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Ajay Patel, VMware | AWS re:Invent 2022


 

>>Hello everyone. Welcome back to the Cube Live, AWS Reinvent 2022. This is our first day of three and a half days of wall to wall coverage on the cube. Lisa Martin here with Dave Valante. Dave, it's getting louder and louder behind us. People are back. They're excited. >>You know what somebody told me today? Hm? They said that less than 15% of the audience is developers. I'm like, no way. I don't believe it. But now maybe there's a redefinition of developers because it's all about the data and it's all about the developers in my mind. And that'll never change. >>It is. And one of the things we're gonna be talking about is app modernization. As customers really navigate the journey to do that so that they can be competitive and, and meet the demands of customers. We've got an alumni back with us to talk about that. AJ Patel joins us, the SVP and GM Modern Apps and Management business group at VMware. Aj, welcome back. Thank >>You. It's always great to be here, so thank you David. Good to see >>You. Isn't great. It's great to be back in person. So the VMware Tansu team here back at Reinvent on the Flow Shore Flow show floor. There we go. Talk about some of the things that you guys are doing together, innovating with aws. >>Yeah, so it's, it's great to be back after in person after multiple years and the energy level continues to amaze me. The partnership with AWS started on the infrastructure side with VMware cloud on aws. And when with tanza, we're extending it to the application space. And the work here is really about how do you make developers productive To your earlier point, it's all about developers. It's all about getting applications in production securely, safely, continuously. And tanza is all about making that bridge between great applications being built, getting them deployed and running, running and operating at scale. And EKS is a dominant Kubernetes platform. And so the better together story of tanu and EKS is a great one for us, and we're excited to announce some sort of innovations in that area. >>Well, Tanu was so front and center at VMware Explorer. I wasn't at in, in VMware Explorer, Europe. Right. But I'm sure it was a similar kind of focus. When are customers choosing Tanu? Why are they choosing Tanu? What's, what's, what's the update since last August when >>We, you know, the market settled into three main use cases. One is all about developer productivity. You know, consistently we're all dealing with skill set gap issues. How do we make every developer productive, modern developer? And so 10 is all about enabling that develop productivity. And we can talk quite a bit about it. Second one is security's front and center and security's being shifted left right into how you build great software. How do you secure that through the entire supply chain process? And how do you run and operationalize secure at runtime? So we're hearing consistently about making secure software supply chain heart of what our solution is. And third one is, how do I run and operate the modern application at scale across any Kubernetes, across any cloud? These are the three teams that are continuing to get resonance and empowering. All of this is exciting. David is this formation of platform teams. I just finished a study with Bain Consulting doing some research for me. 40% of our organization now have some form of a central team that's responsive for, for we call platform engineering and building platforms to make developers productive. That is a big change since about two years ago even. So this is becoming mainstream and customers are really focusing on delivering in value to making developers productive. >>Now. And, and, and the other nuance that I see, and you kinda see it here in the ecosystem, but when you talk about your customers with platform engineering, they're actually building their, they're pointing their business. They gonna page outta aws, pointing their businesses to their customers, right? Becoming software companies, becoming cloud companies and really generating new forms of revenue. >>You know, the interesting thing is, some of my customers I would never have thought as leading edge are retailers. Yeah. And not your typical Starbucks that you get a great example. I have an auto parts company that's completely modernizing how they deliver point of sale all the way to the supply chain. All built on ES at scale. You're typically think of that a financial services or a telco leading the pack. But I'm seeing innovation in India. I'm seeing the innovation in AMEA coming out of there, across the board. Every industry is becoming a product company. A digital twin as we would call it. Yeah. And means they become software houses. Yeah. They behave more like you and I in this event versus a, a traditional enterprise. >>And they're building their own ecosystems and that ecosystem's generating data that's generating more value. And it's just this cycle. It's, >>It's a amazing, it's a flywheel. So innovation continues to grow. Talk about really unlocking the developer experience and delivering to them what they need to modernize apps to move as fast and quickly as they want to. >>So, you know, I think AWS coin this word undifferentiated heavy lifting. If you think of a typical developer today, how much effort does he have to put in before he can get a single line of code out in production? If you can take away all the complexity, typically security compliance is a big headache for them, right? Developer doesn't wanna worry about that. Infrastructure provisioning, getting all the configurations right, is a headache for them. Being able to understand what size of infrastructure or resource to use cost effectively. How do you run it operationally? Cuz the application team is responsible for the operational cost of the product or service. So these are the un you know, heavy lifting that developers want to get away from. So they wanna write great code, build great experiences. And we've always talked about frameworks a way to abstract with the complexity. And so for us, there's a massive opportunity to say, how do I simplify and take away all the heavy lifting to get an idea into production seamlessly, continuously, securely. >>Is that part of your partnership? Because you think about a aws, they're really not about frameworks, they're about primitives. I mean, Warner Vos even talks about that in his, in his speech, you know, but, but that makes it more challenging for developers. >>No, actually, if you look at some of their initial investments around proton and et cetera work, they're starting to do, they're recognized, you know, PS is a bad, bad word, but the outcomes a platform as a service offers is what everybody wants. Just talking to the AWS leaders, responsible area, he actually has a separate build team. He didn't know what to call the third team. He has a Kubernetes team, he has a serverless team and has a build team. And that build team is everything above Kubernetes to make the developer productive. Right. And the ecosystem to bring together to make that happen. So I think AWS is recognizing that primitives are great for the elite developers, but if they want to get the mass scale and adoption in the business, it, if you will, they're gonna have to provide richer set of building blocks and reduce the complex and partnership like ours. Make that a reality. And what I'm excited about is there's a clear gap here, and t's the best platform to kind of fill that gap. Well, >>And I, I think that, you know, they're gonna double down triple, I just wrote about this double down, triple down on the primitives. Yes. They have to have the best, you know, servers and storage and database. And I think the way they, they, I call it taping the seams is with the ecosystem. Correct. You know, and they, nobody has a, a better ecosystem. I mean, you guys are, you know, the, the postage child for the ecosystem and now this even exceeds that. But partnering up, that's how they >>Continue to, and they're looking for someone who's open, right? Yeah. Yeah. And so one of the first question is, you know, are you proprie or open? Because one of the things they're fighting against is the lock in. So they can find a friendly partner who is open source, led, you know, upstream committing to the code, delivering that innovation, and bring the ecosystem into orchestrated choreography. It's like singing a music, right? They're running a, running an application delivery team is like running a, a musical orchestra. There's so many moving parts here, right? How do you make them sing together? And so if Tan Zoo and our platform can help them sing and drive more of their services, it's only more valuable for them. And >>I think the partners would generally say, you know, AWS always talking about customer obsession. It's like becomes this bromine, you go, yeah, yeah. But I actually think in the field, the the sellers would say, yeah, we're gonna do what the customer, if that means we're gonna partner up. Yeah. And I think AWS's comp structure makes it sort >>Of, I learned today how, how incentives with marketplaces work. Yeah. And it is powerful. It's very powerful. Yeah. Right. So you line up the sales incentive, you line up the customer and the benefits, you line up bringing the ecosystem to drive business results and everybody, and so everybody wins. And which is what you're seeing here, the excitement and the crowd is really the whole, all boats are rising. Yeah. Yeah. Right, right. And it's driven by the fact that customers are getting true value out of it. >>Oh, absolutely. Tremendous value. Speaking of customers, give us an example of a customer story that you think really articulates the value of what Tanzi was delivering, especially making that developer experience far simpler. What are some of those big business outcomes that that delivers? >>You know, at Explorer we had the CIO of cvs and with their acquisition of Aetna and CVS Health, they're transforming the, the health industry. And they talked about the whole covid and then how they had to deliver the number of, you know, vaccines to u i and how quickly they had to deliver on that. It talked about Tanu and how they leverage, leverage a Tanza platform to get those new applications out and start to build that. And Ro was basically talking about his number one prior is how does he get his developers more productive? Number to priority? How does he make sure the apps are secure? Number three, priority, how does he do it cost effectively in the world? Particularly where we're heading towards where, you know, the budgets are gonna get tighter. So how do I move more dollars to innovation while I continue to drive more efficiency in my platform? And so cloud is the future. How does he make the best use of the cloud both for his developers and his operations team? Right? >>What's happening in serverless, I, in 2017, Andy Chassy was in the cube. He said if AWS or if Amazon had to build all over again, they would build in, in was using serverless. And that was a big quote. We've mined that for years. And as you were talking about developer productivity, I started writing down all the things developers have to do. Yep. With it, they gotta, they gotta build a container image. They said they gotta deploy an EC two instance. They gotta allocate memory, they gotta fence off the apps in a virtual machine. They gotta run the, you know, compute against the app goes, they gotta pay for all that. So, okay, what's your story on, what's the market asking for in terms of serverless? Because there's still some people who want control over the run time. Help us sift through that. >>And it really comes back to the application pattern or the type you're running. If it's a stateless application that you need to spin up and spin down. Serverless is awesome. Why would I wanna worry about scaling it up in, I wanna set up some SLAs, SLIs service level objectives or, or, or indicators and then let the systems bring the resources I need as I need them. That's a perfect example for serverless, right? On the other hand, if you have a, a more of a workflow type application, there's a sequence, there's state, try building an application using serverless where you had to maintain state between two, two steps in the process. Not so much fun, right? So I don't think serverless is the answer for everything, but many use cases, the scale to zero is a tremendous benefit. Events happen. You wanna process something, work is done, you quietly go away. I don't wanna shut down the server started up, I want that to happen magically. So I think there's a role of serverless. So I believe Kubernetes and servers are the new runtime platform. It's not one or the other. It's about marrying that around the application patterns. I DevOps shouldn't care about it. That's an infrastructure concern. Let me just run application, let the infrastructure manage the operations of it, whether it's serverless, whether it's Kubernetes clusters, whether it's orchestration, that's details right. I I I shouldn't worry about it. Right. >>So we shouldn't think of those as separate architectures. We should think of it as an architecture, >>The continuum in some ways Yeah. Of different application workload types. And, and that's a toolkit that the operator has at his disposal to configure and saying, where does, should that application run? Should I want control? You can run it on a, a conveyance cluster. Can I just run it on a serverless infrastructure and and leave it to the cloud provider? Do it all for me. Sure. What, what was PAs? PAs was exactly that. Yeah. Yeah. Write the code once you do the rest. Yeah. Okay. Those are just elements of that. >>And then K native is kinda in the middle, >>Right? K native is just a technology that's starting to build that capability out in a standards way to make serverless available consistently across all clouds. So I'm not building to a, a lambda or a particular, you know, technology type. I'm building it in a standard way, in a standard programming model. And infrastructure just >>Works for me on any cloud. >>The whole idea portability. Consistency. >>Right. Powerful. Yep. >>What are some of the things that, that folks can expect to learn from VMware Tan to AWS this week at the >>Show? Yeah, so there's some really great announcements. First of all, we're excited to extend our, our partnership with AWS in the area of eks. What I mean by that is we traditionally, we would manage an EKS cluster, you visibility of what's running in there, but we weren't able to manage the lifecycle With this announcement. We can give you a full management of lifecycle of S workloads. Our customers have 400 plus EKS clusters, multiple teams sharing those in a multi-tenanted way with common policy. And they wanna manage a full life cycle, including all the upstream open source component that make up Kubernetes people. That ES is the one thing, it's a collection of a lot of open, open source packages. We're making it simple to manage it consistently from a single place on the security front. We're now making tons of service mesh available in the marketplace. >>And if you look at what service MeSHs, it's an overlay. It's an abstraction. I can create an idea of a global name space that cuts across multiple VPCs. I'm, I'm hearing at Amazon's gonna make some announcements around VPC and how they stitch VPCs together. It's all moving towards this idea of abstractions. I can set policy at logical level. I don't have to worry about data security and the communication between services. These are the things we're now enabling, which are really an, and to make EKS even more productive, making enterprise grade enterprise ready. And so a lot of excitement from the EKS development teams as well to partner closely with us to make this an end to end solution for our >>Customers. Yeah. So I mean it's under chasy, it was really driving those primitives and helping developers under continuing that path, but also recognizing the need for solutions. And that's where the ecosystem comes in, >>Right? And the question is, what is that box? As you said last time, right? For the super cloud, there is a cloud infrastructure, which is becoming the new palette, but how do you make sense of the 300 plus primitives? How do you bring them together? What are the best practices, patterns? How do I manage that when something goes wrong? These are real problems that we're looking to solve. >>And if you're gonna have deeper business integration with the cloud and technology in general, you have to have that >>Abstraction. You know, one of the simple question I ask is, how do you know you're getting value from your cloud investment? That's a very hard question. What's your trade off between performance and cost? Do you know where your security, when a lock 4G happens, do you know all the open source packages you need to patch? These are very simple questions, but imagine today having to do that when everybody's doing in a bespoke manner using the set of primitives. You need a platform. The industry is shown at scale. You have to start standardizing and building a consistent way of delivering and abstracting stuff. And that's where the next stage of the cloud journey >>And, and with the economic environment, I think people are also saying, okay, how do we get more? Exactly. We're in the cloud now. How do we get more? How do we >>Value out of the cloud? >>Exactly. Totally. >>How do we transform the business? Last question, AJ for you, is, if you had a bumper sticker and you're gonna put it on your fancy car, what would it say about VMware tan zone aws? >>I would say tan accelerates apps. >>Love >>It. Thank you so much. >>Thank you. Thank you so much for joining us. >>Appreciate it. Always great to be here. >>Pleasure. Likewise. For our guest, I'm Dave Ante. I'm Lisa Martin. You're watching The Cube, the leader in emerging and enterprise tech coverage.

Published Date : Nov 29 2022

SUMMARY :

Welcome back to the Cube Live, AWS Reinvent 2022. They said that less than 15% of the audience is developers. And one of the things we're gonna be talking about is app modernization. Good to see Talk about some of the things that you guys are doing together, innovating with aws. And so the better together Why are they choosing Tanu? And how do you run and operationalize secure at runtime? but when you talk about your customers with platform engineering, they're actually building their, You know, the interesting thing is, some of my customers I would never have thought as leading edge are retailers. And it's just this cycle. So innovation continues to grow. how do I simplify and take away all the heavy lifting to get an idea into production in his speech, you know, but, but that makes it more challenging for developers. And the ecosystem to bring together to make that happen. And I, I think that, you know, they're gonna double down triple, I just wrote about this double down, triple down on the primitives. And so one of the first question is, I think the partners would generally say, you know, AWS always talking about customer And it's driven by the fact that customers are getting true value out of it. that you think really articulates the value of what Tanzi was delivering, especially making that developer experience far And so cloud is the future. And as you were talking about developer productivity, On the other hand, if you have a, So we shouldn't think of those as separate architectures. Write the code once you do the rest. you know, technology type. The whole idea portability. Yep. And they wanna manage a full life cycle, including all the upstream open source component that make up Kubernetes people. And if you look at what service MeSHs, it's an overlay. continuing that path, but also recognizing the need for solutions. And the question is, what is that box? You know, one of the simple question I ask is, how do you know you're getting value from your cloud investment? We're in the cloud now. Exactly. Thank you so much for joining us. Always great to be here. the leader in emerging and enterprise tech coverage.

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Chuck Whitten, Dell Technologies | Dell Technologies World 2022


 

>> Announcer: theCUBE presents Dell Technologies World brought to you by Dell. >> Welcome back to Dell Tech World 2022. You're watching theCUBE. My name is Dave Vellante, I'm here with my co-host John Furrier, live event, I would say seven to eight thousand people, really exceeded our expectations. And we're here with Chuck Whitten, who is the co chief operating officer and chief dot connector, I sometimes call him, at Dell Technologies. Chuck, welcome to theCUBE. >> I am thrilled to be here. How great is it to be, you know, back in Las Vegas, seven to eight thousand people here, talking innovation. It's great. >> Yeah, it's like Jeff said this morning, I'm not really thrilled to be in Vegas maybe, but I'm happy to be back live, so yeah. >> It's great to be here. >> Awesome. Okay, the operative phrase is multicloud by default, that's kind of the buzz from your keynote. What do you mean by that? >> Well, look, customers have woken up with multiple clouds you know, multiple public clouds, on-premises clouds, increasingly as the edge becomes much more a reality for a customer, clouds at the edge. And so that's what we mean by multicloud by default. It's not yet been designed strategically. I think our argument yesterday was it can be and it should be, it is a very logical place for architecture to land because ultimately customers want the innovation across all of the hyper scale public clouds. They will see workloads and use cases where they want to maintain an on-premises cloud. On-premises clouds are not going away, I mentioned edge cloud, so it should be strategic. It's just not today. It doesn't work particularly well today, so when we say multicloud by default, we mean that's the state of the world today. Our goal is to bring multicloud by design, as you heard. >> Yeah. I mean, I totally agree with you a hundred percent. We all know multicloud exists. It's by default, it's not going away. It's only going to get more complicated. What are you guys seeing in terms of the customer needs as this becomes more of the strategy plus operations, I want to operationalize multicloud as an abstraction layer, how do you guys see the customer requirements? What problems are they trying to solve? >> Well, look, multicloud by default today are isolated clouds. They don't work together. Your data is siloed. It's locked up and it is expensive to move and make sense of it. So, you know, I think the word you and I were batting around before, this is an interconnected tissue. That's what the world needs. They need the clouds to work together as a single platform. That's the problem that we're trying to solve. And you saw it in some of our announcements here that we are starting to make steps on that journey to make multicloud work together much simpler. >> It's interesting. You mentioned the hyperscalers and all that CapEx investments. Why wouldn't you want to take advantage of a cloud and build on the CapEx and then ultimately have the solutions, machine learning is one area, you see some specialization with the clouds, but you start to see the rise of super clouds, Dave calls them, and that's where you can innovate on a cloud. Then go to the multiple clouds, Snowflake's one, we see a lot of examples of super clouds. >> Project Alpine was another one. I mean, it's early, but it's clearly where you're going. The technology is just starting to come around. I mean, it's real. >> Yeah. I mean, why wouldn't you want to take advantage of all of the cloud innovation out there? Well, the answer would be, I don't want to do that if I'm going to feel locked up, if it's going to be too expensive. So again, I think Project Alpine's a perfect example of a step on that journey. If you can create a common storage pool, a fabric if you will, that allows you to choose how, where you're going to process your data and store it. And more importantly, give your teams the same M and O tools, the same skillsets, the ability to operate on-premises or in the public clouds. You know, I think ultimately the theme of the last couple days in multicloud for us has been customer choice. We want to give them the choice to operate, how they want to, so they can take advantage of all those cloud services. >> Real quick. Where does that innovation go from that Alpine Project? Because that's software defined, and I believe that's all your IP to all Dell technologies IP. >> It is, yeah. >> So that factors in, so is that going to make the hardware more innovative? Is it going to be more application specific? Where do you see that going? >> Well, look, our, you know, putting our file block and object storage into the public clouds just gives them choice on taking advantage of enterprise class storage software. You know, you saw in our announcements today, we're not stopping the innovation in our core arrays and hardware. And in fact, the theme today was software innovation. I think we announced five hundred different software updates across power flex, power max and power store. So look, we're going to continue to innovate across the storage portfolio. Now we're giving customers the choice. Hey, you want it in the public cloud? That's what Project Alpine will let you do. >> Michael had a smile on a, I won't say a spring in his step, because he was sitting in that chair, but he was smiling about the market share numbers on that, so pretty impressive. You guys got a good commanding lean there. The super cloud thing, back to that concept, Snowflake is we consider super cloud. They took their IP, put it on a hyperscaler, differentiated themselves, have great value and scale and they're running away with it. It looks like at this point, I mean, you've got data breaks, and you've got Redshift in there and other stuff, but as a concept that's working, and now they're on multiple clouds. How do you see that super cloud connecting with Snowflake, because you guys are building a little Snowflake connected. It's one of the big announcements here is Snowflake and Dell. >> Yeah. >> So can you talk about that? >> It was probably the one that got the most excitement from customers in the last day. And so look, you said it well, Snowflake, you know, one of the most exciting companies in the data space right now, and a vision from that company to say, hey, let's make the consumption of data as simple as cloud operating models have made the consumption of infrastructure. Well we share that vision and love that vision but we're each coming at it from different parts of the stack, right? So we're coming at it from storage up to data, they're coming data management down to data. It's a perfect match of our capabilities. So that, the announcements we made in our partnership, we're going to start with two use cases that our customers have been asking for. You know, the first is the ability to buy directionally copy data from our storage to Snowflake's data cloud. That's exciting, but the more exciting one that created the buzz is, if you don't want to move your data to the public cloud, Snowflake only operates in the public cloud today, we're now giving the opportunity to access their data services on-premises. And that's the excitement from customers that have said, hey, look, I want to take advantage of Snowflake's capabilities, but for regulatory or security reasons, I'm not doing that today. This is a groundbreaker. >> Well, it's the interesting thing, because, you know, as many people know, Snowflake requires you to put their data in their cloud, in Snowflake format, this is the first example of non-native data being accessed into the Snowflake cloud. >> Exactly right, exactly right. So, you know, again for customers that say, I just can't do it, I cannot move my data, now they have the option. It's the first time Snowflake has collaborated with an on-premises infrastructure player. >> How'd that deal come about? >> Well, it started as all great deals in our business do, Michael, to the top. So it was a, you know, and then it's been our teams working together closely, always, you know alongside our customers, because that customer feedback of I want to take advantage of Snowflake's capabilities, you know, it's been, we've been incubating it for a few months now and it was great to bring it out on stage yesterday. >> I mean, it makes a lot of sense. You connected dots so to speak. When you look at what Michael was saying, these compute hubs, towers for 5G to >> Yep. >> Small edges and big edges and data centers all coming together, really key value parts of how data's going to be moving around, it's not just storage, it's data as code. It's a big part of >> Incredible, yeah. I mean, look, this is, that was the, the start of the theme yesterday. Look, the great unsolved problems in infrastructure right now is data is everywhere. It's sprawling. It is less secure than we would like. Help, and help me make sense of multicloud. >> I'd love to get your reaction real quick while I got you up here, because data science is a well known practice. >> Yeah. >> There's been the rise of a hot persona, that seems to be, you know, growing in numbers, but it's a scarce skill that's data engineering. Because the data's not just doing visualizations, there's a lot of architectural work being done to solve that strategy problem. What's your reaction to this new data engineering at the scale that we're talking about? >> Yeah, I mean, it's a space I'm just learning about to be honest with you, data engineering, but look, part of what we observe is, it takes a lot of calories from organizations to get data in a place where you can make sense of it and make decisions. And whether that's data scientists spending too much time cleaning or the advent, as you said, of data engineering to create the architectures, to help make that decision. Look, there's a lot of work that goes into that. It would be great over time to automate that. I think that's also the next great stuff on the journey. >> You know, Chuck, when I did the intro, I really didn't set it up that well, because you know people, oh, hey, here's the new guy, but you have a lot of experience with Dell. You've been a consultant to the company for a long, long time. Tell us a little bit about that. I'm interested in what you see as your greatest strengths that you bring to Dell. >> Yeah, well, as you said, look, I am the new guy-ish, I think it's been eight months. I don't know how long I can continue to use that as the excuse, but I had worked with Dell for over a decade as a consultant previously at Bain Company. So, you know, look, my background is as a strategist and I did lots of work in sort of M and A and private acuity, and so that's my background, I'm your sort of classic MBA, whose spent a decade in technology and a decade alongside Jeff Clark and Michael in the transformation of the company. So I hope I bring the right sort of outsider's but insider's perspective to, you know, to the party, if you will. But you know, I've certainly learned a lot in the last eight months, as you get alongside and inside the machine at Dell. >> So irrespective of the financial magic. >> I think I know what question he's going to ask. >> Irrespective of the financial magic that Dell did with the VMware skin, as a consultant, one could have gone through a mental exercise of saying, hey, what about, you know, spinning it in, because you got this great software asset. Everybody wants software marginal economics. Okay, the decision was made and now we're onto the future. That obviously has an impact on margins and gross margins and everything else. So, I guess as a consultant, you turn that into opportunity. >> Yeah. >> Right. So where is that opportunity? How do you feel about, how do you think about, that really hardware, heavy hardware exposure, and where you want to go in the future? >> Well, look, I think we, that's what we've been been talking about the last couple of days. So, you know, the VMware spinoff was a moment in which the world looked at us and I think asked the question, you did, you know, what are you, right? Are you a legacy hardware company or where you're going? But the reality of the world is, it's a multicloud world, so we are, it was a signal also to the world that we're not a VMware stack competing against other cloud stacks. We are first and best with VMware. They are still our most strategic partner, but we work with all the hyperscalers and it's a big world that is becoming multicloud. So strategically speaking as that becomes the reality of infrastructure and importantly as data explodes at the edge, you know, we're perfectly positioned as a company. That's the strategy, we like to say these trends are coming our way. It's never been a better time, honestly, to be the leader in infrastructure, and the leader in client devices, all the way to sort of the core data center in the cloud. >> How do you think about, you have quite an observation space, as you know, a long time, you know, Bain consultant. How do you think about the skillsets required to make that transition? >> Yeah, absolutely. Well look, we think a lot about it, right? Because certainly we have a lot of the native skills we need to win in the data era as the leader in storage and the leader in infrastructure, you know, we secure more mission critical workloads than anybody. We know a lot about data, but what we're talking about now is not just persisting data. It's about protecting data. It's about moving data, right? And those are different skill sets that we're sort of acquiring and always looking at our teams to think about and look, you know, we can do a lot of that organically. We are also always, you know, contemplating the right strategic M and A at the right time to sort of add to that talent and technology. >> You got the balance sheet for it now, so. >> We do indeed. We do indeed. >> We get the M and A question in there, but my question to you is, as you look at these systems, because we've always said in theCUBE, many times, distributed computing is back. >> Yeah. >> It never went away. Cloud is just a version of that with on-premises and edge. It's an operating system. It's got all the IO, it's got the control plane, it's the internet, right? And so as you look at that, there's a system and with the scale of cloud, ecosystems are emerging and they're super important because if you're plugging and playing solutions, you've got glue layers, you've got automations coming, AI machine learning, the partners aren't just totally dependent on each other, the interdependencies go away. So, as you see partners that could be LEGO blocks, and be composed into these large scale solutions that you guys are rolling out, what is the role of the ecosystem? What does the future ecosystem look like? How do you tell if it's healthy, and take us through that new formula, because we see it changing. >> Well, look, I, you know, we've been very explicit in our strategy, that partnerships have to be a part of our strategy. We can't solve all of the problems of the data in multicloud world alone. And when you see announcements like Snowflake, or you see us announce, continued collaborations with each of the hyperscalers, or even how we continue to invest in and double down on our VMware relationship, it's an acknowledgement that, to solve the problems that our customers are telling us, this super cloud you're describing, this integrated multicloud journey, you know, we're going to solve a lot of it ourselves, but a lot of it we're going to have to partner with. It's just got to be part and parcel of any good strategy. Luckily we're a natural ecosystem partner. As I said, we are not another cloud stack looking to build a walled garden, right. We know our spot in this game and it is to make multicloud simpler across the infrastructure layer. >> Somebody asked me, is Snowflake a part of Dell's ecosystem, or is Dell part of Snowflake's ecosystem? I said, yes. Right, because that's a perfect example. >> I think that's exactly right. These only work, and we've learned this with VMware, when it's mutually beneficial to both sides. So you look at the use cases we're talking about with Snowflake, right? Bio directionally copy data from our storage to their data cloud. That's beneficial to Snowflake and our customers. And of course bringing data cloud on-premises is beneficial to us, so look, there's more win-wins when you stare at these partnerships, than there are zero. >> I think that's a key point from even a decade ago, the platform wars were well identified, viewer platform. They competed against each other. You got now platforms with platforms because of the synergies of the integration. This is new, this is a new dynamic. >> It's the great world of tech, it's cooperation and it's, you know, there's certainly places where we compete sometimes, but other places that we, you know, we cooperate. And so, yeah, we're excited about our position in this multicloud ecosystem. We think we positioned the company perfectly. >> How do you spend your time? >> As a COO? >> Just at Dell? I mean, you know, give us the sort of breakdown. >> Yeah, well look, I mean, I think that what makes it fun is no two days are alike, but, right? But together, Jeff Clark and I share a responsibility for setting strategy with Michael and then aligning the leadership team on our strategic priorities. And you know, in the world we live in, there's days you wake up and today is supply chain day, because something has happened in the world, but you know, often it's with customers or investors, so it's a true COO general manager job. And I would tell you, no two days are the same. >> Strategy, solving problems, keeping things moving. >> Leading the team, setting a vision, and listening to customers. I mean, at the end of the day, we talk a lot about our durable, competitive advantages as a company. I think our single greatest competitive advantage is our go to market reach. And the fact that we touch more customers and partners than anyone in technology. And that gives us a inside track on what they're worried about, what they're thinking about and how we can help. >> It's interesting, you mentioned how earlier, how things come back around on cycles and we're seeing hardware matter more than everything, in fact, we're doing a editorial thing on why hardware matters. Look at the advances in Silicon. >> Yeah. >> And smaller footprint of powerful devices compute, about towers and edges. And so the role of hardware, I think they got the software defined software and the role of open source in all of this, it's almost a perfect storm to kind of reset this, none of the trajectory of growth, where hardware innovations working with the new software. >> For sure, for sure. >> Can you react to that? >> No, I think it's spot on. I think the future of architectural innovation is really exciting, when you look at what CPUs and GPUS and DPUS, and all it's able to do in the future of infrastructure and eventually the ability to compose your infrastructure to the workload versus, you know, have it be rigid and silent. I mean, there's as much innovation inside the infrastructure as there is in the ecosystem. And, you know, that's exciting for our customers, right? It's going to make them more efficient. It's going to make them able to make decisions with data better than they are today. It's great to be in our space for sure. >> It's great to have you on. Now, you're a CUBE alumni. >> All right, well, I've watched from afar and admired, and it was really painless. So thank you. >> Thanks so much for coming on. >> Thanks for having me. >> Keep it right there, everybody, Dave Vellante and John Furrier will be back right after this short break, you're watching theCUBE at Dell Tech World 2022. (upbeat music)

Published Date : May 3 2022

SUMMARY :

brought to you by Dell. to eight thousand people, How great is it to be, you but I'm happy to be back live, so yeah. that's kind of the buzz from your keynote. of the world today. with you a hundred percent. They need the clouds to work and that's where you starting to come around. the ability to operate and I believe that's all your IP Well, look, our, you know, It's one of the big announcements here is that got the most excitement because, you know, as many people know, So, you know, again So it was a, you know, When you look at what Michael was saying, data's going to be moving around, the start of the theme yesterday. while I got you up here, that seems to be, you the advent, as you said, that you bring to Dell. to the party, if you will. question he's going to ask. Irrespective of the financial magic and where you want to go in the future? and the leader in client devices, as you know, a long time, and the leader in infrastructure, You got the balance We do indeed. but my question to you is, And so as you look at and it is to make multicloud simpler I said, yes. So you look at the use because of the synergies it's cooperation and it's, you know, I mean, you know, give And you know, in the world we live in, keeping things moving. I mean, at the end of It's interesting, you and the role of open and eventually the ability to It's great to have you on. and admired, and it was really painless. Dave Vellante and John

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Purna Doddapaneni, Bain & Company | UiPath FORWARD IV


 

>>from the bellagio hotel >>in Las Vegas, it's the cube covering Ui Path forward. Four brought to you >>by Ui Path. Welcome back from the bellagio in Las Vegas. The Cubans live at Ui Path forward for I'm lisa martin here with Dave Volonte. We're gonna be talking about roadblocks to automation and how to navigate around them, joining us next as Pernando Panini expert associate partner at bain and company per night. Welcome to the program. >>Thanks lisa. Happy to be here. >>Talk to us about some of the use cases that bain is working on with you I Path and then we'll dig into some of those roadblocks that you guys have uncovered. >>Yes. Uh I started a few months ago where we're working with Brandon who's the product lead on the Ui part side. We wanted to understand what's the state of citizen development and what are the blockers and how we should Both from the product side. But also on the automation journey side we need to dig deeper and understand where each of the clients and the employees are going through the journey together >>and if you look at it from the citizen developer perspective, what are some of those roadblocks? >>There are a few. So when like if you before we go to the roadblocks there are three main concerns or I would say critical groups that are involved in being successful with automation. The organization or bu leaders, the I. T. And employees. So each of the groups have different perceptions on like misconceptions or perceptions on benefits of automation and how to go up go about it. The blockers that we have seen where like a three sets of blockers. The first is cognitive where employees are unaware of automation on the benefits of automation and the second one is more organizational where organization leaders and how they feel about automation or how the how they think about employees when we introduce automation to them. One part of that is there is a misconception without nation leaders that employees are fearful of job loss when you introduce automation. What we have seen in our research is it's completely the opposite of employees are eager to adopt automation have given an opportunity, they are willing to upscale themselves and they are willing to save the time so that they can spend that on critical value added activities for um for their customers in the process. And a third blocker that we have seen is more on the product side where the some of the employees that we talked to as much as progress has been made by RPF vendors and local local vendors. It's still these tools are not intuitive user friendly for business users. They still feel they need to go through some training programs and have a better user friendly interface is >>what's the entry point she would organization first time I ever heard of Arpaio Years and years and years ago was at a CFO conference. Okay so that's cool. It seems like it forward for there's a lot more C. I. O presence here and that. Is that relatively new or did I just miss it before? >>It is relatively new. So like when we looked at like in the past few years the empty point has been someone in finance or I. T. Has heard about R. P. A. The benefits of head. They went and bought a handful of licenses and then they went and implemented it but it's just a handful of processes. It's not organizational wide. It has been mostly on a smaller sub scale of processes. And projects now that like organizations are realizing employees are asking and we are like slowly growing up with automation ceo es it's now it's intersecting with the C XL level of if it has to intersect with your or if you want to reinvent your business through automation, it has to come from the sea X level and that's where we're seeing more and more. See IOS are being involved in decisions on automation journeys, the technologies they have to buy and adopt for the business processes. >>So I. T. Can be an enabler of course. Also sometimes it can be a blocker. Um and you know, certainly from security standpoint governance etcetera. And so one of the things that we heard today in the keynotes was you don't want to automate the C I. O. He or she owns this application portfolio and everybody wants to do new projects because that's the fun stuff we heard from one CFO. Yeah. You add up all the NPV from the new projects. It's bigger than the valuation of the company. Right. But the C i O is stuck having to manage the infrastructure and all the processes around the existing application portfolio. One of things I heard today was don't automate an application or a process that you're trying to retire because we never get rid of stuff in it. So I wonder should automation like an enterprise wide automation? Should there be kind of an application rationalization exercise or a business process rationalization coincident with that >>initiative? Absolutely. I think that was one of the blockers that we have seen. Like some of the misconceptions and some of the blockers when I looked at it for them, they consider like you're bringing all these tools you're asking business users to like who haven't had haven't been trained in technology or programming, You're asking them to build these automation ins So one they have to manage with the all the applications and the tools for all that happens. And to manage these automation is after business users have either left the company or moved on. So it is essential for them to think through and provide a streamline tools it on on two aspects. one it needs to be as as you started off, it needs to be an enabler to provide them the specific tools that they can, they have already blessed. They've curated it which are ready for business consumption. A second part I can also do is providing collaboration platforms so that business users can learn from each other and from it so that they can one are developing the right processes with the right methodology that is governed by I. T. And no security or data governance issues. Come through. >>One of the things that you mentioned in terms of the three roadblocks ceo uncovered was that you were surprised that the results of the research showed that in fact employees are really wanting to adopt automation. In fact I think the stat is um 86% of employees want automation but only 30% of leaders are giving them the opportunity to use that. That's a big gap. Why do you think that is >>so a few things. Right. I mean as we talked about the three constituents that you have right one is automation leaders. If you consider from them. Their view is their employees are not capable of adopting or building on the automation is using these tools and they need technical skills. But the all the automation vendors have made progress and if you look at the tools today are much more user friendly and business users are willing to adopt. The second part as we talked about is like the fear of job loss from the employee standpoint. Whereas employees are looking at it as an opportunity for them to up skill but also eliminate the pain points that they have today in the day to day activities using the automation tools. And for them it is like this is helping them spend the time with the customers where it matters on critical value added activities versus going through reparative process of the journey. And the third part we talked about earlier with I. T. I. T. Has this notion that they need to build and develop anything technical. Business users will not be able to build or manage and they're also worried about the governance, the security and the third part which you brought up earlier is that tool sprawl, It's like we need to manage like this volume of tools that are coming in which is only adding to their plate of already busy busy workforce. >>I have one of those. It depends questions and it's a good consultant I'm sure you say well it depends but are there patterns best practice or even more than best pressures? Are there sort of play books if you will? And patterns? I'm sure it's situational. But are you seeing patterns emerge, you can say okay this sort of category should approach it this way. Here's another one in a different, maybe it's a department bottoms up top down, can you help us sort of squint through that? >>Yeah. So in terms of approaches like at least up till now the prevalent thing that is happening is like C. O. Es went and buy some licenses they talk about like opportunities that they have. So it's more of a top down driven uh like ceo driven agenda. What we're seeing now especially with citizen automation or democratisation of automation is there's a new approach of including employees into the journey and bringing the bottoms up approach. So there's a happy path where you marry up the top down approach with bottoms up and one you will find opportunities which are organizational wide with the bu leaders and they are ones which are on the long tail of opportunities which employees feel the pain but I. T. Or C. O. He doesn't have the time to come and implement or automate these activities. Um considering like one part we have seen which is increasingly helpful for people who have done this properly is including employees. And one thing we talked yesterday is invest in employees. They consider automation as investment in employees rather than something they're doing to employees. So it's kind of collaborating with employees to make progress which seems to be helping evangelize and also benefit with automation. How >>Have the events of the last 18 months impacted this as well, we've seen so much acceleration and the mandate for automation. What are some of the things that you've seen? >>Sure. So for us like even before the pandemic we've seen in our research so like more than close to 50% of the organizations that they started the automation journey were unable to achieve the savings or targets that they set themselves for whatever the success factors are. Which which hard. A few reasons one they didn't have the organizational support, not they were taking the end to end journey or a customer journey to figure out like what are these big opportunities that they can go through and they haven't included employees and to figure out what are the major pain points to go through the journey. One thing it was clear was with covid, no one expected this kind of disruption in a pan and a pandemic. There are a lot of offshore centres or like pretty much different geography is got disconnected from the work that's being done. You still need to support your customers, there is still a higher demand, what do you do? It's not like you can scale up your employees in a pandemic, that's where like we have seen increasing push towards automation and technology to see that can help and support and scale in a pandemic environment uh and also help your customers in the journey. >>So has in your opinion has automation become a mandate? Uh As a result of the pandemic >>I would say. Yeah I I would consider it's more of like now it's become a I would say uh business won a competitive differentiator to say like one I needed to keep my lights on and resiliency but also the companies have done really well they saw the advantage and they whether the pandemic better with the customers now they use that as a platform to create a competitive differentiation against their peers and push things forward. >>one of the things we heard of today and the keynotes is you got to think about my words, the life cycle, you don't just put in the bot and then just leave it alone. You really have to think through that. And that seems to me to be where you would help customers think through how to get the most return out of their investment. You I passed product company I think it's great. And so you talk about the value layer that you guys bring. >>So for us it's it's like when we talked to mostly be bringing from the business side of the house to understand what are the key drivers that you need to work on. I mean even before we talk about technology, we talk about, let's understand from the customer standpoint what is your customer journey into end and look through that journey lens and let's take the process and to end, let's look at redesigning process and making it more optimal and streamlined and where technology fits in. That's when we talk about like if it is an RPG or if it's a UI Path platform that can support, let's go through that journey versus taking the tool itself as the solution and trying to find every nail that you can hurt, which usually is not sustainable to your point. Like we need to think through the whole life cycle, make sure this is going to last. Or if you are retiring. Like in the ceo panel that was a discussion where that we need to think through when we are going to retire and make sure like we are in that journey versus building all these automation zor bringing all these tools and leaving them alone for I. T. To manage long term. >>No. Again the last 18 months. Again, question about the the um reactions catalyzed facilitated thinking about those three roadblocks. The cognitive roadblocks the organizational roadblocks since particularly what I'm interested in this question and product, what are some of the conversations that you've seen or trends that you seem to help those organizations better understand how to collaborate with each other so that what they're not doing is putting in our P. A point tools but really starting to build the right part of the nomination and and journey into their digital transformation plans. Yeah. >>I mean in a way to again, I'll go back to the three concerns that we talked earlier, right? It's it can only go so far and automate so much because they haven't seen the business lens of like how the processes are what they have to do and to end, which is where you need to involve the business leaders who can give you that view from the business side and employees who are seeing the work day to day and where they can eliminate the pain points. So the organisms that are successful, they are creating a collaborative environment between the three groups to push things forward. You >>have to have that collaboration that's critical. Otherwise, that's probably one of the road blockers as well. >>Yeah, absolutely. >>Where does automation fit? I mean you're obviously heavily into automation, but let's think about the bane portfolio, the boardroom discussions. Where does automation fit? I mean there's security, there's how do we embed ai into our business? How do we sas if I our business um how do we do transform digitally? Where's automation fit in that hole discourse? >>So I think the automation is like at the heart of digital transformation, the part which we have seen where the gap is is not taking the business angle and actually thinking through the process and to end versus picking up a tool and trying to go solve a problem or find a problem to solve. And that's where we think in our discussions with boardrooms, it's more of let's think through how you want to reimagine your company or how you want to be more competitive looking into the future and like walk back from that standpoint and then started part from, I mean, the way we call it the future back like where you are today and now, like let's go forward and to what your end status and where technology broadly a digital tools and where automation fits in the process. >>How do you see what you i path is talking about at this conference? The announcements from yesterday? There's a lot of people here which is fantastic. How do you see what they're announcing? The vision that they set out a couple years ago that they're now delivering on. How is that a facilitator of organizations removing those roadblocks? Because as you said automation is a huge competitive differentiator these days and If we've learned nothing in the last 19 months you gotta you gotta be careful because there's always a competitor in the rear view mirror who might be smaller faster more agile ready to take your place. >>Yeah so like a few things that we've seen in the product roadmap that you talked about is they are providing the collaboration platform or tools where the I. T. Business owners can work through. Like for automation hub is what they talked at length yesterday is that's the platform where business users can provide their ideas. Like you provide process mining tools which can capture the process and the business users understand the process and they are the ones who are putting in an opportunity on the road map. So you have now a platform where all the ideas are being catalogued and once you implement they're being tracked on the automation hub so that that is providing a platform for everyone to collaborate together. The second one which Brandon talked yesterday is the tool itself for Studio X. When we're talking about citizen developers, employees trying to use and make it more user friendly. Is that where the Studio X which is providing that you are interface? Which is easy intuitive for business users to build basic automation is and try to take that long tail of opportunities that we talked about. So all these tools are coming together as one platform play, which you ipod has been talking about all through the conference and that is critical for everyone to collaborate to make a progress versus only thinking it's an easy job to implement the automation opportunities. That >>collaboration is business critical these days. Right. Thank you for joining David me and the program talking about some of the roadblocks that you've uncovered, but also some of the ways that organizations in any industry can navigate around them and really empower those employees who want automation in their jobs. We appreciate your insights. >>Happy to be here. Thanks for having us. You're welcome >>for day Volonte. I'm lisa martin live in las Vegas at UI Path forward for we'll be right back with our next guest. Yeah. >>Yeah. Mm. Mhm

Published Date : Oct 6 2021

SUMMARY :

Four brought to you We're gonna be talking about roadblocks to automation and how to navigate around them, Happy to be here. Talk to us about some of the use cases that bain is working on with you I Path and then we'll dig But also on the automation journey side we need to dig deeper and understand where of the employees that we talked to as much as progress has been made by RPF Is that relatively new or did I just miss it before? the C XL level of if it has to intersect with your or if you And so one of the things that we heard today in the keynotes was you don't want to automate the one it needs to be as as you started off, One of the things that you mentioned in terms of the three roadblocks ceo uncovered was that you were surprised the governance, the security and the third part which you brought up earlier is that tool sprawl, But are you seeing patterns emerge, you can say okay this sort feel the pain but I. T. Or C. O. He doesn't have the time to come What are some of the things that you've seen? the end to end journey or a customer journey to figure out like what are these big opportunities that they can go through advantage and they whether the pandemic better with the customers now they use that as one of the things we heard of today and the keynotes is you got to think about my words, as the solution and trying to find every nail that you can hurt, which usually is not sustainable to The cognitive roadblocks the organizational roadblocks since particularly what I'm interested in this question and product, So the organisms that are successful, they are creating a collaborative environment between the three groups to Otherwise, that's probably one of the road blockers as well. portfolio, the boardroom discussions. I mean, the way we call it the future back like where you are today and now, like let's go forward and to what your How do you see what you i path is talking about at this conference? on the automation hub so that that is providing a platform for everyone to collaborate together. program talking about some of the roadblocks that you've uncovered, but also some of the ways that organizations in any Happy to be here. with our next guest.

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Breaking Analysis: UiPath’s Unconventional $PATH to IPO


 

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> UiPath has had a long, strange trip to IPO. How so you ask? Well, the company was started in 2005. But it's culture, is akin to a frenetic startup. The firm shunned conventions and instead of focusing on a narrow geographic area to prove its product market fit before it started to grow, it aggressively launched international operations prior to reaching unicorn status. Well prior, when it had very little revenue, around a million dollars. Today, more than 60% of UiPath business is outside of the United States. Despite its headquarters being in New York city. There's more, according to recent SEC filings, UiPath total revenue grew 81% last year. But it's free cash flow, is actually positive, modestly. Wait, there's more. The company raised $750 million in a Series F in early February, at a whopping $35 billion valuation. Yet, the implied back of napkin valuation, based on the number of shares outstanding after the offering multiplied by the proposed maximum offering price per share yields evaluation of just under 26 billion. (Dave chuckling) And there's even more to this crazy story. Hello everyone, and welcome to this week's Wikibon CUBE Insights, Powered by ETR. In this Breaking Analysis we'll share our learnings, from sifting through hundreds of pages (paper rustling) of UiPath's red herring. So you didn't have to, we'll share our thoughts on its market, its competitive position and its outlook. Let's start with a question. Mark Roberge, is a venture capitalist. He's a managing director at Stage 2 Capital and he's also a teacher, a professor at the B-School in Harvard. One of his favorite questions that he asks his students and others, is what's the best way to grow a company? And he uses this chart to answer that question. On the vertical axis is customer retention and the horizontal axis is growth to growth rate and you can see he's got modest and awesome and so forth. Now, so I want to let you look at it for a second. What's the best path to growth? Of course you want to be in that green circle. Awesome retention of more than 90% and awesome growth but what's the best way to get there? Should you blitz scale and go for the double double, triple, triple blow it out and grow your go to market team on the horizontal axis or should be more careful and focus on nailing retention and then, and only then go for growth? What do you think? What do you think most VCs would say? What would you say? When you want to maybe run the table, capture the flag before your competitors could get there or would you want to take a more conservative approach? What would Daniel Dines say the CEO of UiPath? Again, I'll let you think about that for a second. Let's talk about UiPath. What did they do? Well, I shared at the top that the company shunned conventions and expanded internationally, very rapidly. Well before it hit escape velocity and they grew like crazy and it got out of control and he had to reign it in, plug some holes, but the growth didn't stop, go. So very clearly based on it's performance and reading through the S1, the company has great retention. It uses a metric called gross retention rate which is at 96 or 97%, very high. Says customers are sticking with it. So maybe that's the right formula go for growth and grow like crazy. Let chaos reign, then reign in the chaos as Andy Grove would say. Go fast horizontally, and you can go vertically. Let me tell you what I think Mark Roberge would say, he told me you can do that. But churn is the silent killer of SaaS companies and perhaps the better path is to nail product market fit. And then your retention metrics, before you go into hyperbolic growth mode. There's all science behind this, which may be antithetical to the way many investors want to roll the dice and go for super growth, like go fast or die. Well, it worked for UiPath you might say, right. Well, no. And this is where the story gets even more interesting and long and strange for UiPath. As we shared earlier, UiPath was founded in 2005 out of Bucharest Romania. The company actually started as a software outsourcing startup. It called the company, DeskOver and it built automation libraries and SDKs for companies like Microsoft, IBM and Google and others. It also built automation scripts and developed importantly computer vision technology which became part of its secret sauce. In December 2015, DeskOver changed its name to UiPath and became a Delaware Corp and moved its headquarters to New York City a couple of years later. So our belief is that UiPath actually took the preferred path of Mark Roberge, five ticks North, then five more East. They slow-cooked for the better part of 10 years trying to figure out what market to serve. And they spent that decade figuring out their product market fit. And then they threw gas in the fire. Pretty crazy. All right, let's take a peak (chuckling) at the takeaways from the UiPath S1 the numbers are impressive. 580 million ARR with 65% growth. That asterisk is there because like you, we thought ARR stood for annual recurring revenue. It really stands for annualized renewal run rate. annualized renewal run rate is a metric that is one of UiPath's internal KPIs and are likely communicate that publicly over time. We'll explain that further in a moment. UiPath has a very solid customer base. Nearly 8,000, I've interviewed many of them. They're extremely happy. They have very high retention. They get great penetration into the fortune 500, around 63% of the fortune 500 has UiPath. Most of UiPath business around 70% comes from existing customers. I always say you're going to get more money out of existing customers than new customers but everybody's trying to go out and get new customers. But UiPath I think is taking a really interesting approach. It's their land and expand and they didn't invent that term but I'll come back to that. It kind of reminds me of the early days of Tableau. Actually I think Tableau is an interesting example. Like UiPath, Tableau started out as pretty much a point tool and it had, but it had very passionate customers. It was solving problems. It was simplifying things. And it would have bid into a company and grow and grow. Now the market fundamentals for UiPath are very good. Automation is super hot right now. And the pandemic has created an automation mandate to date and I'll share some data there as well. UiPath is a leader. I'm going to show you the Gartner Magic Quadrant for RPA. That's kind of a good little snapshot. UiPath pegs it's TAM at 60 billion dollars based on some bottoms up calculations and some data from Bain. Pre-pandemic, we pegged it at over 30 billion and we felt that was conservative. Post-pandemic, we think the TAM is definitely higher because of that automation mandate, it's been accelerated. Now, according to the S1, UiPath is going to raise around 1.2 billion. And as we said, if that's an implied valuation that is lower than the Series F, so we suspect the Series F investors have some kind of ratchet in there. UiPath needed the cash from its Series F investors. So it took in 750 million in February and its balance sheet in the S1 shows about 474 million in cash and equivalent. So as I say, it needed that cash. UiPath has had significant expense reductions that we'll show you in some detail. And it's brought in some fresh talent to provide some adult supervision around 70% of its executive leadership team and outside directors came to the company after 2019 and the company's S1, it disclosed that it's independent accounting firm identified last year what it called the "material weakness in our internal controls over financial report relating to revenue recognition for the fiscal year ending 2018, caused by a lack of oversight and technical competence within the finance department". Now the company outlined the steps it took to remediate the problem, including hiring new talent. However, we said that last year, we felt UiPath wasn't quite ready to go public. So it really had to get its act together. It was not as we said at the time, the well-oiled machine, that we said was Snowflake under Mike Scarpelli's firm operating guidance. The guy's the operational guru, but we suspect the company wants to take advantage of this mock market. It's a good time to go public. It needs the cash to bolster its balance sheet. And the public offering is going to give it cache in a stronger competitive posture relative to its main new competitor, autumn newbie competitor Automation Anywhere and the big whales like Microsoft and others that aspire and are watching what UiPath is doing and saying, hey we want a piece of that action. Now, one other note, UiPath's CEO Daniel Dines owns 100% of the class B shares of the company and has a 35 to one voting power. So he controls the company, subject of course to his fiduciary responsibilities but if UiPath, let's say it gets in trouble financially, he has more latitude to do secondary offerings. And at the same time, it's insulated from activist shareholders taking over his company. So lots of detail in the S1 and we just wanted to give you some of those highlights. Here are the pretty graphs. If whoever wrote this F1 was a genius. It's just beautiful. As we said, ARR, annualized renewal run rate all it does is it annualizes the invoice amount from subscriptions in the maintenance portion of the revenue. In other words, the parts that are recurring revenue, it excludes revenue from support and perpetual license. Like one-time licenses and services is just kind of the UiPath's and maybe that's some sort of legacy there. It's future is that recurring revenue. So it's pretty similar to what we think of as ARR, but it's not exact. Lots of customers with a growing number of six and seven figure accounts and a dollar-based net retention of 145%. This figure represents the rate of net expansion of the UiPath ARR, from existing listing customers over a 12 month period. Translation. This says UiPath's existing customers are spending more with the company, land and expand and we'll share some data from ETR on that. And as you can see, the growth of 86% CAGR over the past nine quarters, very impressive. Let's talk about some of the fundamentals of UiPath's business. Here's some data from the Brookings Institute and the OECD that shows productivity statistics for the US. The smaller charts in the right are for Germany and Japan. And I've shared some similar data before the US showed in the middle there. Showed productivity improvements with the personal productivity boom in the mid to late 90s. And it spilled into the early 2000s. But since then you can see it's dropped off quite significantly. Germany and Japan are also under pressure as are most developed countries. China's labor productivity might show declines but it's level, is at level significantly higher than these countries, April 16th headline of the Wall Street Journal says that China's GDP grew 18% this quarter. So, we've talked about the snapback in post-COVID and the post-isolation economy, but these are kind of one time bounces. But anyway, the point is we're reaching the limits of what humans can do alone to solve some of the world's most pressing challenges. And automation is one key to shifting labor away from these more mundane tasks toward more productive and more important activities that can deliver lasting benefits. This according to UiPath, is its stated purpose to accelerate human achievement, big. And the market is ready to be automated, for the most part. Now the post-isolation economy is increasingly going to focus on automation to drive toward activity as we've discussed extensively, I got to share the RPA Magic Quadrant where nearly everyone's a winner, many people are of course happy. Many companies are happy, just to get into the Magic Quadrant. You can't just, you have to have certain criteria. So that's good. That's what I mean by everybody wins. We've reported extensively on UiPath and Automation Anywhere. Yeah, we think we might shuffle the deck a little bit on this picture. Maybe creating more separation between UiPath and Automation Anywhere and the rest. And from our advantage point, UiPath's IPO is going to either force Automation Anywhere to respond. And I don't know what its numbers are. I don't know if it's ready. I suspect it's not, we'd see that already but I bet you it's trying to get there. Or if they don't, UiPath is going to extend its lead even further, that would be our prediction. Now personally, I would have Pegasystems higher on the vertical. Of course they're not an IPO, RPA specialist, so I kind of get what Gartner is doing there but I think they're executing well. And I'd probably, in a broader context I'd probably maybe drop blue prism down a little bit, even though last year was a pretty good year for the company. And I would definitely have Microsoft looming larger up in the upper left as a challenger more than a visionary in my opinion, but look, Gartner does good work and its analysts are very deep into this stuff, deeper than I am. So I don't want to discount that. It's just how I see it. Let's bring in the ETR data and show some of the backup here. This is a candlestick chart that shows the components of net score, which is spending momentum, however, ETR goes out every quarter. Says you're spending more, you're spending less. They subtract the lesses from the mores and that's net score. It's more complicated than that, but that's that blue line that you see in the top and yes it's trending downward but it's still highly elevated. We'll talk about that. The market share is in the yellow line at the bottom there. That green represents the percentage of customers that are spending more and the reds are spending less or replacing. That gray is flat. And again, even though UiPath's net score is declining, it's that 61%, that's a very elevated score. Anything over 40% in our view is impressive. So it's, UiPath's been holding in the 60s and 70s percents over the past several years. That's very good. Now that yellow line market share, yes it dips a bit, but again it's nuanced. And this is because Microsoft is so pervasive in the data stat. It's got so many mentions that it tends to somewhat overwhelm and skew these curves. So let's break down net score a little bit. Here's another way to look at this data. This is a wheel chart we show this often it shows the components of net score and what's happening here is that bright red is defection. So look at it, it's very small that wouldn't be churn. It's tiny. Remember that it's churn is the killer for software companies. And so that forest green is existing customers spending more at 49%, that's big. That lime green is new customers. So again, it's from the S1, 70% of UiPath's revenue comes from existing customers. And this really kind of underscores that. Now here's more evidence in the ETR data in terms of land and expand. This is a snapshot from the January survey and it lines up UiPath next to its competitors. And it cuts the data just on those companies that are increasing spending. It's so that forest green that we saw earlier. So what we saw in Q1 was the pace of new customer acquisition for UiPath was decelerating from previous highs. But UiPath, it shows here is outpacing its competition in terms of increasing spend from existing customers. So we think that's really important. UiPath gets very high scores in terms of customer satisfaction. There's, I've talked to many in theCUBE. There's places on the web where we have customer ratings. And so you want to check that out, but it'll confirm that the churn is low, satisfaction is high. Yeah, they get dinged sometimes on pricing. They get dinged sometimes, lately on service cause they're growing so fast. So, maybe they've taken the eye off the ball in a couple of counts, but generally speaking clients are leaning in, they're investing heavily. They're creating centers of excellence around RPA and automation, and UiPath is very focused on that. Again, land and expand. Now here's further evidence that UiPath has a strong account presence, even in accounts where its competitors are presence. In the 149 shared accounts from the Q1 survey where UiPath, Automation Anywhere and Microsoft have a presence, UiPath's net score or spending velocity is not only highly elevated, it's relative momentum, is accelerating compared to last year. So there's some really good news in the numbers but some other things stood out in the S1 that are concerning or at least worth paying attention to. So we want to talk about that. Here is the income statement and look at the growth. The company was doing like 1 million dollars in 2015 like I said before. And when it started to expand internationally it surpassed 600 million last year. It's insane growth. And look at the gross profit. Gross margin is almost 90% because revenue grew so rapidly. And last year, its cost went down in some areas like its services, less travel was part of that. Now jump down to the net loss line. And normally you would expect a company growing at this rate to show a loss. The street wants growth and UiPath is losing money, but it's net loss went from 519 million, half a billion down to only 92 million. And that's because the operating expenses went way down. Now, again, typically a company growing at this rate would show corresponding increases in sales and marketing expense, R&D and even G&A but all three declined in the past 12 months. Now reading the notes, there was definitely some meaningful savings from no travel and canceled events. UiPath has great events around the world. In fact theCUBE, Knock Wood is going to be at its event in October, in Las Vegas at the Bellagio . So we're stoked for that. But, to drop expenses that precipitously with such high growth, is kind of strange. Go look at Snowflake's income statement. They're in hyper-growth as well. We like to compare it to Snowflake is a very well-run company and it's in hyper-growth mode, but it's sales and marketing and R&D and G&A expense lines. They're all growing along with that revenue. Now, perhaps they're growing at a slower rate. Perhaps the percent of revenue is declining as it should as they achieve operating leverage but they're not shrinking in absolute dollar terms as shown in the UiPath S1. So either UiPath has applied some magic automation mojo to it's business (chuckling). Like magic beans or magic grits with my cousin Vinny. Maybe it has found the Holy grail of operating leverage. It's a company that's all about automation or the company was running way too hot on the expense side and had a cut and clean up its income statement for the IPO and conserve some cash. Our guess is the latter but maybe there's a combination there. We'll give him the benefit of the doubt. And just to add a bit more to this long, strange trip. When have you seen an explosive growth company just about to go public, show positive cashflow? Maybe it's happened, but it's rare in the tech and software business these days. Again, go look at companies like Snowflake. They're not showing positive cashflow, not yet anyway. They're growing and trying to run the table. So you have to ask why is UiPath operating this way? And we think it's because they were so hot and burning cash that they had to reel things in a little bit and get ready to IPO. It's going to be really interesting to see how this stock reacts when it does IPO. So here's some things that we want you to pay attention to. We have to ask. Is this IPO, is it window dressing? Or did UiPath again uncover some new productivity and operating leverage model. I doubt there's anything radically new here. This company doesn't want to miss the window. So I think it said, okay, let's do this. Let's get ready for IPO. We got to cut expenses. It had a lot of good advisors. It surrounded itself with a new board. Extended that board, new management, and really want to take advantage of this because it needs the cash. In addition, it really does want to maintain its lead. It's got Automation Anywhere competing with it. It's got Microsoft looming large. And so it wants to continue to lead. It's made some really interesting acquisitions. It's got very strong vision as you saw in the Gartner Magic Quadrant and obviously it's executing well but it's really had to tighten things up. So we think it's used the IPO as a fortune forcing function to really get its house in order. Now, will the automation mandate sustain? We think it will. The forced match to digital worked, it was effective. It wasn't pleasant, but even in a downturn we think it will confer advantage to automation players and particularly companies like UiPath that have simplified automation in a big way and have done a great job of putting in training, great freemium model and has a culture that is really committed to the future of humankind. It sounds ambitious and crazy but talk to these people, you'll see it's true. Pricing, UiPath had to dramatically expand or did dramatically expand its portfolio and had to reprice everything. And I'm not so worried about that. I think it'll figure that pricing out for that portfolio expansion. My bigger concern is for SaaS companies in general. I don't like SaaS pricing that has been popularized by Workday and ServiceNow, and Salesforce and DocuSign and all these companies that essentially lock you in for a year or two and basically charge you upfront. It's really is a one-way street. You can't dial down. You can only dial up. It's not true Cloud pricing. You look at companies like Stripe and Datadog and Snowflake. It is true Cloud pricing. It's consumption pricing. I think the traditional SaaS pricing model is flawed. It's very unfairly weighted toward the vendors and I think it's going to change. Now, the reason we put cloud on the chart is because we think Cloud pricing is the right way to price. Let people dial up and dial down, let them cancel anytime and compete on the basis of your product excellence. And yeah, give them a price concession if they do lock in. But the starting point we think should be that flexibility, pay by the drink. Cancel anytime. I mentioned some companies that are doing that as well. If you look at the modern SaaS startups and the forward-thinking VCs they're really pushing their startups to this model. So we think over time that the term lock-in model is going to give way to true consumption-based pricing and at the clients option, allow them to lock-in for a better price, way better model. And UiPath's Cloud revenue today is minimal but over time, we think it's going to continue to grow that cloud. And we think it will force a rethink in pricing and in revenue recognition. So watch for that. How is the street going to react to Daniel Dines having basically full control of the company? Generally, we feel that that solid execution if UiPath can execute is going to outweigh those concerns. In fact, I'm very confident that it will. We'll see, I kind of like what the CEO says has enough mojo to say (chuckling) you know what, I'm not going to let what happened to for instance, EMC happen to me. You saw Michael Dell do that. You saw just this week they're spinning out VMware, he's maintaining his control. VMware Dell shareholders get get 40.44 shares for every Dell share they're holding. And who's the biggest shareholder? Michael Dell. So he's, you got two companies, one chairman. He's controlling the table. Michael Dell beat the great Icahn. Who beats Carl Icahn? Well, Michael Dell beats Carl Icahn. So Daniel Dines has looked at that and says, you know what? I'm not just going to give up my company. And the reason I like that with an if, is that we think will allow the company to focus more on the long-term. The if is, it's got to execute otherwise it's so much pressure and look, the bottom line is that UiPath has really favorable market momentum and fundamentals. But it is signing up for the 90 day short clock. The fact that the CEO has control again means they can look more long term and invest accordingly. Oftentimes that's easier said than done. It does come down to execution. So it is going to be fun to watch (chuckling). That's it for now, thanks to the community for your comments and insights and really always appreciate your feedback. Remember, I publish each week on Wikibon.com and siliconangle.com and these episodes are all available as podcasts. All you got to do is search for the Breaking Analysis podcast. You can always connect with me on Twitter @dvellante or email me at david.vellante@siliconangle.com or comment on my LinkedIn posts. And we'll see you in clubhouse. Follow me and get notified when we start a room, which we've been doing with John Furrier and Sarbjeet Johal and others. And we love to riff on these topics and don't forget, please check out etr.plus for all the survey action. This is Dave Vellante, for theCUBE Insights Powered by ETR. Be well everybody. And we'll see you next time. (gentle upbeat music)

Published Date : Apr 17 2021

SUMMARY :

This is Breaking Analysis And the market is ready to be automated,

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Breaking Analysis: Best of theCUBE on Cloud


 

>> Narrator: From theCUBE Studios in Palo Alto, in Boston bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> The next 10 years of cloud, they're going to differ dramatically from the past decade. The early days of cloud, deployed virtualization of standard off-the-shelf components, X86 microprocessors, disk drives et cetera, to then scale out and build a large distributed system. The coming decade is going to see a much more data-centric, real-time, intelligent, call it even hyper-decentralized cloud that will comprise on-prem, hybrid, cross-cloud and edge workloads with a services layer that will obstruct the underlying complexity of the infrastructure which will also comprise much more custom and varied components. This was a key takeaway of the guests from theCUBE on Cloud, an event hosted by SiliconANGLE on theCUBE. Welcome to this week's Wikibon CUBE Insights Powered by ETR. In this episode, we'll summarize the findings of our recent event and extract the signal from our great guests with a couple of series and comments and clips from the show. CUBE on Cloud is our very first virtual editorial event. It was designed to bring together our community in an open forum. We ran the day on our 365 software platform and had a great lineup of CEOs, CIOs, data practitioners technologists. We had cloud experts, analysts and many opinion leaders all brought together in a day long series of sessions that we developed in order to unpack the future of cloud computing in the coming decade. Let me briefly frame up the conversation and then turn it over to some of our guests. First, we put forth our view of how modern cloud has evolved and where it's headed. This graphic that we're showing here, talks about the progression of cloud innovation over time. A cloud like many innovations, it started as a novelty. When AWS announced S3 in March of 2006, nobody in the vendor or user communities really even in the trade press really paid too much attention to it. Then later that year, Amazon announced EC2 and people started to think about a new model of computing. But it was largely tire kickers, bleeding-edge developers that took notice and really leaned in. Now the financial crisis of 2007 to 2009, really created what we call a cloud awakening and it put cloud on the radar of many CFOs. Shadow IT emerged within departments that wanted to take IT in bite-sized chunks and along with the CFO wanted to take it as OPEX versus CAPEX. And then I teach transformation that really took hold. We came out of the financial crisis and we've been on an 11-year cloud boom. And it doesn't look like it's going to stop anytime soon, cloud has really disrupted the on-prem model as we've reported and completely transformed IT. Ironically, the pandemic hit at the beginning of this decade, and created a mandate to go digital. And so it accelerated the industry transformation that we're highlighting here, which probably would have taken several more years to mature but overnight the forced March to digital happened. And it looks like it's here to stay. Now the next wave, we think we'll be much more about business or industry transformation. We're seeing the first glimpses of that. Holger Mueller of Constellation Research summed it up at our event very well I thought, he basically said the cloud is the big winner of COVID. Of course we know that now normally we talk about seven-year economic cycles. He said he was talking about for planning and investment cycles. Now we operate in seven-day cycles. The examples he gave where do we open or close the store? How do we pivot to support remote workers without the burden of CAPEX? And we think that the things listed on this chart are going to be front and center in the coming years, data AI, a fully digitized and intelligence stack that will support next gen disruptions in autos, manufacturing, finance, farming and virtually every industry where the system will expand to the edge. And the underlying infrastructure across physical locations will be hidden. Many issues remain, not the least of which is latency which we talked about at the event in quite some detail. So let's talk about how the Big 3 cloud players are going to participate in this next era. Well, in short, the consensus from the event was that the rich get richer. Let's take a look at some data. This chart shows our most recent estimates of IaaS and PaaS spending for the Big 3. And we're going to update this after earning season but there's a couple of points stand out. First, we want to make the point that combined the Big 3 now account for almost $80 billion of infrastructure spend last year. That $80 billion, was not all incremental (laughs) No it's caused consolidation and disruption in the on-prem data center business and within IT shops companies like Dell, HPE, IBM, Oracle many others have felt the heat and have had to respond with hybrid and cross cloud strategies. Second while it's true that Azure and GCP they appear to be growing faster than AWS. We don't know really the exact numbers, of course because only AWS provides a clean view of IaaS and passwords, Microsoft and Google. They kind of hide them all ball on their numbers which by the way, I don't blame them but they do leave breadcrumbs and clues on growth rates. And we have other means of estimating through surveys and the like, but it's undeniable Azure is closing the revenue gap on AWS. The third is that I like the fact that Azure and Google are growing faster than AWS. AWS is the only company by our estimates to grow its business sequentially last quarter. And in and of itself, that's not really enough important. What is significant is that because AWS is so large now at 45 billion, even at their slower growth rates it grows much more in absolute terms than its competitors. So we think AWS is going to keep its lead for some time. We think Microsoft and AWS will continue to lead the pack. You know, they might converge maybe it will be a 200 just race in terms of who's first who's second in terms of cloud revenue and how it's counted depending on what they count in their numbers. And Google look with its balance sheet and global network. It's going to play the long game and virtually everyone else with the exception of perhaps Alibaba is going to be secondary players on these platforms. Now this next graphic underscores that reality and kind of lays out the competitive landscape. What we're showing here is survey data from ETR of more than 1400 CIOs and IT buyers and on the vertical axis is Net Score which measures spending momentum on the horizontal axis is so-called Market Share which is a measure of pervasiveness in the data set. The key points are AWS and Microsoft look at it. They stand alone so far ahead of the pack. I mean, they really literally, it would have to fall down to lose their lead high spending velocity and large share of the market or the hallmarks of these two companies. And we don't think that's going to change anytime soon. Now, Google, even though it's far behind they have the financial strength to continue to position themselves as an alternative to AWS. And of course, an analytics specialist. So it will continue to grow, but it will be challenged. We think to catch up to the leaders. Now take a look at the hybrid zone where the field is playing. These are companies that have a large on-prem presence and have been forced to initiate a coherent cloud strategy. And of course, including multicloud. And we include Google in this so pack because they're behind and they have to take a differentiated approach relative to AWS, and maybe cozy up to some of these traditional enterprise vendors to help Google get to the enterprise. And you can see from the on-prem crowd, VMware Cloud on AWS is stands out as having some, some momentum as does Red Hat OpenShift, which is it's cloudy, but it's really sort of an ingredient it's not really broad IaaS specifically but it's a component of cloud VMware cloud which includes VCF or VMware Cloud Foundation. And even Dell's cloud. We would expect HPE with its GreenLake strategy. Its financials is shoring up, should be picking up momentum in the future in terms of what the customers of this survey consider cloud. And then of course you could see IBM and Oracle you're in the game, but they don't have the spending momentum and they don't have the CAPEX chops to compete with the hyperscalers IBM's cloud revenue actually dropped 7% last quarter. So that highlights the challenges that that company facing Oracle's cloud business is growing in the single digits. It's kind of up and down, but again underscores these two companies are really about migrating their software install basis to their captive clouds and as well for IBM, for example it's launched a financial cloud as a way to differentiate and not take AWS head-on an infrastructure as a service. The bottom line is that other than the Big 3 in Alibaba the rest of the pack will be plugging into hybridizing and cross-clouding those platforms. And there are definitely opportunities there specifically related to creating that abstraction layer that we talked about earlier and hiding that underlying complexity and importantly creating incremental value good examples, snowfallLike what snowflake is doing with its data cloud, what the data protection guys are doing. A company like Loomio is headed in that direction as are others. So, you keep an eye on that and think about where the white space is and where the value can be across-clouds. That's where the opportunity is. So let's see, what is this all going to look like? How does the cube community think it's going to unfold? Let's hear from theCUBE Guests and theCUBE on Cloud speakers and some of those highlights. Now, unfortunately we don't have time to show you clips from every speaker. We are like 10-plus hours of video content but we've tried to pull together some comments that summarize the sentiment from the community. So I'm going to have John Furrier briefly explain what theCUBE on Cloud is all about and then let the guests speak for themselves. After John, Pradeep Sindhu is going to give a nice technical overview of how the cloud was built out and what's changing in the future. I'll give you a hint it has to do with data. And then speaking of data, Mai-Lan Bukovec, who heads up AWS is storage portfolio. She'll explain how she views the coming changes in cloud and how they look at storage. Again, no surprise, it's all about data. Now, one of the themes that you'll hear from guests is the notion of a distributed cloud model. And Zhamak Deghani, he was a data architect. She'll explain her view of the future of data architectures. We also have thoughts from analysts like Zeus Karavalla and Maribel Lopez, and some comments from both Microsoft and Google to compliment AWS's view of the world. In fact, we asked JG Chirapurath from Microsoft to comment on the common narrative that Microsoft products are not best-to-breed. They put out a one dot O and then they get better, or sometimes people say, well, they're just good enough. So we'll see what his response is to that. And Paul Gillin asks, Amit Zavery of Google his thoughts on the cloud leaderboard and how Google thinks about their third-place position. Dheeraj Pandey gives his perspective on how technology has progressed and been miniaturized over time. And what's coming in the future. And then Simon Crosby gives us a framework to think about the edge as the most logical opportunity to process data not necessarily a physical place. And this was echoed by John Roese, and Chris Wolf to experience CTOs who went into some great depth on this topic. Unfortunately, I don't have the clips of those two but their comments can be found on the CTO power panel the technical edge it's called that's the segment at theCUBE on Cloud events site which we'll share the URL later. Now, the highlight reel ends with CEO Joni Klippert she talks about the changes in securing the cloud from a developer angle. And finally, we wrap up with a CIO perspective, Dan Sheehan. He provides some practical advice on building on his experience as a CIO, COO and CTO specifically how do you as a business technology leader deal with the rapid pace of change and still be able to drive business results? Okay, so let's now hear from the community please run the highlights. >> Well, I think one of the things we talked about COVID is the personal impact to me but other people as well one of the things that people are craving right now is information, factual information, truth, textures that we call it. But here this event for us Dave is our first inaugural editorial event. Rob, both Kristen Nicole the entire cube team, SiliconANGLE on theCUBE we're really trying to put together more of a cadence. We're going to do more of these events where we can put out and feature the best people in our community that have great fresh voices. You know, we do interview the big names Andy Jassy, Michael Dell, the billionaires of people making things happen, but it's often the people under them that are the real Newsmakers. >> If you look at the architecture of cloud data centers the single most important invention was scale-out. Scale-out of identical or near identical servers all connected to a standard IP ethernet network. That's the architecture. Now the building blocks of this architecture is ethernet switches which make up the network, IP ethernet switches. And then the server is all built using general purpose x86 CPU's with DRAM, with SSD, with hard drives all connected to inside the CPU. Now, the fact that you scale these server nodes as they're called out was very, very important in addressing the problem of how do you build very large scale infrastructure using general purpose compute but this architecture, Dave is a compute centric architecture. And the reason it's a compute centric architecture is if you open this, is server node. What you see is a connection to the network typically with a simple network interface card. And then you have CPU's which are in the middle of the action. Not only are the CPU's processing the application workload but they're processing all of the IO workload what we call data centric workload. And so when you connect SSDs and hard drives and GPU is everything to the CPU, as well as to the network you can now imagine that the CPU is doing two functions. It's running the applications but it's also playing traffic cop for the IO. So every IO has to go to the CPU and you're executing instructions typically in the operating system. And you're interrupting the CPU many many millions of times a second. Now general purpose CPU and the architecture of the CPU's was never designed to play traffic cop because the traffic cop function is a function that requires you to be interrupted very, very frequently. So it's critical that in this new architecture where does a lot of data, a lot of these stress traffic the percentage of workload, which is data centric has gone from maybe one to 2% to 30 to 40%. >> The path to innovation is paved by data. If you don't have data, you don't have machine learning you don't have the next generation of analytics applications that helps you chart a path forward into a world that seems to be changing every week. And so in order to have that insight in order to have that predictive forecasting that every company needs, regardless of what industry that you're in today, it all starts from data. And I think the key shift that I've seen is how customers are thinking about that data, about being instantly usable. Whereas in the past, it might've been a backup. Now it's part of a data Lake. And if you can bring that data into a data lake you can have not just analytics or machine learning or auditing applications it's really what does your application do for your business and how can it take advantage of that vast amount of shared data set in your business? >> We are actually moving towards decentralization if we think today, like if it let's move data aside if we said is the only way web would work the only way we get access to various applications on the web or pages to centralize it We would laugh at that idea. But for some reason we don't question that when it comes to data, right? So I think it's time to embrace the complexity that comes with the growth of number of sources, the proliferation of sources and consumptions models, embrace the distribution of sources of data that they're not just within one part of organization. They're not just within even bounds of organizations that are beyond the bounds of organization. And then look back and say, okay, if that's the trend of our industry in general, given the fabric of compensation and data that we put in, you know, globally in place then how the architecture and technology and organizational structure incentives need to move to embrace that complexity. And to me that requires a paradigm shift a full stack from how we organize our organizations how we organize our teams, how we put a technology in place to look at it from a decentralized angle. >> I actually think we're in the midst of the transition to what's called a distributed cloud, where if you look at modernized cloud apps today they're actually made up of services from different clouds. And also distributed edge locations. And that's going to have a pretty profound impact on the way we go vast. >> We wake up every day, worrying about our customer and worrying about the customer condition and to absolutely make sure we dealt with the best in the first attempt that we do. So when you take the plethora of products we've dealt with in Azure, be it Azure SQL be it Azure cosmos DB, Synapse, Azure Databricks, which we did in partnership with Databricks Azure machine learning. And recently when we sort of offered the world's first comprehensive data governance solution and Azure overview, I would, I would humbly submit to you that we are leading the way. >> How important are rankings within the Google cloud team or are you focused mainly more on growth and just consistency? >> No, I don't think again, I'm not worried about we are not focused on ranking or any of that stuff. Typically I think we are worried about making sure customers are satisfied and the adding more and more customers. So if you look at the volume of customers we are signing up a lot of the large deals we did doing. If you look at the announcement we've made over the last year has been tremendous momentum around that. >> The thing that is really interesting about where we have been versus where we're going is we spend a lot of time talking about virtualizing hardware and moving that around. And what does that look like? And creating that as more of a software paradigm. And the thing we're talking about now is what does cloud as an operating model look like? What is the manageability of that? What is the security of that? What, you know, we've talked a lot about containers and moving into different, DevSecOps and all those different trends that we've been talking about. Like now we're doing them. So we've only gotten to the first crank of that. And I think every technology vendor we talked to now has to address how are they are going to do a highly distributed management insecurity landscape? Like, what are they going to layer on top of that? Because it's not just about, oh, I've taken a rack of something, server storage, compute, and virtualized it. I know have to create a new operating model around it in a way we're almost redoing what the OSI stack looks like and what the software and solutions are for that. >> And the whole idea of we in every recession we make things smaller. You know, in 91 we said we're going to go away from mainframes into Unix servers. And we made the unit of compute smaller. Then in the year, 2000 windows the next bubble burst and the recession afterwards we moved from Unix servers to Wintel windows and Intel x86 and eventually Linux as well. Again, we made things smaller going from million dollar servers to $5,000 servers, shorter lib servers. And that's what we did in 2008, 2009. I said, look, we don't even need to buy servers. We can do things with virtual machines which are servers that are an incarnation in the digital world. There's nothing in the physical world that actually even lives but we made it even smaller. And now with cloud in the last three, four years and what will happen in this coming decade. They're going to make it even smaller not just in space, which is size, with functions and containers and virtual machines, but also in time. >> So I think the right way to think about edges where can you reasonably process the data? And it obviously makes sense to process data at the first opportunity you have but much data is encrypted between the original device say and the application. And so edge as a place doesn't make as much sense as edge as an opportunity to decrypt and analyze it in the care. >> When I think of Shift-left, I think of that Mobius that we all look at all of the time and how we deliver and like plan, write code, deliver software, and then manage it, monitor it, right like that entire DevOps workflow. And today, when we think about where security lives, it either is a blocker to deploying production or most commonly it lives long after code has been deployed to production. And there's a security team constantly playing catch up trying to ensure that the development team whose job is to deliver value to their customers quickly, right? Deploy as fast as we can as many great customer facing features. They're then looking at it months after software has been deployed and then hurrying and trying to assess where the bugs are and trying to get that information back to software developers so that they can fix those issues. Shifting left to me means software engineers are finding those bugs as they're writing code or in the CIC CD pipeline long before code has been deployed to production. >> During this for quite a while now, it still comes down to the people. I can get the technology to do what it needs to do as long as they have the right requirements. So that goes back to people making sure we have the partnership that goes back to leadership and the people and then the change management aspects right out of the gate, you should be worrying about how this change is going to be how it's going to affect, and then the adoption and an engagement, because adoption is critical because you can go create the best thing you think from a technology perspective. But if it doesn't get used correctly, it's not worth the investment. So I agree, what is a digital transformation or innovation? It still comes down to understand the business model and injecting and utilizing technology to grow our reduce costs, grow the business or reduce costs. >> Okay, so look, there's so much other content on theCUBE on Cloud events site we'll put the link in the description below. We have other CEOs like Kathy Southwick and Ellen Nance. We have the CIO of UI path. Daniel Dienes talks about automation in the cloud and Appenzell from Anaplan. And a plan is not her company. By the way, Dave Humphrey from Bain also talks about his $750 million investment in Nutanix. Interesting, Rachel Stevens from red monk talks about the future of software development in the cloud and CTO, Hillary Hunter talks about the cloud going vertical into financial services. And of course, John Furrier and I along with special guests like Sergeant Joe Hall share our take on key trends, data and perspectives. So right here, you see the coupon cloud. There's a URL, check it out again. We'll, we'll pop this URL in the description of the video. So there's some great content there. I want to thank everybody who participated and thank you for watching this special episode of theCUBE Insights Powered by ETR. This is Dave Vellante and I'd appreciate any feedback you might have on how we can deliver better event content for you in the future. We'll be doing a number of these and we look forward to your participation and feedback. Thank you, all right, take care, we'll see you next time. (upbeat music)

Published Date : Jan 22 2021

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Dave Humphrey, Bain Capital | theCUBE on Cloud 2021


 

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by Silicon angle. Hello. We wanna welcome back to the Cuban cloud where we're talking to CEOs, C. E. O s, chief technology officers and investors. On the future of Cloud with me is Dave Humphrey, who is the managing director and co head of Private Equity North America at Bain Capital. They've welcome to the Cube. First time, I think. >>First time. Yeah, David, thanks very much for having so >>let's get right into it. As an investor, how are you thinking about the evolution of cloud? When you look back at the last decade, you know it's not gonna be the same, uh, in this coming decade, you know, Thio ironic 2020 is has thrown us into, you know, the accelerated digital transformation and cloud. But how do you look at the evolution of cloud from an investment perspective? What's your thesis? >>That's a great question, David. You know, for us, we're focused on investing in technology and really across the economy. And I'd say the cloud is the overarching trends and dynamic in the technology markets. And really, for two reasons, one is a major shift. Of course, that's going on. But the second and frankly, even more interesting one to us is all the growth that the cloud is creating in the technology marketplace. You know the ship. It has been well covered. But five years ago in 2015, by our analysis, two thirds of all computing workloads were done on premises and Onley. Five years later, that's that's flipped. So two thirds of all computing workloads now done done in the cloud. And, of course, that shift. There's a lot of ramifications as an investor. But even more interesting dust is the growth in technology and the usage of technology that the cloud is creating. So over that same period of time, the total number of computing workloads run has increased by 2.6 times just a five year period time, which is really a a dramatic thing. And it makes sense when you think about all the new software applications that could be created, all the data that could be used by new users and new segments, and the real time inside that could be gleaned from that is that growth that really were focused on investing behind a Z. Investors in technology. You >>know, it's interesting you just took share those numbers and you hear a lot of numbers. I I actually think you you know, you your even being conservative. You know, Ginny Rometty used to talk about 80% of workloads or are still on Prem. Andy Jassy it reinvent said that 96% of spending is still on premises. So that was kind of an interesting stat. And I guess the other thing that I would, I would note is it's not just a share shift. It is. It's not just, you know, the cloud eating away it on Prem. We've clearly seen that, but there's also incremental opportunity as well. If you look at snowflake, for example, and adding value on top of, you know across multiple clouds and creating new markets, so there's there's that, you know, double that 12 punch of stealing share from on Prem but also incremental growth, which is probably accelerated as a result of this, you know, compressed digital transformation. So when you look at the Big Three cloud players, I mean roughly speaking, they probably account for $80 billion in total revenue which I guess is a small portion of the overall I t. Market. So it has a a long way to go. But But what's the best way to get good returns from an investment standpoint without getting clobbered by their tendency to sometimes coop some of the best ideas and put them on their primary services? >>Yeah, absolutely. Well, you know, for us, uh, it really comes back to the same fundamental principles we look for in any investment, which is finding a business that solves a really important problem for its customers and does so in a way that's really advantaged vs competition can and do something that other competitors just can't do, whether those be the hyper scale is that you're describing or, you know, other specialized and focused competitors, and then finding a way that we can partner with those companies to help them to accelerate their growth. So surely the growth of the likes of AWS and Microsoft and Google, as you're describing, has been a profound competitive shift, along with the cloud shift that we've all talked about. And those companies, of course, can offer and do things that you past purveyors of computing couldn't. But fundamentally, they're selling and infrastructure layer, and there is room for all sorts of new competitors and new applications that can do something better than anybody else can. So any company that we're looking at, we're asking ourselves the question. Why are they the best ones to do what they're doing? How could they solve the most problem for their customers and do that in a way that's that's Brazilian and we see lots of those opportunities, >>and I wanna I wanna pick your brain about the Nutanix investment. But before we get there, I wonder if you could just talk about Bain Capital in their their history of investment in both cloud and infrastructure software and and how do those investments? How would they performed? And how do they inform your current thesis? >>Yeah, absolutely. So being Capital was started in in the mid eighties, 1984 actually has a spin out of being a company consulting, and the basic premise was that if we're good at advising and supporting businesses, we should partner with them and invest behind them, and if they do well, we'll do well. And, as I said, focusing on these businesses but do something really valuable for their customers in a riel advantaged way, with some discontinuous growth opportunity that's led us to grow a lot. You know, we started out actually in the venture business and grew into the private equity business. But now we invest across all life stages of companies and all over the world. So we're $105 billion in assets that we managed across 10 lines of business on were truly global. So I think we have about 470 investment professionals and 210 of those at this point are located outside the U. S. One of the really interesting things for us in investing in technology broadly and in infrastructure in the cloud more specifically is that we're able to do that all over the world. And we're able to do that across all the different life stages of companies. We have a thriving venture capital business that really we've been in since the origins of being capital has invested across countless cloud and security and infrastructure businesses taken successful companies public like like solar wind sold companies to strategic and grown businesses. You know, in really thriving ways we have a, um, growth mid market growth technology business that we launched last year. Called their Technology Opportunities Fund. They've made a really interesting cloud based investment in a company called the Cloud Gurus Cloud Guru Excuse me? That trains the next generation of I t professionals to be successful in the club on then, of course, in our private equity business, you know where I spend my time. We are highly focused on technology sector and the the impacts of the cloud in that sector. Broadly, we've invested in many infrastructure businesses, scale businesses like BMC software and Rockets software security businesses like blue coat systems and semantic. And of course, for those big businesses they've got both on premises solutions. They've got cloud solutions, and often we're focused on helping them continue to grow and innovate and take their solutions to the cloud. And then, uh, that's taking us to our most recent investment in Nutanix that we're very excited about it. We think it's truly a growth business in a large market that has an opportunity to capitalize on these trends we're talking about. >>I wonder if you could comment on some of the changes that have occurred. You guys have been in the private equity business for a long time. And if you look at what you know, kind of the early days of private equity, it was all you know, even, uh, suck as much cash out of the company is possible. You know, whatever's left over will figure out what to do with it. It it seems like you know, investors have realized Wow, we can actually, if we put a little investment in and do some engineering and some go to market, we can actually get better multiples. And so you've got the kind of rule of 30 35 40 where he made a plus. Growth is kind of the metric. How do you think about that? And look at that evolution. >>Yeah, you know, it's interesting because in many ways, being capital was started as the antithesis to what to what you're describing. So we started again, as as with a strategic lens and a focus on growth and a focus on if we got the long term and the lasting impact of our business is right, that the returns would would follow. And you're right that the market has evolved in that way. I mean, I think some of the some of the dynamics that we've seen has been certainly growth of the private equity business. It's It's become a much larger piece of the, you know, the capital markets than it was certainly 10 years ago in 20 years ago. Also, with that growth comes the globalization, that business all over the world and the specialization. So you certainly see technology focused firms and technology focused funds in a way that you didn't see, uh, 10 years ago, or certainly 20 years ago actually being capital. Interestingly enough, we had a technology focused fund in 1989 called called Being Information Partners. So we've been focused on the sector for a very long time. But you certainly see ah, lot more technology investors, uh, than than you did you know 10 or 20 years ago? >>How are you thinking about valuations? Thes days? I mean, that is good. It's good to be in tech. It's even better to be in the cloud. You know, Service officer, software Cloud. You know if if if you're looking at, you know some of the companies, especially the work from home pivot. But a lot of that appears to be. You know, many people believe it's going to be permanent. How are you feeling about the both public market and private market valuations in that dynamic? >>Yeah, well, you know, it's it's amazing, right? I don't think any of us in March, when the covert crisis was just emerging, would have anticipated that that come November, the markets, and certainly the technology markets would be even more robust and stronger than than they were say in January February. But I think it's a testament to the resilience of the technology on that just how intricate and intertwined technology has become with our daily lives and and how much companies depend on its use. And frankly, it's been the cove environments that an accelerant for many of the ways in which we depend on technology. So witnessed this interview, of course, through through the through the cloud, and you're seeing the way that we operate our business day to day the way cos they're accessing their data and information. It's only further accelerated the need for technology and the importance of that technology to how how businesses operate. So I think you're seeing that reflected in the market values out there. But, you know, frost work. We're focused on businesses that still have that catalytic opportunity ahead that can more than compensate for for the price of entry. >>So let's talk about this massive investment. You guys made a Nutanix 750 million, I guess, is a small piece of your 105 billion, but still a massive investment. How did that opportunity come to you? What was your thinking? You know, behind that that investment and what are you looking for in terms of the go forward plan and growth plan for 2021 really importantly, beyond. >>Yeah, absolutely. Well, we're thrilled to be partnered with and invested in Nutanix. We think is a terrific company. And, you know, our most recent technology investment and private equity business. It really came about through a proactive efforts that we had in in the spring. Um, you know, we've got a team focused on the technology sector, focused across infrastructure and applications, and, uh, internet and digital media businesses and financial technology. And, uh, you know, through those efforts, we were looking for businesses. Um, that we felt had faced some dislocation and their market values associated with the Koven environment that we're facing but that we thought were really attractive. Business is well positioned, had leading solutions and had substantial and discontinuous growth opportunities. And as we looked through that effort, we really felt that Nutanix stood out just as a core leader and in fact, really the innovator and the inventor of the market in which it competes with a substantial market share in position solving a really important problem for its customers with a big growth opportunity ahead. But, um, the stock price had had come down because the business has been undergoing ah transition, and we didn't think that that was fully understood by by the market. And so way saw an opportunity Thio partner with Nutanix to invest money into the business to help to fund its transition and its growth. Yeah, and Thio to be partners along for all the value the business will will continue to create. We think it's a terrific company, and we're excited to be to be invested >>Well, you and I have talked about this that transition, you know, from a traditional, you know, license model to one That's Anania recurring revenue model, which many companies have gone through. You know, Adobe certainly has done it. Tableau successfully did it. Splunk is kind of in the middle of that transition right now and maybe not well understood. You've got companies like like Data Dog that and snowflake again to doing consumption based pricing. So there's a lot of confusion in the marketplace, and I wonder if you could talk about that transition and why it It was attractive to you to actually, you know, place that bet now? >>Yeah, absolutely. And as you say, a number of companies at this point have been through various forms of this shift, from from selling their technology upfront to selling it over time on, we find that the model of selling the technology over time eyes one that could be powerful. It could be aligning for customers as well as for, uh, vendor of the software solutions. And in Nutanix in particular again, we saw all the ingredients that we think make this an opportunity for for the business again, market leading technology that customers love. That is solving really important problem. The technology, because Nutanix had been grown and bootstrapped under the leadership of, uh, you know of zeros when it was built and founded, had been selling its software together with an appliance, you know, often in a, um, upfront sale Andi has been undergoing under their own initiative transition from selling that software with an appliance to a software based model to one that s'more rattle over time. And, you know, we thought that there was the opportunity to continue that to continue that transition and by doing that, to be able to offer mawr growth and mawr innovation that we could bring to our customers Thio continue to fund the shift. So something that frankly was well underway before we invested. Um, you know, as a za business makes this transition from collecting upfront Thio, you know, thio more evenly. Over time, you know, we saw a potentially use for our capital to help to fund that growth. And we're just focused on being a good partner toe help the company keep investing in abating, as as it contains to do that. >>I was talking to somebody other day, David. I told him I was interviewing you, and I was mentioning the Nutanix investment. I said, I'm definitely gonna cover that as part of this. You know, Cuban Cloud program. And they said Hit Nutanix. That's not cloud. I'm like, Wait a minute, What's cloud? So we heard Andy Jassy reinvent talking a lot about hybrid Antonio Neary, right after HP made its earnings last earnings announcement he came on on, said that well, we heard the big Cloud player talk about hybrid, and so the definition is changing. But so how are you looking at the market? Uh, certainly. There's this hyper converged infrastructure, but there's also this software play. There's this cloud play. Help us squint through how you see that >>absolutely so Nutanix, as you alluded to, pioneered the market for hyper converged infrastructure for bringing computing storage networking together. Uh, you know, often in private cloud environments in a way that was really powerful for for customers. Make, of course, continue to be the leaders in that marketplace. But they've continued to innovate and invest in ways that can solve problems for customers and related problems across the hybrid cloud. So combining both the public cloud with, you know, with that private cloud and across multiple public clouds with things like clusters and lots of innovation that business is doing in partnership with the likes of, um, Amazon and Microsoft and others. And so, yeah, we think that New Chance has a powerful role to play in that hyper cloud world in a multi cloud world. And we're excited toe back on them. >>Well, I think to what maybe people don't understand is that not only is Nutanix, you know, compatible with AWS and compatible with azure and G C. P. But it's actually kind of create a nabs traction layer across those those clouds. Now there's two sides of that debate. Some some will say, Well, that that that has Leighton see issues or yes, it reduces complexity. But at the same time, it doesn't give you that fine grained access. That's kind of the A W s narrative customers, you know, want simplicity. And we're seeing, you know, the uptake across clouds. I have a multipart question for you, Dave. So obviously being very strong and strategy I'm curious is toe how how much you get involved in the operational details. I mean, obviously 750 million u got a state there, but what are the 2 to 2 or three major strategic considerations for not just even just Nutanix but cloud and software infrastructure companies. And and how much focus do you put on the operational and one of the priorities There? >>Absolutely. Well, you know, we pride ourselves in being good partners to our businesses and in helping them to grow, not just with our capital, which I think is, of course, important, but also, you know, with our sweat equity and our and our human capital in our partnership that we could do that in lots of ways is fundamentally about, um, you know, supporting our businesses, however, is needed to help them thio grow. We've been investing in the technology sector, as I described for over over 30 years. And so we've built up a set of capabilities around things like helping toe partner with the sales force of our company is helping them toe, you know, think about the you know, the ways in which they they allocate their, uh their research and development and their in their innovation raised in which they, you know, continue Thio do acquisitions toe. You know, further that pipeline, we support our businesses in lots of ways, but you know we're not engineers were not. Developers, of course, were looking for businesses that are fundamentally great. They've got great technology. They solve problems for customers in a way, you know, that we could never replicate. That's what's the amazing but a business like Nutanix and just over a 10 year period of time, it literally has customer satisfaction levels that we haven't seen from any other. Infrastructures offer company that we've had the, you know, the pleasure of diligence ing over the last several years. So what we're focused on is how can we take those great products and offerings that Nutanix has and continue to support them through the further growth and expansion in areas like, um, you know, the further salesforce investment Thio expand into these new areas like clusters that we were talking about and thinking about, you know, things that they could do toe further expand the strategic hold. Um, And so, you know, we have, ah, large team of being capital. A zai mentioned 260 investment professionals in a private equity business alone. About a third of those are just available to our companies to help support them. Uh, you know, with various initiatives and efforts after after we invest. And we'll certainly, of course, make all of those available to new taxes. Well, somebody >>was asking me the other day, You know, what's hyper converged infrastructure? How did that come about? I was explaining what, Back in the day you had. You buy some servers and some storage and you have a network and you sort of have different teams and you put applicant, You figure out all out and put the applications on top, you know, test it, make sure it all works. And then and then the guys at V. C and VM Ware and Cisco and the M. C. They got together and said, Okay, we're gonna bolt together a bunch of different components and, you know, pre tested. Here you go. Here's a Here's a skew. And then what Nutanix did was actually really transformational and saying, Okay, look, we do this through software on DSO. And now that was what, Late, late two thousands. Now we're sort of entering this new era, this next generation of cloud cross clouds. So I wonder how you think about, you know, based on what you were just talking about the whole notion of M and A versus organic. There's a lot of organic development that needs to be done. But perhaps you could you could buy in or in organically through emanate toe, actually get there faster. How do you think about that balance? >>Look, I I think that that was an articulate, by the way explanation of I think that the origins of hyper converged infrastructure. So I enjoyed that very much. But, you know, I think that with any of our businesses and with Nutanix, we're of course, looking at where we trying to get to in several years and one of the best ways to support the business to get there, you know? Of course, they'll, um you know, primarily that will be through or continued organic investment in the company and all the innovation in the product. Um, that they've been doing will the company contemplate acquisitions toe further achieve the development goals and the objectives for solving pain points for customers to get, you know, to the strategic places they're trying to get to, of course. But you know, it all is a part of the package of of What's it a good fit company and its growth object. >>I mean, with the size of your portfolio, I mean your full stack investor, I would say, Is there any part of the so called tech stack that you won't touch that you would actually, you know, not not walk, but run away from, >>uh well, you know, I wouldn't say that we're running away from, you know, anything but the questions that we're asking ourselves. Our is the technology that we're investing in durable, ISAT advantaged and does have a growing role in the world. And, you know, if if we think that those things are true are absolutely, um, thrilled toe invest behind those things. You know, if if there are things that we feel like you, that's that's not the case, um, you know, then then we would tend toe to shy away from those investments. We've certainly found opportunities and businesses that people perceived as one. But you know, we believe to be another >>Well, so let me ask you specifically about about Nutanix. I mean, clearly, they achieved escape velocity. One of the few companies actually from last decade. It was Nutanix pure, not a whole lot of others. That actually, you know, were ableto maintain independence as a as a public company. What do you see is their durability. Uh, they're they're they're in their moat. If you if you will. >>Yeah, absolutely. Well, clearly, we think that it's a very durable and very advantage business. You know, that's that's the investment. Look, we think that Nutanix has been able to offer the best hyper converged infrastructure product on the market bar None. Um, one that has got the best ease of use Eyes is the most nimble and flexible for for customers. And you just see that, you know, recently and customer feedback And also that plays across very heterogeneous architectures in a way that, you know, it's really, really powerful because of that. You know, we think that their best position to be able to leverage that technology as they have been, uh, to continue to play across both public and private hybrid cloud environments. And so we're excited toe to back them and and that journey it really starts from solving and acute customer pain point, you know, better than anybody else can. And, you know, we're looking to to back them toe continue to expand that vision. >>Yeah, well, I've talked to a lot of Nutanix customers over the years, and that is the fundamental value. Proposition is it's really simple, very high, you know, customer satisfaction. So that makes a lot of sense. Well, Dave, thanks very much for coming on the Cube and participating in the Cuban cloud. Really? Appreciate your perspectives. Wish you best of luck. And hopefully we could do this again in the future. Maybe face to face >>now, face to face, maybe something even know. Dave, I really appreciate it's been a pleasure and good luck with with the rest of your interviews. >>All right. Thank you. We keep it right. Everybody from or Cuban Cloud, this is Dave Volonte. We'll be right back.

Published Date : Jan 22 2021

SUMMARY :

cloud brought to you by Silicon angle. Yeah, David, thanks very much for having so in this coming decade, you know, Thio ironic 2020 is has thrown us into, And it makes sense when you think about It's not just, you know, the cloud eating away it on Prem. you know, other specialized and focused competitors, and then finding a way that we can partner I wonder if you could just talk about Bain Capital in their their history of in a large market that has an opportunity to capitalize on these trends we're talking about. It it seems like you know, investors have realized Wow, we can actually, It's It's become a much larger piece of the, you know, the capital markets than it was certainly How are you feeling about the both public Yeah, well, you know, it's it's amazing, right? You know, behind that that investment and what are you looking for uh, you know, through those efforts, we were looking for businesses. it It was attractive to you to actually, you know, its software together with an appliance, you know, often in a, But so how are you looking at the market? So combining both the public cloud with, you know, with that private cloud and across multiple public And we're seeing, you know, the uptake across clouds. that we were talking about and thinking about, you know, things that they could do toe further expand Okay, we're gonna bolt together a bunch of different components and, you know, pre tested. the business to get there, you know? that's that's not the case, um, you know, then then we would tend toe to shy away from those investments. That actually, you know, were ableto maintain independence as a as a public And also that plays across very heterogeneous architectures in a way that, you know, it's really, really powerful because Proposition is it's really simple, very high, you know, customer satisfaction. the rest of your interviews. Everybody from or Cuban Cloud, this is Dave Volonte.

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Dheeraj Pandey, Nutanix | theCUBE on Cloud 2021


 

>> Hi, and this is theCUBE on Cloud. I'm Stu Miniman and really excited to welcome to a special Fireside Chat. CUBE Alumni has been on the program so many times. We always love talking to founders. We like talking to deep thinkers and that's why he was one of the early ones that I reached out to when we were working on this event. When we first started conversations, we were looking at how hyperscalers really were taking adoption of the brand new technologies, things like flash, things like software defined networking, and how that would invade the enterprise. That of course has had a huge impact, help create a category called hyperconverged infrastructure and I'm talking about Dheeraj Pandey. He is the founder, chairman, and CEO of Nutanix, taking HCI from hyperconverged infrastructure to hybrid cloud infrastructure. So Dheeraj, welcome to the Fireside Chat. Thank you so much for joining us. >> Thank you, Stu, and thank you for the last 10 years that we've grown together, both theCUBE and Nutanix and myself as a leader in the last 10 years. So bringing HCI from hyperconverged to hybrid cloud just reminds me of how the more things change, the more they remain the same. So looking forward to a great discussion here. >> So talk about that early discussion, what the hyperscalers were doing, how can the enterprise take advantage of that? Over time, enterprise has matured and looked a little bit more like the hyperscalers. Hybrid cloud of course is on everyone's lip, as well as we've seen the hyperscalers themselves look more and more like the enterprise. So hybrid and multicloud is where we are today. We think it'll be in the future. But give us a little bit as to how you've seen that progression today and where are we going down the road here? >> Yeah, I think I talked about this during my .NEXT keynote. And the whole idea of, in every recession, we make things smaller. In '91 we said we're going to go away from mainframes into Unix servers. And we made the unit of compute smaller. Then in the year 2000 when there was the next bubble burst and the recession afterwards, we moved from Unix servers to Wintel: Windows and Intel, x86 and eventually Linux as well. Again we made things smaller going from million dollar servers to $5,000 servers, shorter lived servers. And that's what we did in 2008/2009. I said, look, we don't even need to buy servers. We can do things with virtual machines which are servers that are an incarnation in the digital world. There is nothing in the physical world that actually went lives. But we made it even smaller. And now with cloud in the last three, four years and what will happen in this coming decade, they're going to make it even smaller, not just in space which is size with functions and containers and virtual machines, but also in time. So space and time, we're talking about hourly billing and monthly billing and a one-year term as opposed to really going and committing to five or seven years of hardware and CapEx. So I think as you make things smaller, I mean, and this is true for as consumers, we have short attention spans, things are going fast. The cycle of creative destruction of virtual machines is shrinking as well. So I think in many cases, we know we've gone and created this autonomy, massive sprawl. Like we created a massive sprawl of Intel servers back in '95 and 2005. Then we have to use virtualization to go and consolidate all of it, created beautiful data centers of Intel servers with VMware software. And then we created a massive sprawl of data centers, of consolidated data centers with one click private cloud in the last five years and hopefully in the next five too. But I think we're also now creating a proliferation of clouds. There is a sprawl, massive sprawl of cost centers and such. So we need yet another layer of software for governance to reign in on that chaos, hence the need for a new HCI, hybrid cloud infrastructure. >> Yeah, it's fascinating to kind of watch that progression over time. There was a phenomenal Atlantic article. I think it was from like the 1940s or 1950s where somebody took what was happening post-World War II and projected things out. We're talking really pre the internet, but just the miniaturization and the acceleration, kind of the Moore's law discussion. If you take things out, where it would go. When I talked to Amazon, they said the one thing that we know for sure, I'm talking to Amazon.com is that people will want it faster and cheaper in the future. I don't know which robot or drone or things that they have. But absolutely there are those certain characteristics. So from a leadership standpoint, Dheeraj, talk about these changes? We had the wave of virtualization, the wave of containerization, you talked about functions in serverless. Those are tools. But at the end of the day, it's about the outcomes and how do we take advantage of things? So how as a leader do you make sure that you know where to take the company as these technology waves and changes impact what you're doing? >> Yeah, it's a great point. I mean, we celebrate things in IT a lot, but we don't talk about what does it take? What's the underlying fabric to really use these things successfully and better than others and not just use buzzwords, because new buzzwords will come in the next three years. For example AI and ML has been a great buzzword for the last three, four years. But there's very few companies, probably less than even half a percent who know how to leverage machine learning, even understand the difference between machine learning and AI. And a lot of it comes down to a few principles. There's a culture principles, not the least of which is how you celebrate failure, because now you're doing shorter, smaller things. You've got a more agile, you'll have more velocity. Gone are the days of waterfall where you're doing yearly planning and pre-year releases and such. So as we get into this new world, not everything will be perfect, and you've got to really learn to pick yourself up and recover quickly, heal quickly and such. So that is the fundamental tenet of Silicon Valley. And we got to really go and use this more outside the Valley as well in every company out there. Whether it's East Coast company, the Midwest company that are outside the U.S. I think this idea that you will be vulnerable, more vulnerable as you go and learn to do things faster and shorter. I think product management is a term that we don't fully understand, and this is about the why before the how and the what. We quickly jump to the what: containers and functions and databases, servers, and AI, and ML, they're the what. But how do you really start with the why? You know my fascination for one of my distant mentors, Simon Sinek and how he thinks about most companies just focusing on the what, while very few actually start with why, then the how, then the what itself. And product management has to play a key role in this, which also subsumes design, thinking about simplification and elegance and reducing friction. I think again, very few companies, probably no more than 1% of the companies really understand what it means to start with design and APIs, user experience APIs for developers before you even get to writing any single line of code. So I think to me, that's leadership. When you can stay away from instant gratification of the end result, but start with the why, then the how, then the what. >> Yeah, as we know in the technology space, oftentimes the technology is the easy part. It's helping to drive that change. I think back to the early days when we were talking, it was, hyperconverge, it was a threat to storage. We're going to put you out of a job. And we'd always go and say, "Look, no, no, no. We're not putting you out of a job. We're going to free you up to do the things that you want to do. That security project that's been sitting on the shelf for six months, you can go do that. Helping build new parts of the business. Those things that you can do." It's that shifting a mindset can be so difficult. And Dheeraj, I mean, you look at 2020, everyone has had to shift their mindset for everything. I was spending half my time on the road. I don't miss the hotels. I do miss seeing lots and lots of people in person. So what's your advice for people, how they can stay malleable, be open to some change? What are you seeing out there? What advice do you give there? >> Yeah, I think, as you said, inertia is at the core of most things in our lives, including what we saw in healthcare for the last 20, 30 years. I mean, there was so much regulation. The doctor's community had to move forward, nurses had to move forward. I mean, not just providers, but insurance companies. And finally, all of a sudden, we're talking about telehealth because of the pandemic. We are talking about online learning. I mean the things that higher ed refused to do. I mean if you think about the last 20 years of what had happened with the cost of higher ed, I mean it's 200% growth when the cost of television has gone down by probably 100, 200% with more features. Healthcare, higher ed, education in general, all of a sudden is coming for this deep shock because of the pandemic. And I think it's these kind of black swan moments that really changed the world. And I know it's a cliche to say this. But I feel like we are going to be in a new normal, and we have been forced to this new change of digital. I mean, you and I are sitting and talking over the internet. It's a little awkward right now because there's a little bit of a delay in the way I'm looking at things. But I know it's going to directionally be right. I mean, we will go in a way where it just become seamless over time. So change is the only constant. And I believe that I think what we've seen in the pandemic is just the beginning of what digital will mean going forward. And I think the more people embrace it, the faster we do it. Speed is going to be the name of the game when it comes to survival and thriving in this new age. >> Dheeraj, it's interesting. We do hope, I'm a technologist. I know you're an optimist when it comes to things. So we always look at those silver linings. Like I hope healthcare and education will be able to move forward fast. Higher education costs, inequity out there for access to medicine. It would be wonderful if we could help solve some of that, despite this global pandemic. One of the other results, Dheeraj, we talked about some very shifts in the marketplace, the large tech players really have emerged in winter so far in 2020. I can't help, but watch the stock market. And Apple is bigger than ever, Amazon, Google, all ended up in front of Congress to talk about if they've gotten too big. You've partnered with Amazon, Microsoft, and Google. They are potentially a threat but also a partner. From your standpoint, have they gotten too much power? Do we have an inequity in the tech world that they are creating the universes that they will just kind of block off and limit innovation? What's your take on big tech? >> Yeah, I mean, I feel like there's always been big something. I mean, if you go back to the '90s, Amazon, not Amazon, IBM was big, and Microsoft was big, and AT&T was big. I mean, there's always been big companies because the consumer effect that they've had as well, I mean. And I think what we're seeing right now is no different. I mean, at the end of the day, the great thing about this country is that there's always disruption happening. And sometimes small is way better and way more competitive than big. Now at the same time, I do look up to the way some of them have organized themselves. Like the way Amazon has organized itself is really unique and creative with general managers and very independent, highly autonomous groups. So some of these organizations will definitely survive and thrive in scale. And yet for others, I think decision-making and staying competitive and staying scrappy will come a lot harder. So to me when I look at these big names and what Congress is talking about and such, I feel like there's no different than 20, 30, 40 years ago. I mean, we talked about Rockefeller and the oil giants back from 100 years ago. And so in many ways, I mean, the more things change, the more they remain the same. All we have to do is we have to walk over to where the customer is. And that's what we've done with the partnerships. Like in Amazon and Azure, we're saying look, we can even use your commits and credits. I mean, that is a very elegant way to go to where the customer is, rather than force them to where we are. And the public cloud is facing this too. They've come to realize in the last two years that they cannot force all of enterprise computing to come to hyperscalers data centers. They'll have to take in these bite-size smaller clouds to where the customer is, where the customer's machines are, where the customers people are, where the customers data is. That's where we also take to disperse the cloud itself. So I think there's going to be a yin yang where we'll try to walk with the customer to where we want them to be, whether it's hyperscaler data center or the notion of hybrid cloud infrastructure. But many a time, we've got to walk over to where they are. I mean, and outside the U.S, I mean, the cloud is such a nuanced word. I mean, we're talking about sovereignty, we're talking about data gravity, we're talking about economics of owning versus renting. This trifecta, the laws of the land, the laws of physics, and the laws of economics will dictate many of these things as well. So I think the big folks are also humble and vulnerable to realize that there's nothing more powerful than market forces. And I think the rest will take care of itself. >> Yeah, my quick commentary on that, Dheeraj, I think most of us look back at AT&T and felt the government got it wrong. The way they broke it up and ended up consolidating back together, it didn't necessarily help consumers. Microsoft on the other hand might've had a little bit too much power and was leveraging that against competition and really squashing innovation. So in general, it's good to see that the politics are looking at that and chore felt. The last time I watched things, they were a little bit more educated than some previous times there, where it was almost embarrassing to watch our representatives fumbling around with technology. So it's always good to question authority, question what they have. And one of the things you've brought up many times is you're open to listening and you're bringing in new ideas. I remember one conversation I had with you is there's that direction that you hold on to, but you will assess and do new data. You've made adjustments in the product portfolio and direction based on your customers, based on the ecosystem. And you've mentioned some of the, bring thoughts that you've brought into the company and you share. So you mentioned black swan that seem to head you brought to one of the European .NEXT shows. It was great to be able to see that author and read through advisors like Condoleezza Rice who you've had at the conferences a couple of times. Where are you getting some of your latest inspiration from, any new authors or podcasts that you'd be recommending to the audience? >> Yeah, I look at adjacencies, obviously Simon has been great. He was .NEXT, talked about the Infinite Game. And we'll talk about the Infinite Game with Nutanix too with respect to also my decision. But Brene Brown was been very close to Nutanix. I was just looking at her latest podcast, and she was sitting with the author of Stretch, Scott Sonnenschein, and it's a fascinating read and a great listen, by the way, I think for worth an hour, talking about scrappiness, and talking about resourcefulness. What does it mean to really be resourceful? And we need that even more so as we go through this recession, as we are sheltered in place. I think it's an adjacency to everything that Brene does. And I was just blown away by just listening to it. I'd a love for others to even have a listen and learn to understand what we can do within our families, with our budgets, with our companies, with our startups. I mean, with CUBE, I mean, what does it mean to be scrappy? And celebrate scrappiness and resourcefulness, more so than AI always need more. I think I just found it fascinating in the last week itself listening through it. >> John Farinacci talk many times that founder, startup, that being able to pull themselves up, be able to drive forward, overcome obstacles. So Dheeraj, do you tee it up? It sounds like is the next step for you. There's a transition under discussion. Bain has made an investment. There's a search for new CEO. Are you saying there's a book club in your future to be able to get things ready? Why don't you explain a little bit, 11 years took the company public, over 6,500 employees public company. So tell us a little bit about that decision-making process and what you expect to see in the future? >> Yeah, it's probably one of the hardest things as an entrepreneur is to let go, because it's a creation that you followed from scratch, from nothing. And it was a process for me to rethink about what's next for the company and then what's next for me? And me and the company were so tightly coupled that I was like, wow, at some point, this has to be a little bit more like the way Bill Gates did it with Microsoft, and there's going to be buton zone and you will then start to realize that your identity is different from the company's identity. And maybe the company is built for bigger, better things. And maybe you're built for bigger, better things. And how do you really start to first do this decoupling of the identity? And it's really hard. I mean, I'm sure that parents go through this. I mean, our children are still very young. Our eldest is nine going on 10 and our twin girls are six. I know at some point in the next 10 years, eight to 10 years, we'll have to figure out what it means to let go. And I'm already doing this with my son. I tell him you're born free. I mean, the word born free which drives my wife crazy sometimes. I say this to them, it's about independence. And I think the company is also born free to really think about a life outside of me, as well outside of founder. And that was a very important process for me as I was talking to the board for the last six, seven, eight months. And when the Bain deal came in, I thought it was a great time. We ended the fiscal really well, all things considered. We had a good quarter. The transition has been a journey of a lifetime, the business model transition I speak of. Really three years, I mean, I have aged probably 10 years in these last three years. But I think I would not replaced it for anything. Just the experience of learning what it means to change as a public company when you have short-term goals and long-term goals, we need the conviction, knowing what's right, because otherwise we would not have survived this cloud movement, all this idea of actually becoming a subscription company, changing the core of the business in the on-prem world itself. It's a king to change the wings of a plane at 40,000 feet where none of the passengers blink. It's been phenomenal ride last 11 years, but it's also been nonstop monomaniacal. I mean, I use the word marathon for this, and I figured it's a good time to say figure out a way to let go of this, and think of what's bigger better for Nutanix. And going from zero to a billion six in annual billings, and looking at billion six to 3 billion to four to five, I think it'd be great &to look at this from afar. And at the same time, I think there's vulnerability. I mean, I've made the company vulnerable. I've made myself vulnerable. We don't know who the next leader will be. And I think the next three to six months is one of the most important baton zones that I have ever experienced to be a part of. So looking forward to make sure that baton doesn't fall, redefine what good to great looks like, both for the company and for myself. And at the same time, go read more. I mean, I've been passionate about developers in the last 10 years, 11 years. I was a developer myself. This company, Nutanix, was really built by developers for IT. And I'm learning more about the developer as a consumer. How do you think about their experience? Not just the things that we throw at them from open source point of view and from cloud and technologies and AI and ML point of view, but really their lives, having them think about revenue and business and really blurring the lines between architects and product managers and developers. I think it's just an unfathomable problem we've created in IT that I would love to go and read and write more about. >> Yeah, so many important things you said there. I absolutely think that there are certain things everybody of course will think of you for a long time with Nutanix, but there is that separation between the role in the company and the person itself, and really appreciated how much you've always shared along those lines. So last question I have and you hit it up a little bit when you talked about developers. Take off your Nutanix hat for a second here, now what do we need to do to make sure that the next decade is successful in this space, cloud as a general guideline? Yes, we know we have skill gap. We know we need more people, we need more diversity. But there's so much that we need and there's so much opportunity, but what do you see and any advice areas that you think are critical for success in the future? >> Yeah, I mean, you hit up on something that I have had a passion for, probably more late in this world, more so than conspicuous, and and you hit upon it right now, diversity and inclusion. It's an unresolved problem in the developer community: the black developer, the woman developer. The idea of, I mean, we've two girls, they're twins. I'd love for them to embrace computer science and even probably do a PhD. I mean, I was a dropout. I'd love for them to do better than I did. Get, embrace things that are adjacent to biology and computer science. Go solve really hard problems. And we've not done those things. I mean, we've not looked at the community of developers and said, you know, they are the maker. And they work with managers and the maker manager world is two different worlds. How do you make this less friction? And how do you make this more delightful? And how do you think of developers as business, as if they are the folks who run the business? I think there's a lot that's missing there. And again, we throw a lot of jargons at them, and we talk a lot about automation and tools and such. But those are just things. I think the last 10, 11 years of me really just thinking about product and product portfolio and design and the fact that we have so many developers at Nutanix. I think it has been a mind-boggling experience, thinking about the why and the how and the what of the day in the life of, the month in the life of, and thinking about simple things like OKRs. I mean, we are throwing these jargons of OKRs at them: productivity, offshoring, remote work, over the zoom design sessions. It's just full of conflict and friction. So I think there is an amazing opportunity for Nutanix. There's an amazing opportunity for the industry to elevate this where the the woman developer can speak up in this world that's full of so many men. The black developer can speak up. And all of us can really think of this as something that's more structured, more productive, more revenue-driven, more customer in rather than developer out. That's really been some of the things that have been in my head, things that are still unresolved at Nutanix that I'm pretty sure at many of the places out there. That's what thinking and reading and writing about. >> Well, Dheeraj, first of all, thank you so much again for participating here. It's been great having you in theCUBE community, almost since the inception of us doing it back in 2010. Wish you the best of luck in the current transition. And absolutely look forward to talking more in the future. >> Thank you. And again, a big fan of the tremor rate of John, Dave, and you. Always learn so much from you, folks. Looking forward to be a constant student. Thank you. >> Thank you for joining us at theCUBE on Cloud. Lots more coverage here. Be sure to look throughout the site, engage in the chats, and give us your feedback. We're here to help you with the virtual events. I'm Stu Miniman as always. Thanks for watching.

Published Date : Jan 22 2021

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theCube On Cloud 2021 - Kickoff


 

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle, everybody to Cuban cloud. My name is Dave Volonte, and I'll be here throughout the day with my co host, John Ferrier, who was quarantined in an undisclosed location in California. He's all good. Don't worry. Just precautionary. John, how are you doing? >>Hey, great to see you. John. Quarantine. My youngest daughter had covitz, so contact tracing. I was negative in quarantine at a friend's location. All good. >>Well, we wish you the best. Yeah, well, right. I mean, you know what's it like, John? I mean, you're away from your family. Your basically shut in, right? I mean, you go out for a walk, but you're really not in any contact with anybody. >>Correct? Yeah. I mean, basically just isolation, Um, pretty much what everyone's been kind of living on, kind of suffering through, but hopefully the vaccines are being distributed. You know, one of the things we talked about it reinvent the Amazon's cloud conference. Was the vaccine on, but just the whole workflow around that it's gonna get better. It's kind of really sucky. Here in the California area, they haven't done a good job, a lot of criticism around, how that's rolling out. And, you know, Amazon is now offering to help now that there's a new regime in the U. S. Government S o. You know, something to talk about, But certainly this has been a terrible time for Cove it and everyone in the deaths involved. But it's it's essentially pulled back the covers, if you will, on technology and you're seeing everything. Society. In fact, um, well, that's big tech MIT disinformation campaigns. All these vulnerabilities and cyber, um, accelerated digital transformation. We'll talk about a lot today, but yeah, it's totally changed the world. And I think we're in a new generation. I think this is a real inflection point, Dave. You know, modern society and the geo political impact of this is significant. You know, one of the benefits of being quarantined you'd be hanging out on these clubhouse APS, uh, late at night, listening to experts talk about what's going on, and it's interesting what's happening with with things like water and, you know, the island of Taiwan and China and U. S. Sovereignty, data, sovereignty, misinformation. So much going on to talk about. And, uh, meanwhile, companies like Mark injuries in BC firm starting a media company. What's going on? Hell freezing over. So >>we're gonna be talking about a lot of that stuff today. I mean, Cuba on cloud. It's our very first virtual editorial event we're trying to do is bring together our community. It's a it's an open forum and we're we're running the day on our 3 65 software platform. So we got a great lineup. We got CEO Seo's data Practitioners. We got a hard core technologies coming in, cloud experts, investors. We got some analysts coming in and we're creating this day long Siri's. And we've got a number of sessions that we've developed and we're gonna unpack. The future of Cloud computing in the coming decade is, John said, we're gonna talk about some of the public policy new administration. What does that mean for tech and for big tech in General? John, what can you add to that? >>Well, I think one of the things that we talked about Cove in this personal impact to me but other people as well. One of the things that people are craving right now is information factual information, truth texture that we call it. But hear this event for us, Davis, our first inaugural editorial event. Robbo, Kristen, Nicole, the entire Cube team Silicon angle, really trying to put together Morva cadence we're gonna doom or of these events where we can put out feature the best people in our community that have great fresh voices. You know, we do interview the big names Andy Jassy, Michael Dell, the billionaires with people making things happen. But it's often the people under there that are the rial newsmakers amid savory, for instance, that Google one of the most impressive technical people, he's gotta talk. He's gonna present democratization of software development in many Mawr riel people making things happen. And I think there's a communal element. We're going to do more of these. Obviously, we have, uh, no events to go to with the Cube. So we have the cube virtual software that we have been building and over years and now perfecting and we're gonna introduce that we're gonna put it to work, their dog footing it. We're gonna put that software toe work. We're gonna do a lot mawr virtual events like this Cuban cloud Cuban startup Cuban raising money. Cuban healthcare, Cuban venture capital. Always think we could do anything. Question is, what's the right story? What's the most important stories? Who's telling it and increase the aperture of the lens of the industry that we have and and expose that and fastest possible. That's what this software, you'll see more of it. So it's super exciting. We're gonna add new features like pulling people up on stage, Um, kind of bring on the clubhouse vibe and more of a community interaction with people to meet each other, and we'll roll those out. But the goal here is to just showcase it's cloud story in a way from people that are living it and providing value. So enjoy the day is gonna be chock full of presentations. We're gonna have moderated chat in these sessions, so it's an all day event so people can come in, drop out, and also that's everything's on demand immediately after the time slot. But you >>want to >>participate, come into the time slot into the cube room or breakout session. Whatever you wanna call it, it's a cube room, and the people in there chatting and having a watch party. So >>when you're in that home page when you're watching, there's a hero video there. Beneath that, there's a calendar, and you'll see that red line is that red horizontal line of vertical line is rather, it's a linear clock that will show you where we are in the day. If you click on any one of those sessions that will take you into the chat, we'll take you through those in a moment and share with you some of the guests that we have upcoming and and take you through the day what I wanted to do. John is trying to set the stage for the conversations that folks are gonna here today. And to do that, I wanna ask the guys to bring up a graphic. And I want to talk to you, John, about the progression of cloud over time and maybe go back to the beginning and review the evolution of cloud and then really talk a little bit about where we think it Z headed. So, guys, if you bring up that graphic when a W S announced s three, it was March of 2000 and six. And as you recall, John you know, nobody really. In the vendor and user community. They didn't really pay too much attention to that. And then later that year, in August, it announced E C two people really started. They started to think about a new model of computing, but they were largely, you know, chicken tires. And it was kind of bleeding edge developers that really leaned in. Um what? What were you thinking at the time? When when you saw, uh, s three e c to this retail company coming into the tech world? >>I mean, I thought it was totally crap. I'm like, this is terrible. But then at that time, I was thinking working on I was in between kind of start ups and I didn't have a lot of seed funding. And then I realized the C two was freaking awesome. But I'm like, Holy shit, this is really great because I don't need to pay a lot of cash, the Provisional Data center, or get a server. Or, you know, at that time, state of the art startup move was to buy a super micro box or some sort of power server. Um, it was well past the whole proprietary thing. But you have to assemble probably anyone with 5 to 8 grand box and go in, and we'll put a couple ghetto rack, which is basically, uh, you know, you put it into some coasting location. It's like with everybody else in the tech ghetto of hosting, still paying monthly fees and then maintaining it and provisioning that's just to get started. And then Amazon was just really easy. And then from there you just It was just awesome. I just knew Amazon would be great. They had a lot of things that they had to fix. You know, custom domains and user interface Council got better and better, but it was awesome. >>Well, what we really saw the cloud take hold from my perspective anyway, was the financial crisis in, you know, 709 It put cloud on the radar of a number of CFOs and, of course, shadow I T departments. They wanted to get stuff done and and take I t in in in, ah, pecs, bite sized chunks. So it really was. There's cloud awakening and we came out of that financial crisis, and this we're now in this 10 year plus boom um, you know, notwithstanding obviously the economic crisis with cove it. But much of it was powered by the cloud in the decade. I would say it was really about I t transformation. And it kind of ironic, if you will, because the pandemic it hits at the beginning of this decade, >>and it >>creates this mandate to go digital. So you've you've said a lot. John has pulled forward. It's accelerated this industry transformation. Everybody talks about that, but and we've highlighted it here in this graphic. It probably would have taken several more years to mature. But overnight you had this forced march to digital. And if you weren't a digital business, you were kind of out of business. And and so it's sort of here to stay. How do you see >>You >>know what this evolution and what we can expect in the coming decades? E think it's safe to say the last 10 years defined by you know, I t transformation. That's not gonna be the same in the coming years. How do you see it? >>It's interesting. I think the big tech companies are on, but I think this past election, the United States shows um, the power that technology has. And if you look at some of the main trends in the enterprise specifically around what clouds accelerating, I call the second wave of innovations coming where, um, it's different. It's not what people expect. Its edge edge computing, for instance, has talked about a lot. But industrial i o t. Is really where we've had a lot of problems lately in terms of hacks and malware and just just overall vulnerabilities, whether it's supply chain vulnerabilities, toe actual disinformation, you know, you know, vulnerabilities inside these networks s I think this network effects, it's gonna be a huge thing. I think the impact that tech will have on society and global society geopolitical things gonna be also another one. Um, I think the modern application development of how applications were written with data, you know, we always been saying this day from the beginning of the Cube data is his integral part of the development process. And I think more than ever, when you think about cloud and edge and this distributed computing paradigm, that cloud is now going next level with is the software and how it's written will be different. You gotta handle things like, where's the compute component? Is it gonna be at the edge with all the server chips, innovations that Amazon apple intel of doing, you're gonna have compute right at the edge, industrial and kind of human edge. How does that work? What's Leighton see to that? It's it really is an edge game. So to me, software has to be written holistically in a system's impact on the way. Now that's not necessarily nude in the computer science and in the tech field, it's just gonna be deployed differently. So that's a complete rewrite, in my opinion of the software applications. Which is why you're seeing Amazon Google VM Ware really pushing Cooper Netease and these service messes in the micro Services because super critical of this technology become smarter, automated, autonomous. And that's completely different paradigm in the old full stack developer, you know, kind of model. You know, the full stack developer, his ancient. There's no such thing as a full stack developer anymore, in my opinion, because it's a half a stack because the cloud takes up the other half. But no one wants to be called the half stack developer because it doesn't sound as good as Full Stack, but really Cloud has eliminated the technology complexity of what a full stack developer used to dio. Now you can manage it and do things with it, so you know, there's some work to done, but the heavy lifting but taking care of it's the top of the stack that I think is gonna be a really critical component. >>Yeah, and that that sort of automation and machine intelligence layer is really at the top of the stack. This this thing becomes ubiquitous, and we now start to build businesses and new processes on top of it. I wanna I wanna take a look at the Big Three and guys, Can we bring up the other The next graphic, which is an estimate of what the revenue looks like for the for the Big three. And John, this is I asked and past spend for the Big Three Cloud players. And it's It's an estimate that we're gonna update after earning seasons, and I wanna point a couple things out here. First is if you look at the combined revenue production of the Big Three last year, it's almost 80 billion in infrastructure spend. I mean, think about that. That Z was that incremental spend? No. It really has caused a lot of consolidation in the on Prem data center business for guys like Dell. And, you know, um, see, now, part of the LHP split up IBM Oracle. I mean, it's etcetera. They've all felt this sea change, and they had to respond to it. I think the second thing is you can see on this data. Um, it's true that azure and G C P they seem to be growing faster than a W s. We don't know the exact numbers >>because >>A W S is the only company that really provides a clean view of i s and pass. Whereas Microsoft and Google, they kind of hide the ball in their numbers. I mean, I don't blame them because they're behind, but they do leave breadcrumbs and clues about growth rates and so forth. And so we have other means of estimating, but it's it's undeniable that azure is catching up. I mean, it's still quite distance the third thing, and before I want to get your input here, John is this is nuanced. But despite the fact that Azure and Google the growing faster than a W s. You can see those growth rates. A W s I'll call this out is the only company by our estimates that grew its business sequentially last quarter. Now, in and of itself, that's not significant. But what is significant is because AWS is so large there $45 billion last year, even if the slower growth rates it's able to grow mawr and absolute terms than its competitors, who are basically flat to down sequentially by our estimates. Eso So that's something that I think is important to point out. Everybody focuses on the growth rates, but it's you gotta look at also the absolute dollars and, well, nonetheless, Microsoft in particular, they're they're closing the gap steadily, and and we should talk more about the competitive dynamics. But I'd love to get your take on on all this, John. >>Well, I mean, the clouds are gonna win right now. Big time with the one the political climate is gonna be favoring Big check. But more importantly, with just talking about covert impact and celebrating the digital transformation is gonna create a massive rising tide. It's already happening. It's happening it's happening. And again, this shift in programming, uh, models are gonna really kinda accelerating, create new great growth. So there's no doubt in my mind of all three you're gonna win big, uh, in the future, they're just different, You know, the way they're going to market position themselves, they have to be. Google has to be a little bit different than Amazon because they're smaller and they also have different capabilities, then trying to catch up. So if you're Google or Microsoft, you have to have a competitive strategy to decide. How do I wanna ride the tide If you will put the rising tide? Well, if I'm Amazon, I mean, if I'm Microsoft and Google, I'm not going to try to go frontal and try to copy Amazon because Amazon is just pounding lead of features and scale and they're different. They were, I would say, take advantage of the first mover of pure public cloud. They really awesome. It passed and I, as they've integrated in Gardner, now reports and integrated I as and passed components. So Gardner finally got their act together and said, Hey, this is really one thing. SAS is completely different animal now Microsoft Super Smart because they I think they played the right card. They have a huge installed base converted to keep office 3 65 and move sequel server and all their core jewels into the cloud as fast as possible, clarified while filling in the gaps on the product side to be cloud. So you know, as you're doing trends job, they're just it's just pedal as fast as you can. But Microsoft is really in. The strategy is just go faster trying. Keep pedaling fast, get the features, feature velocity and try to make it high quality. Google is a little bit different. They have a little power base in terms of their network of strong, and they have a lot of other big data capabilities, so they have to use those to their advantage. So there is. There is there is competitive strategy game application happening with these companies. It's not like apples, the apples, In my opinion, it never has been, and I think that's funny that people talk about it that way. >>Well, you're bringing up some great points. I want guys bring up the next graphic because a lot of things that John just said are really relevant here. And what we're showing is that's a survey. Data from E. T. R R Data partners, like 1400 plus CEOs and I T buyers and on the vertical axis is this thing called Net score, which is a measure of spending momentum. And the horizontal axis is is what's called market share. It's a measure of the pervasiveness or, you know, number of mentions in the data set. There's a couple of key points I wanna I wanna pick up on relative to what John just said. So you see A W S and Microsoft? They stand alone. I mean, they're the hyper scale er's. They're far ahead of the pack and frankly, they have fall down, toe, lose their lead. They spend a lot on Capex. They got the flywheel effects going. They got both spending velocity and large market shares, and so, but they're taking a different approach. John, you're right there living off of their SAS, the state, their software state, Andi, they're they're building that in to their cloud. So they got their sort of a captive base of Microsoft customers. So they've got that advantage. They also as we'll hear from from Microsoft today. They they're building mawr abstraction layers. Andy Jassy has said We don't wanna be in that abstraction layer business. We wanna have access to those, you know, fine grain primitives and eso at an AP level. So so we can move fast with the market. But but But so those air sort of different philosophies, John? >>Yeah. I mean, you know, people who know me know that I love Amazon. I think their product is superior at many levels on in its way that that has advantages again. They have a great sass and ecosystem. They don't really have their own SAS play, although they're trying to add some stuff on. I've been kind of critical of Microsoft in the past, but one thing I'm not critical of Microsoft, and people can get this wrong in the marketplace. Actually, in the journalism world and also in just some other analysts, Microsoft has always had large scale eso to say that Microsoft never had scale on that Amazon owned the monopoly on our franchise on scales wrong. Microsoft had scale from day one. Their business was always large scale global. They've always had infrastructure with MSN and their search and the distributive how they distribute browsers and multiple countries. Remember they had the lock on the operating system and the browser for until the government stepped in in 1997. And since 1997 Microsoft never ever not invested in infrastructure and scale. So that whole premise that they don't compete well there is wrong. And I think that chart demonstrates that there, in there in the hyper scale leadership category, hands down the question that I have. Is that there not as good and making that scale integrate in because they have that legacy cards. This is the classic innovator's dilemma. Clay Christensen, right? So I think they're doing a good job. I think their strategy sound. They're moving as fast as they can. But then you know they're not gonna come out and say We don't have the best cloud. Um, that's not a marketing strategy. Have to kind of hide in this and get better and then double down on where they're winning, which is. Clients are converting from their legacy at the speed of Microsoft, and they have a huge client base, So that's why they're stopping so high That's why they're so good. >>Well, I'm gonna I'm gonna give you a little preview. I talked to gear up your f Who's gonna come on today and you'll see I I asked him because the criticism of Microsoft is they're, you know, they're just good enough. And so I asked him, Are you better than good enough? You know, those are fighting words if you're inside of Microsoft, but so you'll you'll have to wait to see his answer. Now, if you guys, if you could bring that that graphic back up I wanted to get into the hybrid zone. You know where the field is. Always got >>some questions coming in on chat, Dave. So we'll get to those >>great Awesome. So just just real quick Here you see this hybrid zone, this the field is bunched up, and the other companies who have a large on Prem presence and have been forced to initiate some kind of coherent cloud strategy included. There is Michael Michael, multi Cloud, and Google's there, too, because they're far behind and they got to take a different approach than a W s. But as you can see, so there's some real progress here. VM ware cloud on AWS stands out, as does red hat open shift. You got VM Ware Cloud, which is a VCF Cloud Foundation, even Dell's cloud. And you'd expect HP with Green Lake to be picking up momentum in the future quarters. And you've got IBM and Oracle, which there you go with the innovator's dilemma. But there, at least in the cloud game, and we can talk about that. But so, John, you know, to your point, you've gotta have different strategies. You're you're not going to take out the big too. So you gotta play, connect your print your on Prem to your cloud, your hybrid multi cloud and try to create new opportunities and new value there. >>Yeah, I mean, I think we'll get to the question, but just that point. I think this Zeri Chen's come on the Cube many times. We're trying to get him to come on lunch today with Features startup, but he's always said on the Q B is a V C at Greylock great firm. Jerry's Cloud genius. He's been there, but he made a point many, many years ago. It's not a winner. Take all the winner. Take most, and the Big Three maybe put four or five in there. We'll take most of the markets here. But I think one of the things that people are missing and aren't talking about Dave is that there's going to be a second tier cloud, large scale model. I don't want to say tear to cloud. It's coming to sound like a sub sub cloud, but a new category of cloud on cloud, right? So meaning if you get a snowflake, did I think this is a tale? Sign to what's coming. VM Ware Cloud is a native has had huge success, mainly because Amazon is essentially enabling them to be successful. So I think is going to be a wave of a more of a channel model of indirect cloud build out where companies like the Cube, potentially for media or others, will build clouds on top of the cloud. So if Google, Microsoft and Amazon, whoever is the first one to really enable that okay, we'll do extremely well because that means you can compete with their scale and create differentiation on top. So what snowflake did is all on Amazon now. They kind of should go to azure because it's, you know, politically correct that have multiple clouds and distribution and business model shifts. But to get that kind of performance they just wrote on Amazon. So there's nothing wrong with that. Because you're getting paid is variable. It's cap ex op X nice categorization. So I think that's the way that we're watching. I think it's super valuable, I think will create some surprises in terms of who might come out of the woodwork on be a leader in a category. Well, >>your timing is perfect, John and we do have some questions in the chat. But before we get to that, I want to bring in Sargi Joe Hall, who's a contributor to to our community. Sargi. Can you hear us? All right, so we got, uh, while >>bringing in Sarpy. Let's go down from the questions. So the first question, Um, we'll still we'll get the student second. The first question. But Ronald ask, Can a vendor in 2021 exist without a hybrid cloud story? Well, story and capabilities. Yes, they could live with. They have to have a story. >>Well, And if they don't own a public cloud? No. No, they absolutely cannot. Uh hey, Sergey. How you doing, man? Good to see you. So, folks, let me let me bring in Sergeant Kohala. He's a He's a cloud architect. He's a practitioner, He's worked in as a technologist. And there's a frequent guest on on the Cube. Good to see you, my friend. Thanks for taking the time with us. >>And good to see you guys to >>us. So we were kind of riffing on the competitive landscape we got. We got so much to talk about this, like, it's a number of questions coming in. Um, but Sargi we wanna talk about you know, what's happening here in Cloud Land? Let's get right into it. I mean, what do you guys see? I mean, we got yesterday. New regime, new inaug inauguration. Do you do you expect public policy? You'll start with you Sargi to have What kind of effect do you think public policy will have on, you know, cloud generally specifically, the big tech companies, the tech lash. Is it gonna be more of the same? Or do you see a big difference coming? >>I think that there will be some changing narrative. I believe on that. is mainly, um, from the regulators side. A lot has happened in one month, right? So people, I think are losing faith in high tech in a certain way. I mean, it doesn't, uh, e think it matters with camp. You belong to left or right kind of thing. Right? But parlor getting booted out from Italy s. I think that was huge. Um, like, how do you know that if a cloud provider will not boot you out? Um, like, what is that line where you draw the line? What are the rules? I think that discussion has to take place. Another thing which has happened in the last 23 months is is the solar winds hack, right? So not us not sort acknowledging that I was Russia and then wish you watching it now, new administration might have a different sort of Boston on that. I think that's huge. I think public public private partnership in security arena will emerge this year. We have to address that. Yeah, I think it's not changing. Uh, >>economics economy >>will change gradually. You know, we're coming out off pandemic. The money is still cheap on debt will not be cheap. for long. I think m and a activity really will pick up. So those are my sort of high level, Uh, >>thank you. I wanna come back to them. And because there's a question that chat about him in a But, John, how do you see it? Do you think Amazon and Google on a slippery slope booting parlor off? I mean, how do they adjudicate between? Well, what's happening in parlor? Uh, anything could happen on clubhouse. Who knows? I mean, can you use a I to find that stuff? >>Well, that's I mean, the Amazons, right? Hiding right there bunkered in right now from that bad, bad situation. Because again, like people we said Amazon, these all three cloud players win in the current environment. Okay, Who wins with the U. S. With the way we are China, Russia, cloud players. Okay, let's face it, that's the reality. So if I wanted to reset the world stage, you know what better way than the, you know, change over the United States economy, put people out of work, make people scared, and then reset the entire global landscape and control all with cash? That's, you know, conspiracy theory. >>So you see the riches, you see the riches, get the rich, get richer. >>Yeah, well, that's well, that's that. That's kind of what's happening, right? So if you start getting into this idea that you can't actually have an app on site because the reason now I'm not gonna I don't know the particular parlor, but apparently there was a reason. But this is dangerous, right? So what? What that's gonna do is and whether it's right or wrong or not, whether political opinion is it means that they were essentially taken offline by people that weren't voted for that. Weren't that when people didn't vote for So that's not a democracy, right? So that's that's a different kind of regime. What it's also going to do is you also have this groundswell of decentralized thinking, right. So you have a whole wave of crypto and decentralized, um, cyber punks out there who want to decentralize it. So all of this stuff in January has created a huge counterculture, and I had predicted this so many times in the Cube. David counterculture is coming and and you already have this kind of counterculture between centralized and decentralized thinking and so I think the Amazon's move is dangerous at a fundamental level. Because if you can't get it, if you can't get buy domain names and you're completely blackballed by by organized players, that's a Mafia, in my opinion. So, uh, and that and it's also fuels the decentralized move because people say, Hey, if that could be done to them, it could be done to me. Just the fact that it could be done will promote a swing in the other direction. I >>mean, independent of of, you know, again, somebody said your political views. I mean Parlor would say, Hey, we're trying to clean this stuff up now. Maybe they didn't do it fast enough, but you think about how new parlor is. You think about the early days of Twitter and Facebook, so they were sort of at a disadvantage. Trying to >>have it was it was partly was what it was. It was a right wing stand up job of standing up something quick. Their security was terrible. If you look at me and Cory Quinn on be great to have him, and he did a great analysis on this, because if you look the lawsuit was just terrible. Security was just a half, asshole. >>Well, and the experience was horrible. I mean, it's not It was not a great app, but But, like you said, it was a quick stew. Hand up, you know, for an agenda. But nonetheless, you know, to start, get to your point earlier. It's like, you know, Are they gonna, you know, shut me down? If I say something that's, you know, out of line, or how do I control that? >>Yeah, I remember, like, 2019, we involved closing sort of remarks. I was there. I was saying that these companies are gonna be too big to fail. And also, they're too big for other nations to do business with. In a way, I think MNCs are running the show worldwide. They're running the government's. They are way. Have seen the proof of that in us this year. Late last year and this year, um, Twitter last night blocked Chinese Ambassador E in us. Um, from there, you know, platform last night and I was like, What? What's going on? So, like, we used to we used to say, like the Chinese company, tech companies are in bed with the Chinese government. Right. Remember that? And now and now, Actually, I think Chinese people can say the same thing about us companies. Uh, it's not a good thing. >>Well, let's >>get some question. >>Let's get some questions from the chat. Yeah. Thank you. One is on M and a subject you mentioned them in a Who do you see is possible emanate targets. I mean, I could throw a couple out there. Um, you know, some of the cdn players, maybe aka my You know, I like I like Hashi Corp. I think they're doing some really interesting things. What do you see? >>Nothing. Hashi Corp. And anybody who's doing things in the periphery is a candidate for many by the big guys, you know, by the hyper scholars and number two tier two or five hyper scholars. Right. Uh, that's why sales forces of the world and stuff like that. Um, some some companies, which I thought there will be a target, Sort of. I mean, they target they're getting too big, because off their evaluations, I think how she Corpuz one, um, >>and >>their bunch in the networking space. Uh, well, Tara, if I say the right that was acquired by at five this week, this week or last week, Actually, last week for $500 million. Um, I know they're founder. So, like I found that, Yeah, there's a lot going on on the on the network side on the anything to do with data. Uh, that those air too hard areas in the cloud arena >>data, data protection, John, any any anything you could adhere. >>And I think I mean, I think ej ej is gonna be where the gaps are. And I think m and a activity is gonna be where again, the bigger too big to fail would agree with you on that one. But we're gonna look at white Spaces and say a white space for Amazon is like a monster space for a start up. Right? So you're gonna have these huge white spaces opportunities, and I think it's gonna be an M and a opportunity big time start ups to get bought in. Given the speed on, I think you're gonna see it around databases and around some of these new service meshes and micro services. I mean, >>they there's a There's a question here, somebody's that dons asking why is Google who has the most pervasive tech infrastructure on the planet. Not at the same level of other to hyper scale is I'll give you my two cents is because it took him a long time to get their heads out of their ads. I wrote a piece of around that a while ago on they just they figured out how to learn the enterprise. I mean, John, you've made this point a number of times, but they just and I got a late start. >>Yeah, they're adding a lot of people. If you look at their who their hiring on the Google Cloud, they're adding a lot of enterprise chops in there. They realized this years ago, and we've talked to many of the top leaders, although Curry and hasn't yet sit down with us. Um, don't know what he's hiding or waiting for, but they're clearly not geared up to chicken Pete. You can see it with some some of the things that they're doing, but I mean competed the level of Amazon, but they have strength and they're playing their strength, but they definitely recognize that they didn't have the enterprise motions and people in the DNA and that David takes time people in the enterprise. It's not for the faint of heart. It's unique details that are different. You can't just, you know, swing the Google playbook and saying We're gonna home The enterprises are text grade. They knew that years ago. So I think you're going to see a good year for Google. I think you'll see a lot of change. Um, they got great people in there. On the product marketing side is Dev Solution Architects, and then the SRE model that they have perfected has been strong. And I think security is an area that they could really had a lot of value it. So, um always been a big fan of their huge network and all the intelligence they have that they could bring to bear on security. >>Yeah, I think Google's problem main problem that to actually there many, but one is that they don't They don't have the boots on the ground as compared to um, Microsoft, especially an Amazon actually had a similar problem, but they had a wide breath off their product portfolio. I always talk about feature proximity in cloud context, like if you're doing one thing. You wanna do another thing? And how do you go get that feature? Do you go to another cloud writer or it's right there where you are. So I think Amazon has the feature proximity and they also have, uh, aske Compared to Google, there's skills gravity. Larger people are trained on AWS. I think Google is trying there. So second problem Google is having is that that they're they're more focused on, I believe, um, on the data science part on their sort of skipping the cool components sort of off the cloud, if you will. The where the workloads needs, you know, basic stuff, right? That's like your compute storage and network. And that has to be well, talk through e think e think they will do good. >>Well, so later today, Paul Dillon sits down with Mids Avery of Google used to be in Oracle. He's with Google now, and he's gonna push him on on the numbers. You know, you're a distant third. Does that matter? And of course, you know, you're just a preview of it's gonna say, Well, no, we don't really pay attention to that stuff. But, John, you said something earlier that. I think Jerry Chen made this comment that, you know, Is it a winner? Take all? No, but it's a winner. Take a lot. You know the number two is going to get a big chunk of the pie. It appears that the markets big enough for three. But do you? Does Google have to really dramatically close the gap on be a much, much closer, you know, to the to the leaders in orderto to compete in this race? Or can they just kind of continue to bump along, siphon off the ad revenue? Put it out there? I mean, I >>definitely can compete. I think that's like Google's in it. Then it they're not. They're not caving, right? >>So But But I wrote I wrote recently that I thought they should even even put mawr oven emphasis on the cloud. I mean, maybe maybe they're already, you know, doubling down triple down. I just I think that is a multi trillion dollar, you know, future for the industry. And, you know, I think Google, believe it or not, could even do more. Now. Maybe there's just so much you could dio. >>There's a lot of challenges with these company, especially Google. They're in Silicon Valley. We have a big Social Justice warrior mentality. Um, there's a big debate going on the in the back channels of the tech scene here, and that is that if you want to be successful in cloud, you have to have a good edge strategy, and that involves surveillance, use of data and pushing the privacy limits. Right? So you know, Google has people within the country that will protest contract because AI is being used for war. Yet we have the most unstable geopolitical seen that I've ever witnessed in my lifetime going on right now. So, um, don't >>you think that's what happened with parlor? I mean, Rob Hope said, Hey, bar is pretty high to kick somebody off your platform. The parlor went over the line, but I would also think that a lot of the employees, whether it's Google AWS as well, said, Hey, why are we supporting you know this and so to your point about social justice, I mean, that's not something. That >>parlor was not just social justice. They were trying to throw the government. That's Rob e. I think they were in there to get selfies and being protesters. But apparently there was evidence from what I heard in some of these clubhouse, uh, private chats. Waas. There was overwhelming evidence on parlor. >>Yeah, but my point is that the employee backlash was also a factor. That's that's all I'm saying. >>Well, we have Google is your Google and you have employees to say we will boycott and walk out if you bid on that jet I contract for instance, right, But Microsoft one from maybe >>so. I mean, that's well, >>I think I think Tom Poole's making a really good point here, which is a Google is an alternative. Thio aws. The last Google cloud next that we were asked at they had is all virtual issue. But I saw a lot of I T practitioners in the audience looking around for an alternative to a W s just seeing, though, we could talk about Mano Cloud or Multi Cloud, and Andy Jassy has his his narrative around, and he's true when somebody goes multiple clouds, they put you know most of their eggs in one basket. Nonetheless, I think you know, Google's got a lot of people interested in, particularly in the analytic side, um, in in an alternative, hedging their bets eso and particularly use cases, so they should be able to do so. I guess my the bottom line here is the markets big enough to have Really? You don't have to be the Jack Welch. I gotta be number one and number two in the market. Is that the conclusion here? >>I think so. But the data gravity and the skills gravity are playing against them. Another problem, which I didn't want a couple of earlier was Google Eyes is that they have to boot out AWS wherever they go. Right? That is a huge challenge. Um, most off the most off the Fortune 2000 companies are already using AWS in one way or another. Right? So they are the multi cloud kind of player. Another one, you know, and just pure purely somebody going 200% Google Cloud. Uh, those cases are kind of pure, if you will. >>I think it's gonna be absolutely multi cloud. I think it's gonna be a time where you looked at the marketplace and you're gonna think in terms of disaster recovery, model of cloud or just fault tolerant capabilities or, you know, look at the parlor, the next parlor. Or what if Amazon wakes up one day and said, Hey, I don't like the cubes commentary on their virtual events, so shut them down. We should have a fail over to Google Cloud should Microsoft and Option. And one of people in Microsoft ecosystem wants to buy services from us. We have toe kind of co locate there. So these are all open questions that are gonna be the that will become certain pretty quickly, which is, you know, can a company diversify their computing An i t. In a way that works. And I think the momentum around Cooper Netease you're seeing as a great connective tissue between, you know, having applications work between clouds. Right? Well, directionally correct, in my opinion, because if I'm a company, why wouldn't I wanna have choice? So >>let's talk about this. The data is mixed on that. I'll share some data, meaty our data with you. About half the companies will say Yeah, we're spreading the wealth around to multiple clouds. Okay, That's one thing will come back to that. About the other half were saying, Yeah, we're predominantly mono cloud we didn't have. The resource is. But what I think going forward is that that what multi cloud really becomes. And I think John, you mentioned Snowflake before. I think that's an indicator of what what true multi cloud is going to look like. And what Snowflake is doing is they're building abstraction, layer across clouds. Ed Walsh would say, I'm standing on the shoulders of Giants, so they're basically following points of presence around the globe and building their own cloud. They call it a data cloud with a global mesh. We'll hear more about that later today, but you sign on to that cloud. So they're saying, Hey, we're gonna build value because so many of Amazon's not gonna build that abstraction layer across multi clouds, at least not in the near term. So that's a really opportunity for >>people. I mean, I don't want to sound like I'm dating myself, but you know the date ourselves, David. I remember back in the eighties, when you had open systems movement, right? The part of the whole Revolution OS I open systems interconnect model. At that time, the networking stacks for S N A. For IBM, decadent for deck we all know that was a proprietary stack and then incomes TCP I p Now os I never really happened on all seven layers, but the bottom layers standardized. Okay, that was huge. So I think if you look at a W s or some of the comments in the chat AWS is could be the s n a. Depends how you're looking at it, right? And you could say they're open. But in a way, they want more Amazon. So Amazon's not out there saying we love multi cloud. Why would they promote multi cloud? They are a one of the clouds they want. >>That's interesting, John. And then subject is a cloud architect. I mean, it's it is not trivial to make You're a data cloud. If you're snowflake, work on AWS work on Google. Work on Azure. Be seamless. I mean, certainly the marketing says that, but technically, that's not trivial. You know, there are latent see issues. Uh, you know, So that's gonna take a while to develop. What? Do your thoughts there? >>I think that multi cloud for for same workload and multi cloud for different workloads are two different things. Like we usually put multiple er in one bucket, right? So I think you're right. If you're trying to do multi cloud for the same workload, that's it. That's Ah, complex, uh, problem to solve architecturally, right. You have to have a common ap ice and common, you know, control playing, if you will. And we don't have that yet, and then we will not have that for a for at least one other couple of years. So, uh, if you if you want to do that, then you have to go to the lower, lowest common denominator in technical sort of stock, if you will. And then you're not leveraging the best of the breed technology off their from different vendors, right? I believe that's a hard problem to solve. And in another thing, is that that that I always say this? I'm always on the death side, you know, developer side, I think, uh, two deaths. Public cloud is a proxy for innovative culture. Right. So there's a catch phrase I have come up with today during shower eso. I think that is true. And then people who are companies who use the best of the breed technologies, they can attract the these developers and developers are the Mazen's off This digital sort of empires, amazingly, is happening there. Right there they are the Mazen's right. They head on the bricks. I think if you don't appeal to developers, if you don't but extensive for, like, force behind educating the market, you can't you can't >>put off. It's the same game Stepping story was seeing some check comments. Uh, guard. She's, uh, linked in friend of mine. She said, Microsoft, If you go back and look at the Microsoft early days to the developer Point they were, they made their phones with developers. They were a software company s Oh, hey, >>forget developers, developers, developers. >>You were if you were in the developer ecosystem, you were treated his gold. You were part of the family. If you were outside that world, you were competitors, and that was ruthless times back then. But they again they had. That was where it was today. Look at where the software defined businesses and starve it, saying it's all about being developer lead in this new way to program, right? So the cloud next Gen Cloud is going to look a lot like next Gen Developer and all the different tools and techniques they're gonna change. So I think, yes, this kind of developer ecosystem will be harnessed, and that's the power source. It's just gonna look different. So, >>Justin, Justin in the chat has a comment. I just want to answer the question about elastic thoughts on elastic. Um, I tell you, elastic has momentum uh, doing doing very well in the market place. Thea Elk Stack is a great alternative that people are looking thio relative to Splunk. Who people complain about the pricing. Of course it's plunks got the easy button, but it is getting increasingly expensive. The problem with elk stack is you know, it's open source. It gets complicated. You got a shard, the databases you gotta manage. It s Oh, that's what Ed Walsh's company chaos searches is all about. But elastic has some riel mo mentum in the marketplace right now. >>Yeah, you know, other things that coming on the chat understands what I was saying about the open systems is kubernetes. I always felt was that is a bad metaphor. But they're with me. That was the TCP I peep In this modern era, C t c p I p created that that the disruptor to the S N A s and the network protocols that were proprietary. So what KUBERNETES is doing is creating a connective tissue between clouds and letting the open source community fill in the gaps in the middle, where kind of way kind of probably a bad analogy. But that's where the disruption is. And if you look at what's happened since Kubernetes was put out there, what it's become kind of de facto and standard in the sense that everyone's rallying around it. Same exact thing happened with TCP was people were trashing it. It is terrible, you know it's not. Of course they were trashed because it was open. So I find that to be very interesting. >>Yeah, that's a good >>analogy. E. Thinks the R C a cable. I used the R C. A cable analogy like the VCRs. When they started, they, every VC had had their own cable, and they will work on Lee with that sort of plan of TV and the R C. A cable came and then now you can put any TV with any VCR, and the VCR industry took off. There's so many examples out there around, uh, standards And how standards can, you know, flair that fire, if you will, on dio for an industry to go sort of wild. And another trend guys I'm seeing is that from the consumer side. And let's talk a little bit on the consuming side. Um, is that the The difference wouldn't be to B and B to C is blood blurred because even the physical products are connected to the end user Like my door lock, the August door lock I didn't just put got get the door lock and forget about that. Like I I value the expedience it gives me or problems that gives me on daily basis. So I'm close to that vendor, right? So So the middle men, uh, middle people are getting removed from from the producer off the technology or the product to the consumer. Even even the sort of big grocery players they have their APs now, uh, how do you buy stuff and how it's delivered and all that stuff that experience matters in that context, I think, um, having, uh, to be able to sell to thes enterprises from the Cloud writer Breuder's. They have to have these case studies or all these sample sort off reference architectures and stuff like that. I think whoever has that mawr pushed that way, they are doing better like that. Amazon is Amazon. Because of that reason, I think they have lot off sort off use cases about on top of them. And they themselves do retail like crazy. Right? So and other things at all s. So I think that's a big trend. >>Great. Great points are being one of things. There's a question in there about from, uh, Yaden. Who says, uh, I like the developer Lead cloud movement, But what is the criticality of the executive audience when educating the marketplace? Um, this comes up a lot in some of my conversations around automation. So automation has been a big wave to automate this automate everything. And then everything is a service has become kind of kind of the the executive suite. Kind of like conversation we need to make everything is a service in our business. You seeing people move to that cloud model. Okay, so the executives think everything is a services business strategy, which it is on some level, but then, when they say Take that hill, do it. Developers. It's not that easy. And this is where a lot of our cube conversations over the past few months have been, especially during the cova with cute virtual. This has come up a lot, Dave this idea, and start being around. It's easy to say everything is a service but will implement it. It's really hard, and I think that's where the developer lead Connection is where the executive have to understand that in order to just say it and do it are two different things. That digital transformation. That's a big part of it. So I think that you're gonna see a lot of education this year around what it means to actually do that and how to implement it. >>I'd like to comment on the as a service and subject. Get your take on it. I mean, I think you're seeing, for instance, with HP Green Lake, Dell's come out with Apex. You know IBM as its utility model. These companies were basically taking a page out of what I what I would call a flawed SAS model. If you look at the SAS players, whether it's salesforce or workday, service now s a P oracle. These models are They're really They're not cloud pricing models. They're they're basically you got to commit to a term one year, two year, three year. We'll give you a discount if you commit to the longer term. But you're locked in on you. You probably pay upfront. Or maybe you pay quarterly. That's not a cloud pricing model. And that's why I mean, they're flawed. You're seeing companies like Data Dog, for example. Snowflake is another one, and they're beginning to price on a consumption basis. And that is, I think, one of the big changes that we're going to see this decade is that true cloud? You know, pay by the drink pricing model and to your point, john toe, actually implement. That is, you're gonna need a whole new layer across your company on it is quite complicated it not even to mention how you compensate salespeople, etcetera. The a p. I s of your product. I mean, it is that, but that is a big sea change that I see coming. Subject your >>thoughts. Yeah, I think like you couldn't see it. And like some things for this big tech exacts are hidden in the plain >>sight, right? >>They don't see it. They they have blind spots, like Look at that. Look at Amazon. They went from Melissa and 200 millisecond building on several s, Right, Right. And then here you are, like you're saying, pay us for the whole year. If you don't use the cloud, you lose it or will pay by month. Poor user and all that stuff like that that those a role models, I think these players will be forced to use that term pricing like poor minute or for a second, poor user. That way, I think the Salesforce moral is hybrid. They're struggling in a way. I think they're trying to bring the platform by doing, you know, acquisition after acquisition to be a platform for other people to build on top off. But they're having a little trouble there because because off there, such pricing and little closeness, if you will. And, uh, again, I'm coming, going, going back to developers like, if you are not appealing to developers who are writing the latest and greatest code and it is open enough, by the way open and open source are two different things that we all know that. So if your platform is not open enough, you will have you know, some problems in closing the deals. >>E. I want to just bring up a question on chat around from Justin didn't fitness. Who says can you touch on the vertical clouds? Has your offering this and great question Great CP announcing Retail cloud inventions IBM Athena Okay, I'm a huge on this point because I think this I'm not saying this for years. Cloud computing is about horizontal scalability and vertical specialization, and that's absolutely clear, and you see all the clouds doing it. The vertical rollouts is where the high fidelity data is, and with machine learning and AI efforts coming out, that's accelerated benefits. There you have tow, have the vertical focus. I think it's super smart that clouds will have some sort of vertical engine, if you will in the clouds and build on top of a control playing. Whether that's data or whatever, this is clearly the winning formula. If you look at all the successful kind of ai implementations, the ones that have access to the most data will get the most value. So, um if you're gonna have a data driven cloud you have tow, have this vertical feeling, Um, in terms of verticals, the data on DSO I think that's super important again, just generally is a strategy. I think Google doing a retail about a super smart because their whole pitches were not Amazon on. Some people say we're not Google, depending on where you look at. So every of these big players, they have dominance in the areas, and that's scarce. Companies and some companies will never go to Amazon for that reason. Or some people never go to Google for other reasons. I know people who are in the ad tech. This is a black and we're not. We're not going to Google. So again, it is what it is. But this idea of vertical specialization relevant in super >>forts, I want to bring to point out to sessions that are going on today on great points. I'm glad you asked that question. One is Alan. As he kicks off at 1 p.m. Eastern time in the transformation track, he's gonna talk a lot about the coming power of ecosystems and and we've talked about this a lot. That that that to compete with Amazon, Google Azure, you've gotta have some kind of specialization and vertical specialization is a good one. But of course, you see in the big Big three also get into that. But so he's talking at one o'clock and then it at 3 36 PM You know this times are strange, but e can explain that later Hillary Hunter is talking about she's the CTO IBM I B M's ah Financial Cloud, which is another really good example of specifying vertical requirements and serving. You know, an audience subject. I think you have some thoughts on this. >>Actually, I lost my thought. E >>think the other piece of that is data. I mean, to the extent that you could build an ecosystem coming back to Alan Nancy's premise around data that >>billions of dollars in >>their day there's billions of dollars and that's the title of the session. But we did the trillion dollar baby post with Jazzy and said Cloud is gonna be a trillion dollars right? >>And and the point of Alan Answer session is he's thinking from an individual firm. Forget the millions that you're gonna save shifting to the cloud on cost. There's billions in ecosystems and operating models. That's >>absolutely the business value. Now going back to my half stack full stack developer, is the business value. I've been talking about this on the clubhouses a lot this past month is for the entrepreneurs out there the the activity in the business value. That's the new the new intellectual property is the business logic, right? So if you could see innovations in how work streams and workflow is gonna be a configured differently, you have now large scale cloud specialization with data, you can move quickly and take territory. That's much different scenario than a decade ago, >>at the point I was trying to make earlier was which I know I remember, is that that having the horizontal sort of features is very important, as compared to having vertical focus. You know, you're you're more healthcare focused like you. You have that sort of needs, if you will, and you and our auto or financials and stuff like that. What Google is trying to do, I think that's it. That's a good thing. Do cook up the reference architectures, but it's a bad thing in a way that you drive drive away some developers who are most of the developers at 80 plus percent, developers are horizontal like you. Look at the look into the psyche of a developer like you move from company to company. And only few developers will say I will stay only in health care, right? So I will only stay in order or something of that, right? So they you have to have these horizontal capabilities which can be applied anywhere on then. On top >>of that, I think that's true. Sorry, but I'll take a little bit different. Take on that. I would say yes, that's true. But remember, remember the old school application developer Someone was just called in Application developer. All they did was develop applications, right? They pick the framework, they did it right? So I think we're going to see more of that is just now mawr of Under the Covers developers. You've got mawr suffer defined networking and software, defined storage servers and cloud kubernetes. And it's kind of like under the hood. But you got your, you know, classic application developer. I think you're gonna see him. A lot of that come back in a way that's like I don't care about anything else. And that's the promise of cloud infrastructure is code. So I think this both. >>Hey, I worked. >>I worked at people solved and and I still today I say into into this context, I say E r P s are the ultimate low code. No code sort of thing is right. And what the problem is, they couldn't evolve. They couldn't make it. Lightweight, right? Eso um I used to write applications with drag and drop, you know, stuff. Right? But But I was miserable as a developer. I didn't Didn't want to be in the applications division off PeopleSoft. I wanted to be on the tools division. There were two divisions in most of these big companies ASAP. Oracle. Uh, like companies that divisions right? One is the cooking up the tools. One is cooking up the applications. The basketball was always gonna go to the tooling. Hey, >>guys, I'm sorry. We're almost out of time. I always wanted to t some of the sections of the day. First of all, we got Holder Mueller coming on at lunch for a power half hour. Um, you'll you'll notice when you go back to the home page. You'll notice that calendar, that linear clock that we talked about that start times are kind of weird like, for instance, an appendix coming on at 1 24. And that's because these air prerecorded assets and rather than having a bunch of dead air, we're just streaming one to the other. So so she's gonna talk about people, process and technology. We got Kathy Southwick, whose uh, Silicon Valley CEO Dan Sheehan was the CEO of Dunkin Brands and and he was actually the c 00 So it's C A CEO connecting the dots to the business. Daniel Dienes is the CEO of you I path. He's coming on a 2:47 p.m. East Coast time one of the hottest companies, probably the fastest growing software company in history. We got a guy from Bain coming on Dave Humphrey, who invested $750 million in Nutanix. He'll explain why and then, ironically, Dheeraj Pandey stew, Minuteman. Our friend interviewed him. That's 3 35. 1 of the sessions are most excited about today is John McD agony at 403 p. M. East Coast time, she's gonna talk about how to fix broken data architectures, really forward thinking stuff. And then that's the So that's the transformation track on the future of cloud track. We start off with the Big Three Milan Thompson Bukovec. At one oclock, she runs a W s storage business. Then I mentioned gig therapy wrath at 1. 30. He runs Azure is analytics. Business is awesome. Paul Dillon then talks about, um, IDs Avery at 1 59. And then our friends to, um, talks about interview Simon Crosby. I think I think that's it. I think we're going on to our next session. All right, so keep it right there. Thanks for watching the Cuban cloud. Uh huh.

Published Date : Jan 22 2021

SUMMARY :

cloud brought to you by silicon angle, everybody I was negative in quarantine at a friend's location. I mean, you go out for a walk, but you're really not in any contact with anybody. And I think we're in a new generation. The future of Cloud computing in the coming decade is, John said, we're gonna talk about some of the public policy But the goal here is to just showcase it's Whatever you wanna call it, it's a cube room, and the people in there chatting and having a watch party. that will take you into the chat, we'll take you through those in a moment and share with you some of the guests And then from there you just It was just awesome. And it kind of ironic, if you will, because the pandemic it hits at the beginning of this decade, And if you weren't a digital business, you were kind of out of business. last 10 years defined by you know, I t transformation. And if you look at some of the main trends in the I think the second thing is you can see on this data. Everybody focuses on the growth rates, but it's you gotta look at also the absolute dollars and, So you know, as you're doing trends job, they're just it's just pedal as fast as you can. It's a measure of the pervasiveness or, you know, number of mentions in the data set. And I think that chart demonstrates that there, in there in the hyper scale leadership category, is they're, you know, they're just good enough. So we'll get to those So just just real quick Here you see this hybrid zone, this the field is bunched But I think one of the things that people are missing and aren't talking about Dave is that there's going to be a second Can you hear us? So the first question, Um, we'll still we'll get the student second. Thanks for taking the time with us. I mean, what do you guys see? I think that discussion has to take place. I think m and a activity really will pick up. I mean, can you use a I to find that stuff? So if I wanted to reset the world stage, you know what better way than the, and that and it's also fuels the decentralized move because people say, Hey, if that could be done to them, mean, independent of of, you know, again, somebody said your political views. and he did a great analysis on this, because if you look the lawsuit was just terrible. But nonetheless, you know, to start, get to your point earlier. you know, platform last night and I was like, What? you know, some of the cdn players, maybe aka my You know, I like I like Hashi Corp. for many by the big guys, you know, by the hyper scholars and if I say the right that was acquired by at five this week, And I think m and a activity is gonna be where again, the bigger too big to fail would agree with Not at the same level of other to hyper scale is I'll give you network and all the intelligence they have that they could bring to bear on security. The where the workloads needs, you know, basic stuff, right? the gap on be a much, much closer, you know, to the to the leaders in orderto I think that's like Google's in it. I just I think that is a multi trillion dollar, you know, future for the industry. So you know, Google has people within the country that will protest contract because I mean, Rob Hope said, Hey, bar is pretty high to kick somebody off your platform. I think they were in there to get selfies and being protesters. Yeah, but my point is that the employee backlash was also a factor. I think you know, Google's got a lot of people interested in, particularly in the analytic side, is that they have to boot out AWS wherever they go. I think it's gonna be a time where you looked at the marketplace and you're And I think John, you mentioned Snowflake before. I remember back in the eighties, when you had open systems movement, I mean, certainly the marketing says that, I think if you don't appeal to developers, if you don't but extensive She said, Microsoft, If you go back and look at the Microsoft So the cloud next Gen Cloud is going to look a lot like next Gen Developer You got a shard, the databases you gotta manage. And if you look at what's happened since Kubernetes was put out there, what it's become the producer off the technology or the product to the consumer. Okay, so the executives think everything is a services business strategy, You know, pay by the drink pricing model and to your point, john toe, actually implement. Yeah, I think like you couldn't see it. I think they're trying to bring the platform by doing, you know, acquisition after acquisition to be a platform the ones that have access to the most data will get the most value. I think you have some thoughts on this. Actually, I lost my thought. I mean, to the extent that you could build an ecosystem coming back to Alan Nancy's premise But we did the trillion dollar baby post with And and the point of Alan Answer session is he's thinking from an individual firm. So if you could see innovations Look at the look into the psyche of a developer like you move from company to company. And that's the promise of cloud infrastructure is code. I say E r P s are the ultimate low code. Daniel Dienes is the CEO of you I path.

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Dheeraj Pandey, Nutanix | CUBE On Cloud


 

>> Hi, and this is theCUBE on Cloud. I'm Stu Miniman and really excited to welcome to a special Fireside Chat. CUBE Alumni has been on the program so many times. We always love talking to founders. We like talking to deep thinkers and that's why he was one of the early ones that I reached out to when we were working on this event. When we first started conversations, we were looking at how hyperscalers really were taking adoption of the brand new technologies, things like flash, things like software defined networking, and how that would invade the enterprise. That of course has had a huge impact, help create a category called hyperconverged infrastructure and I'm talking about Dheeraj Pandey. He is the founder, chairman, and CEO of Nutanix, taking HCI from hyperconverged infrastructure to hybrid cloud infrastructure. So Dheeraj, welcome to the Fireside Chat. Thank you so much for joining us. >> Thank you, Stu, and thank you for the last 10 years that we've grown together, both theCUBE and Nutanix and myself as a leader in the last 10 years. So bringing HCI from hyperconverged to hybrid cloud just reminds me of how the more things change, the more they remain the same. So looking forward to a great discussion here. >> So talk about that early discussion, what the hyperscalers were doing, how can the enterprise take advantage of that? Over time, enterprise has matured and looked a little bit more like the hyperscalers. Hybrid cloud of course is on everyone's lip, as well as we've seen the hyperscalers themselves look more and more like the enterprise. So hybrid and multicloud is where we are today. We think it'll be in the future. But give us a little bit as to how you've seen that progression today and where are we going down the road here? >> Yeah, I think I talked about this during my .NEXT keynote. And the whole idea of, in every recession, we make things smaller. In '91 we said we're going to go away from mainframes into Unix servers. And we made the unit of compute smaller. Then in the year 2000 when there was the next bubble burst and the recession afterwards, we moved from Unix servers to Wintel: Windows and Intel, x86 and eventually Linux as well. Again we made things smaller going from million dollar servers to $5,000 servers, shorter lived servers. And that's what we did in 2008/2009. I said, look, we don't even need to buy servers. We can do things with virtual machines which are servers that are an incarnation in the digital world. There is nothing in the physical world that actually went lives. But we made it even smaller. And now with cloud in the last three, four years and what will happen in this coming decade, they're going to make it even smaller, not just in space which is size with functions and containers and virtual machines, but also in time. So space and time, we're talking about hourly billing and monthly billing and a one-year term as opposed to really going and committing to five or seven years of hardware and CapEx. So I think as you make things smaller, I mean, and this is true for as consumers, we have short retention spans, things are going fast. The cycle of creative destruction of virtual machines is shrinking as well. So I think in many cases, we know we've gone and created this autonomy, massive sprawl. Like we created a massive sprawl of Intel servers back in '95 and 2005. Then we have to use virtualization to go and consolidate all of it, created beautiful data centers of Intel servers with VMware software. And then we created a massive sprawl of data centers, of consolidated data centers with one click private cloud in the last five years and hopefully in the next five too. But I think we're also now creating a proliferation of clouds. There is a sprawl, massive sprawl of cost centers and such. So we need yet another layer of software for governance to reign in on that chaos, hence the need for a new HCI, hybrid cloud infrastructure. >> Yeah, it's fascinating to kind of watch that progression over time. There was a phenomenal Atlantic article. I think it was from like the 1940s or 1950s where somebody took what was happening post-World War II and projected things out. We're talking really pre the internet, but just the miniaturization and the acceleration, kind of the Moore's law discussion. If you take things out, where it would go. When I talked to Amazon, they said the one thing that we know for sure, I'm talking to Amazon.com is that people will want it faster and cheaper in the future. I don't know which robot or drone or things that they have. But absolutely there are those certain characteristics. So from a leadership standpoint, Dheeraj, talk about these changes? We had the wave of virtualization, the wave of containerization, you talked about functions in serverless. Those are tools. But at the end of the day, it's about the outcomes and how do we take advantage of things? So how as a leader do you make sure that you know where to take the company as these technology waves and changes impact what you're doing? >> Yeah, it's a great point. I mean, we celebrate things in IT a lot, but we don't talk about what does it take? What's the underlying fabric to really use these things successfully and better than others and not just use buzzwords, because new buzzwords will come in the next three years. For example AI and ML has been a great buzzword for the last three, four years. But there's very few companies, probably less than even half a percent who know how to leverage machine learning, even understand the difference between machine learning and AI. And a lot of it comes down to a few principles. There's a culture principles, not the least of which is how you celebrate failure, because now you're doing shorter, smaller things. You've got a more agile, you'll have more velocity. Gone are the days of waterfall where you're doing yearly planning and pre-year releases and such. So as we get into this new world, not everything will be perfect, and you've got to really learn to pick yourself up and recover quickly, heal quickly and such. So that is the fundamental tenet of Silicon Valley. And we got to really go and use this more outside the Valley as well in every company out there. Whether it's East Coast company, the Midwest company that are outside the U.S. I think this idea that you will be vulnerable, more vulnerable as you go and learn to do things faster and shorter. I think product management is a term that we don't fully understand, and this is about the why before the how and the what. We quickly jump to the what: containers and functions and databases, servers, and AI, and ML, they're the what. But how do you really start with the why? You know my fascination for one of my distant mentors, Simon Sinek and how he thinks about most companies just focusing on the what, while very few actually start with why, then the how, then the what itself. And product management has to play a key role in this, which also subsumes design, thinking about simplification and elegance and reducing friction. I think again, very few companies, probably no more than 1% of the companies really understand what it means to start with design and APIs, user experience APIs for developers before you even get to writing any single line of code. So I think to me, that's leadership. When you can stay away from instant gratification of the end result, but start with the why, then the how, then the what. >> Yeah, as we know in the technology space, oftentimes the technology is the easy part. It's helping to drive that change. I think back to the early days when we were talking, it was, hyperconverge, it was a threat to storage. We're going to put you out of a job. And we'd always go and say, "Look, no, no, no. We're not putting you out of a job. We're going to free you up to do the things that you want to do. That security project that's been sitting on the shelf for six months, you can go do that. Helping build new parts of the business. Those things that you can do." It's that shifting a mindset can be so difficult. And Dheeraj, I mean, you look at 2020, everyone has had to shift their mindset for everything. I was spending half my time on the road. I don't miss the hotels. I do miss seeing lots and lots of people in person. So what's your advice for people, how they can stay malleable, be open to some change? What are you seeing out there? What advice do you give there? >> Yeah, I think, as you said, inertia is at the core of most things in our lives, including what we saw in healthcare for the last 20, 30 years. I mean, there was so much regulation. The doctor's community had to move forward, nurses had to move forward. I mean, not just providers, but insurance companies. And finally, all of a sudden, we're talking about telehealth because of the pandemic. We are talking about online learning. I mean the things that higher ed refused to do. I mean if you think about the last 20 years of what had happened with the cost of higher ed, I mean it's 200% growth when the cost of television has gone down by probably 100, 200% with more features. Healthcare, higher ed, education in general, all of a sudden is coming for this deep shock because of the pandemic. And I think it's these kind of black swan moments that really changed the world. And I know it's a cliche to say this. But I feel like we are going to be in a new normal, and we have been forced to this new change of digital. I mean, you and I are sitting and talking over the internet. It's a little awkward right now because there's a little bit of a delay in the way I'm looking at things. But I know it's going to directionally be right. I mean, we will go in a way where it just become seamless over time. So change is the only constant. And I believe that I think what we've seen in the pandemic is just the beginning of what digital will mean going forward. And I think the more people embrace it, the faster we do it. Speed is going to be the name of the game when it comes to survival and thriving in this new age. >> Dheeraj, it's interesting. We do hope, I'm a technologist. I know you're an optimist when it comes to things. So we always look at those silver linings. Like I hope healthcare and education will be able to move forward fast. Higher education costs, inequity out there for access to medicine. It would be wonderful if we could help solve some of that, despite this global pandemic. One of the other results, Dheeraj, we talked about some very shifts in the marketplace, the large tech players really have emerged in winter so far in 2020. I can't help, but watch the stock market. And Apple is bigger than ever, Amazon, Google, all ended up in front of Congress to talk about if they've gotten too big. You've partnered with Amazon, Microsoft, and Google. They are potentially a threat but also a partner. From your standpoint, have they gotten too much power? Do we have an inequity in the tech world that they are creating the universes that they will just kind of block off and limit innovation? What's your take on big tech? >> Yeah, I mean, I feel like there's always been big something. I mean, if you go back to the '90s, Amazon, not Amazon, IBM was big, and Microsoft was big, and AT&T was big. I mean, there's always been big companies because the consumer effect that they've had as well, I mean. And I think what we're seeing right now is no different. I mean, at the end of the day, the great thing about this country is that there's always disruption happening. And sometimes small is way better and way more competitive than big. Now at the same time, I do look up to the way some of them have organized themselves. Like the way Amazon has organized itself is really unique and creative with general managers and very independent, highly autonomous groups. So some of these organizations will definitely survive and thrive in scale. And yet for others, I think decision-making and staying competitive and staying scrappy will come a lot harder. So to me when I look at these big names and what Congress is talking about and such, I feel like there's no different than 20, 30, 40 years ago. I mean, we talked about Rockefeller and the oil giants back from 100 years ago. And so in many ways, I mean, the more things change, the more they remain the same. All we have to do is we have to walk over to where the customer is. And that's what we've done with the partnerships. Like in Amazon and Azure, we're saying look, we can even use your commits and credits. I mean, that is a very elegant way to go to where the customer is, rather than force them to where we are. And the public cloud is facing this too. They've come to realize in the last two years that they cannot force all of enterprise computing to come to hyperscalers data centers. They'll have to take in these bite-size smaller clouds to where the customer is, where the customer's machines are, where the customers people are, where the customers data is. That's where we also take to disperse the cloud itself. So I think there's going to be a yin yang where we'll try to walk with the customer to where we want them to be, whether it's hyperscaler data center or the notion of hybrid cloud infrastructure. But many a time, we've got to walk over to where they are. I mean, and outside the U.S, I mean, the cloud is such a nuanced word. I mean, we're talking about sovereignty, we're talking about data gravity, we're talking about economics of owning versus renting. This trifecta, the laws of the land, the laws of physics, and the laws of economics will dictate many of these things as well. So I think the big folks are also humble and vulnerable to realize that there's nothing more powerful than market forces. And I think the rest will take care of itself. >> Yeah, my quick commentary on that, Dheeraj, I think most of us look back at AT&T and felt the government got it wrong. The way they broke it up and ended up consolidating back together, it didn't necessarily help consumers. Microsoft on the other hand might've had a little bit too much power and was leveraging that against competition and really squashing innovation. So in general, it's good to see that the politics are looking at that and chore felt. The last time I watched things, they were a little bit more educated than some previous times there, where it was almost embarrassing to watch our representatives fumbling around with technology. So it's always good to question authority, question what they have. And one of the things you've brought up many times is you're open to listening and you're bringing in new ideas. I remember one conversation I had with you is there's that direction that you hold on to, but you will assess and do new data. You've made adjustments in the product portfolio and direction based on your customers, based on the ecosystem. And you've mentioned some of the, bring thoughts that you've brought into the company and you share. So you mentioned black swan that seem to head you brought to one of the European .NEXT shows. It was great to be able to see that author and read through advisors like Condoleezza Rice who you've had at the conferences a couple of times. Where are you getting some of your latest inspiration from, any new authors or podcasts that you'd be recommending to the audience? >> Yeah, I look at adjacencies, obviously Simon has been great. He was .NEXT, talked about the Infinite Game. And we'll talk about the Infinite Game with Nutanix too with respect to also my decision. But Brene Brown was been very close to Nutanix. I was just looking at her latest podcast, and she was sitting with the author of Stretch, Scott Sonnenschein, and it's a fascinating read and a great listen, by the way, I think for worth an hour, talking about scrappiness, and talking about resourcefulness. What does it mean to really be resourceful? And we need that even more so as we go through this recession, as we are sheltered in place. I think it's an adjacency to everything that Brene does. And I was just blown away by just listening to it. I'd a love for others to even have a listen and learn to understand what we can do within our families, with our budgets, with our companies, with our startups. I mean, with CUBE, I mean, what does it mean to be scrappy? And celebrate scrappiness and resourcefulness, more so than AI always need more. I think I just found it fascinating in the last week itself listening through it. >> John Farinacci talk many times that founder, startup, that being able to pull themselves up, be able to drive forward, overcome obstacles. So Dheeraj, do you tee it up? It sounds like is the next step for you. There's a transition under discussion. Bain has made an investment. There's a search for new CEO. Are you saying there's a book club in your future to be able to get things ready? Why don't you explain a little bit, 11 years took the company public, over 6,500 employees public company. So tell us a little bit about that decision-making process and what you expect to see in the future? >> Yeah, it's probably one of the hardest things as an entrepreneur is to let go, because it's a creation that you followed from scratch, from nothing. And it was a process for me to rethink about what's next for the company and then what's next for me? And me and the company were so tightly coupled that I was like, wow, at some point, this has to be a little bit more like the way Bill Gates did it with Microsoft, and there's going to be buton zone and you will then start to realize that your identity is different from the company's identity. And maybe the company is built for bigger, better things. And maybe you're built for bigger, better things. And how do you really start to first do this decoupling of the identity? And it's really hard. I mean, I'm sure that parents go through this. I mean, our children are still very young. Our eldest is nine going on 10 and our twin girls are six. I know at some point in the next 10 years, eight to 10 years, we'll have to figure out what it means to let go. And I'm already doing this with my son. I tell him you're born free. I mean, the word born free which drives my wife crazy sometimes. I say this to them, it's about independence. And I think the company is also born free to really think about a life outside of me, as well outside of founder. And that was a very important process for me as I was talking to the board for the last six, seven, eight months. And when the Bain deal came in, I thought it was a great time. We ended the fiscal really well, all things considered. We had a good quarter. The transition has been a journey of a lifetime, the business model transition I speak of. Really three years, I mean, I have aged probably 10 years in these last three years. But I think I would not replaced it for anything. Just the experience of learning what it means to change as a public company when you have short-term goals and long-term goals, we need the conviction, knowing what's right, because otherwise we would not have survived this cloud movement, all this idea of actually becoming a subscription company, changing the core of the business in the on-prem world itself. It's a king to change the wings of a plane at 40,000 feet where none of the passengers blink. It's been phenomenal ride last 11 years, but it's also been nonstop monomaniacal. I mean, I use the word marathon for this, and I figured it's a good time to say figure out a way to let go of this, and think of what's bigger better for Nutanix. And going from zero to a billion six in annual billings, and looking at billion six to 3 billion to four to five, I think it'd be great &to look at this from afar. And at the same time, I think there's vulnerability. I mean, I've made the company vulnerable. I've made myself vulnerable. We don't know who the next leader will be. And I think the next three to six months is one of the most important baton zones that I have ever experienced to be a part of. So looking forward to make sure that baton doesn't fall, redefine what good to great looks like, both for the company and for myself. And at the same time, go read more. I mean, I've been passionate about developers in the last 10 years, 11 years. I was a developer myself. This company, Nutanix, was really built by developers for IT. And I'm learning more about the developer as a consumer. How do you think about their experience? Not just the things that we throw at them from open source point of view and from cloud and technologies and AI and ML point of view, but really their lives, having them think about revenue and business and really blurring the lines between architects and product managers and developers. I think it's just an unfathomable problem we've created in IT that I would love to go and read and write more about. >> Yeah, so many important things you said there. I absolutely think that there are certain things everybody of course will think of you for a long time with Nutanix, but there is that separation between the role in the company and the person itself, and really appreciated how much you've always shared along those lines. So last question I have and you hit it up a little bit when you talked about developers. Take off your Nutanix hat for a second here, now what do we need to do to make sure that the next decade is successful in this space, cloud as a general guideline? Yes, we know we have skill gap. We know we need more people, we need more diversity. But there's so much that we need and there's so much opportunity, but what do you see and any advice areas that you think are critical for success in the future? >> Yeah, I mean, you hit up on something that I have had a passion for, probably more late in this world, more so than conspicuous, and and you hit upon it right now, diversity and inclusion. It's an unresolved problem in the developer community: the black developer, the woman developer. The idea of, I mean, we've two girls, they're twins. I'd love for them to embrace computer science and even probably do a PhD. I mean, I was a dropout. I'd love for them to do better than I did. Get, embrace things that are adjacent to biology and computer science. Go solve really hard problems. And we've not done those things. I mean, we've not looked at the community of developers and said, you know, they are the maker. And they work with managers and the maker manager world is two different worlds. How do you make this less friction? And how do you make this more delightful? And how do you think of developers as business, as if they are the folks who run the business? I think there's a lot that's missing there. And again, we throw a lot of jargons at them, and we talk a lot about automation and tools and such. But those are just things. I think the last 10, 11 years of me really just thinking about product and product portfolio and design and the fact that we have so many developers at Nutanix. I think it has been a mind-boggling experience, thinking about the why and the how and the what of the day in the life of, the month in the life of, and thinking about simple things like OKRs. I mean, we are throwing these jargons of OKRs at them: productivity, offshoring, remote work, over the zoom design sessions. It's just full of conflict and friction. So I think there is an amazing opportunity for Nutanix. There's an amazing opportunity for the industry to elevate this where the the woman developer can speak up in this world that's full of so many men. The black developer can speak up. And all of us can really think of this as something that's more structured, more productive, more revenue-driven, more customer in rather than developer out. That's really been some of the things that have been in my head, things that are still unresolved at Nutanix that I'm pretty sure at many of the places out there. That's what thinking and reading and writing about. >> Well, Dheeraj, first of all, thank you so much again for participating here. It's been great having you in theCUBE community, almost since the inception of us doing it back in 2010. Wish you the best of luck in the current transition. And absolutely look forward to talking more in the future. >> Thank you. And again, a big fan of the tremor rate of John, Dave, and you. Always learn so much from you, folks. Looking forward to be a constant student. Thank you. >> Thank you for joining us at theCUBE on Cloud. Lots more coverage here. Be sure to look throughout the site, engage in the chats, and give us your feedback. We're here to help you with the virtual events. I'm Stu Miniman as always. Thanks for watching.

Published Date : Jan 5 2021

SUMMARY :

of the brand new technologies, in the last 10 years. and more like the enterprise. and the recession afterwards, and cheaper in the future. So that is the fundamental I don't miss the hotels. I mean the things that One of the other results, Dheeraj, I mean, at the end of the day, And one of the things you've and a great listen, by the and what you expect to see in the future? And I think the next three to six months and the person itself, and the fact that we have so in the current transition. And again, a big fan of the tremor rate engage in the chats, and

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Sagar Kadakia | CUBE Conversation, December 2020


 

>> From The Cube Studios in Palo Alto and Boston connecting with thought-leaders all around the world, this is a Cube Conversation. >> Hello, everyone, and welcome to this Cube Conversation, I'm Dave Vellante. Now, you know I love data, and today we're going to introduce you to a new data and analytical platform, and we're going to take it to the world of cloud database and data warehouses. And with me is Sagar Kadakia who's the head of Enterprise IT (indistinct) 7Park Data. Sagar, welcome back to the Cube. Good to see you. >> Thank you so much, David. I appreciate you having me back on. >> Hey, so new gig for you, how's it going? Tell us about 7Park Data. >> Yeah. Look, things are going well. It started at about two months ago, just a, you know, busy. I had a chance last, you know a few months to kind of really dig into the dataset. We have a tremendous amount of research coming out in Q4 Q1 around kind of the public cloud database market public cloud analytics market. So, you know, really looking forward to that. >> Okay, good. Well, let's bring up the first slide. Let's talk about where this data comes from. Tell us a little bit more about the platform. Where's the insight. >> Yeah, absolutely. So I'll talk a little about 7Park and then we'd kind of jump into the data a little bit. So 7Park was founded in 2012 in terms of differentiator, you know with other alternative data firms, you know we use NLP machine learning, you know AI to really kind of, you know, structure like noisy and unstructured data sets really kind of generate insight from that. And so, because a lot of that know how we ended up being acquired by Vista back in 2018. And really like for us, you know the mandate there is to really, you know look across all their different portfolio companies and try to generate insight from all the data assets you know, that these portfolio companies have. So, you know, today we're going to be talking about you know, one of the data sets from those companies it's that cloud infrastructure data set. We get it from one of the portfolio companies that you know, helps organizations kind of manage and optimize their cloud spend. It's real time data. We essentially get this aggregated daily. So this certainly different than, you know your traditional providers maybe giving you quarterly or kind of by annual data. This is incredibly granular, real time all the way down to the invoice level. So within this cloud infrastructure dataset we're tracking several billion dollars worth of spend across AWS, Azure and GCP. Something like 350 services across like 20 plus markets. So, you know, security machine learning analytics database which we're going to talk about today. And again like the granularity of the KPIs I think is kind of really what kind of you know, differentiates this dataset you know, with just within database itself, you know we're tracking over 20 services. So, you know, lots to kind of look forward to kind of into Q4 and Q1. >> So, okay. So the main spring of your data is if I'm a customer and I there's a service out there there are many services like this that can help me optimize my spend and the way they do that is I basically connect their APIs. So they have visibility on what the transactions that I'm making my usage statistics et cetera. And then you take that and then extrapolate that and report on that. Is that right? >> Exactly. Yeah. We're seeing just on this one data set that we're going to talk about today, it's something like six 700 million rows worth of data. And so kind of what we do is, you know we kind of have the insight layer on top of that or the analytics layer on top of all that unstructured data, so that we can get a feel for, you know a whole host of different kind of KPIs spend, adoption rates, market share, you know product size, retention rates, spend, you know, net price all that type of stuff. So, yeah, that's exactly what we're doing. >> Love it, there's more transparency the better. Okay. So, so right, because this whole world of market sizing has been very opaque you know, over the years, and it's like you know, backroom conversations, whether it's IDC, Gartner who's got what don't take, you know and the estimations and it's very, very, you know it's not very transparent so I'm excited to see what you guys have. Okay. So, so you have some data on the public cloud and specifically the database market that you want to share with our audience. Let's bring up the next graphic here. What are we looking at here Sagar? What are these blue lines and red lines what's this all about? >> Yeah. So and look, we can kind of start at the kind of the 10,000 foot view kind of level here. And so what we're looking at here is our estimates for the entire kind of cloud database market, including data warehousing. If you look all the way over to the right I'll kind of explain some of these bars in a minute but just high level, you know we're forecasting for this year, $11.8 billion. Now something to kind of remember about that is that's just AWS, Azure and GCP, right? So that's not the entire cloud database market. It's just specific to those three providers. What you're looking at here is the breakout and blue and purple is SQL databases and then no SQL databases. And so, you know, to no one's surprise here and you can see, you know SQL database is obviously much larger from a revenue standpoint. And so you can see just from this time last year, you know the database market has grown 40% among these three cloud providers. And, you know, though, we're not showing it here, you know from like a PI perspective, you know database is playing a larger and larger role for all three of these providers. And so obviously this is a really hot market, which is why, you know we're kind of discussing a lot of the dynamics. You don't need to Q and Q Q4 and Q1 >> So, okay. Let's get into some of the specific firm-level data. You have numbers that you want to share on Amazon Redshift and Google BigQuery, and some comments on Snowflake let's bring up the next graphic. So tell us, it says public cloud data, warehousing growth tempered by Snowflake, what's the data showing. And let's talk about some of the implications there. >> Yeah, no problem. So yeah, this is kind of one of the markets, you know that we kind of did a deep dive in tomorrow and we'll kind of get this, you know, get to this in a few minutes, we're kind of doing a big CIO panel kind of covering data, warehousing, RDBMS documents store key value, graph all these different database markets but I thought it'd be great, you know just cause obviously what's occurring here and with snowflake to kind of talk about, you know the data warehousing market, you know, look if you look here, these are some of the KPIs that we have you know, and I'll kind of start from the left. Here are some of the orange bars, the darker orange bars. Those are our estimates for AWS Redshift. And so you can see here, you know we're projecting about 667 million in revenue for Redshift. But if you look at the lighter arm bars, you can see that the service went from representing about 2% of you know, AWS revenue to about 1.5%. And we think some of that is because of Snowflake. And if we kind of, take a look at some of these KPIs you know, below those bar charts here, you know one of the things that we've been looking at is, you know how are longer-term customer spending and how are let's just say like newer customers spending, so to speak. So kind of just like organic growth or kind of net expansion analysis. And if you look at on the bottom there, you'll see, you know customers in our dataset that we looked at, you know that were there 3Q20 as well as 3Q19 their spend on AWS Redshift is 23%. Right? And then look at the bifurcation, right? When we include essentially all the new customers that onboard it, right after 3Q19, look at how much they're bringing down the spend increase. And it's because, you know a lot of spend that was perhaps meant for Redshift is now going to Snowflake. And look, you would expect longer-term customers to spend more than newer customers. But really what we're doing is here is really highlighting the stark contrast because you have kind of back to back KPIs here, you know between organic spend versus total spend and obviously the deceleration in market share kind of coming down. So, you know, something that's interesting here and we'll kind of continue tracking that. >> Okay. So let's maybe come back to this mass Colombo questions here. So the start with the orange side. So we're talking about Snowflake being 667 million. These are your estimates extrapolated based on what we talked about earlier, 1.5% of the AWS portfolio of course you see things like, they continue to grow. Amazon made a bunch of storage announcements last week at the first week of re-invent (indistinct) I mean just name all kinds of databases. And so it's competing with a lot of other services in the portfolio and then, but it's interesting to see Google BigQuery a much larger percentage of the portfolio, which again to me, makes sense people like BigQuery. They like the data science components that are built in the machine learning components that are built in. But then if you look at Snowflake's last quarter and just on a run rate basis, it's over there over $600 million. Now, if you just multiply their last quarter by four from a revenue standpoint. So they got Redshift in their sites, you know if this is, you know to the extent this is the correct number and I know it's an estimate but I haven't seen any better numbers out there. Interesting Sagar, I mean Snowflake surpassed the value of snowflakes or past service now last Friday, it's probably just in trading today you know, on Monday it's maybe Snowflake is about a billion dollars less than the in value than IBM. So you're saying snowflake in a lot of attention, post IPO the thing is even exploded more. I mean, it's crazy. And I presume that's rippled into the customer interest areas. Now the ironic thing here of course, is that that snowflake most of its revenue comes from AWS running on AWS at the same time, AWS and or Redshift and snowflake compete. So you have this interesting dynamic going on. >> Yeah. You know, we've spoken to so many CIOs about kind of the dynamics here with Redshift and BigQuery and Snowflake, you know as it kind of pertains to, you know, Redshift and Snowflake. I think, you know, what I've heard the most is, look if you're using Redshift, you're going to keep using it. But if you're new to data warehousing kind of, so to speak you're going to move to Snowflake, or you're going to start with Snowflake, you know, that and I think, you know when it comes to data warehousing, you're seeing a lot of decisions kind of coming from, you know, bottom up now. So a lot of developers and so obviously their preference is going to be Snowflake. And then when you kind of look at BigQuery here over to the right again, like look you're seeing revenue growth, but again, as a as a percentage of total, you know, GCP revenue you're seeing it come down and look, we don't show it here. But another dynamic that we're seeing amongst BigQuery is that we are seeing adoption rates fall versus this time last year. So we think, again, that could be because of Snowflake. Now, one thing to kind of highlight here with BigQuery look it's kind of the low cost alternative, you know, so to speak, you know once Redshift gets too expensive, so to speak, you know you kind of move over to, to BigQuery and we kind of put some price KPIs down here all the way at the bottom of the chart, you know kind of for both of them, you know when you kind of think about the net price per kind of TB scan, you know, Redshift does it pro rate right? It's five bucks or whatever you, you know whatever you scan in, whereas, you know GCP and get the first terabyte for free. And then everything is prorated after that. And so you can see the net price, right? So that's the price that people actually pay. You can see it's significantly lower that than Redshift. And again, you know it's a lower cost alternative. And so when you think about, you know organizations or CIO's that want to save some money certainly BigQuery, you know, is an option. But certainly I think just overall, you know, Snowflake is is certainly having, you know, an impact here and you can see it from, you know the percentage of total revenue for both these coming down. You know, if we look at other AWS database services or you mentioned a few other services, you know we're not seeing that trend, we're seeing, you know percentage of total revenue hang in or accelerate. And so that's kind of why we want to point this out as this is something unique, you know for AWS and GCP where even though you're seeing growth, it's decelerating. And then of course you can kind of see the percentage of revenue represents coming down. >> I think it's interesting to look at these two companies and then of course Snowflake. So if you think about Snowflake and BigQuery both of those started in the cloud they were true born in the cloud databases. Whereas Redshift was a deal that Amazon did, you know with parxl back in the day, one time license fee and then they re-engineered it to be kind of cloud based. And so there is some of that historical o6n-prem baggage in there. I know that AWS did a tremendous job in rearchitecting that but nonetheless, so I'll give you a couple of examples. If you go back to last year's reinvent 2019 of course Snowflake was really the first to popularize this idea of separating compute from storage and even compute from compute, which is kind of nuance. So I won't go into that, but the idea being you can dial up or dial down compute as you need it you can even turn off compute in the world of Snowflake and just, you know, you're paying an S3 for storage charges. What Amazon did last reinvent was they announced the separation of compute and storage, but what the way they did it was they did it with a tiering architecture. So you can't ever actually fully turn off the compute, but it's great. I mean, it's customers I've talked to say, yes I'm saving a lot of money, you know, with this approach. But again, there's these little nuances. So what Snowflake announced this year was their data cloud and what the data cloud is as a whole new architecture. It's based on this global mesh. It lives across both AWS and Azure and GCP. And what Snowflake has done is they've taken they've abstracted the complexity of the clouds. So you don't even necessarily have to know what you're running on. You have to worry about it any Snowflake user inside of that data cloud if given access can share data with any other user. So it's a very powerful concept that they're doing. AWS at reinvent this year announced something called AWS glue elastic views which basically allows you to take data across their entire database portfolio. And I'm going to put, share in quotes. And I put it in quotes because it's essentially doing copying from a source pushing to a target AWS database and then doing a change data management capture and pushes that over time. So it, it feels like kind of an attempt to do their own data cloud. The advantages of AWS is that they've got way more data stores than just Snowflake cause it's one data store. So was AWS says Aurora dynamo DB Redshift on and on and on streaming databases, et cetera where Snowflake is just Snowflake. And so it's going to be interesting to see, you know these two juxtaposing philosophies but I want it to sort of lay that out because this is just it's setting up as a really interesting dynamic. Then you can bring in Azure as well with Microsoft and what they're doing. And I think this is going to be really fascinating to see how this plays out over the next decade. >> Yeah. I think some of the points you brought up maybe a little bit earlier were just around like the functional limits of a Redshift. Right. And I think that's where, you know Snowflake obviously does it does very, very well you know, you kind of have these, you know kind of to come, you know, you kind of have these, you know if you kind of think about like the market drivers right? Like, let's think about even like the prior slide that we showed, where we saw overall you know, database growth, like what's driving all of that what's driving Redshift, right. Obviously proximity application, interdependencies, right. Costs. You get all the credits or people are already working with the big three providers. And so there's so many reasons to continue spending with them, obviously, you know, COVID-19 right. Obviously all these apps being developed right in the cloud versus data centers and things of that nature. So you have all of these market drivers, you know for the cloud database services for Redshift. And so from that perspective, you know you kind of think, well why are people even to go to a third party vendor? And I think, you know, at that point it has to be the functional superiority. And so again, like a lot of times it depends on, you know, where decisions are coming from you know, top down or bottom up obviously at the engineering at the developer level they're going to want better functionality. Maybe, you know, top-down sometimes, you know it's like, look, we have a lot of credits, you know we're trying to save money, you know from a security perspective it could just be easier to spin something up you know, in AWS, so to speak. So, yeah, I think these are all the dynamics that, you know organizations have to figure out every day, but at least within the data warehousing space, you are seeing spend go towards Snowflake and it's going away to an extent as we kind of see, you know growth decelerate for both of these vendors, right. It's not that revenue's not going out there is growth which is that growth is, it's just not the same as it used to be, you know, so to speak. So yeah, this is a interesting area to kind of watch and I think across all the other markets as well, you know when you think about document store, right you have AWS document DB, right. What are the impacts there with with Mongo and some of these other kind of third party data warehousing vendors, right. Having to compete with all the, you know all the different services offered by AWS Azure like the cosmos and all that stuff. So, yeah, it's definitely kind of turning into a battle Royal, you know as we kind of head into, into 2021. And so I think having all these KPIs is really helping us kind of break down and figure out, you know which areas like data warehousing are slowing down. But then what other areas in database where they're seeing a tremendous amount of acceleration, like as we said, database revenue is driving. Like it's becoming a bigger part of their overall revenue. And so they are doing well. It just, you know, there's obviously snowflake they have to compete with here. >> Well, and I think maybe to your point I infer from your point, it's not necessarily a zero sum game. And as I was discussing before, I think Snowflake's really trying to create a new market. It's not just trying to steal share from the Terra datas and the Redshifts and the PCPs of the world, big queries and and Azure SQL server and Oracle and so forth. They're trying to create a whole new concept called the data cloud, which to me is really important because my prediction is what Snowflake is doing. And they don't even really talk a ton about this but they sort of do, if you squint through the lines I think what they're doing is first of all, simplicity is there, what they're doing. And then they're putting data in the hands of business people, business line people who have domain context, that's a whole new way of thinking about a data architecture versus the prevalent way to do a data pipeline is you got data engineers and data scientists, and you ingest data. It's goes to the beginning of the pipeline and that's kind of a traditional way to do it. And kind of how I think most of the AWS customers do it. I think over time, because of the simplicity of Snowflake you're going to see people begin to look at new ways to architect data. Anyway, we're almost out of time here but I want to bring up the next slide which is a graphic, which talks about a database discussion that you guys are having on 12/8 at 2:00 PM Eastern time with Bain and Verizon who what's this all about. >> Yeah. So, you know, one of the things we wanted to do is we kind of kick off a lot of the, you know Q4 Q1 research or putting on the database spark. It is just like kind of, we did, you know we did today, which obviously, you know we're really going to expand on tomorrow at a at 2:00 PM is discuss all the different KPIs. You know, we track something like 20 plus database services. So we're going to be going through a lot more than just kind of Redshift and BigQuery. Look at all the dynamics there, look at, you know how they're very against some of the third party vendors like the Snowflake, like a Mongo DB, as an example we got some really great, you know, thought leaders you know, Michael Delzer and Praveen from verizon they're going to kind of help, or they're going to opine on all the dynamics that we're seeing. And so it's going to be a very kind of, you know structured wise, it's going to be very quantitative but then you're going to have this beautiful qualitative discussion to kind of help support a lot of the data points that we're capturing. And so, yeah, we're really excited about the panel you know, from, you know, why you should join standpoint. Look, it's just, it's great, competitive Intel. If you're a third party, you know, database, data warehousing vendor, this is the type of information that you're going to want to know, you know, adoption rates market sizing, retention rates, you know net price reservers, on demand dynamics. You know, we're going through a lot that tomorrow. So I'm really excited about that. I'm just in general, really excited about a lot of the research that we're kind of putting out. So >> That's interesting. I mean, and we were talking earlier about AWS glue elastic views. I'd love to see your view of all the database services from Amazon. Cause that's where it's really designed to do is leverage those across those. And you know, you listen to Andrew, Jesse talk they've got a completely different philosophy than say Oracle, which says, Hey we've got one database to do all things Amazon saying we need that fine granularity. So it's going to be again. And to the extent that you're providing market context they're very excited to see that data Sagar and see how that evolves over time. Really appreciate you coming back in the cube and look forward to working with you. >> Appreciate Dave. Thank you so much. >> All right. Welcome. Thank you everybody for watching. This is Dave Vellante for the cube. We'll see you next time. (upbeat music)

Published Date : Dec 21 2020

SUMMARY :

all around the world, and today we're going to introduce you I appreciate you having me back on. Hey, so new gig for I had a chance last, you know more about the platform. the mandate there is to really, you know And then you take that so that we can get a feel for, you know and it's like you know, And so, you know, to You have numbers that you want one of the markets, you know if this is, you know of the chart, you know interesting to see, you know kind of to come, you know, you and you ingest data. It is just like kind of, we did, you know And you know, you listen Thank you so much. Thank you everybody for watching.

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Breaking Analysis: Legacy Storage Spending Wanes as Cloud Momentum Builds


 

(digital music) >> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> The storage business as we know it has changed forever. On-prem storage was once a virtually unlimited and untapped bastion of innovation, VC funding and lucrative exits. Today it's a shadow of its former self and the glory days of storage will not return. Hello everyone, and welcome to this week's Wikibon CUBE Insights Powered by ETR. In this breaking analysis, we'll lay out our premise for what's happening in the storage industry, and share some fresh insights from our ETR partners, and data that supports our thinking. We've had three decades of tectonic shifts in the storage business. From the simplified history of this industry shows us there've been five major waves of innovation spanning five decades. The dominant industry model has evolved from what was first the mainframe centric vertically integrated business, but of course by IBM and it became a disintegrated business that saw between like 70 or 80 Winchester disk drive companies that rose and then fell. They served a booming PC industry in this way it was led by the likes of Seagate. Now Seagate supplied the emergence of an intelligent controller based external disc array business that drove huge margins for functions that while lucrative was far cheaper than captive storage from system vendors, this era of course was led by EMC and NetApp. And then this business was disrupted by a flash and software defined model that was led by Pure Storage and also VMware. Now the future of storage is being defined by cloud and intelligent data management is being led by AWS and a three letter company that we'll just call TBD, otherwise known as Jump Ball Incorporated. Now, let's get into it here, the impact of AWS cannot be overstated now while legacy storage players, they're sick and tired of talking about the cloud, the reality cannot be ignored. The cloud has been the most disruptive force in storage over the past 10 years, and we've reported on the spending impact extensively. But cloud is not the only factor pressuring the on-prem storage business, flash has killed what we call performance by spindles. In other words, the practice of adding more disk drives to keep performance from tanking. So much flash has been injected into the data center that that no longer is required. But now as you drill down into the cloud, AWS has been by far the most significant factor in our view. Lots of people talked about object storage before AWS, but there sure wasn't much spending going on, S3 changed that. AWS is getting much more aggressive about expanding its storage portfolio and its offerings. S3 came out in 2006 and it was the very first AWS service and then Elastic Block Service EBS came out a couple of years later, nobody really paid much attention. Well last fall at storage day, we saw AWS announce a number of services, many fire-related and this year we saw four new announcements of Amazon at re:Invent. We think AWS' storage revenue will surpass 8 billion this year and could be as high as 10 billion. There's not much data out there, but this would mean that AWS' storage biz is larger than that of a NetApp, which means AWS is larger than every traditional storage player with the exception of Dell. Here's a little glimpse of what's coming at the legacy storage business. It's a clip of the vice-president of AWS storage, her name is Mahlon Thompson Bukovec, watch this. Okay now, you may say Dave, what the heck does that have to do with anything? Yeah, I don't know, but as an older white guy, that's been in this business for awhile, I just think it's badass that this woman boxes and runs a business that we think is approaching $10 billion. Now let's take a quick look at the storage announcements AWS made at re:Invent. The company made four announcements this year, let me try to be brief, the first is EBS io2 Block Express Volumes, got to love the names. AWS was claims this is the first storage area network or sand for the cloud and it offers up to 256,000 IOPS and 4,000 megabytes per second throughput and 64 terabytes of capacity. Hey, sounds pretty impressive right, Well let's dig in a little bit okay, first of all, this is not the first sand in the cloud, at least in my view there may be others but Pure Storage announced cloud block store in 2019 at its annual accelerate customer conference and it's pretty comparable here. Maybe not so much in the speeds and feeds, but the concept of better block storage in the cloud with higher availability. Now, as you may also be saying, what's the big deal? The performance come on, we can smoke that we're on-prem vendor We can bury that. Compared to what we do, AWS' announcement is really not that impressive okay, let me give you a point of comparison there's a startup out there called VAST Data. Just there for you and closure with bundled storage and compute can do 400,000 IOPS and 40,000 megabytes per second and that can be scaled, so yeah, I get it. And AWS also announced that io2 two was priced at 20% less than previous generation volumes, which you might say is also no big deal and I would agree 20% is not as aggressive as the average price decline per gigabyte of any storage technology. AWS loves to make a big deal about its price declines, it's essentially following the industry trends but the point is that this feature will be great for a lot of workloads and it's fully integrated with AWS services meaning for example, it will be very convenient for AWS customers to invoke this capability for example Aurora and other AWS databases through its RDS service, just another easy button for developers to push. This is specially important as we see AWS rapidly expanding its machine learning in AI capabilities with SageMaker, it's embedding ML into things like Redshift and driving analytics, so integration is very key for its customers. Now, is Amazon retail going to run its business on io2 volumes? I doubt it. I believe they're running on Oracle and they need much better performance, but this is a mainstream service for the EBS masses to tap. Now, the other notable announcement was EBS Gp3 volumes. This is essentially a service that lets let you programmatically set SLAs for IOPS and throughput independently without needing to add additional storage. Again, you may be saying things like, well atleast I remember when SolidFire let me do this several years ago and gave me more than 3000 IOPS and 125 megabytes per a second performance, but look, this is great for mainstream customers that want more consistent and predictable performance and that want to set some kind of threshold or floor and it's integrated again into the AWS stack. Two other announcements were made, one that automatically tiers data to colder storage tiers and a replication service. On the former, data migrates to tier two after 90 days of inaccess and tier three, after 180 days. AWS remember, they hired a bunch of folks out of EMC years ago and they put them up in the Boston Seaport area, so they've acquired lots of expertise in a lot of different areas I'm not sure if tiering came out of that group but look, this stuff is not rocket science, but it saves customers money. So these are tried and true techniques that AWS is applying but the important thing is it's in the cloud. Now for sure we'd like to see more policy options than say for example, a fixed 90 day or 180 day policy and more importantly we'd like to see intelligent tiering where the machine is smart enough to elevate and promote certain datasets when they're needed for instance, at the end of a quarter for comparison purposes or at the end of the year, but as NFL Hall of Fame Coach Hank Stram would have said, AWS is matriculating the ball down the field. Okay, let's look at some of the data that supports what we're saying here in our premise today. This chart shows spending across the ETR taxonomy. It depicts the net score or spending velocity for different sectors. We've highlighted storage, now don't put too much weight on the January data because the survey was just launched, but you can see storage continues to be a back burner item relative to some other spending priorities. Now as I've reported, CIOs are really focused on cloud, containers, container orchestration, automation, productivity and other key areas like security. Now let's take a look at some of the financial data from the storage crowd. This chart shows data for eight leading names in storage and we put storage in quotes because as we said earlier, the market is shifting and for sure companies like Cohesity and Rubrik, they're not positioning as storage players in fact, that's the last thing they want to do. Rather they're category creators around data management or intelligent data management but their inadjacency to storage, they're partnering with all the primary storage companies and they're in the ETR taxonomy. Okay, so as you can see, we're showing the year over year, quarterly revenue growth for the leading storage companies. NetApp is a big winner, they're growing at a whopping 2%. They beat expectations, but expectations were way down so you can see in the right most column upper right, we've added the ETR net score from October and net score of 10% says that if you ask customers, are you spending more or less with a company, there are 10% of the customers that are essentially spending more than are spending less, get into that a little further later. For comparison, a company like Snowflake, it has a net score approaching 70% Pure Storage used to be that high several years ago or high sixties anyway. So 10% is in the red zone and yet NetApp, is the big winner this quarter. Now Nutanix isn't really again a storage company, but they're an adjacency and they sell storage and like many of these companies, it's transitioning to a subscription pricing model, so that puts pressure on the income statement, that's why they went out and did a deal with Bain, Bain put in $750 million to help Bridge that transition so that's kind of an interesting move. Every company in this chart is moving to an annual recurring revenue model and that as a service approach is going to be the norm by the end of the decade. HPE's doing it with GreenLake, Dell has announced Apex, virtually every company is headed in this direction. Now speaking of HPE, it's Nimble business that has momentum, but other parts of the storage portfolio are quite a bit softer. Dell continues to see pressure on its storage business although VxRail is a bright spot. Everybody's got a bright spot, everybody's got new stuff that's growing much faster than the old stuff, the problem is the old stuff is much much bigger than the new stuff. IBM's mainframe storage cycle, well that's seems to have run its course, they had been growing for the last several quarters that looks like it's over. And so very very cyclical businesses here now as you can see, The data protection data management companies, they are showing spending momentum but they're not public so we don't have revenue data. But you got to wonder with all the money these guys have raised and the red hot IPO and tech markets, why haven't these guys gone public? The answer has to be that they're either not ready or maybe their a numbers weren't where they want them to be, maybe they're not predictable enough, maybe they don't have their operational act together or maybe they need to you get that in order, some combination of those factors is likely. They'll tell you, they'll give other answers if you ask them, but if they had their stuff together they'd be going out right now. Now here's another look at the spending data in terms of net score, which is again spending velocity. The ETR here is measuring the percent of respondents that are adopting new, spending more, spending flat, spending less or retiring the platform. So net score is adoptions, which is the lime green plus the spending more, which is the forest green. Add those two and then subtract spending less, which is the pink and then leaving the platform, which is the bright red, what's left over is net score. So, let's look at the picture here, Cohesity leads all players in the storage taxonomy, the ETR storage taxonomy, again they don't position that way, but that's the way the customers are answering. They've got 55% net score which is really solid and you can see the data in the upper right-hand corner, it's followed by Nutanix. Now they're really not again in the scope of Pure play storage play but speaking of Pure, its net score has come down from its high of 73% in January, 2016. It's not going to climb back up there, but it's going to be interesting to see if Pure net scorecard rebound in a post COVID world. We're also watching what Pure does in terms of unifying file and object and how it's fairing in cloud and what it does with the Portworx acquisition which is really designed to bring forth a new programming model. Now, Dell is doing fine with VxRail, but VSAN is well off its net score highs which we're in the 60% plus range a couple of years ago, VSAN is definitely been a factor from VMware, but again that's come off its highs, HPE with Nimble still has some room to improve, I think it actually will I think that these figures that we're showing here they're are somewhat depressed by the COVID factor, I expect Nimble is going to bounce back in future surveys. Dell and NetApp are the big leaders in terms of presence or market share in the data other than VMware, 'cause VMware has a lot of instances, it's software defined that's why they're so prominent. And with VMware's large share you'd expect them to have net scores that are tepid and you can see a similar pattern with IBM. So Dell, NetApp, tepid net scores as is IBM because of their large market share VMware, kind of a newer entry into the play and so doing pretty well there from a net score standpoint. Now Commvault like Cohesity and Rubrik is really around intelligent data management, trying to go beyond backup into business recovery, data protection, DevOps, bringing that analytics, bringing that to the cloud, we didn't put Veeam in here and we probably should have. They had pre-COVID net scores well in to the thirties and they have a steadily increasing share of the market, so we expect good things from Veeam going forward. They were acquired earlier this year by Insight, capital private equity firm. So big changes there as well, that was their kind of near-term exit maybe more to come. But look, it's all relative, this is a large and mature market that is moving to the cloud and moving to other adjacencies. And the core is still primary storage, that's the main supreme prerequisite and everything else flows from there, data protection, replication, everything else. This chart gives you another view of the competitive landscape, it's that classic XY chart it plots net score in the vertical axis and market share on the horizontal axis, market share remember is a measure of presence in the dataset. Now think about this from the CIO's perspective, they have their on-prem estate, got all this infrastructure and they're putting a brick wall around their core systems. And what do they want out of storage for that class of workload? They want it to perform consistently, they want it to be efficient and they want it to be cost-effective, so what are they going to do? they're going to consolidate, They're going to consolidate the number of vendors, they're going to consolidate the storage, they're going to minimize complexity, yeah, they're going to worry about the blast radius, but there's ways to architect around that. The last thing they want to worry about is managing a zillion storage vendors this business is consolidating, it has been for some time, we've seen the number of independent storage players that are going public as consolidated over the years, and it's going to continue. so on-prem storage arrays are not giving CIOs the innovation and strategic advantage back when things like storage virtualization, space efficient snapshots, data de-duplication and other storage services were worth maybe taking a flyer on a feature product like for example, a 3PAR or even a Data Domain. Now flash gave the CIOs more headroom and better performance and so as I said earlier, they're not just buying spindles to increase performance, so as more and more work gets pushed to the cloud, you're seeing a bunkering in on these large scale mission-critical workloads. As you saw earlier, the legacy storage market is consolidating and has been for a while as I just said, it's essentially becoming a managed decline business where RnD is going to increasingly get squeezed and go to other areas, both from the vendor community and on the buy-side where they're investing on things like cloud, containers and in building new layers in their business and of course the DX, the Digital Transformation. I mentioned VAST Data before, it is a company that's growing and another company that's growing is Infinidat and these guys are traditional storage on-prem models they don't bristle If I say traditional they're nexgen if you will but they don't own a cloud, so they were selling to the data center. Now Infinidat is focused on petabyte scale and as they say, they're growing revenues, they're having success consolidating storage that thing that I just talked about. Ironically, these are two Israeli founder based companies that are growing and you saw earlier, this is a share shift the market is not growing overall the part of that's COVID, but if you exclude cloud, the market is under pressure. Now these two companies that I'm mentioning, they're kind of the exception to the rule here, they're tiny in the grand scheme of things, they're really not going to shift the market and their end game is to get acquired so they can still share, but they're not going to reverse these trends. And every one on this chart, every on-prem player has to have a cloud strategy where they connect into the cloud, where they take advantage of native cloud services and they help extend their respective install bases into the cloud, including having a capability that is physically proximate to the cloud with a colo like an Equinix or some other approach. Now, for example at re:Invent, we saw that AWS has hybrid strategy, we saw that evolving. AWS is trying to bring AWS to the edge and they treat the data center as just another edge note, so outposts and smaller versions of outposts and things like local zones are all part of bringing AWS to the edge. And we saw a few companies Pure, Infinidant, Veeam come to mind that are connecting to outpost. They saw the Qumulo was in there, Clumio, Commvault, WekaIO is also in there and I'm sure I'm missing some so, DM me, email me, yell at me, I'm sorry I forgot you but you get the point. These companies that are selling on-prem are connecting to the cloud, they're forced to connect to the cloud much in the same way as they were forced to join the VMware ecosystem and try to add value, try to keep moving fast. So, that's what's going on here, what's the prognosis for storage in the coming year? Well, where've of all the good times gone? Look, we would never bet against data but the days of selling storage controllers that masks the deficiencies of spinning disc or add embedded hardware functions or easily picking off a legacy install base with flash, well, those days are gone. Repatriation, it ain't happening it's maybe tiny little pockets. CIOs are rationalizing their on-premises portfolios so they can invest in the cloud, AI, machine learning, machine intelligence, automation and they're re-skilling their teams. Low latency high bandwidth workloads with minimal jitter, that's the sweet spot for on-prem it's becoming the mainframe of storage. CIOs are also developing a cloud first strategy yes, the world is hybrid but what does that mean to CIOs? It means you're going to have some work in the cloud and some work on-prem, there's a hybrid We've got both. Everything that can go to the cloud, will go to the cloud, in our opinion and everything that can't or shouldn't won't. Yes, people will make mistakes and they'll "repatriate" but generally that's the trend. And the CIOs they're building an abstraction layer to connect workloads from an observability and manageability standpoint so they can maintain control and manage lock-in risk, they have options. Everything that doesn't go to the cloud will likely have some type of hybridicity to it, the reverse won't likely be the case. For vendors, cloud strategies involve supporting your install basis migration to the cloud, that's where they're going, that's where they want to go, they want your help there's business to be made there so enabling low latency hybrids in accommodating subscription models, well, that's a whole another topic, but that's the trend that we see and you rethink the business that you're in, for instance, data management and developing an edge strategy that recognizes that edge workloads are going to require new architecture and that's more efficient than what we've seen built around general purpose systems, and wow, that's a topic for another day. You're seeing this whole as a service model really reshape the entire cultures in the way in which the on-prem vendors are operating no longer is it selling a box that has dramatically marked up controllers and disc drives, it's really thinking about services that could be invoked in the cloud. Now remember, these episodes are all available as podcasts, wherever you listen, just search Breaking Analysis podcasts and please subscribe, I'd appreciate that checkout etr.plus for all the survey action. We also publish a full report every week on wikibon.com and siliconangle.com. A lot of ways to get in touch. You can email me at david.vellante@siliconangle.com. you could DM me @dvellante on Twitter, comment on our LinkedIn posts, I always appreciate that. This is Dave Vellante for theCUBE Insights Powered by ETR. Thanks for watching everyone stay safe and we'll see you next time. (upbeat music)

Published Date : Dec 12 2020

SUMMARY :

This is Breaking Analysis and of course the DX, the

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Dave Humphrey, Bain Capital


 

(soft music) >> Hello everyone and welcome back to theCUBE on Cloud, where we're talking to CEOs, CIOs, Chief Technology Officers, and investors on the future of Cloud, with me is Dave Humphrey. Who's the Managing Director, and co-head of private equity in North America at Bain Capital. Dave, welcome to theCUBE first time, I think. >> First time, yeah, Dave, thanks very much for having me. >> So, let's get right into it, as an investor, how are you thinking about the evolution of cloud, when you look back at the last decade? It's not going to be the same, in this coming decade it's ironic 2020 is thrown us into, the accelerated digital transformation and cloud. How do you look at the evolution of cloud, from an investment perspective? What's your thesis? >> That's a great question, David for us we're focused on investing, in technology and really across the economy. And I'd say ,the cloud is the overarching trend, and dynamic in the technology markets. It really affect two reasons. One is a major shift ,of course that's going on. But the second and frankly even more interesting one, just as all the growth, that the cloud is creating, in the technology marketplace. The shift, think is been well covered, but five years ago in 2015, by our analysis, 2/3 of all computing workloads were done on premises. And only five years later, that's that's split. So, 2/3 of all computing workloads now done in the cloud and of course that shift, there's a lot of ramifications, as an investor. But even more interesting to us, is the growth in technology and the usage of technology, that the cloud is creating. So, over that same period of time, the total number of computing workloads run has increased, by 2.6 times, in just a five-year period of time which is really a dramatic thing and it makes sense when you think about, all the new software applications that could be created, all the data that can be used by new users and new segments, and the real-time insight that can be gleaned from there cause that growth, that really were focused on investing behind, as investors in technology. >> It's interesting you share those numbers, and you hear a lot of numbers. I actually think you're even being conservative. Ginni Rometty, used to talk about 80% of workloads, are still on-prem. Andy Jassy at re:Invent said that, 96% of the spending is still on premises. So, that was kind of an interesting stat. And I guess the other thing that I would note is it's not just a share shift, it is, it's not just, the cloud eating away on-prem. We've clearly seen that. But there's also incremental opportunity as well. If you look at Snowflake, for example adding value across multiple clouds and creating new markets. So there's that one-two punch, of stealing share from on-prem (clears throat). Also incremental growth, which is probably accelerated as a result, of this compressed digital transformation. So when you look at the big three Cloud players. I mean, roughly speaking, there probably account for $80 billion in total revenue. Which I guess, is a small portion of the overall IT market. So, it has a long way to go, but what's the best way to get good returns, from an investment standpoint, without getting clobbered, by their tendency to sometimes co-opt some of the best ideas and put them on their primary services. >> Yeah, absolutely, well, for us, it really comes back to the same fundamental principles, we look for in any investment. Which is finding, a business that solves, a really important problem for its customers, and does so in a way that's really advantage, versus competition and can do something, that other competitors just can't do. Whether those be the hyperscalers that you're describing, or other specialized and focused competitors. And then finding a way ,that we can partner with those companies to help them to accelerate their growth. So, surely the growth of the likes of AWS and Microsoft and Google, as you were describing has been a profound, competitive shift, along with the cloud shift, that we've all talked about. And those companies of course can offer, and do things that you asked, purveyors of computing couldn't. But, fundamentally they're selling an infrastructure layer, and there is room for all sorts of new competitors, and new applications that can do something better than anybody else can. So, any company that we're looking at, we're asking ourselves the question, why are they the best ones, to do what they're doing? How can they solve the most problems, for their customers and do that, in a way that's resilient? And we see lots of those opportunities. >> And I want to pick your brain, about the Nutanix investment, but before we get there. I wonder if you could just talk, about Bain Capital their history of investment in both cloud and infrastructure software and how do those investments, how would they perform and how do they inform your current thesis? >> Yeah, absolutely. So, Bain Capital was started in the mid 80s, 1984. Actually, as a spin out Bain Company Consulting. And the basic premise was that, if we're good at advising and supporting businesses. We should partner with them and invest behind them and if they do well, we'll do well. And as I said, focusing on these businesses but do something really valuable for their customers in a real advantage way with some discontinuous growth opportunity. That's led us to grow a lot. We started out actually in the venture business, and grew into the private equity business, but now we invest across all life stages of company all over the world. So we're $105 billion in assets that we manage, across 10 lines of business and we're truly global. So I think we have about 470 investment professionals and 210 of those, at this point are located outside the US. One of the really interesting things for us in investing in technology broadly and in infrastructure and the Cloud more specifically is that we're able to do that all over the world and we're able to do that across all the different life stages of a company. So we have a thrive in venture capital business, that really we've been in, since the origins of Bain Capital has invested across countless cloud and security and infrastructure businesses, taken successful companies public like SolarWinds sold companies to strategic and grown businesses in really thriving ways. We have a growth mid-market growth technology business, that we launched last year, called our Technology Opportunities Fund. They've made a really interesting, cloud-based investment in a company called the Cloud Gurus, Cloud Guru, excuse me. That trains, the next generation of IT professionals to be successful in the cloud. And then of course in our private equity business where I spend my time. We are highly focused on technologist sector. And the impacts of the cloud in that sector broadly, we have invested in many infrastructure businesses, scale businesses like, BMC Software and Rocket Software, security businesses like, Blue Coat Systems and Symantec. And of course, for those big businesses they've got both on premises solutions. They've got cloud solutions and often we're focused on helping them continue to grow and innovate and take their solutions to the cloud. And then, this taken us to our most recent investment in Nutanix that we're very excited about it. We think it's truly a growth business in a large market that has an opportunity to capitalize, on these trends we're talking about. >> I wonder if you could comment on some of the changes that have occurred, you guys have been in the private equity business, for a long time. And if you look at kind of the early days of private equity, it was all, EBITDA suck as much cash out of the company as possible and whatever's left over we'll figure out what to do with it. And it's, it seems like investors have realized, wow, we can actually, if we put a little investment in and do some engineering, and some go to market we can actually, get better multiples. And so you've got the kind of rule of 30, 35 and 40 where EBITDA plus growth is kind of the metric. How do you think about that and look at that evolution? >> Yeah, it's interesting because in many ways Bain Capital was started as the antithesis to what you're describing. >> Great. >> So we started again as, with a strategic lens and a focus on growth and a focus on, if we got the longterm and the lasting impact of our businesses right, that the returns would follow and you're right that the market has evolved in that way. I mean, I think some of the dynamics that we've seen, has been certainly growth of the private equity business. It's become a much larger piece of the capital markets than it was certainly 10 years ago and 20 years ago. Also with that growth comes the globalization of that business all over the world and the specialization. So you certainly see technology focused firms and technology focused funds in a way that you didn't see 10 years ago or certainly 20 years ago. Actually Bain Capital interestingly enough, we had a technology focused fund in 1989 called Bain Information Partners. So we've been focused on the sector for a very long time. But you certainly see a lot more technology investors, than you did in your 10 to 20 years ago. >> How are you thinking about valuations these days? I mean, it's good to be in tech, it's even better to be in the cloud, software, cloud, if you're looking at, some of the companies, especially the work from home pivot. But a lot of that appears to be, many people believe it's going to be permanent. How are you feeling about the both public market and private market valuations in that dynamic? >> Yeah, well, it's amazing, right? I don't think any of us in March when the COVID crisis was just emerging, would've anticipated that come November, the markets and certainly the technology markets, would be even more robust and stronger than they were say in January, February. But I think it's a testament to the resilience of the technology and just how intricate and intertwined technology has become with our daily lives. And how much companies depend on its use. And frankly, it's been, the COVID environment has been an accelerant, for many of the ways in which we depend on technology. So witness this interview, of course, through the cloud, and you're seeing the way that we operate our business day-to-day, the way companies are accessing their data and information it has only further, accelerated the need for technology, and the importance of that technology to how businesses operate. So I think you're seeing that, you're reflected in the market values out there, but for us we're focused on businesses, that still have that catalytic opportunity ahead that can, do more to compensate for the price of entry. >> Let's talk about ,this massive investment you guys made in Nutanix, $750 million. I guess it's a small piece of your 105 billion, but still massive investment. How did that opportunity come to you? What was your thinking behind that investment and what are you looking for in terms of the go-forward plan and growth plan for 2021 and really important beyond? >> Yeah, absolutely, we're thrilled to be partnered with and invested in Nutanix. We think is a terrific company and our most recent technology investment are private equity business. It really came about through a proactive efforts that we had in the spring. We've got a team focused on the technology sector, focused across infrastructure and applications and internet and digital media businesses and financial technology. And through those efforts, we were looking for businesses, that we felt had faced some dislocation in their market values, associated with the COVID environment that we're facing. But that we thought were really attractive businesses, well positioned have leading solutions, and had substantial and discontinuous growth opportunities. And as we look through that effort, we really felt that Nutanix stood out just as a core leader and in fact, really the innovator and the inventor of the market, in which it competes with a substantial market share and position, solving a really important problem for its customers, with a big growth opportunity ahead. But, the stock price had come down, because the business has been undergoing a transition. And we didn't think that was fully understood, by the market. And so, we saw an opportunity to partner with Nutanix, to invest money into the business, to help to fund its transition and its growth, and to be partners along for all the value of the business we'll continue to create, we think it's a terrific company and we're excited to be invested. >> Well, you and I have talked about this, that transition from a traditional license model, to one that's an annual recurring revenue model which many companies have gone through. Adobe certainly has done it, Tableau successfully did it. Splunk is kind of in the middle of that transition right now, and maybe not well understood. You've got companies like, Datadog and Snowflake again to doing consumption-based pricing. So there's a lot of confusion in the marketplace. And I wonder if you could talk about, that transition and why it was attractive to you, to actually place that bet now. >> Yeah, absolutely and as you say, number of companies at this point have been through, various forms of of this shift from selling their technology upfront to selling it over time. And we find that the model of selling the technology over time, is one that can be powerful. It can be aligning for customers, as well as for the vendor of the software solutions. And in Nutanix in particular, again, we saw all the ingredients that we think, make this an opportunity for the business. Again, market-leading technology that customers love that is solving a really important problem that technology because Nutanix had been grown, and bootstrapped under the leadership Dheeraj when it was built and founded. Had been selling its software together within appliance. Often in a upfront sale. And has been undergoing under their own initiative, transitioned from selling that software with an appliance to a software based model to one that's more rattle over time. And we thought that there was the opportunity to continue that transition and by doing that. To be able to offer more growth, and more innovation that we can bring to our customers to continue to fund their shifts. So, something that frankly was well underway before we invested. As the business makes this transition, from collecting upfront to more evenly over time. We saw a potential use for our capital, to help to fund that growth. And we're just focused on being a good partner, to help the company keep investing and innovating, as it continues to do that. >> As I was talking to somebody other day, Dave and I told him, I was interviewing you. And I was mentioning the Nutanix investment. And I said, I'm definitely going to cover that. As part of this Cube on Cloud program and they said, well, then Nutanix, that's not cloud. I'm like, well, wait a minute, what's cloud? So, we heard Andy Jassy at re:Invent, talking all lot about hybrid. Antonio Neri ,right after HPE, made its earning last earnings announcement. He came on and said that, well we heard the big cloud player talk about hybrid. And so the definition is changing. But so how are you looking at the market? Certainly, there's this hyper converged infrastructure, but there's also this software play, there's this cloud play. Help us squint through, how you see that. >> Absolutely, so, Nutanix as you alluded to pioneer the market for hyper converged infrastructure, for bringing compute and storage and networking together. Often in private Cloud environments, in a way that was really powerful for your customers and they can of course continue to be the leaders in that marketplace. But they've continued to innovate and invest in ways that can, solve problems for customers and related problems across the hybrid cloud. So, combining both the public cloud with that private cloud and across multiple public clouds, with things like clusters and lots of innovation, that the business is doing, in partnership with the likes of Amazon and Microsoft and others. And so we think that Nutanix has a powerful role to play, in that hybrid cloud world, in a multi-cloud world. And we're excited to back them in. >> Well, I think too, what maybe people don't understand, is that not only is Nutanix, compatible with AWS and compatible with Azure and GCP, but it's actually trying, to create an abstraction layer across those, those clouds. Now, there's two sides of that debate. Some will say, well, that has latency issues or yes it reduces complexity, but at the same time it doesn't give you, that fine-grained access that's kind of the AWS narrative customers, want simplicity and we're seeing the uptake across clouds. I have a multi-part question for you, Dave. So, obviously Bain very strong in strategy. I'm curious ,as to how much you get involved, in the operational details. I mean, obviously $750 million you've got a stake there. But what are the two or three major strategic considerations for not just even just Nutanix, but Cloud and software infrastructure companies? And how much focus do you put on the operational and what are the priorities there? >> Absolutely, well, we pride ourselves in being good partners to our businesses and in helping them to grow, not just with our capital, which I think is of course important, but also with our sweat equity and our human capital, and our partnership and we can do that in lots of ways. It's fundamentally about supporting our businesses, however, is needed to help them to grow. We've been investing in the technology sector, as I described over, over 30 years. And so, we've built up a set of capabilities around things like, helping to a partner with the Salesforce of a company is helping them to think about the ways in which they allocate their research and development and their innovation ways in which they, continue to do acquisitions, to further that pipeline. We support our businesses in lots of ways. But we're not engineers, we're not developers. Of course, we're looking for businesses that are fundamentally great. They've got great technology. They solve problems for customers in a way, we could never replicate. That's, what's all amazing about a business like Nutanix and just over a 10 year period of time, it literally has customer satisfaction levels, that we haven't seen from any other infrastructure software company that we've had the pleasure of diligencing over the last several years. So, what we're focused on, is how can we take those great products and offerings that Nutanix has, and continue to support them, through the further growth and expansion of areas like, the further Salesforce investment, to expand into these new areas like clusters, that we were talking about and thinking about, things that they can do, to further expand the strategic hold. And so, we have a large team of Bain Capital as I mentioned, 260 investment professionals, in our private equity business alone. About a third of those are just available to our companies to help support them, with various initiatives and efforts after we invest. And we'll certainly, of course make all of those available to Nutanix as well. >> Somebody was asking me the other day, what's hyper-converged infrastructure? How did that come about? And I was explaining, back in the day you had, you'd buy some servers and some storage, and you'd have a network. And you sort of have different teams. And you'd put applicant, you figure it out all out and put the applications on top, test it and make sure it all works and then the guys at VCE and VMware and Cisco and EMC, they got together and said, okay, we're going to bolt together a bunch of different components and pretest it here you go, here's a, here's a skew. And then, what Nutanix did was actually, really transformational and said, okay. Look, we can do this through software. And now that was what late 2000? Now, we're sort of entering this new era, this next generation of cloud, cross clouds. So, I wonder how you think about, based on what you were just talking about the whole notion of MA versus organic. There's a lot of organic development that needs to be done but perhaps you could buy in or inorganically through MA to actually get there faster. How do you think about that balance? >> Look I think that was an articulate by the way explanation of I think that the origins of a hyperconverged infrastructure, so I enjoyed that very much. But I think that with any of our businesses and with Nutanix we're of course looking at where are we trying to get to in several years and what are the best ways to support the business to get there? Of course, they'll primarily that will be through continuing organic investment in the company and all the innovation in the product, that they've been doing. Will the company contemplate acquisitions, to further achieve the development goals and the objectives for solving paying points for customers, to get to the strategic places they're trying to get to of course, but it all, is a part of the package of what's a good fit for the company and its growth objective. >> I mean, with the size of your portfolio, I mean, you're a full stack investor, I would say. Is there any part of the so-called tech stack that you won't touch that you would actually not walk, but run away from? (laughs) >> Well, I wouldn't say that we're running away from anything, but the questions that we're asking ourselves are, is the technology that we're investing endurable? Is it advantaged and does have a growing role in the world? And if we think that those things are true, we're absolutely, thrilled to invest behind those things. If there are things that we feel like, that's not the case. then we would tend to shy away from those investments. We've certainly found opportunities in businesses that people perceived as one, but we believe to be another. >> Well, so, let me ask you specifically about Nutanix. I mean, clearly they achieved escape velocity. One of the few companies actually, from last decade, it was Nutanix pure, not a whole lot of others that actually were able to maintain independence as a public company. What do you see as their durability? They're, moat if you will. >> Yeah, absolutely, well clearly we think that it's a very durable and very advantaged business. Yeah, thus the investment. Look, we think that Nutanix has been able to offer the best hyperconverged infrastructure product in the market bar none. One that is got the best ease of use is the most nimble and flexible for customers. And you just see that resulting customer feedback. And also that plays across very heterogeneous architectures in a way that it's really powerful. Because of that we think that they're best positioned to be able to leverage that technology as they have been, to continue to play across both public and private hybrid cloud environments. And so we're excited to back them in that journey. It really starts from solving an acute customer paying point, better than anybody else can. And we're looking to back them to continue to expand that vision. >> Yeah, well, I've talked to a lot of Nutanix customers, over the years and that is the fundamental value proposition it's really simple, very high, customer satisfaction. So, that makes a lot of sense. Well, Dave, thanks very much for coming on theCUBE and participating in theCUBE on Cloud. Really appreciate your perspectives, wish you best of luck. And hopefully we can do this again in the future. Maybe face to face >> Yeah, face to face maybe someday. Dave, I really appreciate it. It's been a pleasure and good luck with the rest of your interviews. >> All right, thank you. Well keep it right there, everybody for more Cube on Cloud. This is Dave Vellante, we'll be right back. (soft music)

Published Date : Dec 3 2020

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and co-head of private thanks very much for having me. the evolution of cloud, and dynamic in the technology markets. And I guess the other and new applications that about the Nutanix investment, and in infrastructure and the Cloud and some go to market we can to what you're describing. of that business all over the But a lot of that appears to be, and the importance of that technology How did that opportunity come to you? and the inventor of the and Snowflake again to doing of selling the technology And so the definition is changing. that the business is doing, in partnership in the operational details. and in helping them to grow, and put the applications on top, test it and the objectives for solving that you won't touch is the technology that One of the few companies One that is got the best ease of use and that is the fundamental and good luck with the everybody for more Cube on Cloud.

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Breaking Analysis: CIOs Expect 2% Increase in 2021 Spending


 

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante cios in the most recent september etr spending survey tell us that they expect a slight sequential improvement in q4 spending relative to q3 but still down four percent from q4 2019 so this picture is still not pretty but it's not bleak either to whit firms are adjusting to the new abnormal and are taking positive actions that can be described as a slow thawing of the deep freeze hello everyone this is dave vellante and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we're going to review fresh survey data from etr and provide our outlook for both q4 of 2020 and into 2021. now we're still holding at our four to five percent decline in tech spending for 2020 but we do see light at the end of the tunnel with some cautions specifically more than a thousand cios and it buyers have we've surveyed expect tech spending to show a slight upward trend of roughly two percent in 2021. this is off of a q4 decline of 4 relative to q4 2019 but i would put it this way a slightly less worse decline sequentially from q3 last quarter we saw a 5 decline in spending okay so generally more of the same but things seem to be improving again with caveats now in particular we'll show data that suggests technology project freezes are slowly coming back and we see remote workers returning at a fairly significant rate however executives expect nearly double the percentage of employees working remotely in the midterm and even long term than they did pre-covert that suggests that the work from home trend is not cyclical but showing signs of permanence and why not cios report that on balance productivity has been maintained or even improved during covit now of course this all has to be framed in the context of the unknowns like the fall and even winter surge what about fiscal policy there's uncertainty in the election social unrest all right so let's dig into some of the specifics of the etr data now i mentioned uh the number of respondents at over a thousand i have to say this was predominantly a us-based survey so it's it's 80 sort of bias to the u.s and but it's also weighted to the big spenders in larger organizations with a nice representation across industries so it's good data here now you can see here the slow progression of improvement relative to q3 which as i said was down five percent year-on-year with the four percent decline expected in q4 now etr is calling for a roughly four percent decline for the year you know i've been consistently in the four to five percent decline range and agree with that outlook and you can see cios are planning for a two percent uptick in 2021 as we said at the open now in our view this represents some prudent caution and i think there's probably some upside but it's a good planning assumption for the market overall in my view now let's look at some of the actions that organizations are taking and how that's changed over time you can see here that organizations they're slowly releasing that grip on tech spending overall you know still no material change in employees working from home or traveling we can see that hiring freezes are down that's that's positive in the green as our new i.t deployment freezes and a slight uptick in acceleration of new deployments now as well you see fewer companies are planning layoffs and while small the percent of companies adding head count has doubled from last quarter's you know minimal number all right so this is based on survey data at the end of the summer so it reflects that end of summer sentiment so we got to be a little bit cautious here and i think cios are you know by nature cautious on their projections of two percent up in 2021. now importantly remember this does not get us back to 20 20 19 spending levels so we may be seeing a kind of a long slow climb out of this you know tepid market maybe 2022 gets back over 2019 before we start to see sustained growth again and remember these recoveries are rarely smooth they're not straight lines so you got to expect some choppiness with you know some pockets of opportunity which we'll discuss here in this slide we're showing the top areas that respondents cited as spending priorities for q4 and into 2021 so the chart shows the ratings based on a seven-point scale and these are the top spending initiatives heading into the year end now as we've been saying for the better part of a decade cyber security is a do-over and i've joked you know if it ain't broke don't fix it well coven broke everything and cyber is an area that's seeing long-term change in my opinion endpoint security identity access management cloud security security as a service these are all trends that we're seeing as really major waves as a result of covid now it's coming at the expense of large install bases of things like traditional hardware-based firewalls and we've talked about this a lot in previous segments cloud migration is interesting and i really think it needs some interpretation i mean nobody likes to do migrations so i would suggest this includes things like i have a bunch of people answering phones and offices or i had and then overnight boom the offices are closed so i needed a cloud-based solution i didn't just lift and ship my shift my entire phone routing system you know from the office into the cloud but i probably pivoted to a cloud solution to support those work from home employees now my guess is i think that would be included in these responses i mean i do know an example of an insurance company that did migrate its claims application to the cloud during coven but this was something that they were you know planning to do pre-covered and i guess the point here is twofold again like i said migrations are hairy nobody wants to do them and i think this category really means i'm increasing my use of the cloud so i'm kind of migrating my my operations over time to the cloud all right look at collaboration no shocker here we've pounded you know zoom and webex to death analytics is really interesting we have talked extensively uh and have been covering snowflake and we pointed out that there's a new workload that has emerged in the cloud it's not just snowflake you know there are others aws redshift google with bigquery and and others but snowflake is the off the charts you know hot ipo and so we we talk a lot about it but it relates to this easy setup and access to a data layer with having you know requisite security and governance and this market is exploding adding ai on top and really doing this in the cloud so you can scale it up or down and really only pay for what you need that's a real benefit to people compare that to the traditional edw snake swallowing a basketball i got to get every new intel chip you're not dialing up down down you're over provisioning and half the time you're not using you know half most of the time you're not utilizing what you've paid for all right look at networking you know traffic patterns changed overnight with covet ddos attacks are up 25 to 40 percent uh since coven cyber attacks overall are up 400 percent this year so these all have impacts on the network machine learning and ai i talked about a little bit earlier about that but organizations are realizing that infusing ai into the application portfolio it's becoming really an imperative much more important as the automation mandate that we've talked about becomes more acute people you can't scale humans at this at the pace of technology so automation becomes much more important that of course leads us to rpa now you might think rpa should be a higher priority but i think what's happening here is i t organizations they were scrambling to plug holes in the dike rpa is somewhat more strategic and planful our data suggests that rpa remains one of the most elevated spending categories in terms of net score etr's measure of spending momentum so this means way more people are spending more than spending less in the rpa category so it really has a lot of legs in fact with the exception of container orchestration i think rpa is a sector that has the highest net score i think you'll see that in the upcoming surveys it's as high or even higher than ai i think it's higher than cloud it's just that it remember this is an it survey and a lot of the rpa stuff is going on at the business level but it had to keep the ship afloat when coveted hit which somewhat shifted priorities but but rpa remains strong now let's go back uh to the work from home trend for a moment i know it's been been played out and kind of beat on really heavily covered but i got to tell you etr was the very first on this trend it was way back in march and the data here is instructive it shows that the percentage of employees working from home prior to cor covid currently working from home the percent expected in six months and then those expected essentially permanently and this is primarily work from home versus yeah i don't work a day or two per week it's really the the five day a week i i work remotely as you can see only 16 percent of employees were working from home pre pandemic whereas more than 70 percent are at home today and cios they actually see a meaningful decline in that number over the next six months you know we'll see based on how covid comes back and you know this fall and winter surge and how will that will affect these plans but look what it does long term it settles in at like 34 percent that's double pre-covet so really a meaningful and permanent impact is expected from the isolation economy that we're in today and again why not look at this data it shows the distribution of productivity improvements so that while 23 of respondents said work from home productivity impacts were neutral nearly half i think it was 48 if you add up those bars on the right nearly half are seeing productivity improvements well less than 30 percent see a decline in productivity and you can see the etr quants they peg the average gain at between three and five percent that's pretty significant now of course not everyone can work from home if you're working at a restaurant you really you know unless you're in finance you really can't work from home but we're seeing in this digital economy with cloud and other technologies that we actually can work from pretty much anywhere in the world and many employees are going to look at work from home options as a benefit you know it was just a couple years ago remember that we were talking about companies like ibm and yahoo who mandated coming into the office i mean that was like 2017 2018 time frame well that trend is over now let me give you a quick preview of some of the other things that we're seeing and what the etr data shows now let me also say i'm just scratching the surface here etr has deep deep data cuts they have the sas platform allows you to look at the data all different ways and if you're not working with them you should be because the data gets updated so frequently every quarter there's new data there's drill down surveys and it's forward-looking so you know a lot of the survey data or a lot of the data that we use market share data and other data are sort of looking back you know you use your sales data your sales forecast that's obviously forward-looking but but the etr survey data can actually give an observation space outside of your sales force and no i'm not getting paid by etr but but it's been such a valuable resource i want to make it available and make the community aware of it all right so let's do a little speed round on on some of the the vendors of interest that we've talked about in the last several segments last couple years actually many years decade anyway start with aws aws continues to be strong but they they have less momentum than microsoft this is sort of a recurring pattern here but aws churn is low low low not a lot of people leaving the aws platform despite what we hear about this repatriation trend data warehousing is a little bit soft whereas we see snowflake very very strong but aws share is really strong inside of large companies so cloud and teams and security are strong from microsoft whereas data warehouse and ai aren't as robust as we've seen before but but microsoft azure cloud continues to see a little bit more momentum than aws so we'll watch that next quarter for aws earnings call now google has good momentum and they're steady especially in cloud database ai and analytics we've talked a lot about how google's behind the big two but nonetheless they're showing good good momentum servicenow very low churn but they're kind of hitting the law of large numbers still super strong in large accounts but not the same red hot hat red hot momentum as we've seen in the past octa is showing continued momentum they're holding you know close to number one or that top spot in security that we talked about last time no surprise given the increased importance of identity access management that we've been talking about so much crowdstrike last survey in july they showed some softness despite a good quarter and and we we're seeing continued to sell it to deceleration in the survey now that's from extremely elevated levels but it's significantly down from where crowdstrike was at the height of the lockdown i mean we like the sector of endpoint security and crowdstrike is definitely a leader there and you know well-managed company company but you know maybe they got hit with uh with you know a quick covet injection with with a step up function that's maybe moderating somewhat you know maybe there's some competition you know vmware freezing the market with carbon black i i really don't see that i think it's it's it's you know maybe there's some survey data isn't reflective of of what what crowdstrike is seeing we're going to see in the upcoming earnings release but it's something that we're watching very closely you know two survey snapshots with crowdstrike being a little bit softer it doesn't make a sustained trend but we would have liked to seen you know a little bit stronger this this quarter the data's still coming in so we'll see sale point is one we focused on recently and we see very little negative in their numbers so they're holding solid z scalar showing pretty strong momentum and while there was some concern last survey within large organizations it seemed that might have been a survey anomaly because z scalar they had a strong quarter a good outlook and we're seeing a strong recovery in the most recent data so it also looks like z z scaler is pressuring some of palo alto network's dominance and momentum heading into the quarter so we'll pay close attention to that we've said we like palo alto networks but they're so big uh they've got some exposures but they can offset those you know and they're doing a better job in cloud with their pricing models and sort of leaning into some of the the market waves uh sale point appears to be holding serve you know heading into the fourth quarter snowflake i mean what can we say it continues to show some of the strongest spending momentum going into q4 and into 2021 no signs of slowing down they're going to have their first earnings reports coming up you know in a few months so i i got to believe they got it together and and they're going to be strong reports uipath and momentum is is slowing down a bit but existing customers keep spending with ui path and there's very few defections so it looks like their land and expand is working pretty well automation anywhere continues to be strong despite comments about the sector earlier which showed you know maybe it wasn't as high a priority some other sectors but as i said you know it's still really really strong strong in terms of momentum and automation anywhere in uipath they continue to battle it out for the the top spot within the data set within the automation data set well i should say within rpa i mean companies like pega systems have a broader automation agenda and we really like their strategy and their execution databricks you know hot company once a hot company and still hot but we're seeing a little bit of a deceleration in the survey even though new customer acquisition is quite strong put it this way databricks is strong but not the off the chart outperformer that it used to be this is how etr frame that their analysis so i want to obviously credit that to them datadog showing the most strength in the application performance management or monitoring sector whichever you prefer but generally the the net scores in that sector as we talked about last week they're not great as a sector when you compare it to other leading sectors like cloud or automation rpa as an example container orchestration you know apm is kind of you know significantly lower it's not it's not as low as some of the on-prem on-prem infrastructure or some of the on-prem software but you know given datadog's high valuation it's somewhat of a concern so keep an eye on that mongodb you know they got virtually no customer churn but they're losing some momentum in terms of net score in the survey which is something we're keeping an eye on and a big downtick in in large organization acquisitions within the data so in other words they had a lot of new acquisitions within large companies but that's down now again that could be anomalies in the data i don't want to you know go to the bank on that necessarily but that's something to watch zoom they keep growing but etr data cites a churn of actually up to seven percent due to some security concerns so that was widely reported in the press and somewhere slower velocity for zoom overall due to possible competition from microsoft teams but i tell you it has an amazing stat that etr threw out pre-cove at zoom penetration in the education vertical was 15 today it's over 80 percent wowza cisco cisco's core is weak as we've said you've seen that in their earnings numbers it's it's there's softness there but security meraki those are two areas that remain strong same kind of similar story to last quarter survey pure storage you know they're the the high flyer they're like the one-eyed man in the land of the the storage blind so storage you know not a great market we've talked about that we've seen some softness in the the data set from uh in pure storage and really often sympathy with the generally back burner storage market you know again they they still outperforming their peers but we've seen slower growth rates there in the in in the survey and that's been reflected in their earnings uh so we've been talking about that for a while really keeping an eye on on on pure they made some acquisitions trying to expand their market enough said about that rubric rubric's interesting they kind of were off the charts in a couple surveys ago and they really come off of those highs you know anecdotally we're hearing some concerns in in the market it's hard to tell the private company cohesity has overtaken rubric and spending momentum now for the second quarter in a row you know they're still not as prevalent in the data set we'd like to see more ends from cohesity remember this is sort of a random sample across multiple industries we let the or etr lets the the respondents tell them what they're buying and what they're spending on you know but because cohesity has the highest net score relative to to compares like rubric like veeam you know i even threw in when i looked at nutanix pure dell emcs vxrail those are not direct competitors but they're you know kind of quasi compares if you will new relic they're showing some concerning trends on churn and the company is way off its 2018 momentum highs in the survey and we talked about this last week some of the challenges new relic is facing but we like their tech the nrdb is purpose-built for monitoring and performance management and we feel like you know they can retain their leadership if they can can pull it together we talked about elliott management being in there so that's something that we're watching red hat is showing strength in open shift really really strong ibm you know services exposure uh it's it's not the greatest business in the world right now at the same time there's there's crosswinds there at the same time people you know need some services and they need some help there but the certainly the outsourcing business so there's you know countervailing you know crosswinds uh within ibm but openshift bright spot i i think you know when i look at at the the red hat acquisition yeah 34 billion but but it's it's pretty obvious why ibm made that move um but anyway ibm's core business continues to be under under pressure that's why red hat is such an important component which brings me to vmware vmware has been an execution machine they had vmworld this past week uh we talked last month about the strength of vmware cloud on aws and it's still strong and and vmware cloud portfolio with vmware cloud foundation and other offerings but other than tanzu vmware is in this october survey of the first first look shows some deceleration really across the board you know one potential saving grace etr shared with me is that the fortune 500 spending for vmware is stronger so maybe on a spend basis when i say stronger stronger stronger than the mean so maybe on a spend basis vmware is okay but there seems to be some potential exposure there you know we won't know for sure until late next year uh how the dell reshuffle is going to affect them but it's going to be interesting to see how dell restructures vmware's balance sheet to get its own house in order and remember dell wants to get to investment grade for its own balance sheet yet at the same time it wants to keep vmware at investment grade but the interesting thing to watch is what impact that's going to have on vmware's ability to fund its future and we're not going to know that for a long long time but you know we'll keep an eye on on those developments now dell for its part showing strength and work from home and also strengthen giant public and privates which is a bellwether in the etr data set uh you know these are huge private companies for example uh koch industries would be one you know massive private companies mars would be another example not necessarily that they're the ones responding although my guess is they are it's it's anonymous but actually etr actually knows and they can identify who those bell weathers are and it's been a it's been a predictor of performance for the last you know better part of a decade so we'll see vxrail is strong um you know servers and storage they're they're still muted relative to last year but not really down from july so you know holding on dell holding on to it to to a tepid spending outlook they got such huge exposure on-prem you know so on balance i wouldn't expect you know a barn burner out of dell you know but they got a big portfolio and they've got a lot of a lot of options there and remember they still have the the still have they have a pc uh business unlike hpe which i'll talk about in in in a moment talk about now aruba is the bright spot for hpe but servers and storage those seem to be off you know similar to dell uh but but but maybe even down further i think you know dell is kind of holding relative to last quarter survey you know down from earlier this year and certainly down from from last year uh but hpe seems to be on a steeper downward trajectory uh in storage and service from the survey you know we'll see again you know one one snapshot quarter this is not a trend to make uh but again storage looks particularly soft which is a bit of a concern and we saw that you know in hpe's numbers you know last quarter um customer acquisition is strong for nutanix but overall spending is decelerating versus a year ago levels uh we know about the 750 million dollar injection uh from from bain capital basically you know in talking to bain what essentially they're doing is they they're betting on upside in the hyper-converged marketplace it's true that from a penetration standpoint there's a long long way to go and it's also true that nutanix is shifting from a you know perpetual model you know boom by the the capex to a in an annual occurring revenue model and they kind of need a bridge of cash to sort of soften that blow we've seen companies like tableau make that transition adobe successfully made that transition splunk is in that transition now and it's you know kind of funky for them but at any rate you know within that infrastructure software and virtualization sectors you know nutanix is showing some softness but in things like storage actually nutanix looking pretty strong very strong actually so again this theme of of these crosswinds uh supporting some companies whereas they're exposed in other areas you certainly see that with large companies and and nutanix looks like it's got some momentum in some areas and you know challenges in in others okay so that's just a quick speed dating round with some of the vendor previews for the upcoming survey so i just want to summarize now and we'll wrap so we see overall tech spending off four to five percent in 2020 with a slightly less bad slightly less bad q4 sequentially relative to q3 all this is relative to last year so we see continued headwinds coming into 2021 expect low single-digit spending growth next year let's call it two percent and there are some clear pockets of growth taking advantage of what we see is a more secular work from home trend particularly in security although we're watching some of the leaders shift positions cloud despite the commentary earlier remains very very strong aws azure google red hat open shift serverless kubernetes analytic cloud databases all very very strong automation also stands out as as a a priority in what we think is the coming decade with an automation mandate and some of the themes we've talked about for a long time particularly the impact of cloud relative to on-prem you know we don't see this so-called repatriation as much of a trend as it is a bunch of fun from on-prem vendors that don't own a public cloud so just you just don't see it i mean i'm sure there are examples of oh we did something in the cloud we lifted and shifted it didn't work out we didn't change our operating model okay but the the number of successes in cloud is like many orders of magnitude you know greater than the numbers of failures on the plus side however the for the on-prem guys the hybrid and multi-cloud spaces are increasingly becoming strategic for customers so that's something that i've said for a long time particularly with multi-cloud we've kind of been waiting it's been a lot of vendor power points but that really we talked to customers now they're hedging their bets in cloud they're they're putting horses for courses in terms of workloads they're they're they're not betting their business necessarily on a single cloud and as a result they need security and governance and performance and management across clouds that's consistent so that's actually a a really reasonable and significant opportunity for a lot of the on-prem vendors and as we've said before they're probably not necessarily going to trust the cloud players the public cloud players to deliver that they're going to want somebody that's cloud agnostic okay that's it for this week remember all these episodes are available as podcasts wherever you listen so please subscribe i publish weekly on wikibon.com and siliconangle.com and don't forget to check out etr.plus for all the survey action and the analytics these guys are amazing i always appreciate the comments on my linkedin posts thank you very much you can dm me at d vallante or email me at david.volante at siliconangle.com and this is dave vellante thanks for watching this episode of cube insights powered by etr be well and we'll see you next time you

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Tarkan Maner & Rajiv Mirani, Nutanix | Global .NEXT Digital Experience 2020


 

>> Narrator: From around the globe, it's theCUBE with coverage of the Global .NEXT Digital Experience brought to you by Nutanix. >> Welcome back, I'm Stu Miniman and this is theCUBE's coverage of the Nutanix .NEXT Digital Experience. We've got two of the c-suite here to really dig into some of the strategy and partnerships talked at their annual user conference. Happy to welcome back to the program two of our CUBE alumni first of all, we have Tarkan Maner. He is the Chief Customer Officer at Nutanix and joining us also Rajiv Mirani, he is the Chief Technology Officer, CTO. Rajiv, Tarkan, great to see you both. Thanks so much for joining us on theCUBE. >> Great to be back. >> Good to see you. >> All right. So Tarkan talk about a number of announcements. You had some big partner executives up on stage. As I just talked with Monica about, Scott Guthrie wearing the signature red polo, you had Kirk Skaugen from Lenovo of course, a real growing partnership with Nutanix, a bunch of others and even my understanding the partner program for how you go to market has gone through a lot. So a whole lot of stuff to go into, partnerships, don't need to tackle it all here upfront, but give us some of the highlights from your standpoint. >> I'll tell this to my dear friend Rajiv and I've been really busy, last few months and last 12 months have been super, super busy for us. And as you know, the latest announcements we made the new $750 million investment from Bain capital, amazing if by 20 results, Q4, big results. And obviously in the last few months big announcements with AWS as part of our hybrid multicloud vision and obviously Rajiv and I, we're making sale announcements, product announcements, partner announcements at .NEXT. So at a high level, I know Rajiv is going to cover this a little bit more in detail, but we covered everything under these three premises. Run better, run faster and run anywhere. Without stealing the thunder from Rajiv, but I just want to give you at a high level a little bit. What excites us a lot is obviously the customer partner intimacy and all this new IP innovation and announcement also very strong, very tight operational results and operational execution makes the company really special as a independent software vendor in this multicloud era. Obviously, we are the only true independent software vendor to do not run a business in a sense with fast growth. Timed to that announcement chain we make this big announcement with Azure partnership, our Nutanix portfolio under the Nutanix cluster ran now available as Bare-Metal Service on Azure after AWS. The partnership is new with Azure. We just announced the first angle of it. Limited access customers are taking it to look at the service. We're going to have a public preview in a few months, and more to come. And obviously we're not going to stop there. We have tons of work going on with other cloud providers, as well. Tying that, obviously, big focus with our Citrix partnership globally around our end user computing business as Rajiv will outline further, our portfolio on top of our digital infrastructure, tying the data center services, DevOps services, and you user computing services, Citrix partnership becomes a big one, and obviously you're tying the Lenovo and HP partnership to these things as the core platforms to run that business. It's creating tons of opportunity and I'll cover a little bit more further in a bit more detail, but one other partnership we are also focusing on, our Google partnership and on desktop as a service. So these are all coming to get around data center, DevOps, and user competent services on top of that amazing infrastructure Rajiv and team built over the past 10 years. I see Rajiv as one of our co-founders and one side with the right another. So the business is obviously booming in multiple fronts. This, if by 2020 was a great starting point with all this investment, that bank capital $750 million, big execution, ACD transition, software transition. And obviously these cloud partnerships are going to make big differences moving forward. >> Yeah, so Rajiv, want to build off what Tarkan was just saying there, that really coming together, when I heard the strategy run better, run faster, run anywhere, it really pulled together some of the threads I've been watching at Nutanix the last couple of years. There's been some SaaS solutions where it was like, wait, I don't understand how that ties back to really the core of what Nutanix does. And of course, Nutanix is more than just an HCI company, it's software and that simplicity and the experience as your team has always said, trying to make things invisible, but help if you would kind of lay out, there's a lot of announcements, but architecturally, there were some significant changes from the core, as well as, if I'm reading it right, it feels like the portfolio has a little bit more cohesion than I was seeing a year or so ago. >> Yeah, actually the theme around all these announcements is the same really, it's this ability to run any application, whether it's the most demanding traditional applications, the SAP HANA, the Epics and so on, but also the more modern cloud native application, any kind of application, we want the best platform. We want a platform that's simple, seamless, and secure, but we want to be able to run every application, we want to run it with great performance. So if you look at the announcements that are being made around strengthening the core with the Block Store, adding things like virtual networking, as well as announcements we made around building Karbon platform services, essentially making it easier for developers to build applications in a new cloud native way, but still have the choice of running them on premises or in the cloud. We believe we have the best platform for all of that. And then of course you want to give customers the optionality to run these applications anywhere they want, whether that's a private cloud, their own private data centers and service providers, or in the public cloud and the hyperscalers. So we give them that whole range of choices, and you can see that all the announcements fit into that one theme: any application, anywhere, that's basically it. >> Well, I'd like you to build just a little bit more on the application piece. The developer conversation is something we've been hearing from Nutanix the last couple of years. We've seen you in the cloud native space. Of course, Karbon is your Kubernetes offering. So the line I used a couple of years ago at .NEXT was modernize the platform, then you can modernize all of your applications on top of it, so where does Nutanix touch the developer? You know, how does that, building new apps, modernizing my apps tie into the Nutanix discussion? >> Yeah great question, Stu. So last year we introduced Karbon for the first time. And if you look at Karbon, the initial offering was really targeted at an IT audience, right? So it's basically the goal was to make Kubernetes management itself very easy for the IT professional. So essentially, whether you were creating a Nutanix, sorry, a Karbon cluster, or scaling it out or upgrading Kubernetes itself. We wanted to make that part of the life cycle very, very simple for IT. For the developer we offered the Vanilla Kubernetes system. And this was something that developers asked us for again and again, don't go around mucking around with Kubernetes itself, we want Vanilla Kubernetes, we want to use our Kube Cuddle or the tools that we're used to. So don't go fork off and build the economic Kubernetes distribution. That's the last thing we want. So we had a good platform already, but then we wanted to take the next step because very few applications today are self contained in the sense that they run entirely within themselves without dependence on external services, especially when you're building in the cloud, you have access, suppose you're building an Amazon, you have access to RDS to manage your databases. Don't have to manage it yourself. Your object stores, data pipelines, all kinds of platform services available, which really can accelerate development of your own applications, right? So we took the stand said, look, this is good. This is important. We want to give developers the same kind of services, but we want to make it much more democratic in the sense that we want them to be able to run these applications anywhere, not just on AWS or not just on GCP. And that's really the genesis of Kubernetes platform services. We've taken the most common services people use in the cloud and made them available to run anywhere. Public cloud, private cloud, anywhere. So we think it's very exciting. >> Tarkan, we had, you and I had a discussion with one of your partners on how this hybrid cloud scenario is playing out at HP discover, of course, with the GreenLake solution. I'm curious from your standpoint, all the things that Rajiv was just talking about, that's a real change, if you think about kind of the traditional infrastructure people they're needing to move up the stack. You've got partnerships with the hyperscalers. So help explain a little bit the ripple effect as Nutanix helps customers simplify and modernize, how your partners and your channel can still participate. >> So perfect, look, as you heard from Rajiv, this is like all coming super nicely together. As Rajiv outlined, with the data center, operations and services, DevOps services, to enable that faster time to market capable, that Kubernetes offering and user services, our desktop services on top of that classical industry-leading, record-breaking digital infrastructure. That hybrid cloud infrastructure we call today. You play this game with devoting a little bit, as you remember, we used to call hyper-converged infrastructure. Now we call it of the hybrid cloud infrastructure, in a sense. All those pieces coming together nicely end-to-end, unlike any other vendor, and from a software only perspective, we're not owned by a hardware company which is making a huge difference. Gives us tremendous level of flexibility, democratization, and freedom of choice. Cloud to us is basically is not a destination. It's an operating model. You heard me say this before, as Rajiv also said. So in our strategy, when you look at it, Stu, we have a three pronged approach on top of our on-prem, marketplace on-prem capable. There's been 17,000+ customers, 7,000+ channel and strategic partners. Also as part of this big announcement, this new partner program we called Elevate, on the Elevate brand, bringing all the channel partners, ISEs, platform partners, hyperscalers, Telco XPSs, and our global market partners all in one bucket where we manage them, simply the incentives. It's a very simple way to execute that opposite Chris Kaddaras, our Chief Revenue Officer, as well as Christian Alvarez, our Chief Partner Officer sort of speaking on global goal, the channels, working together tightly with our organization on the product front to deliver this. So one key point I want to share with you, tying to what Rajiv said earlier on the multicloud area, obviously we realize customers are looking for freedom of choice. So we have our own cloud, Nutanix cloud, under the XI brand. X-I, XI brand, which is basically our own logistics, our own basically, serviceability, payment capability and our software, running off our portal partnerships like Equinix delivering that software as a service. We started with disaster recovery as a service, very fast growing business. Now we announced our GreenLake partnership with HPE in the backend that data center as a service might be actually HP GreenLake if the customer wants it. So that partnership creates huge opportunities for us. Obviously, on top of that, we have these Telco XSP partnerships. As we're announcing partnerships with some amazing source providers like OBH. You heard today from college Sudani in society general, they are not only using AWS and Azure and Nutanix on-prem and Nutanix clusters on Azure and AWS for their internal departments, but they also use a local service provider in France for data gravity and data security reasons. A French company dealing with French business and data centers, with that kind of data governance requirements within the country, within the borders of France. So in that context we are also the service provider partnerships coming in. We're going to announce a partnership with OVHS vault, which is a big deal for us. And tying to this, as Rajiv talked about, our clusters portfolio, our portfolio basically running on-prem on AWS and Azure. And we're not going to stop there obviously. So give choice to the customers. So as Rajiv said, basically, Nutanix can run anywhere. On top of that we announced just today with Capgemini, a new dev test environment is a service. Where Rajiv's portfolio, end-to-end, data center, DevOps, and some of the UC capabilities for dev test reasons can run as a service on Capgemini cloud. We have similar partnerships with HCL, similar partnerships with (indistinct) and we're super excited for this .NEXT in FI21 because of those reasons. >> Rajiv, one of the real challenges we've had for a long time is, I want to be able to have that optionality. I want to be able to live in any environment. I don't want to be stuck in an environment, but I want to be able to take advantage of the innovation and the functionality that's there. Can you give us a little bit of insight? How do you make sure that Nutanix can live these environments like the new Azure partnership and it has the Nutanix experience, yet I can take advantage of, whether it be AI or some other capabilities that a Google, an Amazon or a Microsoft has. How do you balance that? You have to integrate with all of these partners yet, not lock out the features that they keep adding. >> Right, absolutely, that's a great point, Stu. And that's something we pride ourselves on, that we're not taking shortcuts. We're not trying to create our own bubble in these hyperscalers, where we run in an isolated environment and can't interact with the rest of the services they offer. And that's primarily why we have spent the time and the effort to integrate closely with their virtual networking, with the services that they provide and essentially offer the best of both worlds. We take the Nutanix stack, the entire software stack, everything we build from top to bottom, make it available. So the same experience is there with upgrades and prism, the same experience is available on-prem and in the cloud. But at the same time, as you said, we want people to have full speed access to cloud services. There's things the cloud is doing that will be very difficult for anybody to do. I mean, the kind of thing that, say Google does with AI, or Azure does with databases. It's remarkable what these guys are doing, and you want to take advantage of those services. So for us, it's very, very important, that access is not constrained in any way, but also that customers have the time to make this journey, right? If they want to move to cloud today, they can do that. And then they can refactor and redevelop their applications over time and start consuming these sales. So it's not an all or nothing proposition. It's not that you have to refactor it, rewrite before you can move forward. That's been extremely important for us and it's really topical right now, especially with this pandemic. I think one thing all of IT has realized is that you have to be agile. You have to be able to react to things and timeframes you never thought you needed to, right. So it's not just disaster recovery, but the amount of effort that's gone in the last few months in enabling a distributed workforce, who thought it would happen so quickly? But it's a kind of agility that, an optionality that we are giving to customers that really makes it possible. >> Yeah, absolutely. Right now, things are moving pretty fast. So let me let both of you have the final word. Give us a little bit viewpoint, as things are moving fast, what's on the plate? What should we be expecting to see from Nutanix and your ecosystem through the rest of 2020, Tarkan? >> So look, heard from us, Stu, I know you're talking to multiple folks and you had this discussions with us, end-to-end, and look for the company to be successful, customer partner intimacy, IP innovation, and execution, and operational excellence. Obviously, all three things need to come together. So in a sense, Stu, we just need to keep moving. I give this analogy a lot, as Benjamin Franklin says, the human beings are divided in three categories, you know? The first one is those who are immovable. They never move. Second category, those who, you know, are movable, you can move them if you try hard. And obviously third category, those who just move. Not only themselves, but they move others, like in a sense, in a nice way to refer to Benjamin Franklin, with one of our key founders in the US, in a sense as the founders of this company, with folks like Rajiv and other executives, and some of the newcomers, we a culture, which just keeps moving and the last 12 months, you've seen some of these. And obviously going back to the announcement day, AWS, now Azure, the Capgemini announcement then test as a service around some of the portfolio that Rajiv talked about or a Google partnership on desktop as a service, deep focus on Citrix globally with Azure, Google, and ourselves on-prem, off-prem. And obviously some of the big moves were making with some of the customers, it's going to continue. This is just the beginning. I mean, literally Rajiv and I are doing these .NEXT conferences, announcements, and so on. We're actually doing calls right now to basically execute for the next 12 months. We're planning the next 12 months' execution. So we're super excited now with this new Bain Capital investment, and also the partnership, the product, we're ready to rock and roll. So look forward to seeing you soon, Stu, and we're going to have more news to cover with you. >> Yeah, exactly right, Tarkan. I think as Tarkan said we are at the beginning of a journey right now. I think the way hybrid cloud is now becoming seamless opens up so many possibilities for customers, things that were never possible before. Most people when they talk hybrid cloud, they're talking about fairly separate environments, some applications running in the public cloud, some running on premises. Applications that are themselves hybrid that run across, or that can burst from one to the other, or can move around with both app and data mobility. I think the possibilities are huge. And it's going to be many years before we see the full potential of this platform. >> Well Rajiv and Tarkan, thank you so much for sharing all of the updates, congratulations on the progress, and absolutely look forward to catching up in the near future and watching the journey. >> Thanks, Stu. >> Thank you, Stu. >> And stay with us for more coverage here from the Nutanix .NEXT digital experience. I'm Stu Miniman, and as always, thank you for watching theCUBE. (bright music)

Published Date : Sep 9 2020

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the globe, it's theCUBE of the Nutanix the partner program the latest announcements we made and the experience as the optionality to run these applications So the line I used a couple That's the last thing we want. kind of the traditional on the product front to deliver this. and it has the Nutanix experience, But at the same time, as you said, the rest of 2020, Tarkan? and look for the company to be successful, in the public cloud, congratulations on the progress, the Nutanix

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Rukmini Sivaraman & Prabha Krishna | Nutanix .Next EU 2018


 

>> Livefrom London, England, it's theCUBE, covering .Next Conference Europe 2018. Brought to you by Nutanix. >> Welcome back to London, England. This is theCUBE's exclusive coverage of Nutanix .Next 2018 Europe. My name's Stu Miniman. My cohost for these two days of coverage has been Joep Piscaer. And happy to welcome to the program, two first (mumbles). We're gonna talk about culture and people. To my right is Rukmini Sivaraman, who is the vice president of business operations and chief of staff to the CEO. And sitting next to her is Prabha Krishna, who is the senior vice president of people and places, both of them with Nutanix. Ladies, thank you so much for joining us. >> Thank you. >> Thank you for having us. >> All right so, we've been covering Nutanix for a long time. I've been to every one of the shows. I start out, I guess... Dheeraj talked for a long time about the three Hs. It was humble, hungry, and honest, if I got those right. And more recently, it was with heart. Actually sitting not too far behind us, there's a big booth for heart. So, the culture of the company is something that is tied with the founders. We've watched that growth. I've watched the company go from about 35 people to over 3500 people. So, having those core principles is something that we look at in companies. Why don't we start? If you could both just give quick introduction, what brought you to Nutanix, and what your role is there. >> Sure, I've been at Nutanix a little over 18 months and I started out as an engineer, then went to finance and investment banking of all things, was at Goldman for almost a decade. And Nutanix is a client of Goldman's back form the IPO, and I had heard great things about the company, of course, but wasn't intending to leave Goldman Sachs. But when I got introduced to Dheeraj, there was so much that was compelling about the company, the disruption, the category-defining, category-creating kind of position that the company had. And more importantly, I think, where we were going, which was just phenomenal. it was ambitious, it was bold. And I think for me, it's always been about the people. We spend a lot of time at work and it's really important to feel that connection to the people. And that was really important 'cause I had to pick up and move from New York City to the Bay Area to make this move. And we can talk more about this, but to me the people were, like I said, ambitious, but they were also grounded. And I see it and after being at Nutanix now, it's phenomenal how truly humble the people are and that's always struck me as a great combination. You want ambition and challenging problems to solve, but you also want humility and people that you can relate to. So that's really what got me to Nutanix. >> Please. >> Yeah so, I've actually been following Nutanix for quite a while. It's a company that addresses a space that's very underserved and has created a suite of products that's nothing short of amazing for our customers, entirely focused on our customer base. But for me, the most interesting thing was, it's a company that is as right-brained as it is left-brained. I've actually spent 19 years of my career in engineering and made a career switch into the people side. And it's one of the few companies where that fit is almost perfect. And once I met our founder and our CEO, Dheeraj, this became even more obvious. So. I'm actually very happy to be here. I've been here for about four months now, and it's already very clearly the beginning of a very, very exciting journey. >> Yeah, interesting, both of you kind of making those shifts. Talk a little bit about that, talk about... People from outside of Silicon Valley, always, it's like, "Oh, there's the one where they have the playground "and free meals and free drinks." And it's like, "Yeah, that's because you do the analysis "and if they'll work 18 hours a day, "if we can keep them there, "maybe even put a cot in the office, that's good." I haven't seen cots in the office when I go to Nutanix, but hey are really nice offices. And even on the east coast, we're tartin' to change and see some of those things there. Maybe give us a little bit of insight as to that culture. And Nutanix is much more than just Silicon Valley based now. >> That's right. So we are truly a global organization. And we decided very early on that we wanted to be a global organization, but we're also thinking local. All right, so we do have multiple offices within the US, in Durham and Seattle and other places, but we're also truly global. Our Bangalore office, in India we have a big presence. And so for us what that means is there's people from different perspectives and background. But ultimately, it's our sort of, like you said, the four values, but also our culture principles that we've qualified fairly recently that bind us. And that really help us move forward in the same direction and pointing that same direction, and growing the same way. So that has been a phenomenal to see and it's one that I think we've very deliberately qualified more recently. It's sort of the how, how do we behave that embodies those four values that you talked about. >> So Prabha, so you're a new hire, right? >> Yes. >> You haven't been with Nutanix as much. So while we're talking on the subject, what's your personal experience coming into Nutanix? Is it true what you're talking about? How does it work in real life, in practice? >> No, absolutely. All companies state a culture. All companies, I think, in this day and age at least and definitely in Silicon Valley, are very clear about having a specific culture. But the key, as far as I'm concerned, and the strength of a company is how they live and breathe their culture every single day, in every decision, and every action, right. In every difficult balance that they need to meet, that's where the culture really shows up. And at Nutanix, it is... How shall I put it? It's really the core of every single thing we do. It's the core of how we interact. It's the core of how we grow. It's the core of how we recruit, how we define our organizations. And frankly, I have to say, I have been in a lot of organizations and a lot of organizations over time, actually, and particularly as they reach our size... We're a bit at sort of an inflection point, if you will, in terms of size. Our growth has definitely been very, very quick and continues to accelerate. Having that culture being something that we really live is the most important thing. And it is what will allow us to continue to innovate and continue to succeed all over the globe as Rukmini just explained. For me, it's quite extraordinary to see it in action. >> Yeah, that's really interesting because, one, our industry has some challenges hiring. It's finding the right skillset there. If you match that with a culture, what challenge are there? What are you looking for? What is the fit from the outside to match what you're looking for? >> Yeah, I'm happy to address a little bit. So recruiting for us is everything. We want to bring in the best. We wanna bring in the brightest and we wanna bring in folks who really value our culture and our values, who really understand them. And again, are willing to live them every single day. So we do look for great talent all over the planet because great talent exists all over the planet. This is absolutely fundamental to our growth. We are an infrastructure company and we offer, actually, very interesting work for anyone who is interested in the engineering side, who is interested in the sales side, who's interested in market. And for me, the most interesting part in the roles we have, and frankly the most unusual piece if you will, is we offer opportunities to build things from scratch. So, the creative side, the creative mind is really what we encourage. And it shows up in every single aspect of the way we're structured. So, the diversity of thought, the diversity of background, the diversity of... Whether it's gender or location, philosophies, and all of that, is really what we want to bring in and what will allow us to continue to create these products that are quite unique. >> If I may add to that, we talk internally a lot about the founder's mentality. It's a concept, a framework that was developed by Bain & Company and the gist of it is as follows: When you think about great disruptive startups, they're on this rocket ship, accelerating growth. And then they get to a certain size, so they become a little bigger. And they get enjoy the benefits of scale, economies of scale, and that's a good thing. But the best companies take that and then they enjoy those benefits, but they then also don't lose what got them there in the first place, which is the innovation, the ability to disrupt and look around corners, and all of that. So we want the best of both worlds. And in this framework, it's called a scaled insurgent. So you're scaled, but you're still an insurgency. And that is important to us. Folks that can sort of balance the two, really make sure that we are benefiting from one, but also not losing sight of the other. And it's a paradox in many ways and we believe in embracing those paradoxes. And folks who can sort of balance those two would be really a great fit. >> And so, if you're growing that fast, I can imagine that keeping the balance between culture and engineering, and you're growing, that's difficult. How does Nutanix handle that paradox? >> I think it goes back to what Prabha was saying. And for us, culture and the way we behave is like oxygen. So it almost fuels the fire as opposed to the other way around or having to do two things at once. And that's how we've thought about it. And the principles, when we thought about them and conceived them, it was the same idea, which is how can this just be the way we conduct ourselves we treat our customers, we treat each other, we treat our partners? How can it just become the way we do business? And so far, that's worked well for us. >> So one of my favorite culture principles, actually, is comfortable being uncomfortable. And there's a real reason that because given our scale, given the way we wanna grow, and given the fact that we want to preserve that innovative seed at every step, for us, every single day is about balancing opposing forces. Do we invest in the short term? Do we invest in the long term? Do we manage locally? Do we manage more globally? Do we centralize things, do we not? Do we distribute, right? Every single day is about balancing those kinds of things and it's that balance that encourages the creativity in every single one of us. So, the very fact that we've sort of embodied that in a culture principle, really is a very strong indication of what we look for and what we wanna be. >> Right, with the time that we have left, I wondering if you could talk about both at the show and beyond the show, what things Nutanix is doing. Think tech for good, think about the charitable things. Some of speakers I've seen at these shows... Mick Ebeling is one that stood out from a previous show. On talking about tech for good, Dr. Jane Goodall, who I know spoke at a women's lunch event and in the keynote here today, is just so inspiring. As someone that loves science and animals, it was very powerful. You've got the .heart initiatives here. Maybe help for those that don't know here and what else you're doing around the globe and around the year. >> Did you wanna go first? >> Yeah, so giving back is very important for us. It's very fundamental. Gratitude, understanding where we all came from, where we are, and where we wanna go, and not losing ourselves, that's really the key of, I think, any type of success, frankly. So we have an organization around that. It's a very active organization, we all participate. And the company is very much involved in as many different types of charities as possible. It also feeds into the kinds of sourcing that we do when every bring people in. We look for folks who care. We care very much about our people. The amount of attention and the amount of just knowledge and thought that goes into structuring our organization is very much reflective of that sense of giving back and gratitude as well. Our employees are everything and the folks around us who are in need are also everything. It sort of goes together, if you will. So basically to us, it's a hugely, hugely important effort and we'll continue investing in those kinds of things as we go forward. >> I think one thing I would add is as you saw at the end of the closing keynote, I think we announced or shared that thanks to everyone here, really all the folks here, our customers, partners, all of our participants, we were able to collect over 10,000 pounds for .heart and that is phenomenal. We're forever grateful to our community to be able to do things like that. We also partner with organizations like Girls in Tech, which is doing great work on making sure that we are bringing all kinds of talent, as Prabha said, to the table. We believe there's great people everywhere. And so, how do we harness the power of all of those initiatives? >> All right, those are some great examples. And Prabha, to your point, I think that that individual touch to your employees, that also translates to the customer side. Something I hear from Nutanix customers is despite the fact how large you've grown and how many customers you have, they feel that they get that individual attention. So thank you so much for sharing all of the updates. Wish you both the best of luck in your continued journey. And we wanna thank our community, of course, for tuning in to our coverage. It is truly our pleasure to help document what's happening out in the industry, hopefully be a surrogate for you, to ask the questions that you wanna hear and help you along your journeys. My name's Stu Miniman. My first European cohost who also did a segment in Dutch, Joep Piscaer, Can you goodbye in Dutch for us, Joep? >> (Dutch). >> All right, I'll have to learn that one some time because, unfortunately, my english and speaking numbers in a couple of different languages is where I'm a little bit limited. But once again, thanks for watching. Turn to thecube.net to catch all of the replays from this show as well as all the shows that we will be at. Including, next year, Nutanix will be at Anaheim and the spring and Copenhagen in the fall. And our team look forward to bringing you coverage from both of those. So once again, thank you for watching theCUBE. >> Thank you. (slick electronic music) >> Hi, I'm John Wallis. I've been with theCUBE for a couple years serving as a host here on our broadcast, our flagship broadcast on SiliconANGLE TV. I like to think about the hows and the whys, and the whats of technology. How's it work? Why does it matter? What is it doing for end users? When I think about theCUBE does and what it means, to me, it's an ...

Published Date : Nov 29 2018

SUMMARY :

Brought to you by Nutanix. and chief of staff to the CEO. So, the culture of the company is something And Nutanix is a client of Goldman's back form the IPO, And it's one of the few companies And even on the east coast, we're tartin' to change and pointing that same direction, and growing the same way. Is it true what you're talking about? It's really the core of every single thing we do. What is the fit from the outside And for me, the most interesting part in the roles we have, And that is important to us. I can imagine that keeping the balance between How can it just become the way we do business? given the way we wanna grow, and given the fact that and in the keynote here today, is just so inspiring. And the company is very much involved in And so, how do we harness the power And we wanna thank our community, of course, for tuning in And our team look forward to bringing you Thank you. and the whats of technology.

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David C King, FogHorn Systems | CUBEConversation, November 2018


 

(uplifting orchestral music) >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're at the Palo Alto studios, having theCUBE Conversation, a little break in the action of the conference season before things heat up, before we kind of come to the close of 2018. It's been quite a year. But it's nice to be back in the studio. Things are a little bit less crazy, and we're excited to talk about one of the really hot topics right now, which is edge computing, fog computing, cloud computing. What do all these things mean, how do they all intersect, and we've got with us today David King. He's the CEO of FogHorn Systems. David, first off, welcome. >> Thank you, Jeff. >> So, FogHorn Systems, I guess by the fog, you guys are all about the fog, and for those that don't know, fog is kind of this intersection between cloud, and on prem, and... So first off, give us a little bit of the background of the company and then let's jump into what this fog thing is all about. >> Sure, actually, it all dovetails together. So yeah, you're right, FogHorn, the name itself, came from Cisco's invented term, called fog computing, from almost a decade ago, and it connoted this idea of computing at the edge, but didn't really have a lot of definition early on. And so, FogHorn was started actually by a Palo Alto Incubator, just nearby here, that had the idea that hey, we got to put some real meaning and some real meat on the bones here, with fog computing. And what we think FogHorn has become over the last three and a half years, since we took it out of the incubator, since I joined, was to put some real purpose, meaning, and value in that term. And so, it's more than just edge computing. Edge computing is a related term. In the industrial world, people would say, hey, I've had edge computing for three, 40, 50 years with my production line control and also my distributed control systems. I've got hard wired compute. I run, they call them, industrial PCs in the factory. That's edge compute. The IT roles come along and said, no, no, no, fog compute is a more advanced form of it. Well, the real purpose of fog computing and edge computing, in our view, in the modern world, is to apply what has traditionally been thought of as cloud computing functions, big, big data, but running in an industrial environment, or running on a machine. And so, we call it as really big data operating in the world's smallest footprint, okay, and the real point of this for industrial customers, which is our primary focus, industrial IoT, is to deliver as much analytic machine learning, deep learning AI capability on live-streaming sensor data, okay, and what that means is rather than persisting a lot of data either on prem, and then sending it to the cloud, or trying to stream all this to the cloud to make sense of terabytes or petabytes a day, per machine sometimes, right, think about a jet engine, a petabyte every flight. You want to do the compute as close to the source as possible, and if possible, on the live streaming data, not after you've persisted it on a big storage system. So that's the idea. >> So you touch on all kinds of stuff there. So we'll break it down. >> Unpack it, yeah. >> Unpack it. So first off, just kind of the OT/IT thing, and I think that's really important, and we talked before turning the cameras on about Dr. Tom from HP, he loves to make a big symbolic handshake of the operations technology, >> One of our partners. >> Right, and IT, and the marriage of these two things, where before, as you said, the OT guys, the guys that have been running factories, you know, they've been doing this for a long time, and now suddenly, the IT folks are butting in and want to get access to that data to provide more control. So, you know, as you see the marriage of those two things coming together, what are the biggest points of friction, and really, what's the biggest opportunity? >> Great set of questions. So, quite right, the OT folks are inherently suspicious of IT, right? I mean, if you don't know the history, 40 plus years ago, there was a fork in the road, where in factory operations, were they going to embrace things like ethernet, the internet, connected systems? In fact, they purposely air gapped an island of those systems 'cause they was all about machine control, real-time, for safety, productivity, and uptime of the machine. They don't want any, you can't use kind of standard ethernet, it has to be industrial ethernet, right? It has to have time bound and deterministic. It can't be a retry kind of a system, right? So different MAC layer for a reason, for example. What did the physical wiring look like? It's also different cabling, because you can't have cuts, jumps in the cable, right? So it's a different environment entirely that OT grew up in, and so, FogHorn is trying to really bring the value of what people are delivering for AI, essentially, into that environment in a way that's non-threatening to, it's supplemental to, and adds value in the OT world. So Dr. Tom is right, this idea of bringing IT and OT together is inherently challenging, because these were kind of fork in the road, island-ed in the networks, if you will, different systems, different nomenclature, different protocols, and so, there's a real education curve that IT companies are going through, and the idea of taking all this OT data that's already been produced in tremendous volumes already before you add new kinds of sensing, and sending it across a LAN which it's never talked to before, then across a WAN to go to a cloud, to get some insight doesn't make any sense, right? So you want to leverage the cloud, you want to leverage data centers, you want to leverage the LAN, you want to leverage 5G, you want to leverage all the new IT technologies, but you have to do it in a way that makes sense for it and adds value in the OT context. >> I'm just curious, you talked about the air gapping, the two systems, which means they are not connected, right? >> No, they're connected with a duct, they're connected to themselves, in the industrial-- >> Right, right, but before, the OT system was air gapped from the IT system, so thinking about security and those types of threats, now, if those things are connected, that security measure has gone away, so what is the excitement, adoption scare when now, suddenly, these things that were separate, especially in the age of breaches that we know happen all the time as you bring those things together? >> Well, in fact, there have been cyber breaches in the OT context. Think about Stuxnet, think about things that have happened, think about the utilities back keys that were found to have malwares implanted in them. And so, this idea of industrial IoT is very exciting, the ability to get real-time kind of game changing insights about your production. A huge amount of economic activity in the world could be dramatically improved. You can talk about trillions of dollars of value which the McKenzie, and BCG, and Bain talk about, right, by bringing kind of AI, ML into the plant environment. But the inherent problem is that by connecting the systems, you introduce security problems. You're talking about a huge amount of cost to move this data around, persist it then add value, and it's not real-time, right? So, it's not that cloud is not relevant, it's not that it's not used, it's that you want to do the compute where it makes sense, and for industrial, the more industrialized the environment, the more high frequency, high volume data, the closer to the system that you can do the compute, the better, and again, it's multi-layer of compute. You probably have something on the machine, something in the plant, and something in the cloud, right? But rather than send raw OT data to the cloud, you're going to send processed intelligent metadata insights that have already been derived at the edge, update what they call the fleet-wide digital twin, right? The digital twin for that whole fleet of assets should sit in the cloud, but the digital twin of the specific asset should probably be on the asset. >> So let's break that down a little bit. There's so much good stuff here. So, we talked about OT/IT and that marriage. Next, I just want to touch on cloud, 'cause a lot of people know cloud, it's very hot right now, and the ultimate promise of cloud, right, is you have infinite capacity >> Right, infinite compute. >> Available on demand, and you have infinite compute, and hopefully you have some big fat pipes to get your stuff in and out. But the OT challenge is, and as you said, the device challenge is very, very different. They've got proprietary operating systems, they've been running for a very, very long time. As you said, they put off boatloads, and boatloads, and boatloads of data that was never really designed to feed necessarily a machine learning algorithm, or an artificial intelligence algorithm when these things were designed. It wasn't really part of the equation. And we talk all the time about you know, do you move the compute to the data, you move the data to the compute, and really, what you're talking about in this fog computing world is kind of a hybrid, if you will, of trying to figure out which data you want to process locally, and then which data you have time, relevance, and other factors that just go ahead and pump it upstream. >> Right, that's a great way to describe it. Actually, we're trying to move as much of the compute as possible to the data. That's really the point of, that's why we say fog computing is a nebulous term about edge compute. It doesn't have any value until you actually decide what you're trying to do with it, and what we're trying to do is to take as much of the harder compute challenges, like analytics, machine learning, deep learning, AI, and bring it down to the source, as close to the source as you can, because you can essentially streamline or make more efficient every layer of the stack. Your models will get much better, right? You might have built them in the cloud initially, think about a deep learning model, but it may only be 60, 70% accurate. How do you do the improvement of the model to get it closer to perfect? I can't go send all the data up to keep trying to improve it. Well, typically, what happens is I down sample the data, I average it and I send it up, and I don't see any changes in the average data. Guess what? We should do is inference all the time and all the data, run it in our stack, and then send the metadata up, and then have the cloud look across all the assets of a similar type, and say, oh, the global fleet-wide model needs to be updated, and then to push it down. So, with Google just about a month ago, in Barcelona, at the IoT show, what we demonstrated was the world's first instance of AI for industrial, which is closed loop machine learning. We were taking a model, a TensorFlow model, trained in the cloud in the data center, brought into our stack and referring 100% inference-ing in all the live data, pushing the insights back up into Google Cloud, and then automatically updating the model without a human or data scientist having to look at it. Because essentially, it's ML on ML. And that to us, ML on ML is the foundation of AI for industrial. >> I just love that something comes up all the time, right? We used to make decisions based on the sampling of historical data after the fact. >> That's right, that's how we've all been doing it. >> Now, right, right now, the promise of streaming is you can make it based on all the data, >> All the time. >> All the time in real time. >> Permanently. >> This is a very different thing. So, but as you talked about, you know, running some complex models, and running ML, and retraining these things. You know, when you think of edge, you think of some little hockey puck that's out on the edge of a field, with limited power, limited connectivity, so you know, what's the reality of, how much power do you have at some of these more remote edges, or we always talk about the field of turbines, oil platforms, and how much power do you need, and how much compute that it actually starts to be meaningful in terms of the platform for the software? >> Right, there's definitely use cases, like you think about the smart meters, right, in the home. The older generation of those meters may have had very limited compute, right, like you know, talking about single megabyte of memory maybe, or less, right, kilobytes of memory. Very hard to run a stack on that kind of footprint. The latest generation of smart meters have about 250 megabytes of memory. A Raspberry Pi today is anywhere from a half a gig to a gig of memory, and we're fundamentally memory-bound, and obviously, CPU if it's trying to really fast compute, like vibration analysis, or acoustic, or video. But if you're just trying to take digital sensing data, like temperature, pressure, velocity, torque, we can take humidity, we can take all of that, believe it or not, run literally dozens and dozens of models, even train the models in something as small as a Raspberry Pi, or a low end x86. So our stack can run in any hardware, we're completely OS independent. It's a full up software layer. But the whole stack is about 100 megabytes of memory, with all the components, including Docker containerization, right, which compares to about 10 gigs of running a stream processing stack like Spark in the Cloud. So it's that order of magnitude of footprint reduction and speed of execution improvement. So as I said, world's smallest fastest compute engine. You need to do that if you're going to talk about, like a wind turbine, it's generating data, right, every millisecond, right. So you have high frequency data, like turbine pitch, and you have other conceptual data you're trying to bring in, like wind conditions, reference information about how the turbine is supposed to operate. You're bringing in a torrential amount of data to do this computation on the fly. And so, the challenge for a lot of the companies that have really started to move into the space, the cloud companies, like our partners, Google, and Amazon, and Microsoft, is they have great cloud capabilities for AI, ML. They're trying to move down to the edge by just transporting the whole stack to there. So in a plant environment, okay, that might work if you have massive data centers that can run it. Now I still got to stream all my assets, all the data from all of my assets to that central point. What we're trying to do is come out the opposite way, which is by having the world's smallest, fastest engine, we can run it in a small compute, very limited compute on the asset, or near the asset, or you can run this in a big compute and we can take on lots and lots of use cases for models simultaneously. >> I'm just curious on the small compute case, and again, you want all the data-- >> You want to inference another thing, right? >> Does it eventually go back, or is there a lot of cases where you can get the information you need off the stream and you don't necessarily have to save or send that upstream? >> So fundamentally today, in the OT world, the data usually gets, if the PLC, the production line controller, that has simple KPIs, if temperature goes to X or pressure goes to Y, do this. Those simple KPIs, if nothing is executed, it gets dumped into a local protocol server, and then about every 30, 60, 90 days, it gets written over. Nobody ever looks at it, right? That's why I say, 99% of the brown field data in OT has never really been-- >> Almost like a security-- >> Has never been mined for insight. Right, it just gets-- >> It runs, and runs, and runs, and every so often-- >> Exactly, and so, if you're doing inference-ing, and doing real time decision making, real time actual with our stack, what you would then persist is metadata insights, right? Here is an event, or here is an outcome, and oh, by the way, if you're doing deep learning or machine learning, and you're seeing deviation or drift from the model's prediction, you probably want to keep that and some of the raw data packets from that moment in time, and send that to the cloud or data center to say, oh, our fleet-wide model may not be accurate, or may be drifting, right? And so, what you want to do, again, different horses for different courses. Use our stack to do the lion's share of the heavy duty real time compute, produce metadata that you can send to either a data center or a cloud environment for further learning. >> Right, so your piece is really the gathering and the ML, and then if it needs to go back out for more heavy lifting, you'll send it back up, or do you have the cloud application as well that connects if you need? >> Yeah, so we build connectors to you know, Google Cloud Platform, Google IoT Core, to AWS S3, to Microsoft Azure, virtually any, Kafka, Hadoop. We can send the data wherever you want, either on plant, right back into the existing control systems, we can send it to OSIsoft PI, which is a great time series database that a lot of process industries use. You could of course send it to any public cloud or a Hadoop data lake private cloud. You can send the data wherever you want. Now, we also have, one of our components is a time series database. You can also persist it in memory in our stack, just for buffering, or if you have high value data that you want to take a measurement, a value from a previous calculation and bring it into another calculation during later, right, so, it's a very flexible system. >> Yeah, we were at OSIsoft PI World earlier this year. Some fascinating stories that came out of-- >> 30 year company. >> The building maintenance, and all kinds of stuff. So I'm just curious, some of the easy to understand applications that you've seen in the field, and maybe some of the ones that were a surprise on the OT side. I mean, obviously, preventative maintenance is always towards the top of the list. >> Yeah, I call it the layer cake, right? Especially when you get to remote assets that are either not monitored or lightly monitored. They call it drive-by monitoring. Somebody shows up and listens or looks at a valve or gauge and leaves. Condition-based monitoring, right? That is actually a big breakthrough for some, you know, think about fracking sites, or remote oil fields, or mining sites. The second layer is predictive maintenance, which the next generation is kind of predictive, prescriptive, even preventive maintenance, right? You're making predictions or you're helping to avoid downtime. The third layer, which is really where our stack is sort of unique today in delivering is asset performance optimization. How do I increase throughput, how do I reduce scrap, how do I improve worker safety, how do I get better processing of the data that my PLC can't give me, so I can actually improve the performance of the machine? Now, ultimately, what we're finding is a couple of things. One is, you can look at individual asset optimization, process optimization, but there's another layer. So often, we're deployed to two layers on premise. There's also the plant-wide optimization. We talked about wind farm before, off camera. So you've got the wind turbine. You can do a lot of things about turbine health, the blade pitch and condition of the blade, you can do things on the battery, all the systems on the turbine, but you also need a stack running, like ours, at that concentration point where there's 200 plus turbines that come together, 'cause the optimization of the whole farm, every turbine affects the other turbine, so a single turbine can't tell you speed, rotation, things that need to change, if you want to adjust the speed of one turbine, versus the one next to it. So there's also kind of a plant-wide optimization. Talking about time that's driving, there's going to be five layers of compute, right? You're going to have the, almost what I call the ECU level, the individual sub-system in the car that, the engine, how it's performing. You're going to have the gateway in the car to talk about things that are happening across systems in the car. You're going to have the peer to peer connection over 5G to talk about optimization right between vehicles. You're going to have the base station algorithms looking at a micro soil or macro soil within a geographic area, and of course, you'll have the ultimate cloud, 'cause you want to have the data on all the assets, right, but you don't want to send all that data to the cloud, you want to send the right metadata to the cloud. >> That's why there are big trucks full of compute now. >> By the way, you mentioned one thing that I should really touch on, which is, we've talked a lot about what I call traditional brown field automation and control type analytics and machine learning, and that's kind of where we started in discrete manufacturing a few years ago. What we found is that in that domain, and in oil and gas, and in mining, and in agriculture, transportation, in all those places, the most exciting new development this year is the movement towards video, 3D imaging and audio sensing, 'cause those sensors are now becoming very economical, and people have never thought about, well, if I put a camera and apply it to a certain application, what can I learn, what can I do that I never did before? And often, they even have cameras today, they haven't made use of any of the data. So there's a very large customer of ours who has literally video inspection data every product they produce everyday around the world, and this is in hundreds of plants. And that data never gets looked at, right, other than training operators like, hey, you missed the defects this day. The system, as you said, they just write over that data after 30 days. Well, guess what, you can apply deep learning tensor flow algorithms to build a convolutional neural network model and essentially do the human visioning, rather than an operator staring at a camera, or trying to look at training tapes. 30 days later, I'm doing inference-ing of the video image on the fly. >> So, do your systems close loop back to the control systems now, or is it more of a tuning mechanism for someone to go back and do it later? >> Great question, I just got asked that this morning by a large oil and gas super major that Intel just introduced us to. The short answer is, our stack can absolutely go right back into the control loop. In fact, one of our investors and partners, I should mention, our investors for series A was GE, Bosch, Yokogawa, Dell EMC, and our series debuted a year ago was Intel, Saudi Aramco, and Honeywell. So we have one foot in tech, one foot in industrial, and really, what we're really trying to bring is, you said, IT, OT together. The short answer is, you can do that, but typically in the industrial environment, there's a conservatism about, hey, I don't want to touch, you know, affect the machine until I've proven it out. So initially, people tend to start with alerting, so we send an automatic alert back into the control system to say, hey, the machine needs to be re-tuned. Very quickly, though, certainly for things that are not so time-sensitive, they will just have us, now, Yokogawa, one of our investors, I pointed out our investors, actually is putting us in PLCs. So rather than sending the data off the PLC to another gateway running our stack, like an x86 or ARM gateway, we're actually, those PLCs now have Raspberry Pi plus capabilities. A lot of them are-- >> To what types of mechanism? >> Well, right now, they're doing the IO and the control of the machine, but they have enough compute now that you can run us in a separate module, like the little brain sitting right next to the control room, and then do the AI on the fly, and there, you actually don't even need to send the data off the PLC. We just re-program the actuator. So that's where it's heading. It's eventually, and it could take years before people get comfortable doing this automatically, but what you'll see is that what AI represents in industrial is the self-healing machine, the self-improving process, and this is where it starts. >> Well, the other thing I think is so interesting is what are you optimizing for, and there is no right answer, right? It could be you're optimizing for, like you said, a machine. You could be optimizing for the field. You could be optimizing for maintenance, but if there is a spike in pricing, you may say, eh, we're not optimizing now for maintenance, we're actually optimizing for output, because we have this temporary condition and it's worth the trade-off. So I mean, there's so many ways that you can skin the cat when you have a lot more information and a lot more data. >> No, that's right, and I think what we typically like to do is start out with what's the business value, right? We don't want to go do a science project. Oh, I can make that machine work 50% better, but if it doesn't make any difference to your business operations, so what? So we always start the investigation with what is a high value business problem where you have sufficient data where applying this kind of AI and the edge concept will actually make a difference? And that's the kind of proof of concept we like to start with. >> So again, just to come full circle, what's the craziest thing an OT guy said, oh my goodness, you IT guys actually brought some value here that I didn't know. >> Well, I touched on video, right, so without going into the whole details of the story, one of our big investors, a very large oil and gas company, we said, look, you guys have done some great work with I call it software defined SCADA, which is a term, SCADA is the network environment for OT, right, and so, SCADA is what the PLCs and DCSes connect over these SCADA networks. That's the control automation role. And this investor said, look, you can come in, you've already shown us, that's why they invested, that you've gone into brown field SCADA environments, done deep mining of the existing data and shown value by reducing scrap and improving output, improving worker safety, all the great business outcomes for industrial. If you come into our operation, our plant people are going to say, no, you're not touching my PLC. You're not touching my SCADA network. So come in and do something that's non-invasive to that world, and so that's where we actually got started with video about 18 months ago. They said, hey, we've got all these video cameras, and we're not doing anything. We just have human operators writing down, oh, I had a bad event. It's a totally non-automated system. So we went in and did a video use case around, we call it, flare monitoring. You know, hundreds of stacks of burning of oil and gas in a production plant. 24 by seven team of operators just staring at it, writing down, oh, I think I had a bad flare. I mean, it's a very interesting old world process. So by automating that and giving them an AI dashboard essentially. Oh, I've got a permanent record of exactly how high the flare was, how smoky was it, what was the angle, and then you can then fuse that data back into plant data, what caused that, and also OSIsoft data, what was the gas composition? Was it in fact a safety violation? Was it in fact an environmental violation? So, by starting with video, and doing that use case, we've now got dozens of use cases all around video. Oh, I could put a camera on this. I could put a camera on a rig. I could've put a camera down the hole. I could put the camera on the pipeline, on a drone. There's just a million places that video can show up, or audio sensing, right, acoustic. So, video is great if you can see the event, like I'm flying over the pipe, I can see corrosion, right, but sometimes, like you know, a burner or an oven, I can't look inside the oven with a camera. There's no camera that could survive 600 degrees. So what do you do? Well, that's probably, you can do something like either vibration or acoustic. Like, inside the pipe, you got to go with sound. Outside the pipe, you go video. But these are the kind of things that people, traditionally, how did they inspect pipe? Drive by. >> Yes, fascinating story. Even again, I think at the end of the day, it's again, you can make real decisions based on all the data in real time, versus some of the data after the fact. All right, well, great conversation, and look forward to watching the continued success of FogHorn. >> Thank you very much. >> All right. >> Appreciate it. >> He's David King, I'm Jeff Frick, you're watching theCUBE. We're having a CUBE conversation at our Palo Alto studio. Thanks for watching, we'll see you next time. (uplifting symphonic music)

Published Date : Nov 16 2018

SUMMARY :

of the conference season the background of the company and the real point of this So you touch on Unpack it, of the OT/IT thing, and the marriage of these two things, and the idea of taking all this OT data and something in the cloud, right? and the ultimate promise of cloud, right, and then which data you have time, and all the data, all the time, right? That's right, that's how and how much power do you need, and you have other conceptual data 99% of the brown field data in OT Right, it just gets-- and some of the raw data packets You can send the data wherever you want. that came out of-- and maybe some of the ones the peer to peer connection over 5G of compute now. and essentially do the human visioning, back into the control system to say, and the control of the machine, You could be optimizing for the field. of AI and the edge concept So again, just to come full circle, Outside the pipe, you go video. based on all the data in real time, we'll see you next time.

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Alan Boehme, Procter & Gamble | Mayfield50


 

Sand Hill Road to the heart of Silicon Valley it's the cute presenting the people first Network insights from entrepreneurs and tech leaders when I'm John Ferrari with the cube I'm the co-host also the founder of Silicon angle me we are here on Sand Hill Road at Mayfield for the people first conversations I'm John furry with the cube weird Allen being global CTO and IT of innovation at Procter & Gamble formerly the same position at coca-cola has done a lot of innovations over the years also a reference account back in the day for web methods when they call on the financing of that one of the most famous IPOs which set the groundwork for web services and has a lot of history going back to the 80s we were just talking about it welcome this conversation on people first network thank you for inviting me so the people first network is all about people and it's great to have these conversations you're old school you were doing some stuff back on the 80s talking about doing RPA 3270 you've been old school here yeah I go back to APL as my first programming language went through the the third generation languages and of course the old 30 to 70 emulation which is what we know today is our PA one of the cool things I was excited to hear some of your background around your history web methods you were a reference call for venture financing of web methods which was financed on the credit card for the two founders husband and wife probably one of the most successful I appeals but more importantly at the beginning of the massive wave that we now see with web services this is early days this was very early days when I was at DHL we were looking at what we're gonna do for the future and in fact we built one of the first object-oriented frameworks in C++ at the time because that was all that was available to us or the best was available we rejected Corbis and we said look if we're gonna go this direction and one of my developers found web methods found philip merrick it was literally at the time working out of his garage and had this technology that was going to allow us to start moving into this object-oriented approach and I remember the day Robin Vasan form a field called and said hey I'm thinking about investing in web methods what do you think about it and not only was it one of the first startups that I ever worked with but it's actually the first time I met anybody in the venture community way back in nineteen I think 1997 is what had happened and that was a computing time in computer science and then the rest is history and then XML became what it became lingua franca for the web web services now Amazon Web Services you see in cloud computing micro services kubernetes service meshes this is a new stack that's being developed in the cloud and this is the new generation you've seen many waves and at Procter & Gamble formerly coca-cola you're the same role you have to navigate this so what's different now what's different say 15 20 years ago how are you looking at this market how you implementing some of the IT and infrastructure and software development environments I think what's change is you know when we got into the the early 2000s Nicolas car came out and said IT doesn't matter and I think anybody that was an IT had this very objectionable response initially but when you step back and you looked at it what she realised was in many cases IT didn't matter and those were those areas that were non-competitive those things that could be commoditized and it was completely right the reality is IT has always mattered that technology does give you a competitive advantage in certain markets and certain capabilities for a company but back then we had to go out and we had to purchase equipment we had to configure the equipment there was a lot of heavy lifting in corporations just did not want to invest the capital so they outsource the stuff wholesale I think General Motors was the first one that just out sourced everything and was followed by other companies including Procter & Gamble the decision at that time was probably right but as we go forward and we see what's happened with corporations we see the valuations of corporations the amount of return on equity based on the on the capital that's being invested we can see that data is important we can see that agility flexibility is key to competing in the future and therefore what's changing is we are now moving into an age of away from ERP so we're moving into an age away from these outsource providers on a wholesale basis and using it selectively to drive down costs and allowing us to free up money in order to invest in those things that are most important to the company so you're saying is that the folks naturally the server consolidation they've bought all this gear all this software over you know 18-month rollouts before they even see the first implementation those are the glory days of gravy trains for the vendor's yeah not good for the practitioners but you're saying that the folks who reinvested are investing in IT as a core competency are seeing a competitive advantage they certainly are you know I think I made the statement front of a number of the vendors and a few years ago and people were not comfortable with it but what I said was like you gone are the ears of these 10 20 million dollar deals gone are the ears of the million two million dollar deals we're in the ear of throwaway technology I need to be able to use and invest in technology for a specific purpose for a specific period of time and be able to move on to the next one it's the perfect time for startups but startups shouldn't be looking at the big picture they should be looking at the tail on these investments let me try things let me get out in the market let me have a competitive advantage in marketing which is most important to me or in supply chain those are the areas that I can make a difference with my consumers and my customers and that's where the investments have to go so just in constant of throwaway technology and you know you'd also be said of you know being more agile though interesting to look at the cloud SAS business model if Amazon for us I think that's the gold standard where they actually lower prices on a per unit basis and increase more services and value but in the aggregate you're still paying more but you have more flexibility and that's kind of a good tell sign so that you're seeing that ability to reuse either the infrastructure that's commoditized to shift the value this is are people having a hard time understanding this so I want to get your reaction to how should I tea leaders understand that the wave of cloud the wave of machine learning what a I can bring to the table these new trends how how should leaders figure this out is there a playbook as there are things that you've learned that you could share you know that there's really a playbook it's still early on everyone's looking for one cloud fits all the reality is whether it's Google whether it's Amazon whether it's Microsoft whether it's IBM all clouds are different all clouds have our special are purpose-built for different solutions and I think as an IT leader you have to understand you're not going to take everything and lift and shift that's what we used to do we're now in the position where we have to deconstruct our business we have to understand the services the capabilities that we want to bring to market and not lock ourselves in its building blocks its Legos we're in the period of Legos putting these things together in different manners in order to create new solutions if we try to lock ourselves in the past of how we've always financed things how we've always built things then we're not going to be any better off in the new world than we were in the old alan i want to get your reaction to to two words our PA and containers well as i said earlier our PA is 3270 emulation from the 1980s and for those of us that are old enough to remember that i I still remember scraping the the old green screens and and putting a little process around it it what's nice though is that we have moved forward machine learning and AI and other other capabilities are now present so that we can do this I actually played around with neural nets probably back in 1985 with an Apollo computer so that tells you how far back I go but technologies change processing speeds change everything the technology trends are allowing us to now to do these things the question that we have is also a moral dilemma is are we trying to replace people or are we trying to make improvements and I think that you don't look at our PA as a way simply to replace work it's a way to enhance what we're doing in order to create new value for the customer or for the consumer in our case I think in the in the area of containers you know again been around for a while been around for a while it's just another another approach that we're not we don't want lock in we don't want to be dependent on specific vendors we want the portability we want the flexibility and I think as we start moving containers out to the edge that's where we're gonna start seeing more value as the business processes and the capabilities are spread out again the idea of centralized cloud computing is very good however it doesn't need to be distributed what's interesting I find about the conversation here is that you mentioned a couple things earlier you mentioned the vendors locking you in and saying here's the ERP buy this and with this you have to have a certain process because this is our technology you got to use it this way and you were slave to their their tech on your process serve their tech with containers and say orchestration you now the ability to manage workloads differently and so an interesting time there's that does that change the notion of rip and replace lift and shift because if I a container I could just put a container around it and not have to worry about killing the old to bring in the new this is on the fundamental kind of debate going on do you have to kill the old to bring in the new well you need to kill the old sometimes just because it's old it's time to go other times you do need to repackage it and other times I hate to say it you do need to lift and shift if you're a legacy organization they have a long history such as most of the manufacturing companies in the world today we can't get rid of old things that quickly we can't afford to a lot of the processes are still valid as we're looking to the future we certainly are breaking these things down into services we're looking to containerize these things we're looking to move them into areas where we can compute where we want to when we want to at the right price we're just at the beginning of that journey in the industry I still think there's about five to seven years to go to get there now I'll talk about the role of the edge role of cloud computing as it increases the surface area of IT potentially combined with the fact that IT is a competitive advantage bring those two notions together what's the role of the people because you used to have people that would just manage the rack and stack I'm provisioning some storage I'm doing this as those stovepipes start to be broken down when the service area of IT is bigger how does that change the relationship of the people involved you know you win with people at the end of the day you don't win with technology you know a company of such as Proctor and Gamble and I think what's happened if you look at historically the ERP vendors came out probably 99 2000 and it used to be and remember these I'm old to be honest with you but I remember that we used to have to worry about the amount of memory we were managing we had to be able to tune databases in all of this and the vendors went ahead and they started automating all those processes with the idea that we can do it better than a human and a lot of people a lot of the technology talent then started leaving the organizations and organizations were left with people that we're focusing on process and people a process excuse me process and the the the business which is very good because you need the subject matter experts going forward we have to reinvest in people our people have the subject matter expertise they have some technology skills that they've developed over the years and they've enhanced it on their own but we're in this huge change right now where we have to think different we have to act different and we have to behave differently so doubling down on people is the best thing that you can do and the old outsource model of outsourcing everything kind of reduces the core competency of the people yeah now you got to build it back up again exactly I mean we when we left at P&G 15 years ago about 5,000 people left the organization when we outsource them when we outsource the technology to our partner at that time now it's time we're starting to bring it back in we've brought the network team back in and stood up our own sock in our own NOC for the first time in years just this past year we're doing the same thing by moving things out to the cloud more and more is moving to the cloud we're setting up our own cloud operations and DevOps capabilities I can tell you having been on both sides of it it's a lot harder to be able to bring it back in than it is to take it out and you know interesting proctoring games well known as being a very intimate with the data very data-driven company the data is valuable and having that infrastructure NIT to support the data that's important what's your vision on the data future of the data in the world well I think data is has a value to itself but when you tie it to products you tie it to your customers and consumers it's even more valuable and we're in the process now of things that we used to do completely internally with our own technology or technology partners we're now moving all of that out into the cloud now and I must say cloud its clouds plural again going back to certain clouds are better for certain things so you're seeing a dramatic shift we have a number of projects underway that are in the cloud space but for customers and consumers number of cloud projects in the way for our own internal employees it's all about collecting the data processing the data protecting that data because we take that very seriously and being able to use it to make better decisions I want to get your reaction on two points and two quite lines of questioning here because I think it's very relevant on the enterprise side you're a big account for the big whales the old ERP so the big cloud providers so people want to sell you stuff at the same time you're also running IT innovation so you want to play with the new shiny new toys and experiments start up so if startups want to get your attention and big vendors want to sell to you the tables have kind of turned it's been good this is a good it's a good buyers market right now in my opinion so what's your thoughts on that so you know start with the big companies what do they got to do to win you over well they got to look like how they got to engage and for startups how do they get your attention I think the biggest thing for either startup or large companies understanding the company you're dealing with whether it's Procter & Gamble whether it's coca-cola whether it was DHL if you understand how I operate if you understand how decisions are made if you understand how I'm organized that's gonna give you an a competitive advantage now the large corporations understand this because they've been around through the entire journey of computing with these large corporations the startups need to step back and take a look and see where do I add that competitive advantage many times when you're selling to a large corporate you're not selling to a large corporate you're selling two divisions you're selling two functions and that's how you get in I've been working with startups as I said back since web methods and it was just a two-person company but we brought them in for a very specific capability I then took web methods with me when I left DHL I took them to GE when I left GE I took them to ing because I trusted them and they matured along the way I think finding that right individual that has the right need is the key and working it slowly don't think you're gonna close the deal fast if you're start-up know it's gonna take some time and decide if that's in your best interest or not slow things down focus don't try to boil the ocean over too many of them try to boy you're right Jimmy people try to boil the ocean get that win one win will get you another one which will get you another win and that's the best way to succeed get that beachhead Ellen so if you could go back and knowing what you know now and you're breaking into the IT leadership's position looking forward what would you do differently can do a mulligan hey what would you do differently well you know I think one of the one of the dangers of being an innovator in IT is that you really are risk taker and taking risks is counterculture to corporations so I think I would probably try to get by in a little bit more I mean someone once told me that you know you see the force through the trees before anybody else does your problem is you don't bring people along with you so I think I would probably slow down a little bit not in the adoption of technology but I'd probably take more time to build the case to bring people along a lot faster so that they can see it and they can take credit for it and they can move that needle as well yeah always sometimes early adopters and pioneers had the arrows on the back as they say I've had my share now thanks for sharing your experience what's next for you what's the next mountain you're going to climb well I think that as we're looking forward latency is still an issue you know we have to find a way to defeat latency we're not going to do it through basic physics so we're gonna have to change our business models change our technology distribution change everything that we're doing consumers and customers are demanding instant access to enhanced information through AI and m/l right at the point where they want it and that means we're now dealing with milliseconds and nanoseconds of having to make decisions so I'm very interested in looking at how are we going to change consumer behavior and customer behavior by combining a lot of the new technology trends that are underway and we have to do it also with the security in mind now before we security was secondary now as we're seeing with all of the hacks and the malware and everything that's going on in the world we have to go in and think a little bit different about how we're gonna do that so I'm very much engaged in working with a lot of startups I live here in the Silicon Valley I commute to Cincinnati for Procter & Gamble I'm spending time and just flew in from tel-aviv literally an hour ago I'm in the middle of all the technology hotspots trying to find that next big thing and it's a global it's global innovation happens everywhere and anywhere the venture community if you look at the amount of funds it used to be invested out of the Silicon Valley versus the rest of the world it continues to be on a downward trend not because the funding isn't here in the Silicon Valley but because everyone is recognizing that innovation and technology is developed everywhere in the world Alan Bain was the CTO global CTO and IT innovator there at the cube conversation here in San Hill Road I'm John for a year thanks for watching you

Published Date : Nov 5 2018

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Tiffani Bova, Salesforce | CUBEConversation, July 2018


 

(dramatic music) >> Hi I'm Peter Burris, and welcome to another CUBE Conversation from our wonderful Palo Alto studios in beautiful Palo Alto, California. Another great conversation today, this one's especially interesting to me, we've got Tiffani Bova who's the Global Growth and Innovation Evangelist of Salesforce. Just written a book, great book by the way, Growth IQ, I guess it's coming out later in August of 2018. But Tiffani, I want to talk a little bit about something that seems near and dear to your heart, the notion of customer engagement and how that gets turned into business strategy. So, let's start there. What is, in your two and half years at Saleforce, what have you learned about customer engagement and how actionable is it, really? >> Well, you know, Peter, it's a great question 'cause I'd say this, you know, I thought I knew the answer to that question when I stated two and a half years ago and I've had the wonderful pleasure of spending time with customers of ours around the world and now I have a different perspective on what that is. You know, Clayton Christensen wrote that new book, Competing Against Luck and it was all about, sort of, the job that you have to do, right? You're going to go from point A to point B, are you going to catch a taxi or you going to catch an Uber. And what makes the difference if the job is the same, regardless of what you're doing. In my mind, right, it's the experience or the engagement that that particular driver or brand has with the customer that is riding in the back of the car, satisfying the need for the job that needed to be done. And when I started to shift my thinking around it's really this experience layer and this engagement layer of how easy is it, how friction, you could apply it to all kinds of industries now, you know. Whether it's meal delivery, or buying a book or buy, you know, software from someone like Salesforce or consulting or watching this show. It used to be you had to go and watch it live or you'd have to watch it on television, now we have very different ways and means in which you can be engaged. So that has been super exciting to me to see it live and in person as brands are really focusing on this importance of the way in which they engage with, connect with and inspire customers to do things with them as their brand of choice. >> So, as I said, Tiffani, I like the book and there is three or points that really want to draw out. I want to start with the first one though. >> Okay. >> Let's go back to this notion of engagement. >> Yes. >> You make the observation in the book and I also have some, a background, thinking about customer engagement, customer experience but you make a great point in the book that your brand is the promise that you're make to the marketplace. Customer experience is the customer side of the engagement. >> Right. >> It seems as though if there's a significant miss-match between those two, that's the first indication you've got a problem. If your brand promise and what is being experienced are not aligned, that says something, have I got that right? >> Absolutely and what's fascinating about that is many brands feel like they're totally aligned and then in mass, you know, research from all kinds of people whether it's McKenzie or Bain or Gartner or Forester or anybody else, you're seeing this disconnection where the brand thinks it's great and the customer's going, it's not that great. The gap between those two things, unfortunately, even with all the advancements with technology, I feel like it's getting wider, right? Because their still sort of, brands are still sort pushing out what they think is interesting and engaging and customers are going, it's kind of not so much. And so, this really a way and I really dug into it in Growth IQ of how brands can figure out, how do I get closer to that by starting with the customer and working their way back in. I mean, it's a long discussed topic of outside in versus inside out, it's nothing new there but now we have this advancements of technology that actually allow us to know what that outside in is telling us at scale, without having to throw people at the problem. >> Yeah, through data collection and other types of things. >> Absolutely. >> But it all starts with that impedance miss-match. >> Yes. >> And as you said, if businesses don't accept that they have a problem they're not going to change. But that is a measurable, actionable thing. >> Right. >> So, if nothing else, if nobody reads anything else out of the book, just that simple idea that it's not MPV, it's not, you know, other types of measures, your Net Promoter Score or other types of measures but it's, basically, is there that disconnect. So the second thing is is that you've observed how it can be made actionable. Now, you've come up with 10, a recipe, or let's call them 10 ingredients of different ways of thinking about what you might be able to do from a growth standpoint. Now, rather than going through all of them, let's just say that they're there but the thing that's interesting is you've come up with a general framework for how you can imagine putting those things together. You call it context combination sequence, what does that mean? >> It, I think it's, I, when I decided to embark on this journey of writing this book I said, you know, what do I feel has been missing, or what did I notice as a pattern as I was having conversations since I was traveling around and talking to customers. And it wasn't the decision that they make of how they were going to grow that was interesting, it was actually the fact that it was rarely in isolation. It was never a single answer to a very complex problem, it was a combination of a number of things. So, if you're going to launch a new product, like that's going to be your growth strategy, well, are you going to launch it yourself? Are you going to do it with partners? Are you going to launch it direct to consumer online or you going to go into retail? You have to then combine the fact that you want to launch a new product with other things to help you grow. Or if you you're going to say I want to reduce turn, it's not just, well, I'm going to lower a price because that's going to be a reason for people to stay, it's, well wait a second, are the platforms easy to use? Can people open a ticket easily? It's always in combination. >> Do I have visibility into whom I churn? >> And to whom I churn, right? But the first place people fail to start, let's to back to your original question of this gap between what customers expect and what businesses are doing is the context in the market has significantly shifted over the last decade. You could say, well obvious technology advancements but I think far more disruptive than technology is actually the customers themselves demanding more from brands. I want you to be better to the environment. I want you to be better socially. I want you to give me more value for what I'm spending. I want it as a service not as a product. I want it in a monthly bill not a one-time bill. I want to pay usage. Whatever they're saying, the customer has changed the context of the market. And I think that's one of the big triggers in this, so you start with context, what's going on, next is what are you going to combine those efforts with. And then the third thing and equally import is sequence. The order in which you do things actually has implications to the likelihood of success of whatever it is you're doing. If you're going to launch into a new market with a new product, and you don't have the infrastructure for distribution or selling or service in place before you launch the product, probably the wrong order. >> Right. >> Right and so if you need to set up the partnerships and the distribution and support and sales and marketing, support within region or translate things to language or do the things that you need to do to marketing materials or websites before you get there because if you launch, the first impression is gone if it's not a good experience for the customer. >> Yeah, you only have one time to make a first impression. >> You only have one time and it doesn't need to be perfect, but you cannot be just completely off the mark because getting them to come back is more expensive than it would of been had you just taken a pause, gotten it right and launched at the appropriate time. >> And that notion of context is also especially important because you identify something you call timing which is related to sequence in the fact that you have to be very honest about what you can and cannot effect. There are some things you may want to sequencing, you may want to fall the sequence. >> Right. >> But if the market isn't going to respond favorably, tell us a little bit about timing and how context shapes and resets prioritization as it changes as well. >> Yeah so, if you think of somebody like a Netflix, if Netflix had started with streaming and not with DVD mail, you know, in the United States at least, not everybody had bandwidth, it was too expensive, it was in very specific neighborhoods and as bandwidth started to make its way into the households and the cost started to decline, then they could say, well, wait a second, is this the best way to do it or could we potentially stream it and start doing OTT types of services? But they had to wait for the technology as well as the customer to catch up with what was possible. So, had they not done mail and started with streaming, maybe they couldn't of held on long enough. And so, mail was a great way to do, I'm going to capture these customers, I'm going to penetrate this base, get them to order more movies and do more things with me. Now I'm going to introduce streaming. Now I have this base of customers which now may want to transition to a new kind of delivery or experience that they want to have with us. And you might be surprised that they still have hundreds of thousands of mail customer including my mom, she still gets DVDs in the mail. And it's a huge profit engine for them, actually allows them to reinvest in the business to expand the streaming services other places in the world which may never get mail service, right. But in the beachhead of it and just let the customers churn out, never getting rid of it, not marketing it but not getting rid of it. So, had those timings been offered different, they may not have been as successful. So, it really has implications to think about what is the customer looking for, what is the temperature socially, what can technology help me deliver? Putting those things together and going, knowing what I know, I don't need it to be perfect but I'm willing to test it and fail and iterate and keep going as long as I keep that context of the market in mind and then the customer, you know, as sort of my true north of making sure that I'm aligning those things again, like we were talking about. >> So let me see if I can summarize that, so you got to get the context, which is-- >> Yes. >> What's really in the marketplace, customer, regulatory, competitor, all those other thing we think about. >> All those things. >> You think about the combination of recipes or combination of responses and then how you're going to sequence them out. Then that sequencing decision then goes back and says and what do I need to redefine about my understanding of context. >> That's right, that's right. >> So I got that right? >> You've got that right and I would tell you that-- >> So your avoiding boiling the ocean. >> Yeah, and that's what always, sort of, when I was trying to figure out what did I want to say in this book. I did not want it to be a boil of the ocean. I picked 10 paths to growth, none of which I think will be a surprise to anybody. It's a modernization on what Ansoff had done around the Ansoff four, there's that. There are things that now we have at our disposal which we didn't have at our disposal in 1957 when Ansoff came out. >> Yeah. >> I mean, so, you have to obviously introduce new things. So like, just using something like socially conscious enterprise was not something we were talking about 10 years ago. >> Right. >> But it's being used as a growth path now. And so, I wanted to try to give 10 very distinct growth paths so that people didn't feel overwhelmed by the hundreds of choices they could make. So if I could get it to something that was digestible and then say now, how do I put those things together. So I made natural associations between paths so that people would say, oh, if I'm going to do product and customer diversification, I might need to do partnerships. If I have a churn problem, I may need to optimize sales. Those two things fit together, right? If I'm going to, customer experience is at the foundation of everything. >> Right. >> Right, and so I tried to tell the story that people could say, oh, we're already on this path, should be stay on this path? Is it the right path? Should we be moving? Am I doing everything I could be doing to make this path be more effective? And that's what I was hoping to get out this is that I don't want people to think this is something completely flip the chessboard over and start from scratch. >> Right. >> I want you to pivot ever so slowly and make adjustments in real time so that you're not having to do, this is kind of an evolutionary versus revolutionary kind of transformation. >> Yeah, the strategies that seem to work today, or feature three things and kind of comes from Cluetrain Manifesto, agile, the empirical, they're based on data, they're optimistic, they identify what really can be done and their irritative, they take smaller steps when they do that. >> Yes. >> So, let me return back to kind of the notion of engagement, just for a second. >> Sure. >> One of the reasons why this book has so much prescriptive power is because there is a dramatic shift globally in market power. It used to be the sellers had the market power and therefore the information at your disposal that you used to make a decision largely came from the sellers and now, you're able to move into communities where buyers can come together and identify themselves in each other and use that source of information to help you make decisions. Very, very significant and profound shift and that's in many respects what's driving experience. Historically though, we've talked about sales and marketing alignment. (Tiffani laughing) About how we got to get the right message out, we got to enable sales in the right way. But customers spend most of their time with a brand in the form of a product or service which suggests that he whole notion of customer service and sustaining alignment between expectations and actuality in the customer service function becomes especially important. Have I got that right? >> You nailed it, I mean, I would say also you know, and I'm actually a practitioner before I was at Gartner, so I actually ran a division of Gateway computers, I ran sales and marketing for them. Before that I worked in web hosting company, we were the largest web hoster in the United States, we were actually four times the size of Rackspace. I was the beta client for ALOQUA, I was the beta client for Constant Contact. I was socially selling in 2000. Our shared property is web.com, if you watch golf. And so I was super early, so I'm actually a sales, I sort of say I'm a recovering seller, I bleed sales blood. (Peter laughing) And so when I was running both sales and marketing, I could argue with myself. But when I was just selling, you know, I understand this, you know, marketing giving us leads, sales not doing something with it. Then when I had customer service, you know, those three things together, I think today, is where companies really miss an opportunity. That just getting new customers in the door and it's so much more expensive to recruit new customers and to pay to get them versus just mining the gold you've already got. So, that is something that I'd say over the last two and a half years now that I'm here and I see it at scale that I will have conversations with CMOs and heads of sales and then the head of customer service is not in the room or it's just marketing and sales. So the same way marketing enables sales, they need to enable customer service. >> And, very importantly, the information that is being generated out of customer service-- >> Absolutely. >> Need to enable sales and marketing. >> Absolutely-- >> And in products. >> So I would tell you that in my opinion, the disconnection between what customers expect and businesses are doing actually is a manifestation of the unintentional consequence of the disconnection of teams because of the disconnection of metrics. Sales is very much, like how much did you sell? I mean, I'm over simplifying but how much did you sell. Marketing, how many leads did you, good or bad, how many leads? Customer service, how quickly did you get someone off the phone and how many calls did, tickets did you close today? Those three things pull those three groups in very different directions. So, something like a Net Promoter Score or churn or lifetime values, something can thread those three groups together in a metric so that people know that they're all in this together even though they play different roles. And so, I think the fact that people try to own customer experience worries me because I think the whole company has to be very focused on... >> It's a CEO job. >> But then it's a cultural shift, right? >> Absolutely. >> It's about culture, it's about this customer wants to have me help their problem but I have to get off the phone in two minutes because that's my quota and so do I get off the phone in two minutes or do I help my customer? >> Okay, let me make one quick comment and I'm going to ask you one last question. >> Yeah. >> And the quick comment I'll make is very prominent CEO of a very, very large computing company once said to me, I asked this person, 'cause I thought that they had won large because of marketing. And I said, so, tell me about he role of marketing within your company. And this person said to me, oh, marketing is what I put between engineering and sales so they don't kill each other. (Tiffani laughing) And I think that needs, obviously that orientation needs to change. But the last thing I wanted to talk about is one of the patterns you noted is disruption or disruptive-- >> Yes. >> I don't remember exactly what you called it but it boiled down, it could mean a lot of things, but you specifically focused on and you've already mentioned it, social good. >> Yep. >> As part of a strategy, give us a, you know 30 second, 44 second, why is social good becoming a viable strategy or viable pattern, one of the combinations that's working today? >> Well, I'd say, Salesforce was founded on the 1-1-1 model, which was very much about sort of this doing well by doing good, or doing good by doing good. But I would say this that even if you've watched television commercials over the last year, especially since Super Bowl last year, you'll see brands actually making statements about how they do well for the environment, how they're giving back, how they're hiring veterans, how they're doing things for... You know, Starbucks just announced they're going to- >> How they're willing to fly immigrant children home if they need to. >> Yeah, Starbucks is not doing a Starbucks in DC that will be signing so for hearing impaired. So you see people really making pivots and actually using that as I'm trying to connect with my constituency and my customer base in a new and different way. I love the fact that social consciousness is now getting into Unilever and getting into, you know the 1-1-1 model spread across 3,000 companies now. Or the Tom's model, one for one, buy a shoe, a shoe gets donated. You see it happening with a lot of start ups now where they're trying to start the company that way. Now, if you have a company that didn't start that way, there's not reason why you can't start to find a place where you can inject it going forward. But I'm super excited about that. >> Tiffani Bova, Global Growth Innovation Evangelist Salesforce, talking about the book Growth IQ. Again, great book. >> Thank you. >> Very prescriptive and I mean, I generally hate business books, lot of case studies. Thanks very much for being on theCUBE. >> Thank you for having me, peter, it's been a pleasure. >> Absolutely, so once again, thanks for participating in our CUBE Conversation and until the next one, we'll see you soon. (dramatic music)

Published Date : Jul 31 2018

SUMMARY :

what have you learned about customer engagement sort of, the job that you have to do, right? and there is three or points that really want to draw out. but you make a great point in the book are not aligned, that says something, have I got that right? and then in mass, you know, research from that they have a problem they're not going to change. what you might be able to do from a growth standpoint. I said, you know, what do I feel has been missing, I want you to be better to the environment. or do the things that you need to do but you cannot be just completely off the mark you have to be very honest about what you can But if the market isn't going to respond favorably, and not with DVD mail, you know, What's really in the marketplace, and what do I need to redefine Yeah, and that's what always, sort of, I mean, so, you have to obviously introduce new things. So if I could get it to something that was digestible Is it the right path? I want you to pivot ever so slowly Yeah, the strategies that seem to work today, So, let me return back to kind of to help you make decisions. and it's so much more expensive to recruit new customers I mean, I'm over simplifying but how much did you sell. and I'm going to ask you one last question. is one of the patterns you noted is disruption I don't remember exactly what you called it television commercials over the last year, if they need to. there's not reason why you can't start to find a place talking about the book Growth IQ. I generally hate business books, and until the next one, we'll see you soon.

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Data Science for All: It's a Whole New Game


 

>> There's a movement that's sweeping across businesses everywhere here in this country and around the world. And it's all about data. Today businesses are being inundated with data. To the tune of over two and a half million gigabytes that'll be generated in the next 60 seconds alone. What do you do with all that data? To extract insights you typically turn to a data scientist. But not necessarily anymore. At least not exclusively. Today the ability to extract value from data is becoming a shared mission. A team effort that spans the organization extending far more widely than ever before. Today, data science is being democratized. >> Data Sciences for All: It's a Whole New Game. >> Welcome everyone, I'm Katie Linendoll. I'm a technology expert writer and I love reporting on all things tech. My fascination with tech started very young. I began coding when I was 12. Received my networking certs by 18 and a degree in IT and new media from Rochester Institute of Technology. So as you can tell, technology has always been a sure passion of mine. Having grown up in the digital age, I love having a career that keeps me at the forefront of science and technology innovations. I spend equal time in the field being hands on as I do on my laptop conducting in depth research. Whether I'm diving underwater with NASA astronauts, witnessing the new ways which mobile technology can help rebuild the Philippine's economy in the wake of super typhoons, or sharing a first look at the newest iPhones on The Today Show, yesterday, I'm always on the hunt for the latest and greatest tech stories. And that's what brought me here. I'll be your host for the next hour and as we explore the new phenomenon that is taking businesses around the world by storm. And data science continues to become democratized and extends beyond the domain of the data scientist. And why there's also a mandate for all of us to become data literate. Now that data science for all drives our AI culture. And we're going to be able to take to the streets and go behind the scenes as we uncover the factors that are fueling this phenomenon and giving rise to a movement that is reshaping how businesses leverage data. And putting organizations on the road to AI. So coming up, I'll be doing interviews with data scientists. We'll see real world demos and take a look at how IBM is changing the game with an open data science platform. We'll also be joined by legendary statistician Nate Silver, founder and editor-in-chief of FiveThirtyEight. Who will shed light on how a data driven mindset is changing everything from business to our culture. We also have a few people who are joining us in our studio, so thank you guys for joining us. Come on, I can do better than that, right? Live studio audience, the fun stuff. And for all of you during the program, I want to remind you to join that conversation on social media using the hashtag DSforAll, it's data science for all. Share your thoughts on what data science and AI means to you and your business. And, let's dive into a whole new game of data science. Now I'd like to welcome my co-host General Manager IBM Analytics, Rob Thomas. >> Hello, Katie. >> Come on guys. >> Yeah, seriously. >> No one's allowed to be quiet during this show, okay? >> Right. >> Or, I'll start calling people out. So Rob, thank you so much. I think you know this conversation, we're calling it a data explosion happening right now. And it's nothing new. And when you and I chatted about it. You've been talking about this for years. You have to ask, is this old news at this point? >> Yeah, I mean, well first of all, the data explosion is not coming, it's here. And everybody's in the middle of it right now. What is different is the economics have changed. And the scale and complexity of the data that organizations are having to deal with has changed. And to this day, 80% of the data in the world still sits behind corporate firewalls. So, that's becoming a problem. It's becoming unmanageable. IT struggles to manage it. The business can't get everything they need. Consumers can't consume it when they want. So we have a challenge here. >> It's challenging in the world of unmanageable. Crazy complexity. If I'm sitting here as an IT manager of my business, I'm probably thinking to myself, this is incredibly frustrating. How in the world am I going to get control of all this data? And probably not just me thinking it. Many individuals here as well. >> Yeah, indeed. Everybody's thinking about how am I going to put data to work in my organization in a way I haven't done before. Look, you've got to have the right expertise, the right tools. The other thing that's happening in the market right now is clients are dealing with multi cloud environments. So data behind the firewall in private cloud, multiple public clouds. And they have to find a way. How am I going to pull meaning out of this data? And that brings us to data science and AI. That's how you get there. >> I understand the data science part but I think we're all starting to hear more about AI. And it's incredible that this buzz word is happening. How do businesses adopt to this AI growth and boom and trend that's happening in this world right now? >> Well, let me define it this way. Data science is a discipline. And machine learning is one technique. And then AI puts both machine learning into practice and applies it to the business. So this is really about how getting your business where it needs to go. And to get to an AI future, you have to lay a data foundation today. I love the phrase, "there's no AI without IA." That means you're not going to get to AI unless you have the right information architecture to start with. >> Can you elaborate though in terms of how businesses can really adopt AI and get started. >> Look, I think there's four things you have to do if you're serious about AI. One is you need a strategy for data acquisition. Two is you need a modern data architecture. Three is you need pervasive automation. And four is you got to expand job roles in the organization. >> Data acquisition. First pillar in this you just discussed. Can we start there and explain why it's so critical in this process? >> Yeah, so let's think about how data acquisition has evolved through the years. 15 years ago, data acquisition was about how do I get data in and out of my ERP system? And that was pretty much solved. Then the mobile revolution happens. And suddenly you've got structured and non-structured data. More than you've ever dealt with. And now you get to where we are today. You're talking terabytes, petabytes of data. >> [Katie] Yottabytes, I heard that word the other day. >> I heard that too. >> Didn't even know what it meant. >> You know how many zeros that is? >> I thought we were in Star Wars. >> Yeah, I think it's a lot of zeroes. >> Yodabytes, it's new. >> So, it's becoming more and more complex in terms of how you acquire data. So that's the new data landscape that every client is dealing with. And if you don't have a strategy for how you acquire that and manage it, you're not going to get to that AI future. >> So a natural segue, if you are one of these businesses, how do you build for the data landscape? >> Yeah, so the question I always hear from customers is we need to evolve our data architecture to be ready for AI. And the way I think about that is it's really about moving from static data repositories to more of a fluid data layer. >> And we continue with the architecture. New data architecture is an interesting buzz word to hear. But it's also one of the four pillars. So if you could dive in there. >> Yeah, I mean it's a new twist on what I would call some core data science concepts. For example, you have to leverage tools with a modern, centralized data warehouse. But your data warehouse can't be stagnant to just what's right there. So you need a way to federate data across different environments. You need to be able to bring your analytics to the data because it's most efficient that way. And ultimately, it's about building an optimized data platform that is designed for data science and AI. Which means it has to be a lot more flexible than what clients have had in the past. >> All right. So we've laid out what you need for driving automation. But where does the machine learning kick in? >> Machine learning is what gives you the ability to automate tasks. And I think about machine learning. It's about predicting and automating. And this will really change the roles of data professionals and IT professionals. For example, a data scientist cannot possibly know every algorithm or every model that they could use. So we can automate the process of algorithm selection. Another example is things like automated data matching. Or metadata creation. Some of these things may not be exciting but they're hugely practical. And so when you think about the real use cases that are driving return on investment today, it's things like that. It's automating the mundane tasks. >> Let's go ahead and come back to something that you mentioned earlier because it's fascinating to be talking about this AI journey, but also significant is the new job roles. And what are those other participants in the analytics pipeline? >> Yeah I think we're just at the start of this idea of new job roles. We have data scientists. We have data engineers. Now you see machine learning engineers. Application developers. What's really happening is that data scientists are no longer allowed to work in their own silo. And so the new job roles is about how does everybody have data first in their mind? And then they're using tools to automate data science, to automate building machine learning into applications. So roles are going to change dramatically in organizations. >> I think that's confusing though because we have several organizations who saying is that highly specialized roles, just for data science? Or is it applicable to everybody across the board? >> Yeah, and that's the big question, right? Cause everybody's thinking how will this apply? Do I want this to be just a small set of people in the organization that will do this? But, our view is data science has to for everybody. It's about bring data science to everybody as a shared mission across the organization. Everybody in the company has to be data literate. And participate in this journey. >> So overall, group effort, has to be a common goal, and we all need to be data literate across the board. >> Absolutely. >> Done deal. But at the end of the day, it's kind of not an easy task. >> It's not. It's not easy but it's maybe not as big of a shift as you would think. Because you have to put data in the hands of people that can do something with it. So, it's very basic. Give access to data. Data's often locked up in a lot of organizations today. Give people the right tools. Embrace the idea of choice or diversity in terms of those tools. That gets you started on this path. >> It's interesting to hear you say essentially you need to train everyone though across the board when it comes to data literacy. And I think people that are coming into the work force don't necessarily have a background or a degree in data science. So how do you manage? >> Yeah, so in many cases that's true. I will tell you some universities are doing amazing work here. One example, University of California Berkeley. They offer a course for all majors. So no matter what you're majoring in, you have a course on foundations of data science. How do you bring data science to every role? So it's starting to happen. We at IBM provide data science courses through CognitiveClass.ai. It's for everybody. It's free. And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. The key point is this though. It's more about attitude than it is aptitude. I think anybody can figure this out. But it's about the attitude to say we're putting data first and we're going to figure out how to make this real in our organization. >> I also have to give a shout out to my alma mater because I have heard that there is an offering in MS in data analytics. And they are always on the forefront of new technologies and new majors and on trend. And I've heard that the placement behind those jobs, people graduating with the MS is high. >> I'm sure it's very high. >> So go Tigers. All right, tangential. Let me get back to something else you touched on earlier because you mentioned that a number of customers ask you how in the world do I get started with AI? It's an overwhelming question. Where do you even begin? What do you tell them? >> Yeah, well things are moving really fast. But the good thing is most organizations I see, they're already on the path, even if they don't know it. They might have a BI practice in place. They've got data warehouses. They've got data lakes. Let me give you an example. AMC Networks. They produce a lot of the shows that I'm sure you watch Katie. >> [Katie] Yes, Breaking Bad, Walking Dead, any fans? >> [Rob] Yeah, we've got a few. >> [Katie] Well you taught me something I didn't even know. Because it's amazing how we have all these different industries, but yet media in itself is impacted too. And this is a good example. >> Absolutely. So, AMC Networks, think about it. They've got ads to place. They want to track viewer behavior. What do people like? What do they dislike? So they have to optimize every aspect of their business from marketing campaigns to promotions to scheduling to ads. And their goal was transform data into business insights and really take the burden off of their IT team that was heavily burdened by obviously a huge increase in data. So their VP of BI took the approach of using machine learning to process large volumes of data. They used a platform that was designed for AI and data processing. It's the IBM analytics system where it's a data warehouse, data science tools are built in. It has in memory data processing. And just like that, they were ready for AI. And they're already seeing that impact in their business. >> Do you think a movement of that nature kind of presses other media conglomerates and organizations to say we need to be doing this too? >> I think it's inevitable that everybody, you're either going to be playing, you're either going to be leading, or you'll be playing catch up. And so, as we talk to clients we think about how do you start down this path now, even if you have to iterate over time? Because otherwise you're going to wake up and you're going to be behind. >> One thing worth noting is we've talked about analytics to the data. It's analytics first to the data, not the other way around. >> Right. So, look. We as a practice, we say you want to bring data to where the data sits. Because it's a lot more efficient that way. It gets you better outcomes in terms of how you train models and it's more efficient. And we think that leads to better outcomes. Other organization will say, "Hey move the data around." And everything becomes a big data movement exercise. But once an organization has started down this path, they're starting to get predictions, they want to do it where it's really easy. And that means analytics applied right where the data sits. >> And worth talking about the role of the data scientist in all of this. It's been called the hot job of the decade. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. >> Yes. >> I want to see this on the cover of Vogue. Like I want to see the first data scientist. Female preferred, on the cover of Vogue. That would be amazing. >> Perhaps you can. >> People agree. So what changes for them? Is this challenging in terms of we talk data science for all. Where do all the data science, is it data science for everyone? And how does it change everything? >> Well, I think of it this way. AI gives software super powers. It really does. It changes the nature of software. And at the center of that is data scientists. So, a data scientist has a set of powers that they've never had before in any organization. And that's why it's a hot profession. Now, on one hand, this has been around for a while. We've had actuaries. We've had statisticians that have really transformed industries. But there are a few things that are new now. We have new tools. New languages. Broader recognition of this need. And while it's important to recognize this critical skill set, you can't just limit it to a few people. This is about scaling it across the organization. And truly making it accessible to all. >> So then do we need more data scientists? Or is this something you train like you said, across the board? >> Well, I think you want to do a little bit of both. We want more. But, we can also train more and make the ones we have more productive. The way I think about it is there's kind of two markets here. And we call it clickers and coders. >> [Katie] I like that. That's good. >> So, let's talk about what that means. So clickers are basically somebody that wants to use tools. Create models visually. It's drag and drop. Something that's very intuitive. Those are the clickers. Nothing wrong with that. It's been valuable for years. There's a new crop of data scientists. They want to code. They want to build with the latest open source tools. They want to write in Python or R. These are the coders. And both approaches are viable. Both approaches are critical. Organizations have to have a way to meet the needs of both of those types. And there's not a lot of things available today that do that. >> Well let's keep going on that. Because I hear you talking about the data scientists role and how it's critical to success, but with the new tools, data science and analytics skills can extend beyond the domain of just the data scientist. >> That's right. So look, we're unifying coders and clickers into a single platform, which we call IBM Data Science Experience. And as the demand for data science expertise grows, so does the need for these kind of tools. To bring them into the same environment. And my view is if you have the right platform, it enables the organization to collaborate. And suddenly you've changed the nature of data science from an individual sport to a team sport. >> So as somebody that, my background is in IT, the question is really is this an additional piece of what IT needs to do in 2017 and beyond? Or is it just another line item to the budget? >> So I'm afraid that some people might view it that way. As just another line item. But, I would challenge that and say data science is going to reinvent IT. It's going to change the nature of IT. And every organization needs to think about what are the skills that are critical? How do we engage a broader team to do this? Because once they get there, this is the chance to reinvent how they're performing IT. >> [Katie] Challenging or not? >> Look it's all a big challenge. Think about everything IT organizations have been through. Some of them were late to things like mobile, but then they caught up. Some were late to cloud, but then they caught up. I would just urge people, don't be late to data science. Use this as your chance to reinvent IT. Start with this notion of clickers and coders. This is a seminal moment. Much like mobile and cloud was. So don't be late. >> And I think it's critical because it could be so costly to wait. And Rob and I were even chatting earlier how data analytics is just moving into all different kinds of industries. And I can tell you even personally being effected by how important the analysis is in working in pediatric cancer for the last seven years. I personally implement virtual reality headsets to pediatric cancer hospitals across the country. And it's great. And it's working phenomenally. And the kids are amazed. And the staff is amazed. But the phase two of this project is putting in little metrics in the hardware that gather the breathing, the heart rate to show that we have data. Proof that we can hand over to the hospitals to continue making this program a success. So just in-- >> That's a great example. >> An interesting example. >> Saving lives? >> Yes. >> That's also applying a lot of what we talked about. >> Exciting stuff in the world of data science. >> Yes. Look, I just add this is an existential moment for every organization. Because what you do in this area is probably going to define how competitive you are going forward. And think about if you don't do something. What if one of your competitors goes and creates an application that's more engaging with clients? So my recommendation is start small. Experiment. Learn. Iterate on projects. Define the business outcomes. Then scale up. It's very doable. But you've got to take the first step. >> First step always critical. And now we're going to get to the fun hands on part of our story. Because in just a moment we're going to take a closer look at what data science can deliver. And where organizations are trying to get to. All right. Thank you Rob and now we've been joined by Siva Anne who is going to help us navigate this demo. First, welcome Siva. Give him a big round of applause. Yeah. All right, Rob break down what we're going to be looking at. You take over this demo. >> All right. So this is going to be pretty interesting. So Siva is going to take us through. So he's going to play the role of a financial adviser. Who wants to help better serve clients through recommendations. And I'm going to really illustrate three things. One is how do you federate data from multiple data sources? Inside the firewall, outside the firewall. How do you apply machine learning to predict and to automate? And then how do you move analytics closer to your data? So, what you're seeing here is a custom application for an investment firm. So, Siva, our financial adviser, welcome. So you can see at the top, we've got market data. We pulled that from an external source. And then we've got Siva's calendar in the middle. He's got clients on the right side. So page down, what else do you see down there Siva? >> [Siva] I can see the recent market news. And in here I can see that JP Morgan is calling for a US dollar rebound in the second half of the year. And, I have upcoming meeting with Leo Rakes. I can get-- >> [Rob] So let's go in there. Why don't you click on Leo Rakes. So, you're sitting at your desk, you're deciding how you're going to spend the day. You know you have a meeting with Leo. So you click on it. You immediately see, all right, so what do we know about him? We've got data governance implemented. So we know his age, we know his degree. We can see he's not that aggressive of a trader. Only six trades in the last few years. But then where it gets interesting is you go to the bottom. You start to see predicted industry affinity. Where did that come from? How do we have that? >> [Siva] So these green lines and red arrows here indicate the trending affinity of Leo Rakes for particular industry stocks. What we've done here is we've built machine learning models using customer's demographic data, his stock portfolios, and browsing behavior to build a model which can predict his affinity for a particular industry. >> [Rob] Interesting. So, I like to think of this, we call it celebrity experiences. So how do you treat every customer like they're a celebrity? So to some extent, we're reading his mind. Because without asking him, we know that he's going to have an affinity for auto stocks. So we go down. Now we look at his portfolio. You can see okay, he's got some different holdings. He's got Amazon, Google, Apple, and then he's got RACE, which is the ticker for Ferrari. You can see that's done incredibly well. And so, as a financial adviser, you look at this and you say, all right, we know he loves auto stocks. Ferrari's done very well. Let's create a hedge. Like what kind of security would interest him as a hedge against his position for Ferrari? Could we go figure that out? >> [Siva] Yes. Given I know that he's gotten an affinity for auto stocks, and I also see that Ferrari has got some terminus gains, I want to lock in these gains by hedging. And I want to do that by picking a auto stock which has got negative correlation with Ferrari. >> [Rob] So this is where we get to the idea of in database analytics. Cause you start clicking that and immediately we're getting instant answers of what's happening. So what did we find here? We're going to compare Ferrari and Honda. >> [Siva] I'm going to compare Ferrari with Honda. And what I see here instantly is that Honda has got a negative correlation with Ferrari, which makes it a perfect mix for his stock portfolio. Given he has an affinity for auto stocks and it correlates negatively with Ferrari. >> [Rob] These are very powerful tools at the hand of a financial adviser. You think about it. As a financial adviser, you wouldn't think about federating data, machine learning, pretty powerful. >> [Siva] Yes. So what we have seen here is that using the common SQL engine, we've been able to federate queries across multiple data sources. Db2 Warehouse in the cloud, IBM's Integrated Analytic System, and Hortonworks powered Hadoop platform for the new speeds. We've been able to use machine learning to derive innovative insights about his stock affinities. And drive the machine learning into the appliance. Closer to where the data resides to deliver high performance analytics. >> [Rob] At scale? >> [Siva] We're able to run millions of these correlations across stocks, currency, other factors. And even score hundreds of customers for their affinities on a daily basis. >> That's great. Siva, thank you for playing the role of financial adviser. So I just want to recap briefly. Cause this really powerful technology that's really simple. So we federated, we aggregated multiple data sources from all over the web and internal systems. And public cloud systems. Machine learning models were built that predicted Leo's affinity for a certain industry. In this case, automotive. And then you see when you deploy analytics next to your data, even a financial adviser, just with the click of a button is getting instant answers so they can go be more productive in their next meeting. This whole idea of celebrity experiences for your customer, that's available for everybody, if you take advantage of these types of capabilities. Katie, I'll hand it back to you. >> Good stuff. Thank you Rob. Thank you Siva. Powerful demonstration on what we've been talking about all afternoon. And thank you again to Siva for helping us navigate. Should be give him one more round of applause? We're going to be back in just a moment to look at how we operationalize all of this data. But in first, here's a message from me. If you're a part of a line of business, your main fear is disruption. You know data is the new goal that can create huge amounts of value. So does your competition. And they may be beating you to it. You're convinced there are new business models and revenue sources hidden in all the data. You just need to figure out how to leverage it. But with the scarcity of data scientists, you really can't rely solely on them. You may need more people throughout the organization that have the ability to extract value from data. And as a data science leader or data scientist, you have a lot of the same concerns. You spend way too much time looking for, prepping, and interpreting data and waiting for models to train. You know you need to operationalize the work you do to provide business value faster. What you want is an easier way to do data prep. And rapidly build models that can be easily deployed, monitored and automatically updated. So whether you're a data scientist, data science leader, or in a line of business, what's the solution? What'll it take to transform the way you work? That's what we're going to explore next. All right, now it's time to delve deeper into the nuts and bolts. The nitty gritty of operationalizing data science and creating a data driven culture. How do you actually do that? Well that's what these experts are here to share with us. I'm joined by Nir Kaldero, who's head of data science at Galvanize, which is an education and training organization. Tricia Wang, who is co-founder of Sudden Compass, a consultancy that helps companies understand people with data. And last, but certainly not least, Michael Li, founder and CEO of Data Incubator, which is a data science train company. All right guys. Shall we get right to it? >> All right. >> So data explosion happening right now. And we are seeing it across the board. I just shared an example of how it's impacting my philanthropic work in pediatric cancer. But you guys each have so many unique roles in your business life. How are you seeing it just blow up in your fields? Nir, your thing? >> Yeah, for example like in Galvanize we train many Fortune 500 companies. And just by looking at the demand of companies that wants us to help them go through this digital transformation is mind-blowing. Data point by itself. >> Okay. Well what we're seeing what's going on is that data science like as a theme, is that it's actually for everyone now. But what's happening is that it's actually meeting non technical people. But what we're seeing is that when non technical people are implementing these tools or coming at these tools without a base line of data literacy, they're often times using it in ways that distance themselves from the customer. Because they're implementing data science tools without a clear purpose, without a clear problem. And so what we do at Sudden Compass is that we work with companies to help them embrace and understand the complexity of their customers. Because often times they are misusing data science to try and flatten their understanding of the customer. As if you can just do more traditional marketing. Where you're putting people into boxes. And I think the whole ROI of data is that you can now understand people's relationships at a much more complex level at a greater scale before. But we have to do this with basic data literacy. And this has to involve technical and non technical people. >> Well you can have all the data in the world, and I think it speaks to, if you're not doing the proper movement with it, forget it. It means nothing at the same time. >> No absolutely. I mean, I think that when you look at the huge explosion in data, that comes with it a huge explosion in data experts. Right, we call them data scientists, data analysts. And sometimes they're people who are very, very talented, like the people here. But sometimes you have people who are maybe re-branding themselves, right? Trying to move up their title one notch to try to attract that higher salary. And I think that that's one of the things that customers are coming to us for, right? They're saying, hey look, there are a lot of people that call themselves data scientists, but we can't really distinguish. So, we have sort of run a fellowship where you help companies hire from a really talented group of folks, who are also truly data scientists and who know all those kind of really important data science tools. And we also help companies internally. Fortune 500 companies who are looking to grow that data science practice that they have. And we help clients like McKinsey, BCG, Bain, train up their customers, also their clients, also their workers to be more data talented. And to build up that data science capabilities. >> And Nir, this is something you work with a lot. A lot of Fortune 500 companies. And when we were speaking earlier, you were saying many of these companies can be in a panic. >> Yeah. >> Explain that. >> Yeah, so you know, not all Fortune 500 companies are fully data driven. And we know that the winners in this fourth industrial revolution, which I like to call the machine intelligence revolution, will be companies who navigate and transform their organization to unlock the power of data science and machine learning. And the companies that are not like that. Or not utilize data science and predictive power well, will pretty much get shredded. So they are in a panic. >> Tricia, companies have to deal with data behind the firewall and in the new multi cloud world. How do organizations start to become driven right to the core? >> I think the most urgent question to become data driven that companies should be asking is how do I bring the complex reality that our customers are experiencing on the ground in to a corporate office? Into the data models. So that question is critical because that's how you actually prevent any big data disasters. And that's how you leverage big data. Because when your data models are really far from your human models, that's when you're going to do things that are really far off from how, it's going to not feel right. That's when Tesco had their terrible big data disaster that they're still recovering from. And so that's why I think it's really important to understand that when you implement big data, you have to further embrace thick data. The qualitative, the emotional stuff, that is difficult to quantify. But then comes the difficult art and science that I think is the next level of data science. Which is that getting non technical and technical people together to ask how do we find those unknown nuggets of insights that are difficult to quantify? Then, how do we do the next step of figuring out how do you mathematically scale those insights into a data model? So that actually is reflective of human understanding? And then we can start making decisions at scale. But you have to have that first. >> That's absolutely right. And I think that when we think about what it means to be a data scientist, right? I always think about it in these sort of three pillars. You have the math side. You have to have that kind of stats, hardcore machine learning background. You have the programming side. You don't work with small amounts of data. You work with large amounts of data. You've got to be able to type the code to make those computers run. But then the last part is that human element. You have to understand the domain expertise. You have to understand what it is that I'm actually analyzing. What's the business proposition? And how are the clients, how are the users actually interacting with the system? That human element that you were talking about. And I think having somebody who understands all of those and not just in isolation, but is able to marry that understanding across those different topics, that's what makes a data scientist. >> But I find that we don't have people with those skill sets. And right now the way I see teams being set up inside companies is that they're creating these isolated data unicorns. These data scientists that have graduated from your programs, which are great. But, they don't involve the people who are the domain experts. They don't involve the designers, the consumer insight people, the people, the salespeople. The people who spend time with the customers day in and day out. Somehow they're left out of the room. They're consulted, but they're not a stakeholder. >> Can I actually >> Yeah, yeah please. >> Can I actually give a quick example? So for example, we at Galvanize train the executives and the managers. And then the technical people, the data scientists and the analysts. But in order to actually see all of the RY behind the data, you also have to have a creative fluid conversation between non technical and technical people. And this is a major trend now. And there's a major gap. And we need to increase awareness and kind of like create a new, kind of like environment where technical people also talks seamlessly with non technical ones. >> [Tricia] We call-- >> That's one of the things that we see a lot. Is one of the trends in-- >> A major trend. >> data science training is it's not just for the data science technical experts. It's not just for one type of person. So a lot of the training we do is sort of data engineers. People who are more on the software engineering side learning more about the stats of math. And then people who are sort of traditionally on the stat side learning more about the engineering. And then managers and people who are data analysts learning about both. >> Michael, I think you said something that was of interest too because I think we can look at IBM Watson as an example. And working in healthcare. The human component. Because often times we talk about machine learning and AI, and data and you get worried that you still need that human component. Especially in the world of healthcare. And I think that's a very strong point when it comes to the data analysis side. Is there any particular example you can speak to of that? >> So I think that there was this really excellent paper a while ago talking about all the neuro net stuff and trained on textual data. So looking at sort of different corpuses. And they found that these models were highly, highly sexist. They would read these corpuses and it's not because neuro nets themselves are sexist. It's because they're reading the things that we write. And it turns out that we write kind of sexist things. And they would sort of find all these patterns in there that were sort of latent, that had a lot of sort of things that maybe we would cringe at if we sort of saw. And I think that's one of the really important aspects of the human element, right? It's being able to come in and sort of say like, okay, I know what the biases of the system are, I know what the biases of the tools are. I need to figure out how to use that to make the tools, make the world a better place. And like another area where this comes up all the time is lending, right? So the federal government has said, and we have a lot of clients in the financial services space, so they're constantly under these kind of rules that they can't make discriminatory lending practices based on a whole set of protected categories. Race, sex, gender, things like that. But, it's very easy when you train a model on credit scores to pick that up. And then to have a model that's inadvertently sexist or racist. And that's where you need the human element to come back in and say okay, look, you're using the classic example would be zip code, you're using zip code as a variable. But when you look at it, zip codes actually highly correlated with race. And you can't do that. So you may inadvertently by sort of following the math and being a little naive about the problem, inadvertently introduce something really horrible into a model and that's where you need a human element to sort of step in and say, okay hold on. Slow things down. This isn't the right way to go. >> And the people who have -- >> I feel like, I can feel her ready to respond. >> Yes, I'm ready. >> She's like let me have at it. >> And the people here it is. And the people who are really great at providing that human intelligence are social scientists. We are trained to look for bias and to understand bias in data. Whether it's quantitative or qualitative. And I really think that we're going to have less of these kind of problems if we had more integrated teams. If it was a mandate from leadership to say no data science team should be without a social scientist, ethnographer, or qualitative researcher of some kind, to be able to help see these biases. >> The talent piece is actually the most crucial-- >> Yeah. >> one here. If you look about how to enable machine intelligence in organization there are the pillars that I have in my head which is the culture, the talent and the technology infrastructure. And I believe and I saw in working very closely with the Fortune 100 and 200 companies that the talent piece is actually the most important crucial hard to get. >> [Tricia] I totally agree. >> It's absolutely true. Yeah, no I mean I think that's sort of like how we came up with our business model. Companies were basically saying hey, I can't hire data scientists. And so we have a fellowship where we get 2,000 applicants each quarter. We take the top 2% and then we sort of train them up. And we work with hiring companies who then want to hire from that population. And so we're sort of helping them solve that problem. And the other half of it is really around training. Cause with a lot of industries, especially if you're sort of in a more regulated industry, there's a lot of nuances to what you're doing. And the fastest way to develop that data science or AI talent may not necessarily be to hire folks who are coming out of a PhD program. It may be to take folks internally who have a lot of that domain knowledge that you have and get them trained up on those data science techniques. So we've had large insurance companies come to us and say hey look, we hire three or four folks from you a quarter. That doesn't move the needle for us. What we really need is take the thousand actuaries and statisticians that we have and get all of them trained up to become a data scientist and become data literate in this new open source world. >> [Katie] Go ahead. >> All right, ladies first. >> Go ahead. >> Are you sure? >> No please, fight first. >> Go ahead. >> Go ahead Nir. >> So this is actually a trend that we have been seeing in the past year or so that companies kind of like start to look how to upscale and look for talent within the organization. So they can actually move them to become more literate and navigate 'em from analyst to data scientist. And from data scientist to machine learner. So this is actually a trend that is happening already for a year or so. >> Yeah, but I also find that after they've gone through that training in getting people skilled up in data science, the next problem that I get is executives coming to say we've invested in all of this. We're still not moving the needle. We've already invested in the right tools. We've gotten the right skills. We have enough scale of people who have these skills. Why are we not moving the needle? And what I explain to them is look, you're still making decisions in the same way. And you're still not involving enough of the non technical people. Especially from marketing, which is now, the CMO's are much more responsible for driving growth in their companies now. But often times it's so hard to change the old way of marketing, which is still like very segmentation. You know, demographic variable based, and we're trying to move people to say no, you have to understand the complexity of customers and not put them in boxes. >> And I think underlying a lot of this discussion is this question of culture, right? >> Yes. >> Absolutely. >> How do you build a data driven culture? And I think that that culture question, one of the ways that comes up quite often in especially in large, Fortune 500 enterprises, is that they are very, they're not very comfortable with sort of example, open source architecture. Open source tools. And there is some sort of residual bias that that's somehow dangerous. So security vulnerability. And I think that that's part of the cultural challenge that they often have in terms of how do I build a more data driven organization? Well a lot of the talent really wants to use these kind of tools. And I mean, just to give you an example, we are partnering with one of the major cloud providers to sort of help make open source tools more user friendly on their platform. So trying to help them attract the best technologists to use their platform because they want and they understand the value of having that kind of open source technology work seamlessly on their platforms. So I think that just sort of goes to show you how important open source is in this movement. And how much large companies and Fortune 500 companies and a lot of the ones we work with have to embrace that. >> Yeah, and I'm seeing it in our work. Even when we're working with Fortune 500 companies, is that they've already gone through the first phase of data science work. Where I explain it was all about the tools and getting the right tools and architecture in place. And then companies started moving into getting the right skill set in place. Getting the right talent. And what you're talking about with culture is really where I think we're talking about the third phase of data science, which is looking at communication of these technical frameworks so that we can get non technical people really comfortable in the same room with data scientists. That is going to be the phase, that's really where I see the pain point. And that's why at Sudden Compass, we're really dedicated to working with each other to figure out how do we solve this problem now? >> And I think that communication between the technical stakeholders and management and leadership. That's a very critical piece of this. You can't have a successful data science organization without that. >> Absolutely. >> And I think that actually some of the most popular trainings we've had recently are from managers and executives who are looking to say, how do I become more data savvy? How do I figure out what is this data science thing and how do I communicate with my data scientists? >> You guys made this way too easy. I was just going to get some popcorn and watch it play out. >> Nir, last 30 seconds. I want to leave you with an opportunity to, anything you want to add to this conversation? >> I think one thing to conclude is to say that companies that are not data driven is about time to hit refresh and figure how they transition the organization to become data driven. To become agile and nimble so they can actually see what opportunities from this important industrial revolution. Otherwise, unfortunately they will have hard time to survive. >> [Katie] All agreed? >> [Tricia] Absolutely, you're right. >> Michael, Trish, Nir, thank you so much. Fascinating discussion. And thank you guys again for joining us. We will be right back with another great demo. Right after this. >> Thank you Katie. >> Once again, thank you for an excellent discussion. Weren't they great guys? And thank you for everyone who's tuning in on the live webcast. As you can hear, we have an amazing studio audience here. And we're going to keep things moving. I'm now joined by Daniel Hernandez and Siva Anne. And we're going to turn our attention to how you can deliver on what they're talking about using data science experience to do data science faster. >> Thank you Katie. Siva and I are going to spend the next 10 minutes showing you how you can deliver on what they were saying using the IBM Data Science Experience to do data science faster. We'll demonstrate through new features we introduced this week how teams can work together more effectively across the entire analytics life cycle. How you can take advantage of any and all data no matter where it is and what it is. How you could use your favorite tools from open source. And finally how you could build models anywhere and employ them close to where your data is. Remember the financial adviser app Rob showed you? To build an app like that, we needed a team of data scientists, developers, data engineers, and IT staff to collaborate. We do this in the Data Science Experience through a concept we call projects. When I create a new project, I can now use the new Github integration feature. We're doing for data science what we've been doing for developers for years. Distributed teams can work together on analytics projects. And take advantage of Github's version management and change management features. This is a huge deal. Let's explore the project we created for the financial adviser app. As you can see, our data engineer Joane, our developer Rob, and others are collaborating this project. Joane got things started by bringing together the trusted data sources we need to build the app. Taking a closer look at the data, we see that our customer and profile data is stored on our recently announced IBM Integrated Analytics System, which runs safely behind our firewall. We also needed macro economic data, which she was able to find in the Federal Reserve. And she stored it in our Db2 Warehouse on Cloud. And finally, she selected stock news data from NASDAQ.com and landed that in a Hadoop cluster, which happens to be powered by Hortonworks. We added a new feature to the Data Science Experience so that when it's installed with Hortonworks, it automatically uses a need of security and governance controls within the cluster so your data is always secure and safe. Now we want to show you the news data we stored in the Hortonworks cluster. This is the mean administrative console. It's powered by an open source project called Ambari. And here's the news data. It's in parquet files stored in HDFS, which happens to be a distributive file system. To get the data from NASDAQ into our cluster, we used IBM's BigIntegrate and BigQuality to create automatic data pipelines that acquire, cleanse, and ingest that news data. Once the data's available, we use IBM's Big SQL to query that data using SQL statements that are much like the ones we would use for any relation of data, including the data that we have in the Integrated Analytics System and Db2 Warehouse on Cloud. This and the federation capabilities that Big SQL offers dramatically simplifies data acquisition. Now we want to show you how we support a brand new tool that we're excited about. Since we launched last summer, the Data Science Experience has supported Jupyter and R for data analysis and visualization. In this week's update, we deeply integrated another great open source project called Apache Zeppelin. It's known for having great visualization support, advanced collaboration features, and is growing in popularity amongst the data science community. This is an example of Apache Zeppelin and the notebook we created through it to explore some of our data. Notice how wonderful and easy the data visualizations are. Now we want to walk you through the Jupyter notebook we created to explore our customer preference for stocks. We use notebooks to understand and explore data. To identify the features that have some predictive power. Ultimately, we're trying to assess what ultimately is driving customer stock preference. Here we did the analysis to identify the attributes of customers that are likely to purchase auto stocks. We used this understanding to build our machine learning model. For building machine learning models, we've always had tools integrated into the Data Science Experience. But sometimes you need to use tools you already invested in. Like our very own SPSS as well as SAS. Through new import feature, you can easily import those models created with those tools. This helps you avoid vendor lock-in, and simplify the development, training, deployment, and management of all your models. To build the models we used in app, we could have coded, but we prefer a visual experience. We used our customer profile data in the Integrated Analytic System. Used the Auto Data Preparation to cleanse our data. Choose the binary classification algorithms. Let the Data Science Experience evaluate between logistic regression and gradient boosted tree. It's doing the heavy work for us. As you can see here, the Data Science Experience generated performance metrics that show us that the gradient boosted tree is the best performing algorithm for the data we gave it. Once we save this model, it's automatically deployed and available for developers to use. Any application developer can take this endpoint and consume it like they would any other API inside of the apps they built. We've made training and creating machine learning models super simple. But what about the operations? A lot of companies are struggling to ensure their model performance remains high over time. In our financial adviser app, we know that customer data changes constantly, so we need to always monitor model performance and ensure that our models are retrained as is necessary. This is a dashboard that shows the performance of our models and lets our teams monitor and retrain those models so that they're always performing to our standards. So far we've been showing you the Data Science Experience available behind the firewall that we're using to build and train models. Through a new publish feature, you can build models and deploy them anywhere. In another environment, private, public, or anywhere else with just a few clicks. So here we're publishing our model to the Watson machine learning service. It happens to be in the IBM cloud. And also deeply integrated with our Data Science Experience. After publishing and switching to the Watson machine learning service, you can see that our stock affinity and model that we just published is there and ready for use. So this is incredibly important. I just want to say it again. The Data Science Experience allows you to train models behind your own firewall, take advantage of your proprietary and sensitive data, and then deploy those models wherever you want with ease. So summarize what we just showed you. First, IBM's Data Science Experience supports all teams. You saw how our data engineer populated our project with trusted data sets. Our data scientists developed, trained, and tested a machine learning model. Our developers used APIs to integrate machine learning into their apps. And how IT can use our Integrated Model Management dashboard to monitor and manage model performance. Second, we support all data. On premises, in the cloud, structured, unstructured, inside of your firewall, and outside of it. We help you bring analytics and governance to where your data is. Third, we support all tools. The data science tools that you depend on are readily available and deeply integrated. This includes capabilities from great partners like Hortonworks. And powerful tools like our very own IBM SPSS. And fourth, and finally, we support all deployments. You can build your models anywhere, and deploy them right next to where your data is. Whether that's in the public cloud, private cloud, or even on the world's most reliable transaction platform, IBM z. So see for yourself. Go to the Data Science Experience website, take us for a spin. And if you happen to be ready right now, our recently created Data Science Elite Team can help you get started and run experiments alongside you with no charge. Thank you very much. >> Thank you very much Daniel. It seems like a great time to get started. And thanks to Siva for taking us through it. Rob and I will be back in just a moment to add some perspective right after this. All right, once again joined by Rob Thomas. And Rob obviously we got a lot of information here. >> Yes, we've covered a lot of ground. >> This is intense. You got to break it down for me cause I think we zoom out and see the big picture. What better data science can deliver to a business? Why is this so important? I mean we've heard it through and through. >> Yeah, well, I heard it a couple times. But it starts with businesses have to embrace a data driven culture. And it is a change. And we need to make data accessible with the right tools in a collaborative culture because we've got diverse skill sets in every organization. But data driven companies succeed when data science tools are in the hands of everyone. And I think that's a new thought. I think most companies think just get your data scientist some tools, you'll be fine. This is about tools in the hands of everyone. I think the panel did a great job of describing about how we get to data science for all. Building a data culture, making it a part of your everyday operations, and the highlights of what Daniel just showed us, that's some pretty cool features for how organizations can get to this, which is you can see IBM's Data Science Experience, how that supports all teams. You saw data analysts, data scientists, application developer, IT staff, all working together. Second, you saw how we support all tools. And your choice of tools. So the most popular data science libraries integrated into one platform. And we saw some new capabilities that help companies avoid lock-in, where you can import existing models created from specialist tools like SPSS or others. And then deploy them and manage them inside of Data Science Experience. That's pretty interesting. And lastly, you see we continue to build on this best of open tools. Partnering with companies like H2O, Hortonworks, and others. Third, you can see how you use all data no matter where it lives. That's a key challenge every organization's going to face. Private, public, federating all data sources. We announced new integration with the Hortonworks data platform where we deploy machine learning models where your data resides. That's been a key theme. Analytics where the data is. And lastly, supporting all types of deployments. Deploy them in your Hadoop cluster. Deploy them in your Integrated Analytic System. Or deploy them in z, just to name a few. A lot of different options here. But look, don't believe anything I say. Go try it for yourself. Data Science Experience, anybody can use it. Go to datascience.ibm.com and look, if you want to start right now, we just created a team that we call Data Science Elite. These are the best data scientists in the world that will come sit down with you and co-create solutions, models, and prove out a proof of concept. >> Good stuff. Thank you Rob. So you might be asking what does an organization look like that embraces data science for all? And how could it transform your role? I'm going to head back to the office and check it out. Let's start with the perspective of the line of business. What's changed? Well, now you're starting to explore new business models. You've uncovered opportunities for new revenue sources and all that hidden data. And being disrupted is no longer keeping you up at night. As a data science leader, you're beginning to collaborate with a line of business to better understand and translate the objectives into the models that are being built. Your data scientists are also starting to collaborate with the less technical team members and analysts who are working closest to the business problem. And as a data scientist, you stop feeling like you're falling behind. Open source tools are keeping you current. You're also starting to operationalize the work that you do. And you get to do more of what you love. Explore data, build models, put your models into production, and create business impact. All in all, it's not a bad scenario. Thanks. All right. We are back and coming up next, oh this is a special time right now. Cause we got a great guest speaker. New York Magazine called him the spreadsheet psychic and number crunching prodigy who went from correctly forecasting baseball games to correctly forecasting presidential elections. He even invented a proprietary algorithm called PECOTA for predicting future performance by baseball players and teams. And his New York Times bestselling book, The Signal and the Noise was named by Amazon.com as the number one best non-fiction book of 2012. He's currently the Editor in Chief of the award winning website, FiveThirtyEight and appears on ESPN as an on air commentator. Big round of applause. My pleasure to welcome Nate Silver. >> Thank you. We met backstage. >> Yes. >> It feels weird to re-shake your hand, but you know, for the audience. >> I had to give the intense firm grip. >> Definitely. >> The ninja grip. So you and I have crossed paths kind of digitally in the past, which it really interesting, is I started my career at ESPN. And I started as a production assistant, then later back on air for sports technology. And I go to you to talk about sports because-- >> Yeah. >> Wow, has ESPN upped their game in terms of understanding the importance of data and analytics. And what it brings. Not just to MLB, but across the board. >> No, it's really infused into the way they present the broadcast. You'll have win probability on the bottom line. And they'll incorporate FiveThirtyEight metrics into how they cover college football for example. So, ESPN ... Sports is maybe the perfect, if you're a data scientist, like the perfect kind of test case. And the reason being that sports consists of problems that have rules. And have structure. And when problems have rules and structure, then it's a lot easier to work with. So it's a great way to kind of improve your skills as a data scientist. Of course, there are also important real world problems that are more open ended, and those present different types of challenges. But it's such a natural fit. The teams. Think about the teams playing the World Series tonight. The Dodgers and the Astros are both like very data driven, especially Houston. Golden State Warriors, the NBA Champions, extremely data driven. New England Patriots, relative to an NFL team, it's shifted a little bit, the NFL bar is lower. But the Patriots are certainly very analytical in how they make decisions. So, you can't talk about sports without talking about analytics. >> And I was going to save the baseball question for later. Cause we are moments away from game seven. >> Yeah. >> Is everyone else watching game seven? It's been an incredible series. Probably one of the best of all time. >> Yeah, I mean-- >> You have a prediction here? >> You can mention that too. So I don't have a prediction. FiveThirtyEight has the Dodgers with a 60% chance of winning. >> [Katie] LA Fans. >> So you have two teams that are about equal. But the Dodgers pitching staff is in better shape at the moment. The end of a seven game series. And they're at home. >> But the statistics behind the two teams is pretty incredible. >> Yeah. It's like the first World Series in I think 56 years or something where you have two 100 win teams facing one another. There have been a lot of parity in baseball for a lot of years. Not that many offensive overall juggernauts. But this year, and last year with the Cubs and the Indians too really. But this year, you have really spectacular teams in the World Series. It kind of is a showcase of modern baseball. Lots of home runs. Lots of strikeouts. >> [Katie] Lots of extra innings. >> Lots of extra innings. Good defense. Lots of pitching changes. So if you love the modern baseball game, it's been about the best example that you've had. If you like a little bit more contact, and fewer strikeouts, maybe not so much. But it's been a spectacular and very exciting World Series. It's amazing to talk. MLB is huge with analysis. I mean, hands down. But across the board, if you can provide a few examples. Because there's so many teams in front offices putting such an, just a heavy intensity on the analysis side. And where the teams are going. And if you could provide any specific examples of teams that have really blown your mind. Especially over the last year or two. Because every year it gets more exciting if you will. I mean, so a big thing in baseball is defensive shifts. So if you watch tonight, you'll probably see a couple of plays where if you're used to watching baseball, a guy makes really solid contact. And there's a fielder there that you don't think should be there. But that's really very data driven where you analyze where's this guy hit the ball. That part's not so hard. But also there's game theory involved. Because you have to adjust for the fact that he knows where you're positioning the defenders. He's trying therefore to make adjustments to his own swing and so that's been a major innovation in how baseball is played. You know, how bullpens are used too. Where teams have realized that actually having a guy, across all sports pretty much, realizing the importance of rest. And of fatigue. And that you can be the best pitcher in the world, but guess what? After four or five innings, you're probably not as good as a guy who has a fresh arm necessarily. So I mean, it really is like, these are not subtle things anymore. It's not just oh, on base percentage is valuable. It really effects kind of every strategic decision in baseball. The NBA, if you watch an NBA game tonight, see how many three point shots are taken. That's in part because of data. And teams realizing hey, three points is worth more than two, once you're more than about five feet from the basket, the shooting percentage gets really flat. And so it's revolutionary, right? Like teams that will shoot almost half their shots from the three point range nowadays. Larry Bird, who wound up being one of the greatest three point shooters of all time, took only eight three pointers his first year in the NBA. It's quite noticeable if you watch baseball or basketball in particular. >> Not to focus too much on sports. One final question. In terms of Major League Soccer, and now in NFL, we're having the analysis and having wearables where it can now showcase if they wanted to on screen, heart rate and breathing and how much exertion. How much data is too much data? And when does it ruin the sport? >> So, I don't think, I mean, again, it goes sport by sport a little bit. I think in basketball you actually have a more exciting game. I think the game is more open now. You have more three pointers. You have guys getting higher assist totals. But you know, I don't know. I'm not one of those people who thinks look, if you love baseball or basketball, and you go in to work for the Astros, the Yankees or the Knicks, they probably need some help, right? You really have to be passionate about that sport. Because it's all based on what questions am I asking? As I'm a fan or I guess an employee of the team. Or a player watching the game. And there isn't really any substitute I don't think for the insight and intuition that a curious human has to kind of ask the right questions. So we can talk at great length about what tools do you then apply when you have those questions, but that still comes from people. I don't think machine learning could help with what questions do I want to ask of the data. It might help you get the answers. >> If you have a mid-fielder in a soccer game though, not exerting, only 80%, and you're seeing that on a screen as a fan, and you're saying could that person get fired at the end of the day? One day, with the data? >> So we found that actually some in soccer in particular, some of the better players are actually more still. So Leo Messi, maybe the best player in the world, doesn't move as much as other soccer players do. And the reason being that A) he kind of knows how to position himself in the first place. B) he realizes that you make a run, and you're out of position. That's quite fatiguing. And particularly soccer, like basketball, is a sport where it's incredibly fatiguing. And so, sometimes the guys who conserve their energy, that kind of old school mentality, you have to hustle at every moment. That is not helpful to the team if you're hustling on an irrelevant play. And therefore, on a critical play, can't get back on defense, for example. >> Sports, but also data is moving exponentially as we're just speaking about today. Tech, healthcare, every different industry. Is there any particular that's a favorite of yours to cover? And I imagine they're all different as well. >> I mean, I do like sports. We cover a lot of politics too. Which is different. I mean in politics I think people aren't intuitively as data driven as they might be in sports for example. It's impressive to follow the breakthroughs in artificial intelligence. It started out just as kind of playing games and playing chess and poker and Go and things like that. But you really have seen a lot of breakthroughs in the last couple of years. But yeah, it's kind of infused into everything really. >> You're known for your work in politics though. Especially presidential campaigns. >> Yeah. >> This year, in particular. Was it insanely challenging? What was the most notable thing that came out of any of your predictions? >> I mean, in some ways, looking at the polling was the easiest lens to look at it. So I think there's kind of a myth that last year's result was a big shock and it wasn't really. If you did the modeling in the right way, then you realized that number one, polls have a margin of error. And so when a candidate has a three point lead, that's not particularly safe. Number two, the outcome between different states is correlated. Meaning that it's not that much of a surprise that Clinton lost Wisconsin and Michigan and Pennsylvania and Ohio. You know I'm from Michigan. Have friends from all those states. Kind of the same types of people in those states. Those outcomes are all correlated. So what people thought was a big upset for the polls I think was an example of how data science done carefully and correctly where you understand probabilities, understand correlations. Our model gave Trump a 30% chance of winning. Others models gave him a 1% chance. And so that was interesting in that it showed that number one, that modeling strategies and skill do matter quite a lot. When you have someone saying 30% versus 1%. I mean, that's a very very big spread. And number two, that these aren't like solved problems necessarily. Although again, the problem with elections is that you only have one election every four years. So I can be very confident that I have a better model. Even one year of data doesn't really prove very much. Even five or 10 years doesn't really prove very much. And so, being aware of the limitations to some extent intrinsically in elections when you only get one kind of new training example every four years, there's not really any way around that. There are ways to be more robust to sparce data environments. But if you're identifying different types of business problems to solve, figuring out what's a solvable problem where I can add value with data science is a really key part of what you're doing. >> You're such a leader in this space. In data and analysis. It would be interesting to kind of peek back the curtain, understand how you operate but also how large is your team? How you're putting together information. How quickly you're putting it out. Cause I think in this right now world where everybody wants things instantly-- >> Yeah. >> There's also, you want to be first too in the world of journalism. But you don't want to be inaccurate because that's your credibility. >> We talked about this before, right? I think on average, speed is a little bit overrated in journalism. >> [Katie] I think it's a big problem in journalism. >> Yeah. >> Especially in the tech world. You have to be first. You have to be first. And it's just pumping out, pumping out. And there's got to be more time spent on stories if I can speak subjectively. >> Yeah, for sure. But at the same time, we are reacting to the news. And so we have people that come in, we hire most of our people actually from journalism. >> [Katie] How many people do you have on your team? >> About 35. But, if you get someone who comes in from an academic track for example, they might be surprised at how fast journalism is. That even though we might be slower than the average website, the fact that there's a tragic event in New York, are there things we have to say about that? A candidate drops out of the presidential race, are things we have to say about that. In periods ranging from minutes to days as opposed to kind of weeks to months to years in the academic world. The corporate world moves faster. What is a little different about journalism is that you are expected to have more precision where people notice when you make a mistake. In corporations, you have maybe less transparency. If you make 10 investments and seven of them turn out well, then you'll get a lot of profit from that, right? In journalism, it's a little different. If you make kind of seven predictions or say seven things, and seven of them are very accurate and three of them aren't, you'll still get criticized a lot for the three. Just because that's kind of the way that journalism is. And so the kind of combination of needing, not having that much tolerance for mistakes, but also needing to be fast. That is tricky. And I criticize other journalists sometimes including for not being data driven enough, but the best excuse any journalist has, this is happening really fast and it's my job to kind of figure out in real time what's going on and provide useful information to the readers. And that's really difficult. Especially in a world where literally, I'll probably get off the stage and check my phone and who knows what President Trump will have tweeted or what things will have happened. But it really is a kind of 24/7. >> Well because it's 24/7 with FiveThirtyEight, one of the most well known sites for data, are you feeling micromanagey on your people? Because you do have to hit this balance. You can't have something come out four or five days later. >> Yeah, I'm not -- >> Are you overseeing everything? >> I'm not by nature a micromanager. And so you try to hire well. You try and let people make mistakes. And the flip side of this is that if a news organization that never had any mistakes, never had any corrections, that's raw, right? You have to have some tolerance for error because you are trying to decide things in real time. And figure things out. I think transparency's a big part of that. Say here's what we think, and here's why we think it. If we have a model to say it's not just the final number, here's a lot of detail about how that's calculated. In some case we release the code and the raw data. Sometimes we don't because there's a proprietary advantage. But quite often we're saying we want you to trust us and it's so important that you trust us, here's the model. Go play around with it yourself. Here's the data. And that's also I think an important value. >> That speaks to open source. And your perspective on that in general. >> Yeah, I mean, look, I'm a big fan of open source. I worry that I think sometimes the trends are a little bit away from open source. But by the way, one thing that happens when you share your data or you share your thinking at least in lieu of the data, and you can definitely do both is that readers will catch embarrassing mistakes that you made. By the way, even having open sourceness within your team, I mean we have editors and copy editors who often save you from really embarrassing mistakes. And by the way, it's not necessarily people who have a training in data science. I would guess that of our 35 people, maybe only five to 10 have a kind of formal background in what you would call data science. >> [Katie] I think that speaks to the theme here. >> Yeah. >> [Katie] That everybody's kind of got to be data literate. >> But yeah, it is like you have a good intuition. You have a good BS detector basically. And you have a good intuition for hey, this looks a little bit out of line to me. And sometimes that can be based on domain knowledge, right? We have one of our copy editors, she's a big college football fan. And we had an algorithm we released that tries to predict what the human being selection committee will do, and she was like, why is LSU rated so high? Cause I know that LSU sucks this year. And we looked at it, and she was right. There was a bug where it had forgotten to account for their last game where they lost to Troy or something and so -- >> That also speaks to the human element as well. >> It does. In general as a rule, if you're designing a kind of regression based model, it's different in machine learning where you have more, when you kind of build in the tolerance for error. But if you're trying to do something more precise, then so much of it is just debugging. It's saying that looks wrong to me. And I'm going to investigate that. And sometimes it's not wrong. Sometimes your model actually has an insight that you didn't have yourself. But fairly often, it is. And I think kind of what you learn is like, hey if there's something that bothers me, I want to go investigate that now and debug that now. Because the last thing you want is where all of a sudden, the answer you're putting out there in the world hinges on a mistake that you made. Cause you never know if you have so to speak, 1,000 lines of code and they all perform something differently. You never know when you get in a weird edge case where this one decision you made winds up being the difference between your having a good forecast and a bad one. In a defensible position and a indefensible one. So we definitely are quite diligent and careful. But it's also kind of knowing like, hey, where is an approximation good enough and where do I need more precision? Cause you could also drive yourself crazy in the other direction where you know, it doesn't matter if the answer is 91.2 versus 90. And so you can kind of go 91.2, three, four and it's like kind of A) false precision and B) not a good use of your time. So that's where I do still spend a lot of time is thinking about which problems are "solvable" or approachable with data and which ones aren't. And when they're not by the way, you're still allowed to report on them. We are a news organization so we do traditional reporting as well. And then kind of figuring out when do you need precision versus when is being pointed in the right direction good enough? >> I would love to get inside your brain and see how you operate on just like an everyday walking to Walgreens movement. It's like oh, if I cross the street in .2-- >> It's not, I mean-- >> Is it like maddening in there? >> No, not really. I mean, I'm like-- >> This is an honest question. >> If I'm looking for airfares, I'm a little more careful. But no, part of it's like you don't want to waste time on unimportant decisions, right? I will sometimes, if I can't decide what to eat at a restaurant, I'll flip a coin. If the chicken and the pasta both sound really good-- >> That's not high tech Nate. We want better. >> But that's the point, right? It's like both the chicken and the pasta are going to be really darn good, right? So I'm not going to waste my time trying to figure it out. I'm just going to have an arbitrary way to decide. >> Serious and business, how organizations in the last three to five years have just evolved with this data boom. How are you seeing it as from a consultant point of view? Do you think it's an exciting time? Do you think it's a you must act now time? >> I mean, we do know that you definitely see a lot of talent among the younger generation now. That so FiveThirtyEight has been at ESPN for four years now. And man, the quality of the interns we get has improved so much in four years. The quality of the kind of young hires that we make straight out of college has improved so much in four years. So you definitely do see a younger generation for which this is just part of their bloodstream and part of their DNA. And also, particular fields that we're interested in. So we're interested in people who have both a data and a journalism background. We're interested in people who have a visualization and a coding background. A lot of what we do is very much interactive graphics and so forth. And so we do see those skill sets coming into play a lot more. And so the kind of shortage of talent that had I think frankly been a problem for a long time, I'm optimistic based on the young people in our office, it's a little anecdotal but you can tell that there are so many more programs that are kind of teaching students the right set of skills that maybe weren't taught as much a few years ago. >> But when you're seeing these big organizations, ESPN as perfect example, moving more towards data and analytics than ever before. >> Yeah. >> You would say that's obviously true. >> Oh for sure. >> If you're not moving that direction, you're going to fall behind quickly. >> Yeah and the thing is, if you read my book or I guess people have a copy of the book. In some ways it's saying hey, there are lot of ways to screw up when you're using data. And we've built bad models. We've had models that were bad and got good results. Good models that got bad results and everything else. But the point is that the reason to be out in front of the problem is so you give yourself more runway to make errors and mistakes. And to learn kind of what works and what doesn't and which people to put on the problem. I sometimes do worry that a company says oh we need data. And everyone kind of agrees on that now. We need data science. Then they have some big test case. And they have a failure. And they maybe have a failure because they didn't know really how to use it well enough. But learning from that and iterating on that. And so by the time that you're on the third generation of kind of a problem that you're trying to solve, and you're watching everyone else make the mistake that you made five years ago, I mean, that's really powerful. But that doesn't mean that getting invested in it now, getting invested both in technology and the human capital side is important. >> Final question for you as we run out of time. 2018 beyond, what is your biggest project in terms of data gathering that you're working on? >> There's a midterm election coming up. That's a big thing for us. We're also doing a lot of work with NBA data. So for four years now, the NBA has been collecting player tracking data. So they have 3D cameras in every arena. So they can actually kind of quantify for example how fast a fast break is, for example. Or literally where a player is and where the ball is. For every NBA game now for the past four or five years. And there hasn't really been an overall metric of player value that's taken advantage of that. The teams do it. But in the NBA, the teams are a little bit ahead of journalists and analysts. So we're trying to have a really truly next generation stat. It's a lot of data. Sometimes I now more oversee things than I once did myself. And so you're parsing through many, many, many lines of code. But yeah, so we hope to have that out at some point in the next few months. >> Anything you've personally been passionate about that you've wanted to work on and kind of solve? >> I mean, the NBA thing, I am a pretty big basketball fan. >> You can do better than that. Come on, I want something real personal that you're like I got to crunch the numbers. >> You know, we tried to figure out where the best burrito in America was a few years ago. >> I'm going to end it there. >> Okay. >> Nate, thank you so much for joining us. It's been an absolute pleasure. Thank you. >> Cool, thank you. >> I thought we were going to chat World Series, you know. Burritos, important. I want to thank everybody here in our audience. Let's give him a big round of applause. >> [Nate] Thank you everyone. >> Perfect way to end the day. And for a replay of today's program, just head on over to ibm.com/dsforall. I'm Katie Linendoll. And this has been Data Science for All: It's a Whole New Game. Test one, two. One, two, three. Hi guys, I just want to quickly let you know as you're exiting. A few heads up. Downstairs right now there's going to be a meet and greet with Nate. And we're going to be doing that with clients and customers who are interested. So I would recommend before the game starts, and you lose Nate, head on downstairs. And also the gallery is open until eight p.m. with demos and activations. And tomorrow, make sure to come back too. Because we have exciting stuff. I'll be joining you as your host. And we're kicking off at nine a.m. So bye everybody, thank you so much. >> [Announcer] Ladies and gentlemen, thank you for attending this evening's webcast. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your name badge at the registration desk. Thank you. Also, please note there are two exits on the back of the room on either side of the room. Have a good evening. Ladies and gentlemen, the meet and greet will be on stage. Thank you.

Published Date : Nov 1 2017

SUMMARY :

Today the ability to extract value from data is becoming a shared mission. And for all of you during the program, I want to remind you to join that conversation on And when you and I chatted about it. And the scale and complexity of the data that organizations are having to deal with has It's challenging in the world of unmanageable. And they have to find a way. AI. And it's incredible that this buzz word is happening. And to get to an AI future, you have to lay a data foundation today. And four is you got to expand job roles in the organization. First pillar in this you just discussed. And now you get to where we are today. And if you don't have a strategy for how you acquire that and manage it, you're not going And the way I think about that is it's really about moving from static data repositories And we continue with the architecture. So you need a way to federate data across different environments. So we've laid out what you need for driving automation. And so when you think about the real use cases that are driving return on investment today, Let's go ahead and come back to something that you mentioned earlier because it's fascinating And so the new job roles is about how does everybody have data first in their mind? Everybody in the company has to be data literate. So overall, group effort, has to be a common goal, and we all need to be data literate But at the end of the day, it's kind of not an easy task. It's not easy but it's maybe not as big of a shift as you would think. It's interesting to hear you say essentially you need to train everyone though across the And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. And I've heard that the placement behind those jobs, people graduating with the MS is high. Let me get back to something else you touched on earlier because you mentioned that a number They produce a lot of the shows that I'm sure you watch Katie. And this is a good example. So they have to optimize every aspect of their business from marketing campaigns to promotions And so, as we talk to clients we think about how do you start down this path now, even It's analytics first to the data, not the other way around. We as a practice, we say you want to bring data to where the data sits. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. Female preferred, on the cover of Vogue. And how does it change everything? And while it's important to recognize this critical skill set, you can't just limit it And we call it clickers and coders. [Katie] I like that. And there's not a lot of things available today that do that. Because I hear you talking about the data scientists role and how it's critical to success, And my view is if you have the right platform, it enables the organization to collaborate. And every organization needs to think about what are the skills that are critical? Use this as your chance to reinvent IT. And I can tell you even personally being effected by how important the analysis is in working And think about if you don't do something. And now we're going to get to the fun hands on part of our story. And then how do you move analytics closer to your data? And in here I can see that JP Morgan is calling for a US dollar rebound in the second half But then where it gets interesting is you go to the bottom. data, his stock portfolios, and browsing behavior to build a model which can predict his affinity And so, as a financial adviser, you look at this and you say, all right, we know he loves And I want to do that by picking a auto stock which has got negative correlation with Ferrari. Cause you start clicking that and immediately we're getting instant answers of what's happening. And what I see here instantly is that Honda has got a negative correlation with Ferrari, As a financial adviser, you wouldn't think about federating data, machine learning, pretty And drive the machine learning into the appliance. And even score hundreds of customers for their affinities on a daily basis. And then you see when you deploy analytics next to your data, even a financial adviser, And as a data science leader or data scientist, you have a lot of the same concerns. But you guys each have so many unique roles in your business life. And just by looking at the demand of companies that wants us to help them go through this And I think the whole ROI of data is that you can now understand people's relationships Well you can have all the data in the world, and I think it speaks to, if you're not doing And I think that that's one of the things that customers are coming to us for, right? And Nir, this is something you work with a lot. And the companies that are not like that. Tricia, companies have to deal with data behind the firewall and in the new multi cloud And so that's why I think it's really important to understand that when you implement big And how are the clients, how are the users actually interacting with the system? And right now the way I see teams being set up inside companies is that they're creating But in order to actually see all of the RY behind the data, you also have to have a creative That's one of the things that we see a lot. So a lot of the training we do is sort of data engineers. And I think that's a very strong point when it comes to the data analysis side. And that's where you need the human element to come back in and say okay, look, you're And the people who are really great at providing that human intelligence are social scientists. the talent piece is actually the most important crucial hard to get. It may be to take folks internally who have a lot of that domain knowledge that you have And from data scientist to machine learner. And what I explain to them is look, you're still making decisions in the same way. And I mean, just to give you an example, we are partnering with one of the major cloud And what you're talking about with culture is really where I think we're talking about And I think that communication between the technical stakeholders and management You guys made this way too easy. I want to leave you with an opportunity to, anything you want to add to this conversation? I think one thing to conclude is to say that companies that are not data driven is And thank you guys again for joining us. And we're going to turn our attention to how you can deliver on what they're talking about And finally how you could build models anywhere and employ them close to where your data is. And thanks to Siva for taking us through it. You got to break it down for me cause I think we zoom out and see the big picture. And we saw some new capabilities that help companies avoid lock-in, where you can import And as a data scientist, you stop feeling like you're falling behind. We met backstage. And I go to you to talk about sports because-- And what it brings. And the reason being that sports consists of problems that have rules. And I was going to save the baseball question for later. Probably one of the best of all time. FiveThirtyEight has the Dodgers with a 60% chance of winning. So you have two teams that are about equal. It's like the first World Series in I think 56 years or something where you have two 100 And that you can be the best pitcher in the world, but guess what? And when does it ruin the sport? So we can talk at great length about what tools do you then apply when you have those And the reason being that A) he kind of knows how to position himself in the first place. And I imagine they're all different as well. But you really have seen a lot of breakthroughs in the last couple of years. You're known for your work in politics though. What was the most notable thing that came out of any of your predictions? And so, being aware of the limitations to some extent intrinsically in elections when It would be interesting to kind of peek back the curtain, understand how you operate but But you don't want to be inaccurate because that's your credibility. I think on average, speed is a little bit overrated in journalism. And there's got to be more time spent on stories if I can speak subjectively. And so we have people that come in, we hire most of our people actually from journalism. And so the kind of combination of needing, not having that much tolerance for mistakes, Because you do have to hit this balance. And so you try to hire well. And your perspective on that in general. But by the way, one thing that happens when you share your data or you share your thinking And you have a good intuition for hey, this looks a little bit out of line to me. And I think kind of what you learn is like, hey if there's something that bothers me, It's like oh, if I cross the street in .2-- I mean, I'm like-- But no, part of it's like you don't want to waste time on unimportant decisions, right? We want better. It's like both the chicken and the pasta are going to be really darn good, right? Serious and business, how organizations in the last three to five years have just And man, the quality of the interns we get has improved so much in four years. But when you're seeing these big organizations, ESPN as perfect example, moving more towards But the point is that the reason to be out in front of the problem is so you give yourself Final question for you as we run out of time. And so you're parsing through many, many, many lines of code. You can do better than that. You know, we tried to figure out where the best burrito in America was a few years Nate, thank you so much for joining us. I thought we were going to chat World Series, you know. And also the gallery is open until eight p.m. with demos and activations. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your

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John Donahoe, ServiceNow | ServiceNow Knowledge17


 

>> Voiceover: Live from Orlando, Florida, it's theCUBE, covering ServiceNow Knowledge17. Brought to you by ServiceNow. (upbeat electronic music) >> Welcome back to sunny Orlando, everybody. This is ServiceNow Knowledge17 #Know17. I'm Dave Vellante with Jeff Frick. John Donahoe is here as the newly-minted CEO and President of ServiceNow, fresh off the keynote, fresh off 49 days in. John, welcome to theCUBE, thanks for coming on. >> Thank you very much, it's great to be here. >> John: So how'd you feel up there? You had the theater in the round, you were working the audience, I loved how you walked on the stage and really got into it. How's it feel? >> Well, what I love about ServiceNow, is it's a community-based business and a community-based company. And so, we had 15,000 members of our community out there, and that community feeling is, I think, one of the real powers of the movement that's called ServiceNow and of the ethos of this company. So, I loved that, I fed off that energy. >> So, at the risk of some repetition, a little bit of background about yourself, a former Bain, former eBay CEO, you shared that with the audience. What is relevant about your background to the ServiceNow experience that you expect to have? >> Well, you know it's funny Dave, I spent the first 20 years of my career at Bain doing business transformation. And a lot of what I talked about today was digital transformation, that is, every company is trying to transform. And I spent the first 20 years of my career focused on that. And then we talked a lot about great customer experiences. Well, the consumer world and consumer-based applications like eBay, or PayPal, or many other consumer applications, are defining the new standards of what kind of easy, simple, intuitive experiences are possible. And employees are consumers at home and they're increasingly expecting the same kind of great experiences they have at home at work, and as customers of enterprises. And so I think you're going to see the world of consumer and enterprise converging. And so that's why I'm very excited about being a part of ServiceNow. >> So, you talked to the audience, as I say, about your background. You're a family man, you've got Four children. >> John: Yeah >> Jeff: Pictures on stage; which I love. You know, it really kind of goes with the folksy, you know, history of this company and the community base. Not too many people put their family photo up on the keynote. I thought it was great. >> John: Yeah, well, they're my bosses, so... (all laughing) >> Dave: Well, like you said, they make you humble >> John: Yeah. >> Dave: and you learn a lot from them, so... So I appreciated you starting that. I've got Four kids, Jeff's got kids, and so... >> John: That's great. >> Dave: And you're hosting a women in tech breakfast tomorrow, a real passion of ours, so, maybe talk about that a little bit. >> Well, I just think it's really, really important. And, people ask me: "Why do you think that way?" I think it's good business, right? At the end of the day, the ultimate thing we do to succeed in business is we need to attract, develop, and retain the very best people, >> Dave: Right. >> John: and by definition, 50% of the workforce is female. And so, to not be aggressively trying to cultivate that part of our team is to miss an opportunity. And doing it well is hard, but if you do it well, it could be a source of competitive advantage. So, I care deeply about it professionally, and then also personally as a father of a daughter, the question I ask men that have daughters and say: "Do you want your daughter to grow up and be part of a work environment that's even better than the one they would have been if they'd come at your time?" And almost all of us say, "Yes!" >> Jeff: Of course >> John: So, it's a responsibility we all share. >> So, I want to ask about your management philosophy. You know, I've heard the term, of course you have too, "benevolent dictator". You use the term, >> "servant leadership". >> "servant leadership". >> John: Yeah. >> Dave: Which starts at the customer on top. Explain your philosophy there. >> Well, it's a way I learned to lead early in my career; which is: that it's the opposite of a classic pyramid. Right, where the CEO's on top and everything's underneath. No, this is an upside-down triangle, where the reason we're here is to serve our customers, to serve our employees as they serve our customers, to serve the purpose and to the extent you can, to serve the communities in which we are part of. And my experience is that: building that deeply into the culture of a company breeds a level of commitment and a level of long-term orientation that's really important. And ServiceNow's had that from the beginning. Think about Fred Luddy embodied that. He was a brilliant technologist, and he said, "You know what, I'm going to recruit a CEO" "before the company goes public who has those skills." So, he recruited Frank, right? And Fred stayed involved. Frank embodied servant leadership. Frank could've stayed forever. Frank said I was the right CEO to serve this purpose from 75 million to a Billion Four. And then he started to looking for someone that's the right person to serve for the next generation; which is me. So this notion of stewardship, we're all here to serve our customers and try to make our purpose come alive over a long period of time. And I think it's the most enduring motivation and inspiration we can have. And it keeps the customer front and center. >> Well, so one of the first things you did in your first 100 days, you said you wanted to see 100 customers, you actually accomplished that in 45 days. So, first of all congratulations, first of all how'd you do that? (all laughing) >> Well, I went at a roadshow to 10 cities across the U.S. and just packed my days full of meetings with customers. And they were individual meetings, and we had some group meetings, some lunches and dinners. And those are some of the best because you get a conversation going. I had Four or Five, Six customers around a breakfast table or dinner table and we start talking about their issues. And, the dynamic in every situation was they would start sharing with each other. They would say, "Well, how are you addressing this?" And they'd starting saying they have similar issues, similar challenges, similar ideas of how they're going to address it. So, the power, that community power, I was seeing firsthand in smaller settings. And for me, it was just so energizing because our limitation of how quickly we can get better is well we understand our customer's needs, and also understand their feedback about where we can get better. >> Well it's interesting, you said you were a customer when you ran eBay... >> John: Yes. >> Jeff: of ServiceNow, so that's kind of some of your background knowledge of the company. When you went out on your tour, what were some of the things that surprised you that you didn't know even though you had been kind of a ServiceNow customer in the past? >> Well, I think what I hadn't fully understood was the power of the ServiceNow platform, and how it's getting pulled into new areas across the company. So, it's getting pulled to customer-facing applications, customer-facing processes like Ashley at GE is talking about. >> Jeff: Right. >> John: And it makes sense, right? I know at eBay and PayPal, we really worried a lot about how do we handle inbound contacts from our users. And password reset was the #1 inbound contact. (dave laughing) Well, password reset is a perfect process that can be handled in an automated in a self-help way; which is ultimately what the customer wants. >> Jeff: Right. >> John: And ServiceNow can help enable that. And so, as I was sort of surprised and delighted by how this platform is getting pulled into new use cases, that in many ways are back to what Fred Luddy imagined when he founded the company. The interesting thing is, Fred founded the company as a platform to serve all services, businesses, business processes across the enterprise. And then, but platforms don't generate revenue, They don't sell. So, he found an application: ITSM; which was the first application, and it took off. And so ServiceNow began to be known as the IT company. But that was never what Fred envisioned. It was a company that enabled and empowered IT to simplify and automate and transform the entire company. >> It's interesting, password reset. Because it seems like such a simple process. And it doesn't necessarily seem like a high-value process. But in fact, it's hugely high-value for the customer. It's hugely cumbersome in terms of the time it takes. So, to automate something that seems so simple as password reset, has huge implications in terms of efficiency inside and customer satisfaction on the outside. What a great example. >> Well, and here's what's so interesting about that example: Is, it touches multiple parts of the company. Because, people actually, your password is your security. And you could automate changing it in a way that was insecure. But, you've got to do it in a way that it's the convenience that we want to reset our passwords, but we want to know we're safe. And so, that password reset flow has to touch security, it has to touch engineering, it has to touch operations and customer support, it has to touch the customer's record, and so it's a classic multi-function, multi-discipline flow, but you want to make that easy and simple for a user, and yet also have them feel safe. Simple and safe is hard to do. >> John, you mentioned Ashley from GE, I want to talk about digital transformation. It's one of those terms you hear a lot at these conferences, sometimes it's amorphous, it's kind of like A.I. We'll talk about that if we have time. But Jeff, I love your quote. We follow GE quite closely, and Jeffrey Immelt said: "I went to bed an industrial giant," "and I woke up a software company one day." >> John: Yep. >> Dave: And you see this everywhere. So what is digital transformation to you and the customer's that you've been talking to? >> Well, here's, technology and software in particular on one hand is disrupting every company in every industry. I view that as a motivation. I view that as a wake-up call for all of us, including a software company. And, software is an opportunity. An opportunity to make changes and advancements at a pace and a magnitude that's been unparallelled in business history. So every company needs to define how they're going to use technology, how they're going to use software, how they're going to use digital capability to their advantage. To their advantage with their own consumers, their own customers, either industrial customer or a consumer in a consumer business, and how to use it to change the employee's experience and improve it. So, employees are spending time not on manual tasks; which now can be done by technology, but on higher value-added activities, and then how you can operate a global enterprise in an effective and efficient manner. And so, technology is an offensive weapon if you will, an offensive tool, is something that's on the mind of every CEO, and every company. And that's where they're looking for how do they have a few trusted partners. A few trusted technology partners that help them navigate their way through that, help them drive their way through, and that's ultimately what ServiceNow is. >> So these are big ideas, and they involve a lot of different constituencies within your customer base. Obviously, your IT peeps, as we like to say, but the CIO, who's role is changing, and also the line of business folks. So these are big, heavy lifts that you can't do alone. You've got to have an ecosystem to do that. When we did our first Knowledge in 2013, the SIs were a lot of companies frankly that we never even heard of. And now, you're seeing all the big SIs. I don't even want to name them because I'll forget some. But, your partner strategy is critical to achieving that vision that you just laid out, isn't it? >> Absolutely, Absolutely. Because it takes both of us. It takes our software and then their capabilities to help our shared customers, shared clients, implement the software, and do it increasingly in a way that is as configurable as possible; which means as minimum customization as possible, and also as quickly as possible. And our partner ecosystem's an essential partner in doing that. And there's the big SIs, and then also some of the smaller ones. I spent some time with customers in some smaller cities where they're saying having local capabilities, local teams, that were trained and certified on ServiceNow was really important to them. Often they end up being acquired by or joining the bigger SIs over time, but that sort of grass roots opportunity. Because that's also job creation. That's job creation in communities. I got to see how talented, computer-literate, software-literate people in different cities around the world are seeing an opportunity to create a livelihood by helping customers integrate ServiceNow in the most effective way. >> So two years ago, Frank Slootman in his keynote said that the CIO's role is changing and they're becoming business people. >> John: Yes. >> Dave: And kind of challenged CIOs, if you don't speak wallet you better start learning that language, the "lingua franca" of the business. So, you obviously agree with that. But, how is the CIO role changing, and how does it support other roles within the organization, that you're trying to apply ServiceNow to? >> Well, I have a really, Jeff, a really outside-in... Or, Dave, really outside-in...sorry about that. >> Dave: It's alright. >> John: I've had a lot of names this morning. >> Jeff: I'm sure you have. >> Dave: That's pretty good. >> John: Outside-In view of this. Which is through the eyes of the customer, alright? The CEO is thinking about: "Alright, I've got to serve our customers better," "I've got to retain our customers" "and serve our customers better." "And then I've got to tract and retain employees" as we've been talking about. "And I need the digital capability," "I need technology to help us do that." Their going to turn to the most technically-literate person in the C-suite to help do that. That's the CIO, right? And so the CIO by very definition has to play a broader role of partnering with the business unit leaders, with the functional leaders, to drive that end-to-end business transformation or digital transformation. And the CIOs that I met are ready to take on that challenge. They couldn't have done that before the cloud technologies that give them the ability to play offense. But these cloud technologies now cut across, they don't just sit in IT, they cut across all of the enterprise. >> Jeff: Right, right. >> John: And so, I would say there's almost this gigantic sucking sound, if you will, to use an old Ross Perot-ism, that IT and the CIO are being asked to play this role, be change agents, strategic change agents, across the enterprise. And they're ready to do that, but they do need to speak business in business terms, and business value, and business value means: Are we serving our customers better? What's our customer NPS? What's our customer response time? What's our customer retention? They need to speak employee value terms: What's our ability to retain our best employees? What's their satisfaction? And then of course they have to speak the business terms of efficiency, right? Are we being more productive and more efficient as we're serving our customers and as we're serving our employees? And so, the CIOs I met and the IT professionals I met, are asking for help to translate what they do into that business language. And the very best ones are doing it. And I think you'll see that trend continue more and more. >> And they've got to have automation, and they've got to have efficiency because their budgets aren't going up commiserately with their increased responsibility to drive this digital transformation. So they've got to wring that extra value out of the tools and processes and people that they have, and that's where you really help them quite a bit. I think I saw a quote the other day that someone went from 60 days to Two days in a business process, amazing. >> Well, and it's interesting because companies are investing more in technology than they ever have. If you take the broad technology spend, they're investing more in technology. But, they expect to get productivity and efficiency, not just out of IT, but across the entire enterprise. >> Jeff: Across the board. >> John: And that's the opportunity: More investment, greater productivity, greater value for customers and employees. >> You talked yesterday to the financial analyst about the sort of execution machine that you inherited. Personally, I think you have a great CFO, one of the best if not the best in the business. So I presume you're not going to be spending a lot of your time trying to restructure reporting and counting beans, no pejorative intended there. So, what do you bring to the organization? Where are you going to spend your time? And what are your main goals over the next mid-term and long-term? >> Well, as you said, I'm blessed. Mike Scarpelli, I think, is a world-class CFO and the best in the industry and I'm honored and thrilled to work with him. Same with Dave Schneider and Kevin Haverty who run our sales force. And now CJ Desai, our Chief Product Officer, Dan Rogers, we've got a really strong team. My focus is to have us continue our current momentum, continue the current execution that we're focusing on. But then, to begin to sort of chart a course for 2018, 2019, 2020, and beyond as we go from being a billion-dollar company, to a four, to five-billion dollar company, to beyond to a 10-billion dollar company. And the nice news is that it's building on top of this very solid foundation. As we evolve from being what has been an IT-focused platform company to be more of a digital transformation platform and company. And helping our clients, helping our customers, achieve their aims and their goals, and being one of the few trusted technology partners. Every company has a few trusted technology partners and we want ServiceNow to be one of those. And, to do that, you've got to be viewed as mission-critical and adding real value, both of which I think we are. >> Dave: So you could joke, you know, don't mess it up. >> John: Yes. >> Dave: Okay, and take it to another level; which really is kind of what seems to be your expertise. Bringing it into the line of business is talking to the CEO and other C-level executives. And actually, marrying the expertise of the CIO has cross-organizational purview, leveraging that capability and super-powering that. >> Exactly. Exactly. You know, it's interesting. If I were to look back on the last 15 years, the C-suite role that has changed the most in the last 15 years has been that of the CFO. 15 years ago CFOs were being counters. >> Dave: Yeah. >> John: Right? Today, as you said, as Mike Scarpelli and Bob Swan, my previous CFO at eBay and the best CFOs, they drive value across the enterprise. Right? They're almost COOs in their mindset. They work with business units, and they add enormous value. So that job has become significantly more important and powerful. I see the same thing happening with the CIO over the next Five to 10 years where the CIOs role with grow, and expand, and broaden. And that's exciting. >> Well, you know, one of the things, actually, you know, we come to these conferences, and there's obviously a lot of messaging, but we try to understand how that messaging actually fits with what customers are doing. One of the things that you guys are messaging this year is light speed. And so, when you talk about the CFO and the changing role, it brings up, to my mind anyway, light speed requires a new set of metrics, and listening to, like Scarpelli, talk yesterday, he's all over the metrics. And these aren't, you know, your typical, you know, EBITDA metrics, they are just a new set. Do you see that happening within, not only ServiceNow, but within your customer base, where the so-called, I'll call them, "light speed" metrics are emerging? >> Absolutely. I mean, you saw the example of Dave Wright going through the machine learning, and how the machine learning capability, when applied to the ServiceNow platform, applied to specific problems, helps you fix problems before they happen in an automated fashion. Imagine that, right? That's light speed. Dave said it so well on stage. (all laughing) That's even faster than light speed. And so, you begin to see, alright, how do you measure, in delivering a great customer experience, how do you measure the reductions of problems? How do you measure the prevention of problems that provides greater availability, greater reliability, greater consistency, of a customer's experience? Now, ultimately that measure will be in customer NPS or some other customer metrics. But, some of the subordinate metrics I think you will see a growing number of what I would call L2, L3 metrics, that is, a dashboard of how to run a great company around customers, employees, and financials. >> Alright John, I know you're super busy, we've got to leave it there. Thank you so much for coming on theCUBE and congratulations on the role, great keynote, and best of luck. We'll be watching. >> John: Thanks very much Dave, thanks >> You're welcome, alright. >> From me, congratulations. Keep it right there, buddy, we'll be right back with our next guest. This is theCUBE, we're live from ServiceNow, Knowledge17. Be right back. (upbeat electronic music)

Published Date : May 10 2017

SUMMARY :

Brought to you by ServiceNow. John Donahoe is here as the newly-minted John: So how'd you feel up there? and of the ethos of this company. to the ServiceNow experience that you expect to have? And I spent the first 20 years of my career focused on that. So, you talked to the audience, as I say, You know, it really kind of goes with the folksy, you know, John: Yeah, well, they're my bosses, so... Dave: and you learn a lot from them, so... so, maybe talk about that a little bit. and retain the very best people, John: and by definition, 50% of the workforce is female. of course you have too, "benevolent dictator". Dave: Which starts at the customer on top. that's the right person to serve Well, so one of the first things you did So, the power, that community power, I was seeing firsthand Well it's interesting, you said you were a customer kind of a ServiceNow customer in the past? So, it's getting pulled to customer-facing applications, And password reset was the #1 inbound contact. And so ServiceNow began to be known as the IT company. and customer satisfaction on the outside. And so, that password reset flow has to touch security, It's one of those terms you hear a lot at these conferences, and the customer's that you've been talking to? and how to use it to change the employee's experience and also the line of business folks. in different cities around the world that the CIO's role is changing But, how is the CIO role changing, Well, I have a really, Jeff, a really outside-in... And the CIOs that I met are ready to take on that challenge. that IT and the CIO are being asked to play this role, and that's where you really help them quite a bit. But, they expect to get productivity and efficiency, John: And that's the opportunity: about the sort of execution machine that you inherited. and being one of the few trusted technology partners. And actually, marrying the expertise of the CIO in the last 15 years has been that of the CFO. over the next Five to 10 years One of the things that you guys are messaging this year and how the machine learning capability, and congratulations on the role, This is theCUBE, we're live from ServiceNow, Knowledge17.

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Alan Nance, Virtual Clarity– DataWorks Summit Europe 2017 #DW17 #theCUBE


 

>> Narrator: At the DataWorks Summit, Europe 2017. Brought to you by Hortonworks. >> Hey, welcome back everyone. We're here live from Munich, Germany at DataWorks 2017, Hadoop Summit formerly, the conference name before it changed to DataWorks. I'm John Furrier with my cohost Dave Vellante. Our next guest, we're excited to have Alan Nance who flew in, just for the CUBE interview today. Executive Vice President with Virtual Clarity. Former star, I call practitioner of the Cloud, knows the Cloud business. Knows the operational aspects of how to use technology. Alan, it's great to see you. Thanks for coming on the CUBE. >> Thank you for having me again. >> Great to see you, you were in the US recently, we had a chance to catch up. And one of the motivations that we talked with you today was, a little bit about some of the things you're looking at, that are transformative. Before we do that, let's talk a little about your history. And what your role is at Virtual Clarity. >> So, as you guys have, basically, followed that career, I started out in the transformation time with ING Bank. And started out, basically, technology upwards. Looking at converged infrastructure, converged infrastructure into VDI. When you've got that, you start to look at Clouds. Then you start to experiment with Clouds. And I moved from ING, from earlier experimentation, into Phillips. So, while Phillips, at that time had both the health care and lighting group. And then you start to look at consumption based Cloud propositions. And you remember the big thing that we were doing at that time, when we identified that 80% of the IT spend was non differentiating. So the thing was, how do we get away from almost a 900 million a year spend on legacy? How do we turn that into something that's productive for the Enterprise? So we spent a lot of time creating the consumption based infrastructure operating platform. A lot of things we had to learn. Because let's be honest, Amazon was still trying to become the behemoth it is now. IBM still didn't get the transition, HP didn't get it. So there was a lot of experimentation on which of the operating model-- >> You're the first mover on the operating model, The Cloud, that has scaled to it. And really differentiated services for your business, for also, cost reductions. >> Cost reductions have been phenomenal. And we're talking about halving the budget over a three year period. We're talking about 500 million a year savings. So these are big, big savings. The thing I feel we still need to tackle, is that when we re-platform your business, it should leave to agile acceleration of your growth path. And I think that's something that we still haven't conquered. So I think we're getting better and better at using platforms to save money, to suppress the expenditure. What we now need to do is to convert that into growth platform business. >> So, how about the data component? Because you were CIO of infrastructure at Phillips. But lately, you've been really spending a lot of time thinking about the data, how data adds value. So talk about your data journey. >> Well if I look at the data journey, the journey started for me, with, basically, a meeting with Tom Ritz in 2013. And he came with a very, very simple proposition. "You guys need to learn how to create "and store, and reason over data, "for the benefit of the Enterprise." And I think, "Well that's cool." Because up until that point, nobody had really been talking about data. Everyone was talking about the underlying technologies of the Cloud, but not really of the data element. And then we had a session with JP Rangaswami, who was at Salesforce, who basically, also said, "Well don't just think "about data lakes, but think also "about data streams and data rivers. "Because the other thing that's "going to happen here is that data's "not going to be stagnant in a company like yours." So we took that, and what happened, I think, in Phillips, which I think you see in a lot of companies, is an explosion across the Enterprise. So you've got people in social doing stuff. You got CDO's appearing. You've got the IOT. You've got the old, legacy systems, the systems of record. And so you end up with this enormous fragmentation of data. And with that you get a Wild West of what I call data stewardship. So you have a CDO who says, "Well I'm in charge of data." And you got a CMO who says, "Well I'm in charge of marketing data." Or you've got a CSO, says, "Yeah, "but I'm the security data guy." And there's no coherence, in terms of moving the Enterprise forward. Because everybody's focused on their own functionality around that data and not connecting it. So where are we now? I think right now we have a huge proliferation of data that's not connected, in many organizations. And I think we're going to hybrid but I don't think that's a future proof thing for most organizations. >> John: What do you mean by that? >> Well, if I look at what a lot of those suppliers are saying, they're really saying, "The solution "that you need, is to have a hybrid solution "between the public Cloud and your own Cloud." I thought, "But that's not the problem "that we need to solve." The problem that we need to solve is first of all, data gravity. So if I look at all the transformations that are running into trouble, what do they forget? When we go out and do IOT, when we go out and do social media analysis, it all has to flow back into those legacy systems. And those legacy systems are all going to be in the old world. And so you get latency issues, you get formatting issues. And so, we have to solve the data gravity issue. And we have to also solve this proliferation of stewardship. Somebody has to be in charge of making this work. And it's not going to be, just putting in a hybrid solution. Because that won't change the operating model. >> So let me ask the question, because on one of the things you're kind of dancing around, Dave brought up the data question. Something that I see as a problem in the industry, that hasn't yet been solved, and I'm just going to throw it out there. The CIO has always been the guy managing IT. And then he would report to the CFO, get the budget, blah, blah, blah. We know that's kind of played out its course. But there's no operational playbook to take the Cloud, mobile data at scale, that's going to drive the transformative impact. And I think there's some people doing stuff here and there, pockets. And maybe there's some organizations that have a cadence of managers, that are doing compliance, security, blah, blah, blah. But you have a vision on this. And some information that you're tracking around. An architecture that would bring it to scale. Could you share your thoughts on this operational model of Cloud, at a management level? >> Well, part of this is also based on your own analyst, Peter Boris. When he says, "The problem with data "is that its value is inverse to its half life." So, what the Enterprise has to do is it has to get to analyzing and making this data valuable, much, much faster then it is right now. And Chris Sellender of Unifi recently said, "You know, the problem's not big data. "The problem's fast data." So, now, who is best positioned in the organization to do this? And I believe it's the COO. >> John: Chief Operating Officer? >> Chief Operating Officer. I don't think it's going to be the CIO. Because I'm trying to figure out who's got the problem. Who's got the problem of connecting the dots to improving the operation of the company? Who is in charge of actually creating an operating platform that the business can feed off of? It's the C Tower. >> John: Why not the CFO? >> No, I think the CFO is going to be a diminishing value, over time. Because a couple of reasons. First of all, we see it in Phillips. There's always going to be a fiduciary role for the CFO. But we're out of the world of capex. We're out of the world of balancing assets. Everything is now virtual. So really, the value of a CFO, as sitting on the tee, if I use the racquetball, the CFO standing on the tee is not going to bring value to the Enterprise. >> And the CIO doesn't have the business juice, is your argument? Is that right? >> It depends on the CIO. There are some CIO's out there-- >> Dave: But in general, we're generalizing. >> Generally not. Because they've come through the ranks of building applications, which now has to be thrown away. They've come through the ranks of technology, which is now less relevant. And they've come through the ranks of having huge budgets and huge people to deploy certain projects. All of that's going away. And so what are you left with? Now you're left with somebody who absolutely has to understand how to communicate with the business. And that's what they haven't done for 30 years. >> John: And stream line business process. >> Well, at least get involved in the conversation. At least get involved in the conversation. Now if I talk to business people today, and you probably do too, most of them will still say there's this huge communication gulf. Between what we're trying to achieve and what the technology people are doing with our goals. I mean, I was talking to somebody the other day. And this lady heads up the sales for a global financial institution. She's sitting on the business side of this. And she's like, "The conversation should be "about, if our company wants to improve "our cost income ratio, and they ask me, "as sales to do it, I have to sell 10 times "more to make a difference. "Then if IT would save money. "So for every Euro they save. "And give me an agile platform, "is straight to the bottom line. "Every time I sell, because of our "cost income ratio, I just can't sell against that. "But I can't find on the IT side, "anybody who, sort of, gets my problem. "And is trying to help me with it." And then you look at her and what? You think a hybrid solution's going to help her? (laughs) I have no idea what you're talking about. >> Right, so the business person here then says, "I don't really care where it runs." But to your point, you care about the operational model? >> Alan: Absolutely. >> And that's really what Cloud should be, right? >> I think everybody who's going to achieve anything from an investment in Cloud, will achieve it in the operating world. They won't just achieve it on the cost savings side. Or on making costs more transparent, or more commoditized. Where it has to happen is in the operating model. In fact, we actually have data of a very large, transportation, logistics company, who moved everything that they had, in an attempt to be in a zero Cloud. And on the benchmark, saved zero. And they saved zero because they weren't changing the operating model. So they were still-- >> They lifted and shifted, but didn't change the operational mindset. >> Not at all. >> But there could have been business value there. Maybe things went faster? >> There could have been. >> Maybe simpler? >> But I'm not seeing it. >> Not game changing. >> Not game changing, certainly yes. >> Not as meaningful, it was a stretch. >> Give an example of a game changing scenario. >> Well for me, and I think this is the next most exciting thing. Is this idea of platforms. There's been an early adoption of this in Telco. Where we've seen people coming in and saying, "If you stock all of this IT, as we've known it, "and you leverage the ideas of Cloud computing, "to have scalable, invisible, infrastructure. "And you put a single platform on top of it "to run your business, you can save money." Now, I've seen business cases where people who are about to embark on this program are taking a billion a year out of their cost base. And in this company, it's 1/7th of their total profit. That's a game changer, for me. But now, who's going to help them do that? Who's going to help them-- >> What's the platform look like? >> And a million's a lot of money. >> Let's go, grab a sheet of paper how we-- >> So not everybody will even have a billion-- >> But that gets the attention of certainly, the CEO, the COO, CFO says, "Tell me more." >> You're alluding to it, Dave. You need to build a layer to punch, to doing that. So you need to fix the data stewardship problem. You have to create the invisible infrastructure that enables that platform. And you have to have a platform player who is prepared to disrupt the industry. And for me-- >> Dave: A Cloud player. >> A Cloud player, I think it's a born in the Cloud player. I think, you know, we've talked about it privately. >> So who are the forces to attract? You got Microsoft, you got AWS, Google, maybe IBM, maybe Oracle. >> See, I think it's Google. >> Dave: Why, why do you think it's Google? >> I think it's because, the platforms that I'm thinking of, and if I look in retail, if I look in financial services, it's all about data. Because that's the battle, right. We all agree, the battle's on data. So it's got to be somebody who understands data at scale, understands search at scale, understands deep learning at scale. And understands technology enough to build that platform and make it available in a consumption model. And for me, Google would be the ideal player, if they would make that step. Amazon's going to have a different problem because their strategy's not going down that route. And I think, for people like IBM or Oracle, it would require cannibalizing too much of their existing business. But they may dally with it. And they may do it in a territory where they have no install base. But they're not going to be disrupting the industry. I just don't think it's going to be possible for them. >> And you think Google has the Enterprise chops to pull it off? >> I think Google has the platform. I would agree with Alan on this. Something, I've been very critical on Google. Dave brings this up because he wants me to say it now, and I will. Google is well positioned to be the platform. I am very bullish on Google Cloud with respect to their ability to moon shot or slingshot to the future faster, than, potentially others. Or as they say in football, move the goal posts and change the game. That being said, where I've been critical of Google, and this is where, I'll be critical, is their dogma is very academic, very, "We're the technology leader, "therefore you should use Google G Suite." I think that they have to change their mindset, to be more Enterprise focused, in the sense of understand not the best product will always win, but the B chip they have to develop, have to think about the Enterprise. And that's a lot of white glove service. That's a lot of listening. That's not being too arrogant. I mean, there's a borderline between confidence and arrogance. And I think Google crosses it a little bit too much, Dave. And I think that's where Google recognizes, some people in Google recognize that they don't have the Enterprise track record, for sure on the sales side. You could add 1,000 sales reps tomorrow but do they have experience? So there's a huge translation issue going on between Google's capability and potential energy. And then the reality of them translating that into an operational footprint. So for them to meet the mark of folks like you, you can't be speaking Russian and English. You got to speak the same language. So, the language barrier, so to speak, the linguistics is different. That's my only point. >> I sense in your statements, there's a frustration here. Because we know that the key to some really innovative, disruption is with Google. And I think what we'd all like to do, even while I was addressing the camera. I'd love to see Diane, who does understand Enterprise, who's built a whole career servicing Enterprises extremely well, I'd like to see a little bit of a glimpse of, "We are up for this." And I understand when you're part of the bigger Google, the numbers are a little bit skewered against you to make a big impact and carry the firm with you. But I do believe there's an enormous opportunity in the Enterprise space. And people are just waiting for this. >> Well Diane Greene knows the Enterprise. So she came in, she's got to change the culture. And I know she's doing it. Because I have folks at Google, that I know that work there, that tell me privately, that it's happening, maybe not fast enough. But here's the thing. If you walked in the front door at Google, Alan Nance, this is my point, and he said, "I have experience and I have a plan "to build a platform, to knock a billion "dollars off seven companies, that I know, personally. "That I can walk in and win. "And move a billion dollars to their "bottom line with your platform." They might not understand what that means. >> I don't know, you know I was at Google Next a few weeks ago, last month. And I thought they were more, to your point, open to listening. Maybe not as arrogant as you might be presenting. And somewhat more humble. Still pretty ballsy. But I think Google recognizes that it needs help in the Enterprise. And here's why. Something that we've talked about in the past, is, you've got top down initiatives. You've got bottom up initiatives. And you've got middle out. What frequently happens, and I'd love for you to describe your experiences. The leaders say, the top CXO's say, "Okay we're going." And they take off and the organization doesn't follow them. If it's bottoms up, you don't have the top down in premature. So how do you address that? What are you seeing and how do you address that problem? >> So I think that's a really, really good observation. I mean, what I see in a lot of the big transformations that I've been involved in, is that speed is of the essence. And I think when CEO's, because usually it's the CEO. CEO comes in and they think they've got more time than they actually have to make the impact in the Enterprise. And it doesn't matter if they're coming in from the outside or they've grown up. They always underestimate their ability to do change, in time. And now what's changed over the past few years, is the average tenure of a CEO is six years. You know, I mean, Jack Welch was 20 years at GE. You can do a lot of damage in 20 years. And he did a lot of great things at GE over a 20 year period. You've only got six years now. And what I see in these big transformation programs is they start with a really good vision. I mean Mackenzie, Bain, Boston. They know the essence of what needs to happen. >> Dave: They can sell the dream. >> They can sell the dream. And the CEO sort of buys into it. And then immediately you get into the first layer, "Okay, okay, so we've got to change the organization." And so you bring in a lot of these companies that will run 13 work streams over three years, with hundreds of people. And at the end of that time, you're almost halfway through your tenure. And all you've got is a new design. Or a new set of job descriptions or strategies. You haven't actually achieved anything. And then the layer down is going to run into real problems. One of the problems that we had at the company I worked at before, was in order to support these platforms you needed really good master data management. And we suddenly realized that. And so we had to really put in an accelerated program to achieve that, with Impatica. We did it, but it cost us a year and 1/2. At a bank I know, they can't move forward because they're looking at 700 million of technology debt, they can't get past. So they end up going down a route of, "Maybe one of these big suppliers "can buy our old stuff. "And we can tag on some transformational "deal at the back end of that." None of those are working. And then what happens is, in my mind, if the CEO, from what I see, has not achieved escape velocity at the end of year three. So he's showing the growth, or she's showing the digital transformation, it's kind of game over. The Enterprise has already figured out they've stalled it long enough, not intentionally. And then we go back into an austerity program. Because you got to justify the millions you've spent in the last three years. And you've got nothing to show for it. >> And you're preparing three envelopes. >> So you got to accelerate those layers. You got to take layers out and you've got to have a really, I would say almost like, 90 day iteration plans that show business outcomes. >> But the technology layer, you can put in an abstraction layer, use APIs and infrastructure as code, all that cool stuff. But you're saying it's the organizational challenges. >> I think that's the real problem. It is the real problem, is the organization. And also, because what you're really doing in terms of the Enterprise, is you're moving from a more traditional supply chain that you own. And you've matriculated with SAP or with Oracle. Now you're talking about creating a digital value chain. A digital value chain that's much more based on a more mobile ecosystem, where you would have thin text in one area or insurance text, that have to now fit into an agile supply chain. It's all about the operating model. If you don't have people who know how to drive that, the technology's not going to help you. So you've got to have people on the business side and the technology side coming together to make this work. >> Alan, I have a question for you. What's you're prediction, okay, knowing what you know. And kind of, obviously, you have some frustrations in platforms with trying to get the big players to listen. And I think they should listen to you. But this is going to happen. So I would believe that what you're saying with the COO, operational things radically changing differently. Obviously, the signs are all there. Data centers are moving into the Cloud. I mean this is radical stuff, in a good way. And so, what's your prediction for how this plays out vis a vis Amazon Web Services, Google Cloud Platform Azure, IBM Cloud SoftLayer. >> Well here's my concern a little bit. I think if Google enters the fray I think everybody will reconfigure. Because if we'd assume that Google plays to its strengths and goes out there and finds the right partners. It's going to reconfigure the industry. If they don't do that, then what the industry's going to do is what it's done. Which means that the platforms are going to be hybrid platforms that are dominated by the traditional players. By the SOPs, by the Oracles, by the IBMs. And what I fear is that there may actually be a disillusionment. Because they will not bring the digital transformation and all the wonderful things that we all know, are out there to be gained. So you may get, "We've invested all this money." You see it a little bit with big data. "I've got this huge layer. "I've got petabytes. "Why am I not smarter? "Why is my business not going so much better? "I've put everything in there." I think we've got to address the operating problem. And we have to find a dialogue at the C Suite. >> Well to your point, and we talked about this. You know, you look at the core of Enterprise apps, the Oracle stuff is not moving in droves, to the Cloud. Oracle's freezing the market right now. Betting that it can get there before the industry gets there. And if it does-- >> Alan: It's not. >> And it might, but if it does, it's not going to be that radical transformation you're prescribing. >> They have too much to lose. Let's be honest, right. So Oracle is a victim of it's own success, pretty much like SAP. It has to go to the Cloud as a defensive play. Because the last thing either of those want is to be disintermediated by Amazon. Which may or may not happen anyway. Because a lot of companies will disintermediate if they can. Because the licensing is such a painful element for most enterprises, when they deal with these companies. So they have to believe that the platform is not going to look like that. >> And they're still trying to figure out the pricing models, and the margin models, and Amazon's clearly-- >> You know what's driving the pricing models is not the growth on the consumer side. >> Right, absolutely. >> That's not what's driving it. So I think we need another player. I really think we need another player. If it's not Google, somebody else. I can't think who would have the scale, the money to-- >> The only guys who have the scale, you got 10 cents, maybe a couple China Clouds, maybe one Japan Cloud and that's it. >> To be honest, you raise a good point. I haven't really looked at the Ali Baba's and the other people like that who may pick up that mantle. I haven't looked at them. Ali Baba's interesting, because just like Amazon, they have their own business that runs on platforms. And a very diverse business, which is growing faster than Amazon and is more profitable than Amazon. So they could be interesting. But I'm still hopeful. We should figure this out. >> Google should figure it out. You're absolutely right. They're investing, and I thought they put forth a pretty good messaging at the Google Next. You covered it remotely but I think they understand the opportunity. And I think they have the stomach for it. >> We had reporters there as well, at the event. We just did, they came to our studio. Google is self aware that they need to work on the Enterprise. I think the bigger thing that you're highlighting is the operational model is shifting to a scale point where it's going to change stewardship and COO meaning to be, I like that. The other thing I want to get your reaction to is something I heard this morning, on the CUBE from Sean Connelly. Which that goes with some of the things that we're seeing where you're seeing Cloud becoming a more centralized view. Where IOT is an Edge case. So you have now, issues around architectural things. Your thoughts and reaction to this balance between Edge and Cloud. >> Well I think this is where you're also going to have your data gravity challenge. So, Dave McCrory has written a lot about the concept of data gravity. And in my mind, too many people in the Enterprise don't understand it. Which is basically, that data attracts more data. And more data you have, it'll attract more. And then you create all these latency issues when you start going out to the Edge. Because when we first went out to the Edge I think, even at Phillips, we didn't realize how much interaction needed to come back. And that's going to vary from company to company. So some company's are going to want to have that data really quickly because they need to react to it immediately. Others may not have that. But what you do have is you have this balancing act. About, "What do I keep central? "And what do I put at the Edge?" I think Edge Technology is amazing. And when we first looked at it, four years ago, I mean, it's come such a long way. And what I am encouraged by is that, that data layer, so the layer that Sean talks about, there's a lot of exciting things happening. But again, my problem is what's the Enterprise going to do with that? Because it requires a different operating model. If I take an example of a manufacturing company, I know a manufacturing company right now that does work in China. And it takes all the data back to its central mainframes for processing. Well if you've got the Edge, you want to be changing the way you process. Which means that the decision makers on the business need to be insitu. They need to be in China. And we need to be bringing, systems of record data and combining it with local social data and age data, so we get better decisions. So we can drive growth in those areas. If I just enable it with technology but don't change the business model the business is not going to grow. >> So Alan, we always loved having you on. Great practitioner, but now you've kind of gone over to the dark side. We've heard of a company called Virtual Clarity. Tell us about what you're doing there. >> So what we're vested in, what I am very much vested in, with my team at Virtual Clarity, is creating this concept of precision guided transformation. Where you work on the business, on what are the outcomes we really need to get from this? And then we've combined, I would say it's like a data nerve center. So we can quickly analyze, within a matter of weeks, where we are with the company, and what routes to value we can create. And then we'll go and do it. So we do it in 90 day increments. So the business now starts to believe that something's really going to happen. None of these big, insert miracle here after three year programs. But actually going out and doing it. The second thing that I think that we're doing that I'm excited about is bringing in enlightened people who represent the Enterprise. So, one of my colleagues, former COO of Unilever, we just brought on a very smart lady, Dessa Grassa, who was the CDO at JP Morgan Chase. And the idea is to combine the insights that we have on the demand side, the buy side, with the insights that we have on the technology side to create better operating models. So that combination of creating a new view that is acceptable to the C Suite. Because these people understand how you talk to them. But at the same time, runs on this concept of doing everything quickly. That's what we're about right now. >> That's awesome, we should get you hooked up with our new analyst we just hired, James Corbelius, from IBM. Was focusing on exactly that. The intersections of developers, Cloud, AI machine learning and data, all coming together. And IOT is going to be a key application that we're going to see coming out of that. So, congratulations. Alan thank you for spending the time to come in. >> Thanks for allowing me. >> To see us in the CUBE. It's the CUBE, bringing you more action. Here from DataWorks 2017. I'm John Furrier with my cohost Dave Vallante, here on the CUBE, SiliconANGLE Media's flagship program. Where we've got the events, straight from SiliconANGLE. Stay with us for more great coverage. Day one of two days of coverage at DataWorks 2017. We'll be right back.

Published Date : Apr 5 2017

SUMMARY :

Brought to you by Hortonworks. Thanks for coming on the CUBE. And one of the motivations that So the thing was, how do we get away from that has scaled to it. And I think that's something that we So, how about the data component? of moving the Enterprise forward. And it's not going to be, just So let me ask the question, because on And I believe it's the COO. I don't think it's going to be the CIO. So really, the value of a CFO, as sitting It depends on the CIO. Dave: But in general, And so what are you left with? "But I can't find on the IT side, Right, so the business And on the benchmark, saved zero. change the operational mindset. But there could have Give an example of a And in this company, it's But that gets the And you have to have a platform player a born in the Cloud player. You got Microsoft, you got AWS, Google, So it's got to be somebody who understands So, the language barrier, so to speak, And I think what we'd all like to do, But here's the thing. The leaders say, the top CXO's say, is that speed is of the essence. And at the end of that time, you're almost You got to take layers But the technology It is the real problem, And I think they should listen to you. the industry's going to in droves, to the Cloud. it's not going to be that radical So they have to believe that the platform is not the growth on the consumer side. the scale, the money to-- you got 10 cents, maybe I haven't really looked at the Ali Baba's And I think they have the stomach for it. is the operational model is shifting the business is not going to grow. kind of gone over to the dark side. And the idea is to combine the insights the time to come in. It's the CUBE, bringing you more action.

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