, with a lot of the development that we've done and some of the partnering that we've done, we are now able to take without changing a line of code of your terradata applications, you load the data within the Green Plum platform, you can point those applications directly to Green Plum and run them unchanged, so I think in the past, the reticence to move to any other platform was really the amount of time it would take to actually redevelop all of the stuff that you had. We offer an ability to go from an immediate ROI to a platform that again, bridges that gap, allows you to really be modern. >> Peter, I want to talk to you about that importance that we just said because you've been studying the private cloud report, true private cloud which is on premises, coming from a cloud operating model, automating away undifferentiated labor and shipping that to differentiated labor, but this brings up what customers want in hybrid cloud and ultimately having public cloud and private cloud so hybrid sits there. They don't want to change their code basis, this is a huge deal. >> Obviously a couple things to go along with what Jacque said. The first thing is that you're right, people want the data to run where the data naturally needs to run or should run, that's the big argument about public versus hybrid versus what we call true private cloud. The idea that decreasing the workload needs to be located where the data, where it naturally should be located because of the physical, legal, regulatory, intellectual property attributes of the data, being able to do that is really really important. The other thing that Jacque said that goes right into this question John, is that ultimately in too many domains in this analytics world, which is fundamentally predicated on the idea of breaking data out of applications so that you can use it in new and novel and more value creating ways, is that the data gets locked up in a data warehouse. What's valuable in a data warehouse is not the hardware. It's the data. By providing the facility for being able to point an application at a couple of different data source including one that's more modern, or which takes advantage of more modern technology, that can be considerably cheaper, it means the shop can elevate the story about the asset and the asset here is the data and the applications that run against it, not the hardware and the system where the data's stored and located. One of the biggest challenges, we talked earlier just to go on for a second, we talked earlier with a couple of other guests about the fact that the industry still, what your average person still doesn't understand how to value data. How to establish a data asset and one of the reasons is because it's so constantly co-mingled with the underlying hardware. >> And actually I'd even further go on, I think the advent of some of these cloud data warehouses forgets that notion of being able to run it different places and provides one of the things that customers are really looking for which is simplicity. The ability to spin up a quick MPP SQL system within say Amazon for example, almost without a doubt, a lot of the business users that I speak to are willing to sacrifice capabilities within the platform which they are for the simplicity of getting up and going. One of the things that we really focused on in V5 is being able to give that same turnkey feel and so Green Plum exists within the Amazon marketplace, within the Azure marketplace, Google later this quarter, and then in addition to the simplicity, it has all of the functionality that is missing in those platforms, again, all the analytics, all the ability to reach out and federate queries against different types of data, I think it's exciting as we continue to progress in our releases, Green Plum has, for a number of years, had this ability to seamlessly query HGFS. Like a lot of the competitors, but HGFS isn't going away, neither is a generic object store like S3. But we continue to extend that to things like Spark for example, so now the ability to actually house your data within a data platform and seamlessly integrate with Spark back and forth, if you want to use Spark, use Spark, but somewhere that data needs to be materialized so that other applications can leverage it as well. >> But even then people have been saying well, if you want to put it on this disk, then put it on this disk. Given the question about Spark versus another database manager is a higher level conversation than many of the shops who are investing millions and millions and millions of dollars in their analytic application portfolio and all you're trying to do is, as I interpret it, is trying to say look, the value in the portfolio is the applications and the data. It's not the underlying elements. There's a whole bunch of new elements we can use, you can put it in the cloud, you can put it on premise if that's where the data belongs. Use some of these new and evolving technologies, but you're focused on how the data and the applications continue to remain valuable to the business over time and not the traditional hardware assets. >> Correct and I'll again leverage a notion that we get from labs, which is this idea of user centric design and so everything that we've been putting into the Green Plum database is around, ideally the four primary users of our system. Not just the analysts and not just the data scientists, but also the operators and the IT folks. That is where I'd say the last tenant of where we're going really is this idea of coopetition. I would, as the Pivotal Green Plum guy that's been around for 10 plus years, I would tell you very straight up that we are again, an open source MPP data platform that can rival any other platform out there, whether it's terradata, whether it's Haduke, we can beat that platform. >> Why should customers call you up? Why should they call you? There's all this other stuff out there, you got legacy, you got terradata, might have other things, people are knocking at my door, they're getting pounded with sales messages, buy me I'm better than the other guy. Why Pivotal data? >> The first thing I would say is, the latest reviews from Gardner for example, well actually let me rewind. I will easily argue that terradata has been the data warehouse platform for the last 30 years that everyone has tried to emulate. I'd even argue so much as that when Haduke came on the scene eight years ago, what they did was they changed the dynamics and what they're doing now is actually trying to emulate the terradata success through things like SQL on top of Haduke. What that has basically gotten us to is we're looking for a terradata replacement at Haduke like prices, that's what Green Plum has to offer in spades. Now, if you actually extend that just a little bit, I still recognize that not everybody's going to call us, there are still 200 other vendors out there that are selling a similar product or similar kinds of stories. What I would tell you in response to those folks is that Green Plum has been around in production for the last 10 plus years, we're a proven technology for solving problems, many of those are not. We work very well in this cooperative spirit of, Green Plum can be the end all be all, but I recognize it's not going to be the end all be all so this is why we have to work within the ecosystem. >> You have to, open source is dominating. At the Linux event, we just covered open source summit, 90% of software written will be open source libraries, 10% is where the value's being added. >> For sure, if you were to start up a new star up right now, would you go with a commercial product? >> No, just postgres database is good. All right final question to end the segment. This big data space that's now being called data, certainly Strata, Haduke is now Strata Data, just trying to keep that show going longer. But you got Microsoft Azure making a lot of waves going on right now with Microsoft Ignite, so cloud is into the play here, data's changed, so the question is how has this industry changed over the past eight years. You go back to 2010, I saw Green Plum coming prior to even getting bought out, but they were kicking ass, same product evolved. Where has the space gone? What's happened, how would you summarize it to someone who's walking in for the first year like hey back in the old days, we used to walk to school in the snow with no shoes on both ways. Now it's like get off my lawn you young developers. Seriously what is the evolution of that, how would you explain it? >> Again, I would start with terradata started the industry, by far and then folks like Netease and Green Plum came around to really give a lower cost alternative. Haduke came on the scene eight some years ago, and what I pride myself in being at Green Plum for this long and Green Plum implemented the map produced paradigm as Haduke was starting to build and as it continued to build, we focused on building our own distribution and SQL and Haduke, I think what we're getting down to is the brass tacks of the business is tired of technological science experiments and they just want to get stuff done. >> And a cost of ownership that's manageable. >> And sustainable. >> And sustainable and not in a spot where they're going to be locked into a single vendor, hence the open source. >> The ones that are winning today employed what strategy that ended up working out and what strategy didn't end up working out, if you go back and say, the people who took this path failed, people who took this approach won. What's the answer there? >> Clearly anybody who was an appliance that has long since drifted. I'd also say Green Plum's in this unique position where, >> An appliance too though. >> Well, pseudo appliance yes, I still have to respond to that, we were always software. >> You pivoted luckily. >> But putting that aside, the hardware vendors have gone away, all of the software competitors that we had have actually either been sunset, sold off and forgotten and so Green Plum, here we sit as the sole standard or person that's been around for the long haul. We are now seeing a spot where we have no competition other than the forgotten really legacy guys like terradata. People are longing to get off of legacy and onto something modern, the trick will be whether that modern is some of these new and upcoming players and technologies, or whether it really focuses on solving problems. >> What's the strategy with the winning strategy? Stick to your knitting, stick to what you know or was it more of, >> For us it was two fold, one it was continuing to service our customers and make them successful so that was how we built a profitable data platform business and then the other was to double down on the strategies that seemed to be interesting to organizations which were cloud, open source, and analytics and like you said, I talked to one of the folks over at the Air Force and he was mentioning how to him, data's actually more important than fuel, being able to understand where the airplanes are, where the fuel is, where the people are, where the missiles are etc., that's actually more important than the fuel itself. Data is the thing that powers everything. >> Data's currency of everything now, great Jacque thinks so much for coming on the Cube, Pivotal Data Platform, Data Suite, Green Plum now with all these other adds, that's great congratulations. Stay on the path helping customers, you can't lose. >> Exactly. >> The Cube here helping you figure out the big data noise, we're obviously in big data New York City event for our annual, the annual Cube Wikibon event, in conjunction with Strata Data across the street, more live coverage here for three days here in New York City I'm John Furrier, Peter Burris, we'll be back after this short break. (electronic music)

Published Date : Sep 27 2017

SUMMARY :

Brought to you by Silicon Angle Media Welcome to the Cube, good to see you again. to the data suite, so you guys analysts and customers that the Green Plum Green Plum might get lost in the messaging and over the last year and a half of Green Plum R&D, It's a nuance but it's table stakes in the enterprise. I presume it's got to have something to do with and provide both in the same platform, and both to the postgres community. of postgres because of the success, It is the most full featured, and operating applications might have actually come to in the past of, we need an open source alternative of the types of problems it was going to take on. MPP data platform that can allow you the reticence to move to any other platform and shipping that to differentiated labor, is that the data gets locked up in a data warehouse. all the ability to reach out and federate queries and the applications continue to remain valuable but also the operators and the IT folks. Why should customers call you up? I still recognize that not everybody's going to call us, At the Linux event, we just covered open source summit, in the snow with no shoes on both ways. and Green Plum implemented the map produced paradigm And sustainable and not in a spot where they're going to be the people who took this path failed, that has long since drifted. to respond to that, we were always software. But putting that aside, the hardware on the strategies that seemed to be interesting Stay on the path helping customers, you can't lose. for our annual, the annual Cube Wikibon event,

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Manish Goyal, IBM - IBM Fast Track Your Data 2017


 

>> Announcer: Live from Munich, Germany, it's theCUBE. Covering IBM, Fast Track Your Data, brought to you by IBM. >> We're back in Munich, Germany this is Fast Track Your Data and this is theCUBE, the leader in live tech coverage, we go out to the events. We extract a signal from the noise my name is Dave Vellante and I'm here with my co-host Jim Kobielus. We just came off of the main stage. IBM had a very choreographed, really beautiful, Kate Silverton was there of BBC Fame talking to various folks within the IBM community. IBM executives, practitioners, and quite a main stage production Jim. IBM always knows how to do it right. Manish Goyal here, he's the Director of Product Management for the Watson Data Platform. Something we covered on theCUBE extensively, that announcement last year in New York City. Manish welcome to theCUBE. >> Thank you for having me. >> Dave: So this is, it really was your signature moment back in last fall at Strata in New York City. We covered that, big announcement, lot of customers there. You guys demonstrated sort of the next generation of platform that you guys are announcing. >> Manish: That's right. >> So take us, bring us up to date. How's it going, where are we at, and what are you guys doing here? >> So, again thank you for having me. >> Dave: You're welcome. >> Let me take a minute to just let all the viewers know what is alternate about form. So the Watson Data Platform is our cloud analytics platform, and it's really three things. It's a set of composable data services, for ingest, analyze, processed. It's a set of tailor-made experiences for the different personas. Whether you are a data engineer, a business analyst, data scientist, or the steward. And connecting all of these, both of these is a set of data fabric, which is really the secret sauce. And think of this as being the governance layer that ensures that everything that we're doing, that everything that is being done by any of these personas is working on trusted data, and that the insights that are being generated can be trusted by the risk folks, the business folks, as they put the analytics into production. >> Dave: So just to review for our audience, there are a number of components to the Watson Data Platform. >> That's right, yep. >> Dave: There's the governance components you mentioned, there's the visualization, there's analytics. Now, many people criticized Watson Data Platform, they said oh it's just IBM putting a bunch of despaired products together, some acquisitions and then wrapping some services around it. When we talked to you guys in October, you said no, no, that's not the case. But can you affirm that? >> That is exactly right, that is not the case. It's not just us putting stuff together and calling it a new name, and think oh that's the platform, just a set of despaired services. That is absolutely not, and that's why I was emphasizing this common data fabric, right. I've got a couple of, let me sort of dive a little bit deeper into it. >> Sure, great. >> Manish: So the biggest problem that customers and data users in general complain about is, extremely hard to find data, right. The tools that they're working with are all siloed. So even if, you know, you and I are working on, you know our analytics projects, very hard for me to share what I'm working on with you, the environment that I am running on with you, et cetera. And this... The third piece is, a real issue with is the data that I'm working with trusted? Like can I actually believe that this is the best data that I can use, so that when I put something into production when I create my machine learning models I put them into my production environment. The risk guys are going to be fine with it, I'm going to be fine with it, I see the results that I'm getting. And so, getting this data fabric which is addressing these issues. One, it's addressing it first and foremost with a data catalog, a governance layer. So that it's very clear, irrespective, whether you're a data engineer, business analyst, data scientist or the data steward, from the CDO's office, you're all working off the same version of the truth, right. >> Jim: Manish is that something a DevOps platform, is it like DevOps for data science or for machine learning development or is it... How would you describe... Does that make sense? The automated release pipeline that's-- >> Manish: In a way yes. >> With the governance baked in? >> Yes, in a way that's one way to describe it. So that's one aspect right? Making sure that you're working with the trusted data, making it very easy to find the data, so that's sort of the governance aspect. The second piece that sort of really makes this a platform is that you're working off the same notion of a workspace, we call it a project. So, you may start out as a data engineer being asked yourself, take all these different data sources that are coming in and create and publish a data set that can be consumed for dashboarding, for data analysis whatever. And you're working on that in a project, now if you have a data science team that needs to be working on the same thing, you can just invite them to the same project. So they're working on the same thing, similarly to a business analyst, et cetera. And all of these results, and when we talk about governance it's not about just data sets, it's all analytical products. So it is the model that you're creating are being put back into the catalog and governed. Data flows-- >> It's model governance. >> Jim: Model governance, it's model governance? >> Exactly. >> And aiding governance. >> Manish: So it's a huge problem that customers have. I was just talking to a large insurance company yesterday, and they're question was, "What are you doing to make sure that I don't have to spend an enormous amount of time that I have to with the risk group, before I can put a model into production." Because they want complete lineage all the way back, saying "Okay you created this model, you're going to put it into production, whether it's for allowing credit card insurance, whatever your product is that you're selling. How do you make sure that there's no bias in the model that is created, can you show me the data set on which you trained it? And then when you re-trained it can you show me that data set?" So in case they're audited, that there's complete way to go back from the production model all the way back to the data set that was created. And which goes even further back from all the different data sources. Where it was cleansed, et cetera, the ETL, where it was published, and then picked up by data science team. So all of these things, putting it together with this data fabric. Governance being a huge, huge portion of that that goes across everything that we're doing. Giving these tailor-made experiences for the different business personas, oh sorry, the data personas, and just making it extremely simple for generating insights that can be trusted. So that is what we are trying to do with the Watson Data Platform. As, since last fall when we announced it, we have had a huge update on our data science experience, you heard a lot about that in the presentation this morning. As well as, all of our other cloud data services and the governance put forth. >> Dave: And that data science experience is embedded fundamental to the platform. >> It is, it is. >> Dave: You know I want to ask you about that. Because I don't know if you remember Jim and Manish, a few years ago, several years ago, Pivotal announced this thing called Chorus and it went, it was a collaboration platform and it really went nowhere. Now part of the reason it went nowhere was because it was early days, but also there wasn't the analytics solution underneath it. But a lot of people questioned, "Well do we really need to collaborate across those personas?" Again maybe they were immature at the time. So convince me that there's a need for that and that this is actually getting used in the world. >> There was an example, probably you've always seen the venn diagram or for data scientist, right? With all the different skills that they need, they are a unicorn, and there are no unicorns. It's extremely hard for our customers, in fact just finding really good data scientist is extremely hard. It's a very limited supply of that talent. So that's one thing right. So you can't find enough of these folks to scale out the level of analytics that is needed, if you want to use data for a comparative advantage. So that's one aspect right, of talent being a huge issue. The second aspect of it is you really do need specialized skill in data engineer. You don't want your PhD data scientist spending 60% of their time finding cleansing data. You have folks who really do that well and you want to enable them to work closely with the data science team. And you really do need business analyst who are the key to sort of understanding the business problem that needs to be solved, because that's where you always want to start any analytics product. What is it that you're trying to improve, or reduce cost on, or whatever your problem is that you're addressing. And so you really need, it is a team sport. You can't just do it without. Now if it is a team sport, how are these folks going to collaborate, right? And that is why, in all of our interactions with our customers and their data science teams. They absolutely love the collaboration features that we have put in, and we have put in a lot of effort in data science experience and the same collaboration features are actually going to extend across the portfolio of these experiences on the data platform. >> And the whole notion of personas is so fundamental to Watson Data Platform. And I'm wondering, is IBM evolving the range and variety of personas for which you're providing these experiences? And what I mean by that is, examples, we see more and more data science application development projects focusing on for example, chat bots. That involves human conversation, you need a bit more, possibly a persona, a computational linguist. Or cognitive IoT, like Watson, you know IoT, that's sensors, that's hardware devices maybe hardware engineers, hardware engineering experiences. You see what I'm getting at is that data science centric projects are increasingly moving from the totally virtual world, to being very much embedding in the physical world and the world of human guided, machine learning guided conversation. What are your thoughts about evolving the personas mix? >> So application, application developers, or the persona I actually missed when I was talking about this before, it's absolutely central because almost anything that the data science team is doing is going to create, at the end of the day, sort of create models. But the hope is that it's going to put into production system. And that job typically is the role of an application developer. Now, Jim you mentioned sort of, there's a lot of emphasis these days on conversational chat bots. And again, at the end of the day with data science projects you are in many ways, trying to improve the experience that you're giving your customers. Or personalizing the experience that you're giving your customers. A celebrity experience that Rob talked about this morning. And there are other personas involved in that sense, so to get a chat bot right, I mean there is data that you can obviously harvest and use to create that flow, an intelligence in chat bot. But there are elements where you do need a subject matter expert to curate that. To make sure that it doesn't seem robotic, that it does feel genuine. And so there is a role for a subject matter expert, we sort of collaborate with a business analyst role, or persona. But yes, all of these roles play an important part in sort of putting together the entire package. It just feels seamless, and that's why I sort of come back to saying that it is a team sport and if you do not enable the teams to work closely together, and enhance their productivity, you can go after all the data that's being generated and all the opportunity that data is presenting. And the prize is to gain a competitive advantage. >> Dave: One of the things Manish, you demonstrated last fall was this sort of, it was sort of a recommendation engine and very personalized. And it was quite a nice demo and it wasn't a fake demo from what I understood, it was real data. Can you share with us in the time we have remaining, just some of your favorite examples of how people are applying the Watson Data Platform and affecting business? >> Manish: Sure yeah so, I'll tell you a couple of examples. So I was actually in London earlier this week, meeting with a customer and they are using DSX, our data science experience, with a couple of utility companies. One is a water company, water utility company. And the problem that they're trying to solve is, they're supplying water in a hilly area and they want to optimize the power that they use to power the pumps to pump out water. Because it can be very expensive if the pumps are running all the time, et cetera. And so they're using data science experience to optimize when and how, and how long the pumps need to run to enable that the customers are happy with the level of water supply that they're getting and the force that they're getting it with. While the utility company is optimizing the expense in actually powering these things. So that's just a recent example that comes to mind. There are others, there's a logistics, huge logistics in transportation company who's using data science experience to optimize how the refrigeration of the storage units that are going all across the globe for transporting sort of food and other articles like that. How they can optimize the temperature of the goods that they're transporting, again to make sure that there's absolutely the minimum amount of wastage that occurs in the transportation process. But at the same time optimizing the cost that they incur, because all of that sort of shows up in the end product that you and I buy from retailers. >> Dave: And is there instrumentation in the field involved in that? Is that kind of a semi-IoT example? >> Absolutely, right, so in this case, actually both of these cases, in one case there are smart meters that are throwing out data every 15 minutes. In the other example of the logistics one, it is data that is almost streaming coming in. So in one case you can use batch processing, even though it's coming in at a 15 minute intervals, to predict out what you want to do. In the other case it's streaming data, which you want to analyze as it streams. >> Excellent, alright well exciting times here for you and your group. >> Absolutely >> Dave: Congratulations on getting the product out and getting it adopted. >> Thank you. >> Glad to see that. And thanks for coming on theCUBE. >> Manish: Thank you. Thanks for having me. >> Alright! >> Dave: Keep it right there everybody. Jim and I will be back, we're live from Munich, Germany, unscripted, bringing theCUBE to you. Bringing Fast Track Your Data. We'll be right back. (techno music)

Published Date : Jun 24 2017

SUMMARY :

brought to you by IBM. for the Watson Data Platform. platform that you guys are announcing. and what are you guys doing here? So the Watson Data Platform is our cloud analytics platform, Dave: So just to review for our audience, Dave: There's the governance components you mentioned, That is exactly right, that is not the case. Manish: So the biggest problem that customers Jim: Manish is that something a DevOps platform, So it is the model that you're creating all the way back, saying "Okay you created this model, Dave: And that data science experience is embedded and that this is actually getting used in the world. the business problem that needs to be solved, and the world of human guided, And the prize is to gain a competitive advantage. Dave: One of the things Manish, and how long the pumps need to run to enable that to predict out what you want to do. for you and your group. Dave: Congratulations on getting the product out Glad to see that. Manish: Thank you. Dave: Keep it right there everybody.

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Rob Thomas, IBM Analytics | IBM Fast Track Your Data 2017


 

>> Announcer: Live from Munich, Germany, it's theCUBE. Covering IBM: Fast Track Your Data. Brought to you by IBM. >> Welcome, everybody, to Munich, Germany. This is Fast Track Your Data brought to you by IBM, and this is theCUBE, the leader in live tech coverage. We go out to the events, we extract the signal from the noise. My name is Dave Vellante, and I'm here with my co-host Jim Kobielus. Rob Thomas is here, he's the General Manager of IBM Analytics, and longtime CUBE guest, good to see you again, Rob. >> Hey, great to see you. Thanks for being here. >> Dave: You're welcome, thanks for having us. So we're talking about, we missed each other last week at the Hortonworks DataWorks Summit, but you came on theCUBE, you guys had the big announcement there. You're sort of getting out, doing a Hadoop distribution, right? TheCUBE gave up our Hadoop distributions several years ago so. It's good that you joined us. But, um, that's tongue-in-cheek. Talk about what's going on with Hortonworks. You guys are now going to be partnering with them essentially to replace BigInsights, you're going to continue to service those customers. But there's more than that. What's that announcement all about? >> We're really excited about that announcement, that relationship, just to kind of recap for those that didn't see it last week. We are making a huge partnership with Hortonworks, where we're bringing data science and machine learning to the Hadoop community. So IBM will be adopting HDP as our distribution, and that's what we will drive into the market from a Hadoop perspective. Hortonworks is adopting IBM Data Science Experience and IBM machine learning to be a core part of their Hadoop platform. And I'd say this is a recognition. One is, companies should do what they do best. We think we're great at data science and machine learning. Hortonworks is the best at Hadoop. Combine those two things, it'll be great for clients. And, we also talked about extending that to things like Big SQL, where they're partnering with us on Big SQL, around modernizing data environments. And then third, which relates a little bit to what we're here in Munich talking about, is governance, where we're partnering closely with them around unified governance, Apache Atlas, advancing Atlas in the enterprise. And so, it's a lot of dimensions to the relationship, but I can tell you since I was on theCUBE a week ago with Rob Bearden, client response has been amazing. Rob and I have done a number of client visits together, and clients see the value of unlocking insights in their Hadoop data, and they love this, which is great. >> Now, I mean, the Hadoop distro, I mean early on you got into that business, just, you had to do it. You had to be relevant, you want to be part of the community, and a number of folks did that. But it's really sort of best left to a few guys who want to do that, and Apache open source is really, I think, the way to go there. Let's talk about Munich. You guys chose this venue. There's a lot of talk about GDPR, you've got some announcements around unified government, but why Munich? >> So, there's something interesting that I see happening in the market. So first of all, you look at the last five years. There's only 10 companies in the world that have outperformed the S&P 500, in each of those five years. And we started digging into who those companies are and what they do. They are all applying data science and machine learning at scale to drive their business. And so, something's happening in the market. That's what leaders are doing. And I look at what's happening in Europe, and I say, I don't see the European market being that aggressive yet around data science, machine learning, how you apply data for competitive advantage, so we wanted to come do this in Munich. And it's a bit of a wake-up call, almost, to say hey, this is what's happening. We want to encourage clients across Europe to think about how do they start to do something now. >> Yeah, of course, GDPR is also a hook. The European Union and you guys have made some talk about that, you've got some keynotes today, and some breakout sessions that are discussing that, but talk about the two announcements that you guys made. There's one on DB2, there's another one around unified governance, what do those mean for clients? >> Yeah, sure, so first of all on GDPR, it's interesting to me, it's kind of the inverse of Y2K, which is there's very little hype, but there's huge ramifications. And Y2K was kind of the opposite. So look, it's coming, May 2018, clients have to be GDPR-compliant. And there's a misconception in the market that that only impacts companies in Europe. It actually impacts any company that does any type of business in Europe. So, it impacts everybody. So we are announcing a platform for unified governance that makes sure clients are GDPR-compliant. We've integrated software technology across analytics, IBM security, some of the assets from the Promontory acquisition that IBM did last year, and we are delivering the only platform for unified governance. And that's what clients need to be GDPR-compliant. The second piece is data has to become a lot simpler. As you think about my comment, who's leading the market today? Data's hard, and so we're trying to make data dramatically simpler. And so for example, with DB2, what we're announcing is you can download and get started using DB2 in 15 minutes or less, and anybody can do it. Even you can do it, Dave, which is amazing. >> Dave: (laughs) >> For the first time ever, you can-- >> We'll test that, Rob. >> Let's go test that. I would love to see you do it, because I guarantee you can. Even my son can do it. I had my son do it this weekend before I came here, because I wanted to see how simple it was. So that announcement is really about bringing, or introducing a new era of simplicity to data and analytics. We call it Download And Go. We started with SPSS, we did that back in March. Now we're bringing Download And Go to DB2, and to our governance catalog. So the idea is make data really simple for enterprises. >> You had a community edition previous to this, correct? There was-- >> Rob: We did, but it wasn't this easy. >> Wasn't this simple, okay. >> Not anybody could do it, and I want to make it so anybody can do it. >> Is simplicity, the rate of simplicity, the only differentiator of the latest edition, or I believe you have Kubernetes support now with this new addition, can you describe what that involves? >> Yeah, sure, so there's two main things that are new functionally-wise, Jim, to your point. So one is, look, we're big supporters of Kubernetes. And as we are helping clients build out private clouds, the best answer for that in our mind is Kubernetes, and so when we released Data Science Experience for Private Cloud earlier this quarter, that was on Kubernetes, extending that now to other parts of the portfolio. The other thing we're doing with DB2 is we're extending JSON support for DB2. So think of it as, you're working in a relational environment, now just through SQL you can integrate with non-relational environments, JSON, documents, any type of no-SQL environment. So we're finally bringing to fruition this idea of a data fabric, which is I can access all my data from a single interface, and that's pretty powerful for clients. >> Yeah, more cloud data development. Rob, I wonder if you can, we can go back to the machine learning, one of the core focuses of this particular event and the announcements you're making. Back in the fall, IBM made an announcement of Watson machine learning, for IBM Cloud, and World of Watson. In February, you made an announcement of IBM machine learning for the z platform. What are the machine learning announcements at this particular event, and can you sort of connect the dots in terms of where you're going, in terms of what sort of innovations are you driving into your machine learning portfolio going forward? >> I have a fundamental belief that machine learning is best when it's brought to the data. So, we started with, like you said, Watson machine learning on IBM Cloud, and then we said well, what's the next big corpus of data in the world? That's an easy answer, it's the mainframe, that's where all the world's transactional data sits, so we did that. Last week with the Hortonworks announcement, we said we're bringing machine learning to Hadoop, so we've kind of covered all the landscape of where data is. Now, the next step is about how do we bring a community into this? And the way that you do that is we don't dictate a language, we don't dictate a framework. So if you want to work with IBM on machine learning, or in Data Science Experience, you choose your language. Python, great. Scala or Java, you pick whatever language you want. You pick whatever machine learning framework you want, we're not trying to dictate that because there's different preferences in the market, so what we're really talking about here this week in Munich is this idea of an open platform for data science and machine learning. And we think that is going to bring a lot of people to the table. >> And with open, one thing, with open platform in mind, one thing to me that is conspicuously missing from the announcement today, correct me if I'm wrong, is any indication that you're bringing support for the deep learning frameworks like TensorFlow into this overall machine learning environment. Am I wrong? I know you have Power AI. Is there a piece of Power AI in these announcements today? >> So, stay tuned on that. We are, it takes some time to do that right, and we are doing that. But we want to optimize so that you can do machine learning with GPU acceleration on Power AI, so stay tuned on that one. But we are supporting multiple frameworks, so if you want to use TensorFlow, that's great. If you want to use Caffe, that's great. If you want to use Theano, that's great. That is our approach here. We're going to allow you to decide what's the best framework for you. >> So as you look forward, maybe it's a question for you, Jim, but Rob I'd love you to chime in. What does that mean for businesses? I mean, is it just more automation, more capabilities as you evolve that timeline, without divulging any sort of secrets? What do you think, Jim? Or do you want me to ask-- >> What do I think, what do I think you're doing? >> No, you ask about deep learning, like, okay, that's, I don't see that, Rob says okay, stay tuned. What does it mean for a business, that, if like-- >> Yeah. >> If I'm planning my roadmap, what does that mean for me in terms of how I should think about the capabilities going forward? >> Yeah, well what it means for a business, first of all, is what they're going, they're using deep learning for, is doing things like video analytics, and speech analytics and more of the challenges involving convolution of neural networks to do pattern recognition on complex data objects for things like connected cars, and so forth. Those are the kind of things that can be done with deep learning. >> Okay. And so, Rob, you're talking about here in Europe how the uptick in some of the data orientation has been a little bit slower, so I presume from your standpoint you don't want to over-rotate, to some of these things. But what do you think, I mean, it sounds like there is difference between certainly Europe and those top 10 companies in the S&P, outperforming the S&P 500. What's the barrier, is it just an understanding of how to take advantage of data, is it cultural, what's your sense of this? >> So, to some extent, data science is easy, data culture is really hard. And so I do think that culture's a big piece of it. And the reason we're kind of starting with a focus on machine learning, simplistic view, machine learning is a general-purpose framework. And so it invites a lot of experimentation, a lot of engagement, we're trying to make it easier for people to on-board. As you get to things like deep learning as Jim's describing, that's where the market's going, there's no question. Those tend to be very domain-specific, vertical-type use cases and to some extent, what I see clients struggle with, they say well, I don't know what my use case is. So we're saying, look, okay, start with the basics. A general purpose framework, do some tests, do some iteration, do some experiments, and once you find out what's hunting and what's working, then you can go to a deep learning type of approach. And so I think you'll see an evolution towards that over time, it's not either-or. It's more of a question of sequencing. >> One of the things we've talked to you about on theCUBE in the past, you and others, is that IBM obviously is a big services business. This big data is complicated, but great for services, but one of the challenges that IBM and other companies have had is how do you take that service expertise, codify it to software and scale it at large volumes and make it adoptable? I thought the Watson data platform announcement last fall, I think at the time you called it Data Works, and then so the name evolved, was really a strong attempt to do that, to package a lot of expertise that you guys had developed over the years, maybe even some different software modules, but bring them together in a scalable software package. So is that the right interpretation, how's that going, what's the uptake been like? >> So, it's going incredibly well. What's interesting to me is what everybody remembers from that announcement is the Watson Data Platform, which is a decomposable framework for doing these types of use cases on the IBM cloud. But there was another piece of that announcement that is just as critical, which is we introduced something called the Data First method. And that is the recipe book to say to a client, so given where you are, how do you get to this future on the cloud? And that's the part that people, clients, struggle with, is how do I get from step to step? So with Data First, we said, well look. There's different approaches to this. You can start with governance, you can start with data science, you can start with data management, you can start with visualization, there's different entry points. You figure out the right one for you, and then we help clients through that. And we've made Data First method available to all of our business partners so they can go do that. We work closely with our own consulting business on that, GBS. But that to me is actually the thing from that event that has had, I'd say, the biggest impact on the market, is just helping clients map out an approach, a methodology, to getting on this journey. >> So that was a catalyst, so this is not a sequential process, you can start, you can enter, like you said, wherever you want, and then pick up the other pieces from majority model standpoint? Exactly, because everybody is at a different place in their own life cycle, and so we want to make that flexible. >> I have a question about the clients, the customers' use of Watson Data Platform in a DevOps context. So, are more of your customers looking to use Watson Data Platform to automate more of the stages of the machine learning development and the training and deployment pipeline, and do you see, IBM, do you see yourself taking the platform and evolving it into a more full-fledged automated data science release pipelining tool? Or am I misunderstanding that? >> Rob: No, I think that-- >> Your strategy. >> Rob: You got it right, I would just, I would expand a little bit. So, one is it's a very flexible way to manage data. When you look at the Watson Data Platform, we've got relational stores, we've got column stores, we've got in-memory stores, we've got the whole suite of open-source databases under the composed-IO umbrella, we've got cloud in. So we've delivered a very flexible data layer. Now, in terms of how you apply data science, we say, again, choose your model, choose your language, choose your framework, that's up to you, and we allow clients, many clients start by building models on their private cloud, then we say you can deploy those into the Watson Data Platform, so therefore then they're running on the data that you have as part of that data fabric. So, we're continuing to deliver a very fluid data layer which then you can apply data science, apply machine learning there, and there's a lot of data moving into the Watson Data Platform because clients see that flexibility. >> All right, Rob, we're out of time, but I want to kind of set up the day. We're doing CUBE interviews all morning here, and then we cut over to the main tent. You can get all of this on IBMgo.com, you'll see the schedule. Rob, you've got, you're kicking off a session. We've got Hilary Mason, we've got a breakout session on GDPR, maybe set up the main tent for us. >> Yeah, main tent's going to be exciting. We're going to debunk a lot of misconceptions about data and about what's happening. Marc Altshuller has got a great segment on what he calls the death of correlations, so we've got some pretty engaging stuff. Hilary's got a great piece that she was talking to me about this morning. It's going to be interesting. We think it's going to provoke some thought and ultimately provoke action, and that's the intent of this week. >> Excellent, well Rob, thanks again for coming to theCUBE. It's always a pleasure to see you. >> Rob: Thanks, guys, great to see you. >> You're welcome; all right, keep it right there, buddy, We'll be back with our next guest. This is theCUBE, we're live from Munich, Fast Track Your Data, right back. (upbeat electronic music)

Published Date : Jun 22 2017

SUMMARY :

Brought to you by IBM. This is Fast Track Your Data brought to you by IBM, Hey, great to see you. It's good that you joined us. and machine learning to the Hadoop community. You had to be relevant, you want to be part of the community, So first of all, you look at the last five years. but talk about the two announcements that you guys made. Even you can do it, Dave, which is amazing. I would love to see you do it, because I guarantee you can. but it wasn't this easy. and I want to make it so anybody can do it. extending that now to other parts of the portfolio. What are the machine learning announcements at this And the way that you do that is we don't dictate I know you have Power AI. We're going to allow you to decide So as you look forward, maybe it's a question No, you ask about deep learning, like, okay, that's, and speech analytics and more of the challenges But what do you think, I mean, it sounds like And the reason we're kind of starting with a focus One of the things we've talked to you about on theCUBE And that is the recipe book to say to a client, process, you can start, you can enter, and deployment pipeline, and do you see, IBM, models on their private cloud, then we say you can deploy and then we cut over to the main tent. and that's the intent of this week. It's always a pleasure to see you. This is theCUBE, we're live from Munich,

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David Hseih, Qubole - DataWorks Summit 2017


 

>> Announcer: Live from San Jose in the heart of Silicon Valley, it's theCube. Covering DataWorks Summit 2017. Brought to you by Hortonworks. >> Hey, welcome back to theCUBE. We are live on day one of the DataWorks Summit in the heart of Silicon Valley. I'm Lisa Martin with my co-host Peter Burgess. Just chatting with our next guest about the Warriors win yesterday we're also pretty excited about that. David Hseih the SVP of Marketing from Qubole, hi David. >> David: Hey, thanks for having me. >> Welcome to theCUBE, we're glad you still have a voice after no doubt cheering on the home team last night. >> It was a close call 'cause I was yelling pretty loud yesterday. >> So talk to us about you the SVP of Marketing for Qubole. Big data platform in the cloud. You guys just had a big announcement a few weeks ago. >> David: Right. >> What are your thoughts, what's going on with Qubole? What's going on with big data? What are you seeing in the market? So you know we're a cloud-native data platform and you know when we talk to customers, we're really, you know, they're really complaining about how they're just struggling with complexity and the barriers to entry and you know, they're really crying out for help. And the good news I suppose is we're in an industry that has a very high pace of innovation. That's great right. Spark has had eight versions now in two years, but that pace of innovation is, you know, making the complexity even harder. I was watching Cloudera bragging about how their new product is a combination of 24 open source projects. You know that's tough stuff, right. So if you're a practitioner trying to get big data operationalized in your company. And trying to scale the use of data and analytics across the company. The nature of open source is it's designed for flexibility. Right, the source codes public, you have all these options, configuration settings et cetera. But moving those into production and then scaling them in a reliable way is just crushing practitioners. And so data teams are suffering, and I think frankly it's bad for our industry, because, you know, Gardner's talking about a, you know, 80% failure rate of big data projects by 2018. Think about that, what industry can survive when 70 or 80% of the projects fail? >> Well I think what's let me push on that a little bit. Because I think that the concern is about, is not about 70 to 80% of the efforts to reach an answer in a complex big data thing, it's going to fail. We can probably accommodate that, but what we can't accommodate is failure in the underlying infrastructure. >> David: Absolutely. >> So the research we've done, suggest something as well that we are seeing an enormous amount of time spent on the underlying infrastructure. And there's a lot of failures there. People would say, I have a question, I want to know if there's an answer and try to get to that answer, and not getting the answer they want, >> David: Yep. or getting a different answer. That kind of failure is still okay. >> David: Right. >> Because that's experience, you get more and more and more. >> David: Absolutely. >> So it's not the failure in the data science side or the application side. >> Actually I would say getting to an answer you don't like, is a form of success. Like you have an idea, you try it out, that's all great. >> So what Gardner is really saying it's failure in the implementation of the infrastructure. >> That's exactly right. >> So it's the administrative and operational sides. >> Correct, it's a project that didn't deliver then resolve. If the end result what you hoped, great. >> You couldn't even answer your question. >> Exactly, couldn't even answer the question. >> So let me test something on you Dave, David. We've been carrying a thesis at Wikibon for awhile that it looks like opensource is proving that it's very good at mimicking, and not quite as good at inventing. >> David: Right. >> So by that I mean if you put an operating, drop an operating system in front of Linus Torvalds he can look at that and say I can do that. >> David: Right. >> And do a great job of it. If you put a development tool same kind of thing. But big data is very complex, a lot of it, an enormous number of usecases. >> David: Correct. >> And open source has done a good job at a tool level and it looks as though the tools are being built to make other tools more valuable, >> David: Ha, right. >> As opposed to making it easy for a business to operationalize data science and the use of big data in their business. Would you agree or disagree with that? >> I yeah, I think that sort of like fundamentally the philosophy of open source. You know I'm going to do my work, something I need for me, but I'm going to share it with everybody else. And they can contribute. But at the end of the day, you know, unlike commercial software, there's sort of no one throat to choke. Right and there's nobody who is going to guarantee the interoperability and the success of the piece of software that you're trying to deploy. >> There's mot even a real coherent vision in many respects. >> David: No, absolutely not. >> What the final product's going to end up looking like. >> So what you have is a lot of really great cutting edge technology that a lot of really smart people, sort of poured their hearts and souls into. But that's a little different than trying to get to an end result. And, you know. Like it or not, commercial software packages are designed to deliver the result you pay for. Open source being sort of philosophically, very different I think breeds you know inherent complexity. And that complexity right now, is I think the root of the problem in our industry. >> So give us an example David, you know, you're a Marketing guy, I'm a marketing gal. >> Sure. >> Give us an example of a customer, maybe one of your favorite examples, where are you helping them? They're struggling here, they've made significant investments from an infrastructure perspective. They know there's value in the data, >> David: Yup. varying degrees as we've talked about before. How does Qubole get in there and start helping this usecase customer start to optimize, and really start making this big data project successful? >> That's a great question. So there's really two things, number one is that we are a SAAS based platform in the cloud and what we do basically is make big data into more of a turnkey service. So actually the other day, I was sort of surfing the internet, and we have a customer from Sonic Drive-In. You know they do hamburgers and stuff. >> Lisa: Oh yeah. >> And they're doing a bunch of big data, and this guy was at a data science meet, talking about. We didn't put him up to this, he just volunteered. He was talking about how we made his life so much easier. Why, because all of the configurations stuff, the settings, and you know, how to manage costs, was basically filling out a form and setting policy and parameters. And not having to write scripts and figure out all these configuration settings. If I set this one this way and that one that way, what happens. You know, we have a sort of more curated environment that makes that easy. But the thing that I'm really excited about is we think this is the time to really look at having data platforms that can you know, build or run autonomously. Today companies have to hire really expensive, really highly skilled, super smart data engineers, and data ops people to run their infrastructure. And you know, if you look at studies, we're about a 180,000 people short of the number of data engineers, data ops this industry needs. So try to scale by adding more smart people is super hard. Right but instead if you could start to get machines to do what people are doing. Just faster, cheaper, more reliably. Then you can scale your data platform. So we basically, made an announcement a couple weeks ago, kind of about the industry's first autonomous data platform. And what we're building, are software agents that can take over certain types of data management tasks so that data engineers don't have to do it. Or don't have to be up at three in the morning making sure everything is going right. >> And from a market segmentation perspective where's your sweet spot for that? Enterprise, SMB, somewhere in the middle? >> The bigger you have to scale. It's not about company size it's really about sort of the scope and scale of your big data efforts. So you know, the more people you have using it, then the more data you have. The more you want automation to make things easier. It's sort of true of any industry, it's certainly going to be true of the big data industry. >> Peter: Yeah more complexity in the question set, >> Correct. >> The more complexity-- >> Or the more users you have, the more it gives. Adds more data sources. >> Which presumable is going to be correlated. >> Absolutely correct. >> Which is we can use a big data project to ascertain that. >> Well in fact that sort of what we're doing. Because we're a SAAS platform we take in the metadata from what our customers are doing. What users, what clusters, what queries, which tables, all that stuff. We basically use machine learning and artificial intelligence to analyze how you're using your data platform. And tell you what you could do better or automates stuff that you don't have to do anymore. >> So we've presumed that the industry at some point of time, the big data industry at some point of time, is going to start moving it's attention to things like machine learning and A.I., you know, up into applications. >> David: Yep. >> Are we going to see the big data industry basically more pretty rapidly into more of inservice or application conversation, or is it going to kind of are we going to see a rebirth, as folks try to bring a more coherent approach to the existing, many of the tools that are here right now. >> David: Right. >> What do you think? >> Well I think, we're going to see some degree of industry consolidation, and you're going to see vendors, you know, and you're seeing it today. Try to simplify and consolidate. Right so some of that is moving stack towards applications some of that is about repackaging their offerings and adding simplicity. It's about using artificial intelligence to make the operational platform itself easier. I think you'll see a variety of those things, because you know, companies have too many places where they can stumble in their deployment. And you know, it's going to be, you know, the vendor community has to step in and simplify those things to basically gain greater adoption. >> So if you think about it, what is, I mean I have my own idea, but what do you think the metric that businesses should be using as they conceive of how to source different tools and invest in different tools, put things together. I think it's increasingly we're going to talk about time to value. What do you think? >> I think time to value is one. I think another one you could look at is the number of people who have access to the data to create insights. Right so you know, you can say a 100% of my company has access to the data and analytics that they need to help their function run better. Whatever it is, that's a pretty awesome accomplishment. And you know, there's a bunch of people who may or may not have 100% but they're pretty close, right. And they've really become a data driven enterprise. And then you have lots of companies what are sort of stuck with, okay we have this usecase running, thank goodness. Took us two years and a couple million bucks and now they're trying to figure out how to get to the next step. And so they have five users who are able to use their data platform successfully. That's you know, I think that's a big measure of success. >> So I want to talk quickly about, if I may about the cloud. >> David: Yeah. >> Because it's pretty clear there are a number of, that there are some very, very large shops. >> David: Yep. >> That are starting to conceive of important parts of their overall approach to data. >> David: Right. >> And putting things into the cloud. There's a lot of advantages of doing it that way. At the same time they're also thinking about, and how I'm going to integrate, the models that I generate out of big data back into applications that might be running in a lot of different places. >> Right. >> That suggests there's going to be a new challenge on the horizon. Of how do we think about end to end bringing applications together with predictable date of movement and control and other types of activities. >> David: Yeah. >> Do you agree that's on the horizon of how we think about end to end performance across multiple different clouds? >> I think that's coming, you know, I think I'm still surprised at how many people have not figured out that the economic and agility advantages of cloud, are so great, that'd you'd be honestly foolish not to, you know, consider cloud and have that proactive way to migrate there. And so there is just you know a shocking amount of companies that are still plotting away, you know, and building their own prime infrastructures et cetera. And they still have hesitancy and questions about the cloud. I do think that you're right, but I think what you're talking about is, you know, three to five years out for the mainstream in the industry. Certainly there are early adopters you know, who have sort of gotten there. They're talking about that now. But as sort of a mainstream phenomenon I think that's a couple years out. >> Excuse me Peter, one of the things that just kind of made me think of was, you know, these companies as what you're saying, that is till had hesitancy regarding cloud. >> Right. >> And kind of vendor lock in popped into my head. And that kid of brought me back to one of the things that you were mentioning in the beginning. Open source, complexity there. >> David: Yep. >> Are you seeing, or are you helping companies to go back to more of that commercialized proprietary software. Are you seeing a shift in enterprises being less concerned about lock-in because they want simplicity? >> You know that's a great question. I think in the big data space it's hard to avoid, you know, sort of going down the open source path. I think what people are getting concerned about is getting locked into a single cloud vendor. So more and more of the conversations we have are about, what are your multi-cloud and eventually cross-cloud capabilities? >> Peter: That's the question I just asked, right. >> Exactly so I think more and more of that's coming to the front. I was with a large, very large healthcare company a week ago, and I said, what's your cloud strategy? And they said we have a no vendor left behind policy. So you know our, we're standardized on Azure, we've got a bunch of pilots on AWS, and we're planning to move from a data warehousing vendor to Oracle in the cloud. Ha so, I think for large companies a lot of them can't control the fact that different division, departments, whatever will use different clouds. So architecturally, they're going to have to start to think about using these multi-cloud, cross-cloud you know, scenarios. And you know, most large companies, given a choice, will not bet the farm on a single cloud provider. And you know, we're great partners and we love Amazon, but every time they have you know, an S3 outage like they had a few months ago. You know, it really makes people think carefully about what their infrastructure is and how they're dealing with reliability. >> Well in fairness they don't have that many, >> They don't, it only takes one. >> That's right, that's right, and there's reasons to suspect that there will be increased specialization of services in the cloud. >> David: Correct. >> So I mean it's going to get more complex as we go as well. >> David: Oh absolutely correct. >> Not less. >> Well David Hseih, SVP of Marketing at Qubole. Thank you so much for joining, >> Thank you. >> And sharing your insights with Peter and myself. It's been very insightful. >> Right. >> So this is another great example of how we've been talking about the Warriors and food, Sonic was brought up into play here. >> David: Exactly, go Sonic. Very exciting you never know what's going to happen on theCUBE. So for David and Peter, I am Lisa Martin, You're watching Day One, of the Data Work Summit, in the heart of Silicon Valley. But stick around because we've got more great content coming your way.

Published Date : Jun 13 2017

SUMMARY :

Brought to you by Hortonworks. in the heart of Silicon Valley. Welcome to theCUBE, we're glad you still have a voice It was a close call 'cause I was So talk to us about you the SVP of Marketing for Qubole. and the barriers to entry and you know, is not about 70 to 80% of the efforts to reach So the research we've done, suggest something as well That kind of failure is still okay. So it's not the failure in the Like you have an idea, you try it out, that's all great. it's failure in the implementation of the infrastructure. If the end result what you hoped, great. So let me test something on you Dave, David. So by that I mean if you put an operating, If you put a development tool same kind of thing. and the use of big data in their business. But at the end of the day, you know, unlike are designed to deliver the result you pay for. So give us an example David, you know, you're a They know there's value in the data, and really start making this big data project successful? So actually the other day, I was sort of surfing the the settings, and you know, how to manage costs, So you know, the more people you have Or the more users you have, the more it gives. or automates stuff that you don't have to do anymore. you know, up into applications. many of the tools that are here right now. And you know, it's going to be, you know, I mean I have my own idea, but what do you think And you know, there's a bunch of people who may or that there are some very, very large shops. of their overall approach to data. and how I'm going to integrate, the models That suggests there's going to be I think that's coming, you know, I think I'm still just kind of made me think of was, you know, And that kid of brought me back to one of the things Are you seeing, or are you helping companies So more and more of the conversations we have And you know, we're great partners and we love Amazon, to suspect that there will be increased Thank you so much for joining, And sharing your insights with Peter and myself. talking about the Warriors and food, Very exciting you never know what's

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