>> Narrator: Live from Las Vegas, it's theCUBE, covering UiPath Forward Americas 2019, brought to you by UiPath. >> Hi everybody welcome back to Las Vegas, we're at the Bellagio at UiPath Forward III, day two of theCUBE covers. theCUBE is a leader in live tech coverage. We go out to the events. We extract the signal from the noise. Erik Alexis here is the Vice President of Global Intelligent Process Automation at GE. Eric thanks for coming on. >> Yeah absolutely excited to be here. >> So, you guys have a COE, you're obviously heavily involved in essentially running the COE, is that right? >> Yeah that's my role at GE. I lead our Global Center of Excellence for intelligent process automation. Our journey started with UiPath a while back in 2016. So, it's been an incredible journey so far. >> And I want to get into that. So, before I do, I was struck by the Forrester analyst, Craig LeClair this morning made a statement. I don't know if you're in there, but he said, "Yeah COE, setting up a COE, "maybe that's asking too much." But I talk to a lot of people that have a center of excellence. Maybe it's definitional but what does your COE look like in terms of just it's role, size? >> Yeah it's a great question, so I think in terms of the role that we play more broadly, I mean we provide a lot of the technical expertise, the hands-on development and the operational support for our business units. And so we've really kind of developed that expertise over time, and we use our business units to really drive and identify the opportunities that come in through the COE. So, in terms of the size of the COE, we've got in total number of heads, we've got about 50 primarily technical resources there, that are supporting development as well as ongoing operation. >> Awesome, okay so let's talk about your journey. When did it start? What was the motivation behind it? How did you make the business case, and we'll get into it. >> Yeah so our journey started back in 2016, GE, we used to have a shared services organization that we had a very forward-thinking CEO at the time who wanted to really disrupt the way that we worked. And so RPA was something that was just coming out and kind of getting noticed by a lot of these shared services organizations. And so throughout the year we assessed a couple of technologies obviously landing on UiPath for a number of reasons. I would say in terms of our journey 2017 was kind of our year to prove the technology. We wanted to see if this stuff could really work long term and operate at scale. Given that I'm still here obviously, we proved that was correct and then 2018 was kind of the year of scaling and operationalizing kind of a sustainable model to support our business units across the board from an RPA standpoint. So, really building out a proper structure, building out the governance that goes along with building robots and building a kind of a resource team to continue to support the bots that we were at scale at that point, so maintaining those bots is critically important. And then 2019 has really been the year and I think the theme of this conference in general, a bot for every person I think that's the direction we're moving in 2019. We've kind of perfected the concept of the back office robot and the development of those, and running those at scale. And now we're moving towards a whole new market share when it comes to attended automation and citizen development. >> So, in '16 it was kind of kicking the tires it was almost like R&D. And then '17 was really essentially a proof-of-concept right so still a small team, a two piece kind of team kind of thing right? And then when you talked about scale, helped us understand what's involved in scale, I know it's also another big theme of this conference. What are the challenges of scaling and how did you resolve those? >> Yeah that's a very good question. I think it's a question that has been very common throughout this entire conference. I would say when I think about scaling what I've noticed over the past few years is that, the actual bot development is about 25% of the work that you need to do, right? When it comes to scale there is everything outside of the actual development is the important part. So, how are you funneling opportunities into a pipeline, how are you streamlining the entire process reengineering of fitting an RPA into an existing process, what's governance you have in place to make sure that the code of that development is clean and can be maintained long term? And then more importantly I think that people overlook, people think of scale as being able to develop a lot of bots. I think more importantly what scale is is being able to efficiently maintain a large portfolio of bots, and that's what I've realized this year. We've got now about 300 automations in production and your reputation as an organization is really on how well you maintain those bots, because if your bots are consistently failing, and you're not fixing them quick enough for your functional users to leverage them, then you lose a lot of credibility. So, I think that's been a big learning for us as we reach scale. >> That's interesting I mean I think about scripts, how fragile scripts are and you got a lot of 'em, and they almost always break. And so what is the discipline that allows you to have that quality of bot that is maintainable? Is it a coding discipline? Is it a governance? Is there other automation involved in maintaining those bots? >> No there is and I think the team that's under me, my technical team has done a phenomenal job of setting this up, but we've got some very rigorous standards that we've put in place around. We do have reusable components for example that need to be used on every single robot that goes into production, so that when I look at for example a bots login, that bots login is going to be the same across all my bots. So, every developer who's going to be maintaining that bot knows what it is and how to fix it. I think the standardized logging as well to make sure that we've got robust logging for every single robot is incredibly important because again that's going to be critical when somebody goes to try and fix the bot. >> So you are like an app store, you're enforcing rules like Apple for developers. >> Exactly. >> Okay so let me ask you a question. See now several years in if you had a mulligan, what would you do differently? >> Yeah I think that's another very good question. I think when you first start with this technology, it's unbelievably exciting, because it's something that you can immediately see the difference and the impact it can make, and so you want to try and apply it everywhere to everything, to solve every problem. And I think that's kind of where we got a little ahead of ourselves. We weren't as thoughtful as we should have been when we started taking in the use cases that we were bringing in and while I sit here and tell you that we've got 300 automations in production, I've also decommissioned about 90 automations as well. Because you kind of live and you learn as you go through that process on. This doesn't make sense for RPA. It's not driving the value anymore. It's not driving the right value for the company. >> And is that because the process needs to be reworked before it's automated or there are other factors? >> Yeah I think there's a couple of factors there. I think number one, some bots are intentionally just for short-term use. We look across the portfolio, some bots you design for to operate for two weeks for a massive for example document transition or something like that. So, that's a common reason for decommissioning. I would say secondly you just picked the wrong process. It's not big enough. You think this is perfect for RPA, but it's saving somebody maybe five or 10 minutes a week, which in reality do you really want to put all the effort and to continue to maintain something like that on a back office level? So, I think the size of the processes and the complexity you've got to be thoughtful about as well. >> Thinking about a bot for every worker, what does that actually look like? Is that like you get a laptop and you get a bot? How does that actually manifest itself? >> Yeah I think as I've talked to some of the teams and Daniel as well about this, it's really around I mean imagine opening it up just like any other application on your computer and Excel, you've got that sitting on your desktop and you use that for a number of different things. I think that's kind of how I envision it and everyone when they come into GE, they'll get their laptop and it's part of their kind of package of software that they get. One of them will be UiPath and I think again if GE where I see that as the future. We've got to be thoughtful about how that's rolled out because you want to make sure it's done the right way and you want to make sure that that succeeds and what comes along with that is a lot of education. There's a lot of people that need to be educated on the technology in order to roll that out effectively. >> It's part of the onboarding part, just part of the HR onboarding, and so you open up your laptop and based on your role you'll have a library of bots that are applicable for your job. Is that kind of what you envision? >> Again I think that's kind of the future state and so HR will have a common library that they can pull from and Finance will have a common library that they can pull from. And I think the announcement this weekend of or this week of our StudioX is going to make life significantly easier. So, if you need to kind of edit any of those components or make any custom steps, you can do that with StudioX, but I think having a pre-built set of bots by function would be extremely important. >> And StudioX is the citizen developer right? So, okay now how do you then enforce the edicts of the COE if Dave Vallente's writing automations. >> It's honestly a question that we haven't answered yet and I think that's the piece that we're trying to solve for now, to roll it out more broadly. And I think part of it's going to be training right? Educating the broader group, part of it is giving them access to front office robots and so you do have the code back at the orchestrator so that you can see kind of what's going on and make sure if there are massive changes that need to be made, you can make some of that centrally, so I think figuring out how to centrally maintain and store some of that code is going to be important. >> And the idea of moving beyond this what they call this morning the snowflake into the snowball. So, reusable components is something that I've heard a lot about. That's not trivial yeah right because mapping the right component for the right job is always going to be some kind of unique, not always, but there could be some unique element to put in words. So, what are your thoughts on kind of future? I mean we touched on some of them. It sounds like even though you started early, 2016, it sounds like you still got a long way to go. What's the roadmap look like for you guys? >> Well it's really never-ending because you know you see how quickly the industry is changing and how quickly these automation platforms. I think we're at the point now where these are no longer RPA platforms. They're automation platforms with all of the different features and you look at the broader ecosystem of the technologies being pulled into play. I think it's moving from robotics process automation into intelligent process automation. And that's really our goal and leveraging the ecosystem that the UiPath is built is I think what we want to do more of going forward. >> And the primary measurement of value to you, I'm inferring is time saved from doing non-differentiated tasks, is that really a key metric or are there others that you're looking at, bottom line dollars that you're saving or what? >> I think the way that we measure productivity is really in three major buckets. One is the hours saved so that employees can do other things and I would say that is far and away, the largest bucket that we have. But I think additionally you've got to think about direct cost out. I mean if my finance team comes to me and says, we're thinking about hiring a person to do this why not an RPA? Why can't we use an RPA to do that instead? So, it's not like anyone's losing their job over. It's just figuring out a better way to supplement your existing workforce. Then I would say the third way really is thinking about the compliance element of things. So, and that's often overlooked. You may not save anyone time. You may not save anyone hours or dollars, but what you can do is expand for example in your audit function, expand your testing or sampling of a certain criteria, instead of sampling maybe the top 20 risky units, you can now sample a 100% of a population, which fundamentally changes how you can get comfortable with your financial statements and other elements of the compliance. >> Talking earlier just I asked is sampling dead because of RPA right? >> It really feels like that you know. >> Dave: Eric it's super knowledgeable. I really appreciate you coming on. >> Absolutely. >> Dave: Congratulations on all your success really. >> Thank you very much Dave. I appreciate it. >> You're welcome. All right keep it right there everybody, we will be back with our next guest right after this short break. We're live from UiPath Forward III from Las Vegas. You're watching theCUBE. (upbeat music)

(upbeat music) >> Hey everyone, welcome back to theCUBE's continuous coverage of AWS reinvent 2021, I'm Lisa Martin. This is day four for theCUBE. We have two live sets, I'm here with Dave Nicholson, Dave two live sets, 100 guests on theCUBE for AWS Re:Invent 2021. >> Not all at the same time. >> Not all-- That's a good, he brings up a good point, not all at the same time, we are pleased to welcome Gretchen Peri who's going to be sitting down and chatting with Dave with me next. She is from Slalom, at the US State Local and Education, SLED leader. We're going to be talking about Slalom and AWS digital innovation in the public sector. Gretchen, it's a pleasure to have you on the program. >> Thank you for having me. >> For the audience that might not be familiar with Slalom before we dig into AWS and SLED in particular, talk to us about Slalom and what it is that you guys do. >> I'd love to. So Slalom's a modern business and technology consulting firm. We're headquartered in Seattle Washington, we have about 11,000 employees across 40 markets globally. And what's different about Slalom is we're local model firm, so our consultants live and work in the same locale, which means we're personally invested in our client's outcomes because they impact us directly in the communities in which we live. >> And you've been in a leader in SLED for a long time, talk to us about what's going on on SLED these days. Obviously the last 18, 22 months have been quite dynamic, but what's going on in the market? >> Absolutely. What we're seeing is an extra emphasis on data data data, obviously, data is king and data is queen right now, right? So when the pandemic hit, we saw a ton of digital innovation, as our SLED clients needed to get their services online. That had been going on for a long time but it absolutely accelerated when then pandemic it and then it was a public health hazard, to ask people to come into the location. So what we saw was for constituents, we saw just absolute blast of omni-channel service delivery, so we saw the advent of SMS and chat bots and the more tech services, right? Leveraging AWS Lex and Transcribe and other services of AWS really helped our SLED clients react to the pandemic and respond to make sure that their constituents were receiving the digital services they needed, and their employees were able to be productive at home. >> Well, that was one of the keys the employee productivity, the student productivity, when everything's went remote overnight, one of the most challenging things was the demand for collaboration tools. Then of course, there's security challenges, there was concerns there, but talk to us about, and we've seen so much innovation out of AWS in the last, I mean always, but even what they announced the last couple of days, the innovation flywheel of AWS is probably stronger than ever enabling organizations like SLED, FED, private sector, public sector to be data-driven. >> Absolutely. One thing that's really exciting right now is to see the evolution of how our SLED customers are thinking about data. So we've been working on like integrated visions in SLED for a long time, integrated justice, integrated health care, integrated eligibility, how do we bring all this information together so that we can supply the right information to the right people at the right time to deliver the right outcomes? And AWS has been a huge part of that. It's not the journey to get to the cloud, it's the destination once you get there, right? Because then you can leverage all their AIML tools, IOT, edge, container, blockchain. And so our customers, who have already made that switch to AWS, they're able to take advantage of that. It's not what you can do in the cloud anymore is what you can't do without it really, right? So we're seeing tons of advances, intelligent document processing is one area I'm really excited about for our SLED clients, and working very closely with AWS to make sure that we see our clients adopt that and achieve the value out of it. >> AWS is dominating the IT space, although what five to 15% of IT is in the cloud, which means the vast majority is still on premises. So there's a huge potential for growth. In this sort of wild, wild west that we're in, there are all sorts of different kinds of services and consultancy partners, that are seeking to bridge the gap between the technology that AWS delivers and the outcomes that customers desire. >> Right. >> Now I've had a couple of experiences actually with Slalom folks, that were very, very positive. And what I saw was that the Slalom people were embedded in a way that you don't see some other consultancies embedded. You mentioned that something that piqued my interest, you talked about the local nature, is that your superpower? Because it sure seemed to be powerful to see this person where some of these very, very large global companies had no idea who Slalom was, until they realized that Sally was the one who had the best relationship with the customer. So Sally's a fictitious name that I just came up with, but I want to hear a little more about Slalom and your superpower and your differentiation. 'Cause it's a crowded space, you've got global systems integrators, you got all kinds of people. What makes you special? >> It's really the breadth of professional services that we provide, combined with AWS's cloud technologies and services. What we do I think a little bit differently is whereas AWS works back from the customer, we work back from our customer's vision. And so what we do with our, especially with our SLED clients, but with all of our commercial clients, is we say, what is your business strategy and your business vision, and how do we design the technology solutions, working back from that. So you're able to answer the business questions through data-driven tech technology, that's really important to you. And when we look at that, it's not just generating data to create information to then garner insights, but let's go one step further. And how do we create knowledge and how do we create wisdom this space, right? Where we understand situational awareness, common operating pictures, that's really what we want to do. When we talk about criminal justice and public safety, I love how we're thinking about joining data in new and different ways. It's not necessarily applications anymore, right? How do we create data as a service? How do we create documents as a service? Where we're pulling out the exact information that we need from semi-structured, structured and unstructured data and providing it to the right people to make the right decisions. >> Talk to us about intelligent document processing, a lot of buzz going on with that. What is it? Where are public sector agencies in terms of embracing it, adopting it and having it be part of that vision? >> Yeah, the promise is huge for IDP. What IDP is basically is leveraging AWS AI services to create intelligent automation solutions that help extract information from printed documents, digital documents, paper documents, right? So leveraging AWS services like Amazon Textract, Comprehend, Augmented AI, things like, and Kendra. What that does in combination, is it helps our clients unlock the data from, you can imagine government, it's heavy, heavy documents, and in criminal justice and public safety in particular, these documents represent key milestones and processes, right? So we're never going to get rid of documents in SLED, they're going to be used in perpetuity, it's important for accessibility and practicality and everything else. But what this does is it lets us unlock the data from those kind of stale documents and create it into usable formats for so that people can make decisions. >> That's critical because there's, I mean, we talk about in Amazon, AWS been this week have been talking about it and Dave, we have too. Every company, public sector, private sector, it needs to be a data-driven company, but they need to be able to extract that value from the data and the data isn't just digital. And that's something that, to your point, that's going to be persistent within SLED, they have to be able to extract the value from it quickly. >> Yes. >> To be able to see what new products and services can we deliver? What directions should we be going? And what outcomes should we be driving based on that visibility? And that visibility is critical. >> Exactly. And right now we absolutely have to support our communities. And we have a lot of our slide clients who are talking about this is a time where we don't just respond in a way that helps people kind of navigate this pandemic, we have to build resiliency as well in our communities and we do that through helping people through these hard times and making sure that we're moving our services to places where people can access them, in any language from wherever they are, right? We're having to actually go into people's homes on their couches, to deliver government services. Where we used to bring them into a single location. >> Right. >> Typically public sector has often been seen as lagging behind the private sector in some ways, the pandemic, as I'm sure ignited a fire with, especially with federal acknowledgement of things that need to happen, budgets flowing, are you seeing even more of an awakening from a cloud perspective within public sector? >> We are, we are and we're seeing really interesting initiatives pop up like, behavioral health initiatives, that are meant to address some really serious concerns in our country like nationwide 988 suicide prevention projects, right? And the federal government is providing a lot of funding to states and local governments so that they can help take care of our communities and also make sure that we're moving our services online so everyone can access them. >> I'm curious about that point, the funding. >> Yeah. >> Do you find yourself almost in the position of prize patrol? Where were some of the state local governments aren't necessarily as aware as Slalom might be of programs that are coming down immediately. Is that part of the conversation? >> It is part of the conv-- That's a great point because what we do is we look at what's coming down from the federal government, how is it going to flow to the states? How is it going to land ultimately, and then helping governments come up with a strategy for how to spend that money in the right way is really important, right? And we saw with some of the funding that come out, that there were delays on getting like eviction prevention funding out to folks. And so making sure that we have the technology to support those outcomes. >> It's all about outcomes. >> Yes. >> Speaking of outcomes, something I want to congratulate Slalom on is winning the first ever National Essay Partner of the Year for the US. >> Yes. >> Nice. >> That's awesome, congratulations. >> What does that mean for Slalom and what direction can we expect the Slalom and AWS partnership to go? >> Up and up. >> To the right? >> Yes. For us it's about validating the relationship that we have, right? It's really, when we walk into a client conversation, what we want to do is develop trust that our clients know we're looking for their best interest and their best outcomes. We're not trying to sell them something we're trying to solve their problems together. And it validates that for us, our partnership with AWS obviously is so important. And what we're doing in terms of making sure that we have a strong bench full of certifications and we can go to market together in the right way for our clients. This is a huge award and the recognition is very powerful for us. >> Well, congratulations. And so last question, you mentioned AWS and we always talk about when we talk with them at their event, we talk about their customer obsession, right? They work backwards, as you said, from the customer. And you guys from customer vision. Talk to me about when you go in jointly together, work with the customer, what does that alignment look like? >> Absolutely. So what we typically do is, Slalom will focus on what is the business outcome that we want to generate? And we will help design, how are we going to go about solving that problem? And how is AWS going to help support us with enabling technology? And so we will go into client conversations together, say, what is the outcome we want from this initiative together? And how are both partners going to get aligned to support the client in that conversation, in that product. >> That alignment is (indistinct). Gretchen, thank you for joining Dave and me today, talking about Slalom, what you guys are doing, how you're really helping organizations in SLED transform and not just survive challenging time but really thrive and be data-driven. We appreciate your insights and congratulations again on the National Essay Partner of The Year. >> Thank you so much. >> All right. For Dave Nicholson, I'm Lisa Martin. You're watching theCUBE, the global leader in live tech coverage. (lively music)

(upbeat music) >> Welcome back to theCUBE's continuous coverage of AWS re:invent 2021. I'm here with my co-host John Furrier and we're running one of the largest, most significant technology events in the history of 2021. Two live sets here in Las Vegas, along with our two studios. And we are absolutely delighted. We're incredibly delighted to welcome a returning alumni. It's not enough to just say that you're an alumni because you have been such a fixture of theCUBE for so many years. Annie Weinberger. And Annie is head of product marketing for applications at AWS. Annie, welcome. >> Thank you so much, it's great to be back. >> It's wonderful to have you back. Let's dive right into it. >> Okay. >> Talk to us about Connect. What does that mean when I say Connect? >> Yes, well, I think if we talk about Amazon Connect, we have to go back to the beginning of the origin story. So, over 10 years ago, when Amazon retail was looking for a solution to manage their customer service and their contact center, we went out and we looked at different solutions and nothing really met our needs. Nothing could kind of provide the scale that we needed at Amazon, or could really be as flexible as we needed to ensure that we're our customer obsession could come through in our customer service. So we built our own solution. And over the years, customers were coming to us and asking, you know, what do you use for your customer service technology? And so we launched Amazon Connect, our omni-channel cloud contact center solution just over four years ago. And it is the one of the fastest growing services at AWS. We have tens of thousands of customers using it today, like Capital One into it, Bank of Omaha, Mutual of Omaha, Best Western, you know, I can go on and on. And they're using it to have over 10 million interactions with customers every day. So it's, you know, growing phenomenally and we just couldn't be more proud to help our customers with their customer service. >> So, yeah. Talk about some of the components that go into that. What are the sort of puzzle pieces that make up AWS Connect? Because obviously connecting with a customer can take a whole bunch of different forms with email, text, voice. >> Yeah >> What's included in that? >> So it's an omni-channel cloud contact center. It provides, you know, any way you want to talk to your customers. There's traditional methods of voice. There's automated ways to connect. So IVRs or interactive voice responses where you call with voice prompts, there's chat, you know. We have Lex Bots that use the same technology that powers Alexa for natural language understanding. And I think customers really like it for a few reasons. One is that unlike kind of other contact center solutions, you can set it up in minutes. You know, American Preparatory Academy had to set up a contact center, they did it in two days. And then it's very, very easy to customize and use. So another example is, you know, when Priceline was going through COVID and they realized their call volume went up 300% overnight, and everybody was just sitting near the queue waiting to talk to an agent. So in 20 minutes, we were able to go in and very easily with a drag and drop interface, customize the ad flow so that people who had a reservation in the next 72 hours were prioritized. So very, very easily. >> You just jumped the gun on me. I was going to ask this because we never boarding that Connect during the pandemic was a huge success. >> Annie: Yes. >> It was many, many examples where people were just located, disrupted by the pandemic. And you guys had tons of traction from government public sector to commercial across the board. Adam Solecki told me in person a couple weeks ago that it was on fire, Connect was on fire. So again, a tailwind, one of those examples with the pandemic, but it highlights this idea or purpose built, ready to go. >> Pre-built the applications. >> Pre-built application. This is a phenomenon. >> It's moving up the stack for AWS. It's very exciting. I think, yeah, we had over 5,000 new contact centers stood up in March and April of 2020 alone. >> Dave: Wow. >> Give it some scale, just go back to the scale piece. Cause this is like, like amazing to stand up a call center like hours, days. Like this is like incredible to, give us some stats on some examples of how fast people were standing up Connect. >> Yeah, I mean, you could stand it up overnight. American Preparatory Academy, as I mentioned did it in two days, we had, you know, this county of Los Angeles did theirs I think at a day. You could go and right now you don't need any technical expertise, even though you have some. >> theCUBE call center, we don't need people calling. >> We had everyone from a Mexican restaurant needed to take to go orders. Cause now it's COVID and they don't have a call. They've been able to set that up, grab a phone number and start taking takeout orders all the way to like capital one, you know, with 40,000 agents that need to move remote overnight. And I think that it's because of that ease to set up, but also the scale and the way that we charge. So, you know, it's AWS consumption-based pricing. You only pay for the interactions with customers. So the barrier to entry is really, really low. You don't have to migrate everything over and buy a bunch of new licenses. You can just stand it up and you're only charged for the interactions with customers. And then if you want to scale down like into it, obviously tax season they're bringing on a lot more agents to handle calls, when those agents aren't really needed for that busy time, you're not paying for those seats. >> You're flex. Take me through the, okay, that's a win, I get that. So home run, great success. Now, the machine learning story is interesting too, because you have the purpose-built platform. There's some customizations that can happen on top of it. So it's not just, here's a general purpose piece of software. People are using some customizations. Take us through the other things. >> Well, the exciting thing is they're not even real customizations because we're AWS, we can leverage the AML services and built pre-built purpose-built features. So there it's embedded and you know, Amazon Connect has been cloud native and AI born since the very beginning. So we've taken a lot of the AI services and built them into you don't need any knowledge. You don't have to know anything about AIML. You can just go in and start leveraging it. And it has huge powerful effects for our customers. We launched three new features this year. One was Amazon Wisdom. That's part of Amazon Connect. And what that does is, you know, if you're an agent and you're on the phone and customer's asking questions, today what they have to do is go in and search across all these different knowledge repositories to find the answer or, you know, how do I issue a refund? You know, we're hearing about this feature that's broken on our product. We're listening behind the scenes to that call and then just automatically providing the knowledge articles as they're on the call saying, this is what you should do, giving them recommendations so we can help the customer much more quickly. >> I love them moving up the stack. Again, a huge fan of Connect. We've highlighting in all of our stories. It's a phenomenon that's translating to other areas, but I want to tie back in where it goes next cause on these keynotes, Adam Solecki's and today was Swami, the conversations about a horizontal data plane. And so as customers would say, use Connect, I might want, if I'm a big customer I want to integrate that into my data because it's voice data, it's call centers, customer data, but I have other databases. So how do you guys look at that integration layer snapping it together with say, a time series database, or maybe a CRM system or retail e-commerce because again, it's all data but it's connected call center. Some may think it's silo, but it's not really siloed. So, I'm a customer. How do I integrate call center? >> Yeah and it's, you know, we have a very strong partner with Salesforce. They're actually a reseller of Connect. So we work with them very, very closely. We have out of the box integrations with Salesforce, with your other, you know, analytics databases with Marketo with other services that you need. I think again, it's one of the benefits of being AWS, it's very extensible, very flexible, and really easy to bring in and share the data that we have with other systems. >> John: So it's not an issue then. >> One of the conversation points that's come up is the, this idea that a large majority of IT Spend is still on premises today. In other words, the AWS total addressable market hasn't been tapped yet. And, you imagine going through the pandemic, someone using AWS Connect to create a virtual call center, now as we hopefully come out and people some return to the office, but now they have the tools to be able to stay at home and be more flexible. Those people, maybe they weren't in the cloud that much before. But to John's point, now you start talking about connecting all of those other data sources. Well, where do those data sources belong? They belong in AWS. So, from your perspective, on the surface it looks like, well, wait, you have these products, but really those are gateways to everything else that AWS does. Is that a fair statement? >> I think it's very, yeah. Absolutely. >> Yeah. >> The big thing I want to get into is okay, we're, I mean, we don't have a lot of people calling for theCUBE but I mean, we wouldn't use the call center, but there's audio involved. Are people more going back to the old school phones for support now with the pandemic? Cause you've mentioned that earlier about the price line, having more- >> I think it's, you know, when we talk to our customers too, it's about letting, letting any customer contact you the way they want to. You know, we, you know, I was talking to Delta, spoke with us yesterday in the business application leadership session. And she said, you know, when someone has a flight issue, I'm sure you can attest to this. I did the same thing. They call, you know, if your, if your flight got canceled or it's looking like it's going to keep pushing, you don't necessarily want to go, you know, use a chat bot or send an email or a text, but there's other use cases where you just want a quick answer, you know, if you contact, I haven't received my product yet, you know, it said it was shipped, I didn't get it. I don't necessarily want to talk to someone, but so, it's just about making that available. >> On the voice side, is it other apps are integrating voice? So what's the interface to call center? Is it, can I integrate like an app voice integrated through the app or it's all phone? >> Because for the agents, there's an agent UI. So they'll see kind of calls that they have in their queue coming up, they'll see the tasks that they have to issue or refund. They'll see the kind of analytics that they have. The knowledge works. There's a supervisor view, so they could go see, you know, we with contact lens for Amazon Connect, we had a launch this, you know, this week, every event around contact lens, it lets you see the trends and sentiment of what's going on the call. It gives them like those training moments. If people aren't using the standard sign-off or the standard greeting on the call, it's a training moment and they can kind of see what's happening and get real-time alerts. If two keywords of a customer saying they cancel into the call, that can get a flag and they can go in and help the agent if necessary. So. >> All kinds of metadata extraction going on in real time. >> Yeah. >> How do you, how would AWS to go through the process of determining what should be bespoke solution hearing versus something that can be productized? And we know there are 475 different kinds of instances. However, you can come up with a package solution where people could pick features and get up and running really quickly. How is that decision making process? >> Well, I mean, you know, 90% at least of what we do build, it comes from what our customers ask for. So we don't, it's the onus is not on us. We listen to our customers, they tell us what they want us to build. Contact center solutions are their line of business applications are purchased by business decision makers and they're used to doing more buying than building. So they wanted to be more out of the box, more like pre-built, but we still are AWS. We make it very, very extensible, very easy to customize, like pull in other data sources. But when we look at how we are going to move up the stack and other areas, we just continue to listen to our customers. >> What's the biggest thing you learned in the pandemic from the team? What's the learnings coming out of the pandemic as hybrid world is upon us? >> I mean, I think a few things with, you know, starting, as you mentioned with the cloud, that the kind of idea of a contact center being a massive building, usually in the middle of America where, you know, people go and they sit and they have conversations. If that was really turned on its head and you can have very secure and accessible solutions through the cloud so that you can work from anywhere. So that was really fantastic to see. >> That's going to be interesting to see moving forward. How that paradigm shifts some centralized call centers, but a lot of this aggregated work that can be done. >> I mean, who knows the, you know, gig economy could be in the contact center, you know. >> Yeah, absolutely >> Yeah >> Maybe get some CUBE hosts, give us theCUBE Connect. We get some CUBE hosts remote. >> That's important work, yeah. >> We need, we need to talk. I got to got my phone number in that list. Annie, it's been fantastic to have you. >> Thank you guys so much. I really appreciate it. >> For John Furrier, this is Dave Nicholson telling you, thank you for joining our continuous coverage of AWS reinvent 2021. Stick with theCUBE for the best in hybrid event coverage. (upbeat music)

>> Okay. We want to pick up on a couple of themes that Mick discussed, you know, supercharging your business with AI, for example, and this notion of getting hybrid right. So right now we're going to turn the program over to Rob Bearden, the CEO of Cloudera and Manuvir Das who's the head of enterprise computing at NVIDIA. And before I hand it off to Rob, I just want to say for those of you who follow me at the Cube, we've extensively covered the transformation of the semiconductor industry. We are entering an entirely new era of computing in the enterprise and it's being driven by the emergence of data intensive applications and workloads. No longer will conventional methods of processing data suffice to handle this work. Rather, we need new thinking around architectures and ecosystems. And one of the keys to success in this new era is collaboration between software companies like Cloudera and semiconductor designers like NVIDIA. So let's learn more about this collaboration and what it means to your data business. Rob, take it away. >> Thanks Mick and Dave. That was a great conversation on how speed and agility is everything in a hyper competitive hybrid world. You touched on AI as essential to a data first strategy in accelerating the path to value and hybrid environments. And I want to drill down on this aspect. Today, every business is facing accelerating change. Everything from face-to-face meetings to buying groceries has gone digital. As a result, businesses are generating more data than ever. There are more digital transactions to track and monitor now. Every engagement with coworkers, customers and partners is virtual. From website metrics to customer service records and even onsite sensors. Enterprises are accumulating tremendous amounts of data and unlocking insights from it is key to our enterprises success. And with data flooding every enterprise, what should the businesses do? At Cloudera, we believe this onslaught of data offers an opportunity to make better business decisions faster and we want to make that easier for everyone, whether it's fraud detection, demand forecasting, preventative maintenance, or customer churn. Whether the goal is to save money or produce income, every day that companies don't gain deep insight from their data is money they've lost. And the reason we're talking about speed and why speed is everything in a hybrid world and in a hyper competitive climate, is that the faster we get insights from all of our data, the faster we grow and the more competitive we are. So those faster insights are also combined with the scalability and cost benefit that cloud provides. And with security and edge to AI data intimacy, that's why the partnership between Cloudera and NVIDIA together means so much. And it starts with a shared vision, making data-driven decision-making a reality for every business. And our customers will now be able to leverage virtually unlimited quantities and varieties of data to power an order of magnitude faster decision-making. And together we turbo charged the enterprise data cloud to enable our customers to work faster and better, and to make integration of AI approaches a reality for companies of all sizes in the cloud. We're joined today by NVIDIA's Manduvir Das, and to talk more about how our technologies will deliver the speed companies need for innovation in our hyper competitive environment. Okay, Manuvir, thank you for joining us. Over to you now. >> Thank you Rob, for having me. It's a pleasure to be here on behalf of NVIDIA. We're so excited about this partnership with Cloudera. You know, when, when NVIDIA started many years ago, we started as a chip company focused on graphics. But as you know, over the last decade, we've really become a full stack, accelerated computing company where we've been using the power of GPU hardware and software to accelerate a variety of workloads, AI being a prime example. And when we think about Cloudera, and your company, your great company, there's three things we see Rob. The first one is that for the companies that were already transforming themselves by the use of data, Cloudera has been a trusted partner for them. The second thing we've seen is that when it comes to using your data, you want to use it in a variety of ways with a powerful platform, which of course you have built over time. And finally, as we've heard already, you believe in the power of hybrid, that data exists in different places and the compute needs to follow the data. Now, if you think about NVIDIA's mission going forward to democratize accelerated computing for all companies, our mission actually aligns very well with exactly those three things. Firstly, you know, we've really worked with a variety of companies to date who have been the early adopters using the power acceleration by changing their technology and their stacks. But more and more we see the opportunity of meeting customers where they are with tools that they're familiar with, with partners that they trust. And of course, Cloudera being a great example of that. The second part of NVIDIA's mission is we focused a lot in the beginning on deep learning where the power of GPU is really shown through. But as we've gone forward, we found that GPU's can accelerate a variety of different workloads from machine learning to inference. And so again, the power of your platform is very appealing. And finally, we know that AI is all about data, more and more data. We believe very strongly in the idea that customers put their data, where they need to put it. And the compute, the AI compute, the machine learning compute, needs to meet the customer where their data is. And so that matches really well with your philosophy, right? And, and Rob, that's why we were so excited to do this partnership with you. It's come to fruition. We have a great combined stack now for the customer and we already see people using it. I think the IRS is a fantastic example where, literally, they took the workflow they had, they took the servers they had, they added GPUs into those servers. They did not change anything. And they got an eight times performance improvement for their fraud detection workflows, right? And that's the kind of success we're looking forward to with all customers. So the team has actually put together a great video to show us what the IRS is doing with this technology. Let's take a look. >> How you doing? My name's Joe Ansaldi. I'm the branch chief of the technical branch in RAS. It's actually the research division, research and statistical division of the IRS. Basically, the mission that RAS has is we do statistical and research on all things related to taxes, compliance issues, fraud issues, you know, anything that you can think of basically, we do research on that. We're running into issues now that we have a lot of ideas to actually do data mining on our big troves of data, but we don't necessarily have the infrastructure or horsepower to do it. So our biggest challenge is definitely the, the infrastructure to support all the ideas that the subject matter experts are coming up with in terms of all the algorithms they would like to create. And the diving deeper within the algorithm space, the actual training of those algorithms, the number of parameters each of those algorithms have. So that's, that's really been our challenge now. The expectation was that with NVIDIA and Cloudera's help and with the cluster, we actually build out to test this on the actual fraud detection algorithm. Our expectation was we were definitely going to see some speed up in computational processing times. And just to give you context, the size of the data set that we were, the SME was actually working her algorithm against was around four terabytes. If I recall correctly, we had a 22 to 48 times speed up after we started tweaking the original algorithm. My expectations, quite honestly, in that sphere, in terms of the timeframe to get results, was it that you guys actually exceeded them. It was really, really quick. The definite now term, short term, what's next is going to be the subject matter expert is actually going to take our algorithm run with that. So that's definitely the now term thing we want to do. Going down, go looking forward, maybe out a couple of months, we're also looking at procuring some A-100 cards to actually test those out. As you guys can guess, our datasets are just getting bigger and bigger and bigger, and it demands to actually do something when we get more value added out of those data sets is just putting more and more demands on our infrastructure. So, you know, with the pilot, now we have an idea with the infrastructure, the infrastructure we need going forward and then also just our in terms of thinking of the algorithms and how we can approach these problems to actually code out solutions to them. Now we're kind of like the shackles are off and we can just run a, you know, run to our heart's desire, wherever our imaginations takes our SMEs to actually develop solutions. Now have the platforms to run them on. Just kind of to close out, we really would be remiss, I've worked with a lot of companies through the year and most of them been spectacular. And you guys are definitely in that category, the whole partnership, as I said, a little bit early, it was really, really well, very responsive. I would be remiss if I didn't thank you guys. So thank you for the opportunity. Doing fantastic. and I'd have to also, I want to thank my guys. my staff, Raul, David worked on this, Richie worked on this, Lex and Tony just, they did a fantastic job and I want to publicly thank them for all the work they did with you guys and Chev, obviously also is fantastic. So thank you everyone. >> Okay. That's a real great example of speed and action. Now let's get into some follow up questions guys, if I may, Rob, can you talk about the specific nature of the relationship between Cloudera and NVIDIA? Is it primarily go to market or are you doing engineering work? What's the story there? >> It's really both. It's both go to market and engineering The engineering focus is to optimize and take advantage of NVIDIA's platform to drive better price performance, lower cost, faster speeds, and better support for today's emerging data intensive applications. So it's really both. >> Great. Thank you. Manuvir, maybe you could talk a little bit more about why can't we just use existing general purpose platforms that are, that are running all this ERP and CRM and HCM and you know, all the, all the Microsoft apps that are out there. What, what do NVIDIA and Cloudera bring to the table that goes beyond the conventional systems that we've known for many years? >> Yeah. I think Dave, as we've talked about the asset that the customer has is really the data, right? And the same data can be utilized in many different ways. Some machine learning, some AI, some traditional data analytics. So, the first step here was really to take a general platform for data processing, Cloudera data platform, and integrate with that. Now NVIDIA has a software stack called rapids, which has all of the primitives that make different kinds of data processing go fast on GPU's. And so the integration here has really been taking rapids and integrating it into a Cloudera data platform so that regardless of the technique the customer is using to get insight from the data, the acceleration will apply in all cases. And that's why it was important to start with a platform like Cloudera rather than a specific application. >> So, I think this is really important because if you think about, you know, the software defined data center brought in, you know, some great efficiencies, but at the same time, a lot of the compute power is now going towards doing things like networking and storage and security offloads. So the good news, the reason this is important is because when you think about these data intensive workloads, we can now put more processing power to work for those, you know, AI intensive things. And so that's what I want to talk about a little bit, maybe a question for both of you, maybe Rob, you could start. You think about AI that's done today in the enterprise. A lot of it is modeling in the cloud, but when we look at a lot of the exciting use cases, bringing real-time systems together, transaction systems and analytics systems, and real-time AI inference, at least even at the edge, huge potential for business value. In a consumer, you're seeing a lot of applications with AI biometrics and voice recognition and autonomous vehicles and the liking. So you're putting AI into these data intensive apps within the enterprise. The potential there is enormous. So what can we learn from sort of where we've come from, maybe these consumer examples and Rob, how are you thinking about enterprise AI in the coming years? >> Yeah, you're right. The opportunity is huge here, but you know, 90% of the cost of AI applications is the inference. And it's been a blocker in terms of adoption because it's just been too expensive and difficult from a performance standpoint. And new platforms like these being developed by Cloudera and NVIDIA will dramatically lower the cost of enabling this type of workload to be done. And what we're going to see the most improvements will be in the speed and accuracy for existing enterprise AI apps like fraud detection, recommendation engine, supply chain management, drug province. And increasingly the consumer led technologies will be bleeding into the enterprise in the form of autonomous factory operations. An example of that would be robots. That AR, VR and manufacturing so driving better quality. The power grid management, automated retail, IOT, you know, the intelligent call centers, all of these will be powered by AI, but really the list of potential use cases now are going to be virtually endless. >> I mean, Manufir, this is like your wheelhouse. Maybe you could add something to that. >> Yeah. I mean, I agree with Rob. I mean he listed some really good use cases, you know, The way we see this at NVIDIA, this journey is in three phases or three steps, right? The first phase was for the early adopters. You know, the builders who assembled use cases, particular use cases like a chat bot from the ground up with the hardware and the software. Almost like going to your local hardware store and buying piece parts and constructing a table yourself right now. Now, I think we are in the first phase of the democratization. For example, the work we do with Cloudera, which is for a broader base of customers, still building for a particular use case, but starting from a much higher baseline. So think about, for example, going to Ikea now and buying a table in a box, right. And you still come home and assemble it, but all the parts are there, the instructions are there, there's a recipe you just follow and it's easy to do, right? So that's sort of the phase we're in now. And then going forward, the opportunity we really look forward to for the democratization, you talked about applications like CRM, et cetera. I think the next wave of democratization is when customers just adopt and deploy the next version of an application they already have. And what's happening is that under the covers, the application is infused by AI and it's become more intelligent because of AI and the customer just thinks they went to the store and bought a table and it showed up and somebody placed it in the right spot. Right? And they didn't really have to learn how to do AI. So these are the phases. And I think we're very excited to be going there. >> You know, Rob, the great thing about, for your customers is they don't have to build out the AI. They can, they can buy it. And just in thinking about this, it seems like there are a lot of really great and even sometimes narrow use cases. So I want to ask you, you know, staying with AI for a minute, one of the frustrations, and Mick I talked about this, the GIGO problem that we've all, you know, studied in college, you know, garbage in, garbage out. But, but the frustrations that users have had is really getting fast access to quality data that they can use to drive business results. So do you see, and how do you see AI maybe changing the game in that regard, Rob, over the next several years? >> So yeah, the combination of massive amounts of data that had been gathered across the enterprise in the past 10 years with an open APIs are dramatically lowering the processing costs that perform at much greater speed and efficiency. And that's allowing us as an industry to democratize the data access while at the same time delivering the federated governance and security models. And hybrid technologies are playing a key role in making this a reality and enabling data access to be quote, hybridized, meaning access and treated in a substantially similar way, irrespective of the physical location of where that data actually resides. >> And that's great. That is really the value layer that you guys are building out on top of all this great infrastructure that the hyperscalers have have given us. You know, a hundred billion dollars a year that you can build value on top of, for your customers. Last question, and maybe Rob, you could, you could go first and then Manuvir, you could bring us home. Where do you guys want to see the relationship go between Cloudera and NVIDIA? In other words, how should we as outside observers be, be thinking about and measuring your project, specifically in the industry's progress generally? >> Yes. I think we're very aligned on this and for Cloudera, it's all about helping companies move forward, leverage every bit of their data and all the places that it may be hosted and partnering with our customers, working closely with our technology ecosystem of partners, means innovation in every industry and that's inspiring for us. And that's what keeps us moving forward. >> Yeah and I agree with Rob and for us at NVIDIA, you know, we, this partnership started with data analytics. As you know, Spark is a very powerful technology for data analytics. People who use Spark rely on Cloudera for that. And the first thing we did together was to really accelerate Spark in a seamless manner. But we're accelerating machine learning. We're accelerating artificial intelligence together. And I think for NVIDIA it's about democratization. We've seen what machine learning and AI have done for the early adopters and help them make their businesses, their products, their customer experience better. And we'd like every company to have the same opportunity.

>>Have you ever wondered how we sequence the human genome, how your smartphone is so well smart, how we will ever analyze all the patient data for the new vaccines or even how we plan to send humans to Mars? Well, at Cloudera, we believe that data can make what is impossible today possible tomorrow we are the enterprise data cloud company. In fact, we provide analytics and machine learning technology that does everything from making your smartphone smarter, to helping scientists ensure that new vaccines are both safe and effective, big data, no problem out era, the enterprise data cloud company. >>So I think for a long time in this country, we've known that there's a great disparity between minority populations and the majority of population in terms of disease burden. And depending on where you live, your zip code has more to do with your health than almost anything else. But there are a lot of smaller, um, safety net facilities, as well as small academic medical colleges within the United States. And those in those smaller environments don't have the access, you know, to the technologies that the larger ones have. And, you know, I call that, uh, digital disparity. So I'm, Harry's in academic scientist center and our mission is to train diverse health care providers and researchers, but also provide services to underserved populations. As part of the reason that I think is so important for me hearing medical college, to do data science. One of the things that, you know, both Cloudera and Claire sensor very passionate about is bringing those height in technologies to, um, to the smaller organizations. >>It's very expensive to go to the cloud for these small organizations. So now with the partnership with Cloudera and Claire sets a clear sense, clients now enjoy those same technologies and really honestly have a technological advantage over some of the larger organizations. The reason being is they can move fast. So we were able to do this on our own without having to, um, hire data scientists. Uh, we probably cut three to five years off of our studies. I grew up in a small town in Arkansas and is one of those towns where the railroad tracks divided the blacks and the whites. My father died without getting much healthcare at all. And as an 11 year old, I did not understand why my father could not get medical attention because he was very sick. >>Since we come at my Harry are looking to serve populations that reflect themselves or affect the population. He came from. A lot of the data you find or research you find health is usually based on white men. And obviously not everybody who needs a medical provider is going to be a white male. >>One of the things that we're concerned about in healthcare is that there's bias in treatment already. We want to make sure those same biases do not enter into the algorithms. >>The issue is how do we get ahead of them to try to prevent these disparities? >>One of the great things about our dataset is that it contains a very diverse group of patients. >>Instead of just saying, everyone will have these results. You can break it down by race, class, cholesterol, level, other kinds of factors that play a role. So you can make the treatments in the long run. More specifically, >>Researchers are now able to use these technologies and really take those hypotheses from, from bench to bedside. >>We're able to overall improve the health of not just the person in front of you, but the population that, yeah, >>Well, the future is now. I love a quote by William Gibson who said the future is already here. It's just not evenly distributed. If we think hard enough and we apply things properly, uh, we can again take these technologies to, you know, underserved environments, um, in healthcare. Nobody should be technologically disadvantage. >>When is a car not just a car when it's a connected data driven ecosystem, dozens of sensors and edge devices gathering up data from just about anything road, infrastructure, other vehicles, and even pedestrians to create safer vehicles, smarter logistics, and more actionable insights. All the data from the connected car supports an entire ecosystem from manufacturers, building safer vehicles and fleet managers, tracking assets to insurers monitoring, driving behaviors to make roads safer. Now you can control the data journey from edge to AI. With Cloudera in the connected car, data is captured, consolidated and enriched with Cloudera data flow cloud Dara's data engineering, operational database and data warehouse provide the foundation to develop service center applications, sales reports, and engineering dashboards. With data science workbench data scientists can continuously train AI models and use data flow to push the models back to the edge, to enhance the car's performance as the industry's first enterprise data cloud Cloudera supports on-premise public and multi-cloud deployments delivering multifunction analytics on data anywhere with common security governance and metadata management powered by Cloudera SDX, an open platform built on open source, working with open compute architectures and open data stores all the way from edge to AI powering the connected car. >>The future has arrived. >>The Dawn of a retail Renaissance is here and shopping will never be the same again. Today's connected. Consumers are always on and didn't control. It's the era of smart retail, smart shelves, digital signage, and smart mirrors offer an immersive customer experience while delivering product information, personalized offers and recommendations, video analytics, capture customer emotions and gestures to better understand and respond to in-store shopping experiences. Beacons sensors, and streaming video provide valuable data into in-store traffic patterns, hotspots and dwell times. This helps retailers build visual heat maps to better understand custom journeys, conversion rates, and promotional effectiveness in our robots automate routine tasks like capturing inventory levels, identifying out of stocks and alerting in store personnel to replenish shelves. When it comes to checking out automated e-commerce pickup stations and frictionless checkouts will soon be the norm making standing in line. A thing of the past data and analytics are truly reshaping. >>The everyday shopping experience outside the store, smart trucks connect the supply chain, providing new levels of inventory visibility, not just into the precise location, but also the condition of those goods. All in real time, convenience is key and customers today have the power to get their goods delivered at the curbside to their doorstep, or even to their refrigerators. Smart retail is indeed here. And Cloudera makes all of this possible using Cloudera data can be captured from a variety of sources, then stored, processed, and analyzed to drive insights and action. In real time, data scientists can continuously build and train new machine learning models and put these models back to the edge for delivering those moment of truth customer experiences. This is the enterprise data cloud powered by Cloudera enabling smart retail from the edge to AI. The future has arrived >>For is a global automotive supplier. We have three business groups, automotive seating in studios, and then emission control technologies or biggest automotive customers are Volkswagen for the NPSA. And we have, uh, more than 300 sites. And in 75 countries >>Today, we are generating tons of data, more and more data on the manufacturing intelligence. We are trying to reduce the, the defective parts or anticipate the detection of the, of the defective part. And this is where we can get savings. I would say our goal in manufacturing is zero defects. The cost of downtime in a plant could be around the a hundred thousand euros. So with predictive maintenance, we are identifying correlations and patterns and try to anticipate, and maybe to replace a component before the machine is broken. We are in the range of about 2000 machines and we can have up to 300 different variables from pressure from vibration and temperatures. And the real-time data collection is key, and this is something we cannot achieve in a classical data warehouse approach. So with the be data and with clouded approach, what we are able to use really to put all the data, all the sources together in the classical way of working with that at our house, we need to spend weeks or months to set up the model with the Cloudera data lake. We can start working on from days to weeks. We think that predictive or machine learning could also improve on the estimation or NTC patient forecasting of what we'll need to brilliance with all this knowledge around internet of things and data collection. We are applying into the predictive convene and the cockpit of the future. So we can work in the self driving car and provide a better experience for the driver in the car. >>The Cloudera data platform makes it easy to say yes to any analytic workload from the edge to AI, yes. To enterprise grade security and governance, yes. To the analytics your people want to use yes. To operating on any cloud. Your business requires yes to the future with a cloud native platform that flexes to meet your needs today and tomorrow say yes to CDP and say goodbye to shadow it, take a tour of CDP and see how it's an easier, faster and safer enterprise analytics and data management platform with a new approach to data. Finally, a data platform that lets you say yes, >>Welcome to transforming ideas into insights, presented with the cube and made possible by cloud era. My name is Dave Volante from the cube, and I'll be your host for today. And the next hundred minutes, you're going to hear how to turn your best ideas into action using data. And we're going to share the real world examples and 12 industry use cases that apply modern data techniques to improve customer experience, reduce fraud, drive manufacturing, efficiencies, better forecast, retail demand, transform analytics, improve public sector service, and so much more how we use data is rapidly evolving as is the language that we use to describe data. I mean, for example, we don't really use the term big data as often as we used to rather we use terms like digital transformation and digital business, but you think about it. What is a digital business? How is that different from just a business? >>Well, digital business is a data business and it differentiates itself by the way, it uses data to compete. So whether we call it data, big data or digital, our belief is we're entering the next decade of a world that puts data at the core of our organizations. And as such the way we use insights is also rapidly evolving. You know, of course we get value from enabling humans to act with confidence on let's call it near perfect information or capitalize on non-intuitive findings. But increasingly insights are leading to the development of data, products and services that can be monetized, or as you'll hear in our industry, examples, data is enabling machines to take cognitive actions on our behalf. Examples are everywhere in the forms of apps and products and services, all built on data. Think about a real-time fraud detection, know your customer and finance, personal health apps that monitor our heart rates. >>Self-service investing, filing insurance claims and our smart phones. And so many examples, IOT systems that communicate and act machine and machine real-time pricing actions. These are all examples of products and services that drive revenue cut costs or create other value. And they all rely on data. Now while many business leaders sometimes express frustration that their investments in data, people, and process and technologies haven't delivered the full results they desire. The truth is that the investments that they've made over the past several years should be thought of as a step on the data journey. Key learnings and expertise from these efforts are now part of the organizational DNA that can catapult us into this next era of data, transformation and leadership. One thing is certain the next 10 years of data and digital transformation, won't be like the last 10. So let's get into it. Please join us in the chat. >>You can ask questions. You can share your comments, hit us up on Twitter right now. It's my pleasure to welcome Mick Holliston in he's the president of Cloudera mic. Great to see you. Great to see you as well, Dave, Hey, so I call it the new abnormal, right? The world is kind of out of whack offices are reopening again. We're seeing travel coming back. There's all this pent up demand for cars and vacations line cooks at restaurants. Everything that we consumers have missed, but here's the one thing. It seems like the algorithms are off. Whether it's retail's fulfillment capabilities, airline scheduling their pricing algorithms, you know, commodity prices we don't know is inflation. Transitory. Is it a long-term threat trying to forecast GDP? It's just seems like we have to reset all of our assumptions and make a feel a quality data is going to be a key here. How do you see the current state of the industry and the role data plays to get us into a more predictable and stable future? Well, I >>Can sure tell you this, Dave, uh, out of whack is definitely right. I don't know if you know or not, but I happen to be coming to you live today from Atlanta and, uh, as a native of Atlanta, I can, I can tell you there's a lot to be known about the airport here. It's often said that, uh, whether you're going to heaven or hell, you got to change planes in Atlanta and, uh, after 40 minutes waiting on algorithm to be right for baggage claim when I was not, I finally managed to get some bag and to be able to show up dressed appropriately for you today. Um, here's one thing that I know for sure though, Dave, clean, consistent, and safe data will be essential to getting the world and businesses as we know it back on track again, um, without well-managed data, we're certain to get very inconsistent outcomes, quality data will the normalizing factor because one thing really hasn't changed about computing since the Dawn of time. Back when I was taking computer classes at Georgia tech here in Atlanta, and that's what we used to refer to as garbage in garbage out. In other words, you'll never get quality data-driven insights from a poor data set. This is especially important today for machine learning and AI, you can build the most amazing models and algorithms, but none of it will matter if the underlying data isn't rock solid as AI is increasingly used in every business app, you must build a solid data foundation mic. Let's >>Talk about hybrid. Every CXO that I talked to, they're trying to get hybrid, right? Whether it's hybrid work hybrid events, which is our business hybrid cloud, how are you thinking about the hybrid? Everything, what's your point of view with >>All those descriptions of hybrid? Everything there, one item you might not have quite hit on Dave and that's hybrid data. >>Oh yeah, you're right. Mick. I did miss that. What, what do you mean by hybrid data? Well, >>David in cloud era, we think hybrid data is all about the juxtaposition of two things, freedom and security. Now every business wants to be more agile. They want the freedom to work with their data, wherever it happens to work best for them, whether that's on premises in a private cloud and public cloud, or perhaps even in a new open data exchange. Now this matters to businesses because not all data applications are created equal. Some apps are best suited to be run in the cloud because of their transitory nature. Others may be more economical if they're running a private cloud, but either way security, regulatory compliance and increasingly data sovereignty are playing a bigger and more important role in every industry. If you don't believe me, just watch her read a recent news story. Data breaches are at an all time high. And the ethics of AI applications are being called into question every day and understanding the lineage of machine learning algorithms is now paramount for every business. So how in the heck do you get both the freedom and security that you're looking for? Well, the answer is actually pretty straightforward. The key is developing a hybrid data strategy. And what do you know Dave? That's the business cloud era? Is it on a serious note from cloud era's perspective? Adopting a hybrid data strategy is central to every business's digital transformation. It will enable rapid adoption of new technologies and optimize economic models while ensuring the security and privacy of every bit of data. What can >>Make, I'm glad you brought in that notion of hybrid data, because when you think about things, especially remote work, it really changes a lot of the assumptions. You talked about security, the data flows are going to change. You've got the economics, the physics, the local laws come into play. So what about the rest of hybrid? Yeah, >>It's a great question, Dave and certainly cloud era itself as a business and all of our customers are feeling this in a big way. We now have the overwhelming majority of our workforce working from home. And in other words, we've got a much larger surface area from a security perspective to keep in mind the rate and pace of data, just generating a report that might've happened very quickly and rapidly on the office. Uh, ether net may not be happening quite so fast in somebody's rural home in, uh, in, in the middle of Nebraska somewhere. Right? So it doesn't really matter whether you're talking about the speed of business or securing data, any way you look at it. Uh, hybrid I think is going to play a more important role in how work is conducted and what percentage of people are working in the office and are not, I know our plans, Dave, uh, involve us kind of slowly coming back to work, begin in this fall. And we're looking forward to being able to shake hands and see one another again for the first time in many cases for more than a year and a half, but, uh, yes, hybrid work, uh, and hybrid data are playing an increasingly important role for every kind of business. >>Thanks for that. I wonder if we could talk about industry transformation for a moment because it's a major theme of course, of this event. So, and the case. Here's how I think about it. It makes, I mean, some industries have transformed. You think about retail, for example, it's pretty clear, although although every physical retail brand I know has, you know, not only peaked up its online presence, but they also have an Amazon war room strategy because they're trying to take greater advantage of that physical presence, uh, and ended up reverse. We see Amazon building out physical assets so that there's more hybrid going on. But when you look at healthcare, for example, it's just starting, you know, with such highly regulated industry. It seems that there's some hurdles there. Financial services is always been data savvy, but you're seeing the emergence of FinTech and some other challenges there in terms of control, mint control of payment systems in manufacturing, you know, the pandemic highlighted America's reliance on China as a manufacturing partner and, and supply chain. Uh it's so my point is it seems that different industries they're in different stages of transformation, but two things look really clear. One, you've got to put data at the core of the business model that's compulsory. It seems like embedding AI into the applications, the data, the business process that's going to become increasingly important. So how do you see that? >>Wow, there's a lot packed into that question there, Dave, but, uh, yeah, we, we, uh, you know, at Cloudera I happened to be leading our own digital transformation as a technology company and what I would, what I would tell you there that's been arresting for us is the shift from being largely a subscription-based, uh, model to a consumption-based model requires a completely different level of instrumentation and our products and data collection that takes place in real, both for billing, for our, uh, for our customers. And to be able to check on the health and wellness, if you will, of their cloud era implementations. But it's clearly not just impacting the technology industry. You mentioned healthcare and we've been helping a number of different organizations in the life sciences realm, either speed, the rate and pace of getting vaccines, uh, to market, uh, or we've been assisting with testing process. >>That's taken place because you can imagine the quantity of data that's been generated as we've tried to study the efficacy of these vaccines on millions of people and try to ensure that they were going to deliver great outcomes and, and healthy and safe outcomes for everyone. And cloud era has been underneath a great deal of that type of work and the financial services industry you pointed out. Uh, we continue to be central to the large banks, meeting their compliance and regulatory requirements around the globe. And in many parts of the world, those are becoming more stringent than ever. And Cloudera solutions are really helping those kinds of organizations get through those difficult challenges. You, you also happened to mention, uh, you know, public sector and in public sector. We're also playing a key role in working with government entities around the world and applying AI to some of the most challenging missions that those organizations face. >>Um, and while I've made the kind of pivot between the industry conversation and the AI conversation, what I'll share with you about AI, I touched upon a little bit earlier. You can't build great AI, can't grow, build great ML apps, unless you've got a strong data foundation underneath is back to that garbage in garbage out comment that I made previously. And so in order to do that, you've got to have a great hybrid dated management platform at your disposal to ensure that your data is clean and organized and up to date. Uh, just as importantly from that, that's kind of the freedom side of things on the security side of things. You've got to ensure that you can see who just touched, not just the data itself, Dave, but actually the machine learning models and organizations around the globe are now being challenged. It's kind of on the topic of the ethics of AI to produce model lineage. >>In addition to data lineage. In other words, who's had access to the machine learning models when and where, and at what time and what decisions were made perhaps by the humans, perhaps by the machines that may have led to a particular outcome. So every kind of business that is deploying AI applications should be thinking long and hard about whether or not they can track the full lineage of those machine learning models just as they can track the lineage of data. So lots going on there across industries, lots going on as those various industries think about how AI can be applied to their businesses. Pretty >>Interesting concepts. You bring it into the discussion, the hybrid data, uh, sort of new, I think, new to a lot of people. And th this idea of model lineage is a great point because people want to talk about AI, ethics, transparency of AI. When you start putting those models into, into machines to do real time inferencing at the edge, it starts to get really complicated. I wonder if we could talk about you still on that theme of industry transformation? I felt like coming into the pandemic pre pandemic, there was just a lot of complacency. Yeah. Digital transformation and a lot of buzz words. And then we had this forced March to digital, um, and it's, but, but people are now being more planful, but there's still a lot of sort of POC limbo going on. How do you see that? Can you help accelerate that and get people out of that state? It definitely >>Is a lot of a POC limbo or a, I think some of us internally have referred to as POC purgatory, just getting stuck in that phase, not being able to get from point a to point B in digital transformation and, um, you know, for every industry transformation, uh, change in general is difficult and it takes time and money and thoughtfulness, but like with all things, what we found is small wins work best and done quickly. So trying to get to quick, easy successes where you can identify a clear goal and a clear objective and then accomplish it in rapid fashion is sort of the way to build your way towards those larger transformative efforts set. Another way, Dave, it's not wise to try to boil the ocean with your digital transformation efforts as it relates to the underlying technology here. And to bring it home a little bit more practically, I guess I would say at cloud era, we tend to recommend that companies begin to adopt cloud infrastructure, for example, containerization. >>And they begin to deploy that on-prem and then they start to look at how they may move those containerized workloads into the public cloud. That'll give them an opportunity to work with the data and the underlying applications themselves, uh, right close to home in place. They can kind of experiment a little bit more safely and economically, and then determine which workloads are best suited for the public cloud and which ones should remain on prem. That's a way in which a hybrid data strategy can help get a digital transformation accomplish, but kind of starting small and then drawing fast from there on customer's journey to the we'll make we've >>Covered a lot of ground. Uh, last question. Uh, w what, what do you want people to leave this event, the session with, and thinking about sort of the next era of data that we're entering? >>Well, it's a great question, but, uh, you know, I think it could be summed up in, uh, in two words. I want them to think about a hybrid data, uh, strategy. So, uh, you know, really hybrid data is a concept that we're bringing forward on this show really for the, for the first time, arguably, and we really do think that it enables customers to experience what we refer to Dave as the power of, and that is freedom, uh, and security, and in a world where we're all still trying to decide whether each day when we walk out each building, we walk into, uh, whether we're free to come in and out with a mask without a mask, that sort of thing, we all want freedom, but we also also want to be safe and feel safe, uh, for ourselves and for others. And the same is true of organizations. It strategies. They want the freedom to choose, to run workloads and applications and the best and most economical place possible. But they also want to do that with certainty, that they're going to be able to deploy those applications in a safe and secure way that meets the regulatory requirements of their particular industry. So hybrid data we think is key to accomplishing both freedom and security for your data and for your business as a whole, >>Nick, thanks so much great conversation and really appreciate the insights that you're bringing to this event into the industry. Really thank you for your time. >>You bet Dave pleasure being with you. Okay. >>We want to pick up on a couple of themes that Mick discussed, you know, supercharging your business with AI, for example, and this notion of getting hybrid, right? So right now we're going to turn the program over to Rob Bearden, the CEO of Cloudera and Manny veer, DAS. Who's the head of enterprise computing at Nvidia. And before I hand it off to Robin, I just want to say for those of you who follow me at the cube, we've extensively covered the transformation of the semiconductor industry. We are entering an entirely new era of computing in the enterprise, and it's being driven by the emergence of data, intensive applications and workloads no longer will conventional methods of processing data suffice to handle this work. Rather, we need new thinking around architectures and ecosystems. And one of the keys to success in this new era is collaboration between software companies like Cloudera and semiconductor designers like Nvidia. So let's learn more about this collaboration and what it means to your data business. Rob, thanks, >>Mick and Dave, that was a great conversation on how speed and agility is everything in a hyper competitive hybrid world. You touched on AI as essential to a data first strategy and accelerating the path to value and hybrid environments. And I want to drill down on this aspect today. Every business is facing accelerating everything from face-to-face meetings to buying groceries has gone digital. As a result, businesses are generating more data than ever. There are more digital transactions to track and monitor. Now, every engagement with coworkers, customers and partners is virtual from website metrics to customer service records, and even onsite sensors. Enterprises are accumulating tremendous amounts of data and unlocking insights from it is key to our enterprises success. And with data flooding every enterprise, what should the businesses do? A cloud era? We believe this onslaught of data offers an opportunity to make better business decisions faster. >>And we want to make that easier for everyone, whether it's fraud, detection, demand, forecasting, preventative maintenance, or customer churn, whether the goal is to save money or produce income every day that companies don't gain deep insight from their data is money they've lost. And the reason we're talking about speed and why speed is everything in a hybrid world and in a hyper competitive climate, is that the faster we get insights from all of our data, the faster we grow and the more competitive we are. So those faster insights are also combined with the scalability and cost benefit they cloud provides and with security and edge to AI data intimacy. That's why the partnership between cloud air and Nvidia together means so much. And it starts with the shared vision making data-driven, decision-making a reality for every business and our customers will now be able to leverage virtually unlimited quantities of varieties, of data, to power, an order of magnitude faster decision-making and together we turbo charge the enterprise data cloud to enable our customers to work faster and better, and to make integration of AI approaches a reality for companies of all sizes in the cloud. >>We're joined today by NVIDIA's Mandy veer dos, and to talk more about how our technologies will deliver the speed companies need for innovation in our hyper competitive environment. Okay, man, you're veer. Thank you for joining us over the unit. >>Thank you, Rob, for having me. It's a pleasure to be here on behalf of Nvidia. We are so excited about this partnership with Cloudera. Uh, you know, when, when, uh, when Nvidia started many years ago, we started as a chip company focused on graphics, but as you know, over the last decade, we've really become a full stack accelerated computing company where we've been using the power of GPU hardware and software to accelerate a variety of workloads, uh, AI being a prime example. And when we think about Cloudera, uh, and your company, a great company, there's three things we see Rob. Uh, the first one is that for the companies that will already transforming themselves by the use of data, Cloudera has been a trusted partner for them. The second thing seen is that when it comes to using your data, you want to use it in a variety of ways with a powerful platform, which of course you have built over time. >>And finally, as we've heard already, you believe in the power of hybrid, that data exists in different places and the compute needs to follow the data. Now, if you think about in various mission, going forward to democratize accelerated computing for all companies, our mission actually aligns very well with exactly those three things. Firstly, you know, we've really worked with a variety of companies today who have been the early adopters, uh, using the power acceleration by changing the technology in their stacks. But more and more, we see the opportunity of meeting customers, where they are with tools that they're familiar with with partners that they trust. And of course, Cloudera being a great example of that. Uh, the second, uh, part of NVIDIA's mission is we focused a lot in the beginning on deep learning where the power of GPU is really shown through, but as we've gone forward, we found that GPU's can accelerate a variety of different workloads from machine learning to inference. >>And so again, the power of your platform, uh, is very appealing. And finally, we know that AI is all about data, more and more data. We believe very strongly in the idea that customers put their data, where they need to put it. And the compute, the AI compute the machine learning compute needs to meet the customer where their data is. And so that matches really well with your philosophy, right? And Rob, that's why we were so excited to do this partnership with you. It's come to fruition. We have a great combined stack now for the customer and we already see people using it. I think the IRS is a fantastic example where literally they took the workflow. They had, they took the servers, they had, they added GPS into those servers. They did not change anything. And they got an eight times performance improvement for their fraud detection workflows, right? And that's the kind of success we're looking forward to with all customers. So the team has actually put together a great video to show us what the IRS is doing with this technology. Let's take a look. >>My name's Joanne salty. I'm the branch chief of the technical branch and RAs. It's actually the research division research and statistical division of the IRS. Basically the mission that RAs has is we do statistical and research on all things related to taxes, compliance issues, uh, fraud issues, you know, anything that you can think of. Basically we do research on that. We're running into issues now that we have a lot of ideas to actually do data mining on our big troves of data, but we don't necessarily have the infrastructure or horsepower to do it. So it's our biggest challenge is definitely the, the infrastructure to support all the ideas that the subject matter experts are coming up with in terms of all the algorithms they would like to create. And the diving deeper within the algorithm space, the actual training of those Agra algorithms, the of parameters each of those algorithms have. >>So that's, that's really been our challenge. Now the expectation was that with Nvidia in cloud, there is help. And with the cluster, we actually build out the test this on the actual fraud, a fraud detection algorithm on our expectation was we were definitely going to see some speed up in prom, computational processing times. And just to give you context, the size of the data set that we were, uh, the SMI was actually working, um, the algorithm against Liz around four terabytes. If I recall correctly, we'd had a 22 to 48 times speed up after we started tweaking the original algorithm. My expectations, quite honestly, in that sphere, in terms of the timeframe to get results, was it that you guys actually exceeded them? It was really, really quick. Uh, the definite now term short term what's next is going to be the subject matter expert is actually going to take our algorithm run with that. >>So that's definitely the now term thing we want to do going down, go looking forward, maybe out a couple of months, we're also looking at curing some, a 100 cards to actually test those out. As you guys can guess our datasets are just getting bigger and bigger and bigger, and it demands, um, to actually do something when we get more value added out of those data sets is just putting more and more demands on our infrastructure. So, you know, with the pilot, now we have an idea with the infrastructure, the infrastructure we need going forward. And then also just our in terms of thinking of the algorithms and how we can approach these problems to actually code out solutions to them. Now we're kind of like the shackles are off and we can just run them, you know, come onto our art's desire, wherever imagination takes our skis to actually develop solutions, know how the platforms to run them on just kind of the close out. >>I rarely would be very missed. I've worked with a lot of, you know, companies through the year and most of them been spectacular. And, uh, you guys are definitely in that category. The, the whole partnership, as I said, a little bit early, it was really, really well, very responsive. I would be remiss if I didn't. Thank you guys. So thank you for the opportunity to, and fantastic. And I'd have to also, I want to thank my guys. My, uh, my staff, David worked on this Richie worked on this Lex and Tony just, they did a fantastic job and I want to publicly thank him for all the work they did with you guys and Chev, obviously also. Who's fantastic. So thank you everyone. >>Okay. That's a real great example of speed and action. Now let's get into some follow up questions guys, if I may, Rob, can you talk about the specific nature of the relationship between Cloudera and Nvidia? Is it primarily go to market or you do an engineering work? What's the story there? >>It's really both. It's both go to market and engineering and engineering focus is to optimize and take advantage of invidious platform to drive better price performance, lower cost, faster speeds, and better support for today's emerging data intensive applications. So it's really both >>Great. Thank you. Many of Eric, maybe you could talk a little bit more about why can't we just existing general purpose platforms that are, that are running all this ERP and CRM and HCM and you know, all the, all the Microsoft apps that are out there. What, what do Nvidia and cloud era bring to the table that goes beyond the conventional systems that we've known for many years? >>Yeah. I think Dave, as we've talked about the asset that the customer has is really the data, right? And the same data can be utilized in many different ways. Some machine learning, some AI, some traditional data analytics. So the first step here was really to take a general platform for data processing, Cloudera data platform, and integrate with that. Now Nvidia has a software stack called rapids, which has all of the primitives that make different kinds of data processing go fast on GPU's. And so the integration here has really been taking rapids and integrating it into a Cloudera data platform. So that regardless of the technique, the customer's using to get insight from that data, the acceleration will apply in all cases. And that's why it was important to start with a platform like Cloudera rather than a specific application. >>So I think this is really important because if you think about, you know, the software defined data center brought in, you know, some great efficiencies, but at the same time, a lot of the compute power is now going toward doing things like networking and storage and security offloads. So the good news, the reason this is important is because when you think about these data intensive workloads, we can now put more processing power to work for those, you know, AI intensive, uh, things. And so that's what I want to talk about a little bit, maybe a question for both of you, maybe Rob, you could start, you think about the AI that's done today in the enterprise. A lot of it is modeling in the cloud, but when we look at a lot of the exciting use cases, bringing real-time systems together, transaction systems and analytics systems and real time, AI inference, at least even at the edge, huge potential for business value and a consumer, you're seeing a lot of applications with AI biometrics and voice recognition and autonomous vehicles and the like, and so you're putting AI into these data intensive apps within the enterprise. >>The potential there is enormous. So what can we learn from sort of where we've come from, maybe these consumer examples and Rob, how are you thinking about enterprise AI in the coming years? >>Yeah, you're right. The opportunity is huge here, but you know, 90% of the cost of AI applications is the inference. And it's been a blocker in terms of adoption because it's just been too expensive and difficult from a performance standpoint and new platforms like these being developed by cloud air and Nvidia will dramatically lower the cost, uh, of enabling this type of workload to be done. Um, and what we're going to see the most improvements will be in the speed and accuracy for existing enterprise AI apps like fraud detection, recommendation, engine chain management, drug province, and increasingly the consumer led technologies will be bleeding into the enterprise in the form of autonomous factory operations. An example of that would be robots that AR VR and manufacturing. So driving quality, better quality in the power grid management, automated retail IOT, you know, the intelligent call centers, all of these will be powered by AI, but really the list of potential use cases now are going to be virtually endless. >>I mean, this is like your wheelhouse. Maybe you could add something to that. >>Yeah. I mean, I agree with Rob. I mean he listed some really good use cases. You know, the way we see this at Nvidia, this journey is in three phases or three steps, right? The first phase was for the early adopters. You know, the builders who assembled, uh, use cases, particular use cases like a chat bot, uh, uh, from the ground up with the hardware and the software almost like going to your local hardware store and buying piece parts and constructing a table yourself right now. I think we are in the first phase of the democratization, uh, for example, the work we did with Cloudera, which is, uh, for a broader base of customers, still building for a particular use case, but starting from a much higher baseline. So think about, for example, going to Ikea now and buying a table in a box, right. >>And you still come home and assemble it, but all the parts are there. The instructions are there, there's a recipe you just follow and it's easy to do, right? So that's sort of the phase we're in now. And then going forward, the opportunity we really look forward to for the democratization, you talked about applications like CRM, et cetera. I think the next wave of democratization is when customers just adopt and deploy the next version of an application they already have. And what's happening is that under the covers, the application is infused by AI and it's become more intelligent because of AI and the customer just thinks they went to the store and bought, bought a table and it showed up and somebody placed it in the right spot. Right. And they didn't really have to learn, uh, how to do AI. So these are the phases. And I think they're very excited to be going there. Yeah. You know, >>Rob, the great thing about for, for your customers is they don't have to build out the AI. They can, they can buy it. And, and just in thinking about this, it seems like there are a lot of really great and even sometimes narrow use cases. So I want to ask you, you know, staying with AI for a minute, one of the frustrations and Mick and I talked about this, the guy go problem that we've all studied in college, uh, you know, garbage in, garbage out. Uh, but, but the frustrations that users have had is really getting fast access to quality data that they can use to drive business results. So do you see, and how do you see AI maybe changing the game in that regard, Rob over the next several years? >>So yeah, the combination of massive amounts of data that have been gathered across the enterprise in the past 10 years with an open API APIs are dramatically lowering the processing costs that perform at much greater speed and efficiency, you know, and that's allowing us as an industry to democratize the data access while at the same time, delivering the federated governance and security models and hybrid technologies are playing a key role in making this a reality and enabling data access to be hybridized, meaning access and treated in a substantially similar way, your respect to the physical location of where that data actually resides. >>That's great. That is really the value layer that you guys are building out on top of that, all this great infrastructure that the hyperscalers have have given us, I mean, a hundred billion dollars a year that you can build value on top of, for your customers. Last question, and maybe Rob, you could, you can go first and then manufacture. You could bring us home. Where do you guys want to see the relationship go between cloud era and Nvidia? In other words, how should we, as outside observers be, be thinking about and measuring your project specifically and in the industry's progress generally? >>Yeah, I think we're very aligned on this and for cloud era, it's all about helping companies move forward, leverage every bit of their data and all the places that it may, uh, be hosted and partnering with our customers, working closely with our technology ecosystem of partners means innovation in every industry and that's inspiring for us. And that's what keeps us moving forward. >>Yeah. And I agree with Robin and for us at Nvidia, you know, we, this partnership started, uh, with data analytics, um, as you know, a spark is a very powerful technology for data analytics, uh, people who use spark rely on Cloudera for that. And the first thing we did together was to really accelerate spark in a seamless manner, but we're accelerating machine learning. We accelerating artificial intelligence together. And I think for Nvidia it's about democratization. We've seen what machine learning and AI have done for the early adopters and help them make their businesses, their products, their customer experience better. And we'd like every company to have the same opportunity. >>Okay. Now we're going to dig into the data landscape and cloud of course. And talk a little bit more about that with drew Allen. He's a managing director at Accenture drew. Welcome. Great to see you. Thank you. So let's talk a little bit about, you know, you've been in this game for a number of years. Uh, you've got particular expertise in, in data and finance and insurance. I mean, you know, you think about it within the data and analytics world, even our language is changing. You know, we don't say talk about big data so much anymore. We talk more about digital, you know, or, or, or data driven when you think about sort of where we've come from and where we're going. What are the puts and takes that you have with regard to what's going on in the business today? >>Well, thanks for having me. Um, you know, I think some of the trends we're seeing in terms of challenges and puts some takes are that a lot of companies are already on this digital journey. Um, they focused on customer experience is kind of table stakes. Everyone wants to focus on that and kind of digitizing their channels. But a lot of them are seeing that, you know, a lot of them don't even own their, their channels necessarily. So like we're working with a big cruise line, right. And yes, they've invested in digitizing what they own, but a lot of the channels that they sell through, they don't even own, right. It's the travel agencies or third party, real sellers. So having the data to know where, you know, where those agencies are, that that's something that they've discovered. And so there's a lot of big focus on not just digitizing, but also really understanding your customers and going across products because a lot of the data has built, been built up in individual channels and in digital products. >>And so bringing that data together is something that customers that have really figured out in the last few years is a big differentiator. And what we're seeing too, is that a big trend that the data rich are getting richer. So companies that have really invested in data, um, are having, uh, an outside market share and outside earnings per share and outside revenue growth. And it's really being a big differentiator. And I think for companies just getting started in this, the thing to think about is one of the missteps is to not try to capture all the data at once. The average company has, you know, 10,000, 20,000 data elements individually, when you want to start out, you know, 500, 300 critical data elements, about 5% of the data of a company drives 90% of the business value. So focusing on those key critical data elements is really what you need to govern first and really invest in first. And so that's something we, we tell companies at the beginning of their data strategy is first focus on those critical data elements, really get a handle on governing that data, organizing that data and building data products around >>That day. You can't boil the ocean. Right. And so, and I, I feel like pre pandemic, there was a lot of complacency. Oh yeah, we'll get to that. You know, not on my watch, I'll be retired before that, you know, is it becomes a minute. And then of course the pandemic was, I call it sometimes a forced March to digital. So in many respects, it wasn't planned. It just ha you know, you had to do it. And so now I feel like people are stepping back and saying, okay, let's now really rethink this and do it right. But is there, is there a sense of urgency, do you think? Absolutely. >>I think with COVID, you know, we were working with, um, a retailer where they had 12,000 stores across the U S and they had didn't have the insights where they could drill down and understand, you know, with the riots and with COVID was the store operational, you know, with the supply chain of the, having multiple distributors, what did they have in stock? So there are millions of data points that you need to drill down at the cell level, at the store level to really understand how's my business performing. And we like to think about it for like a CEO and his leadership team of it, like, think of it as a digital cockpit, right? You think about a pilot, they have a cockpit with all these dials and, um, dashboards, essentially understanding the performance of their business. And they should be able to drill down and understand for each individual, you know, unit of their work, how are they performing? That's really what we want to see for businesses. Can they get down to that individual performance to really understand how their business >>Is performing good, the ability to connect those dots and traverse those data points and not have to go in and come back out and go into a new system and come back out. And that's really been a lot of the frustration. W where does machine intelligence and AI fit in? Is that sort of a dot connector, if you will, and an enabler, I mean, we saw, you know, decades of the, the AI winter, and then, you know, there's been a lot of talk about it, but it feels like with the amount of data that we've collected over the last decade and the, the, the low costs of processing that data now, it feels like it's, it's real. Where do you see AI fitting? Yeah, >>I mean, I think there's been a lot of innovation in the last 10 years with, um, the low cost of storage and computing and these algorithms in non-linear, um, you know, knowledge graphs, and, um, um, a whole bunch of opportunities in cloud where what I think the, the big opportunity is, you know, you can apply AI in areas where a human just couldn't have the scale to do that alone. So back to the example of a cruise lines, you know, you may have a ship being built that has 4,000 cabins on the single cruise line, and it's going to multiple deaths that destinations over its 30 year life cycle. Each one of those cabins is being priced individually for each individual destination. It's physically impossible for a human to calculate the dynamic pricing across all those destinations. You need a machine to actually do that pricing. And so really what a machine is leveraging is all that data to really calculate and assist the human, essentially with all these opportunities where you wouldn't have a human being able to scale up to that amount of data >>Alone. You know, it's interesting. One of the things we talked to Nicolson about earlier was just the everybody's algorithms are out of whack. You know, you look at the airline pricing, you look at hotels it's as a consumer, you would be able to kind of game the system and predict that they can't even predict these days. And I feel as though that the data and AI are actually going to bring us back into some kind of normalcy and predictability, uh, what do you see in that regard? Yeah, I think it's, >>I mean, we're definitely not at a point where, when I talked to, you know, the top AI engineers and data scientists, we're not at a point where we have what they call broad AI, right? You can get machines to solve general knowledge problems, where they can solve one problem and then a distinctly different problem, right? That's still many years away, but narrow why AI, there's still tons of use cases out there that can really drive tons of business performance challenges, tons of accuracy challenges. So for example, in the insurance industry, commercial lines, where I work a lot of the time, the biggest leakage of loss experience in pricing for commercial insurers is, um, people will go in as an agent and they'll select an industry to say, you know what, I'm a restaurant business. Um, I'll select this industry code to quote out a policy, but there's, let's say, you know, 12 dozen permutations, you could be an outdoor restaurant. >>You could be a bar, you could be a caterer and all of that leads to different loss experience. So what this does is they built a machine learning algorithm. We've helped them do this, that actually at the time that they're putting in their name and address, it's crawling across the web and predicting in real time, you know, is this a address actually, you know, a business that's a restaurant with indoor dining, does it have a bar? Is it outdoor dining? And it's that that's able to accurately more price the policy and reduce the loss experience. So there's a lot of that you can do even with narrow AI that can really drive top line of business results. >>Yeah. I liked that term, narrow AI, because getting things done is important. Let's talk about cloud a little bit because people talk about cloud first public cloud first doesn't necessarily mean public cloud only, of course. So where do you see things like what's the right operating model, the right regime hybrid cloud. We talked earlier about hybrid data help us squint through the cloud landscape. Yeah. I mean, I think for most right, most >>Fortune 500 companies, they can't just snap their fingers and say, let's move all of our data centers to the cloud. They've got to move, you know, gradually. And it's usually a journey that's taking more than two to three plus years, even more than that in some cases. So they're have, they have to move their data, uh, incrementally to the cloud. And what that means is that, that they have to move to a hybrid perspective where some of their data is on premise and some of it is publicly on the cloud. And so that's the term hybrid cloud essentially. And so what they've had to think about is from an intelligence perspective, the privacy of that data, where is it being moved? Can they reduce the replication of that data? Because ultimately you like, uh, replicating the data from on-premise to the cloud that introduces, you know, errors and data quality issues. So thinking about how do you manage, uh, you know, uh on-premise and, um, public as a transition is something that Accenture thinks, thinks, and helps our clients do quite a bit. And how do you move them in a manner that's well-organized and well thought of? >>Yeah. So I've been a big proponent of sort of line of business lines of business becoming much more involved in, in the data pipeline, if you will, the data process, if you think about our major operational systems, they all have sort of line of business context in them. And then the salespeople, they know the CRM data and, you know, logistics folks there they're very much in tune with ERP, almost feel like for the past decade, the lines of business have been somewhat removed from the, the data team, if you will. And that, that seems to be changing. What are you seeing in terms of the line of line of business being much more involved in sort of end to end ownership, if you will, if I can use that term of, uh, of the data and sort of determining things like helping determine anyway, the data quality and things of that nature. Yeah. I >>Mean, I think this is where thinking about your data operating model and thinking about ideas of a chief data officer and having data on the CEO agenda, that's really important to get the lines of business, to really think about data sharing and reuse, and really getting them to, you know, kind of unlock the data because they do think about their data as a fiefdom data has value, but you've got to really get organizations in their silos to open it up and bring that data together because that's where the value is. You know, data doesn't operate. When you think about a customer, they don't operate in their journey across the business in silo channels. They don't think about, you know, I use only the web and then I use the call center, right? They think about that as just one experience and that data is a single journey. >>So we like to think about data as a product. You know, you should think about a data in the same way. You think about your products as, as products, you know, data as a product, you should have the idea of like every two weeks you have releases to it. You have an operational resiliency to it. So thinking about that, where you can have a very product mindset to delivering your data, I think is very important for the success. And that's where kind of, there's not just the things about critical data elements and having the right platform architecture, but there's a soft stuff as well, like a, a product mindset to data, having the right data, culture, and business adoption and having the right value set mindset for, for data, I think is really >>Important. I think data as a product is a very powerful concept and I think it maybe is uncomfortable to some people sometimes. And I think in the early days of big data, if you will, people thought, okay, data is a product going to sell my data and that's not necessarily what you mean, thinking about products or data that can fuel products that you can then monetize maybe as a product or as a, as, as a service. And I like to think about a new metric in the industry, which is how long does it take me to get from idea I'm a business person. I have an idea for a data product. How long does it take me to get from idea to monetization? And that's going to be something that ultimately as a business person, I'm going to use to determine the success of my data team and my data architecture. Is that kind of thinking starting to really hit the marketplace? Absolutely. >>I mean, I insurers now are working, partnering with, you know, auto manufacturers to monetize, um, driver usage data, you know, on telematics to see, you know, driver behavior on how, you know, how auto manufacturers are using that data. That's very important to insurers, you know, so how an auto manufacturer can monetize that data is very important and also an insurance, you know, cyber insurance, um, are there news new ways we can look at how companies are being attacked with viruses and malware. And is there a way we can somehow monetize that information? So companies that are able to agily, you know, think about how can we collect this data, bring it together, think about it as a product, and then potentially, you know, sell it as a service is something that, um, company, successful companies, you're doing great examples >>Of data products, and it might be revenue generating, or it might be in the case of, you know, cyber, maybe it reduces my expected loss and exactly. Then it drops right to my bottom line. What's the relationship between Accenture and cloud era? Do you, I presume you guys meet at the customer, but maybe you could give us some insight. >>Yeah. So, um, I, I'm in the executive sponsor for, um, the Accenture Cloudera partnership on the Accenture side. Uh, we do quite a lot of business together and, um, you know, Cloudera has been a great partner for us. Um, and they've got a great product in terms of the Cloudera data platform where, you know, what we do is as a big systems integrator for them, we help, um, you know, configure and we have a number of engineers across the world that come in and help in terms of, um, engineer architects and install, uh, cloud errors, data platform, and think about what are some of those, you know, value cases where you can really think about organizing data and bringing it together for all these different types of use cases. And really just as the examples we thought about. So the telematics, you know, um, in order to realize something like that, you're bringing in petabytes and huge scales of data that, you know, you just couldn't bring on a normal, uh, platform. You need to think about cloud. You need to think about speed of, of data and real-time insights and cloud era is the right data platform for that. So, um, >>Having a cloud Cloudera ushered in the modern big data era, we kind of all know that, and it was, which of course early on, it was very services intensive. You guys were right there helping people think through there weren't enough data scientists. We've sort of all, all been through that. And of course in your wheelhouse industries, you know, financial services and insurance, they were some of the early adopters, weren't they? Yeah, absolutely. >>Um, so, you know, an insurance, you've got huge amounts of data with loss history and, um, a lot with IOT. So in insurance, there's a whole thing of like sensorized thing in, uh, you know, taking the physical world and digitizing it. So, um, there's a big thing in insurance where, um, it's not just about, um, pricing out the risk of a loss experience, but actual reducing the loss before it even happens. So it's called risk control or loss control, you know, can we actually put sensors on oil pipelines or on elevators and, you know, reduce, um, you know, accidents before they happen. So we're, you know, working with an insurer to actually, um, listen to elevators as they move up and down and are there signals in just listening to the audio of an elevator over time that says, you know what, this elevator is going to need maintenance, you know, before a critical accident could happen. So there's huge applications, not just in structured data, but in unstructured data like voice and audio and video where a partner like Cloudera has a huge role to play. >>Great example of it. So again, narrow sort of use case for machine intelligence, but, but real value. True. We'll leave it like that. Thanks so much for taking some time. Yes. Thank you so much. Okay. We continue now with the theme of turning ideas into insights. So ultimately you can take action. We heard earlier that public cloud first doesn't mean public cloud only, and a winning strategy comprises data, irrespective of physical location on prem, across multiple clouds at the edge where real time inference is going to drive a lot of incremental value. Data is going to help the world come back to normal. We heard, or at least semi normal as we begin to better understand and forecast demand and supply and balances and economic forces. AI is becoming embedded into every aspect of our business, our people, our processes, and applications. And now we're going to get into some of the foundational principles that support the data and insights centric processes, which are fundamental to digital transformation initiatives. And it's my pleasure to welcome two great guests, Michelle Goetz. Who's a Kuba woman, VP and principal analyst at Forrester, and doing some groundbreaking work in this area. And Cindy, Mikey, who is the vice president of industry solutions and value management at Cloudera. Welcome to both of >>You. Welcome. Thank you. Thanks Dave. >>All right, Michelle, let's get into it. Maybe you could talk about your foundational core principles. You start with data. What are the important aspects of this first principle that are achievable today? >>It's really about democratization. If you can't make your data accessible, um, it's not usable. Nobody's able to understand what's happening in the business and they don't understand, um, what insights can be gained or what are the signals that are occurring that are going to help them with decisions, create stronger value or create deeper relationships, their customers, um, due to their experiences. So it really begins with how do you make data available and bring it to where the consumer of the data is rather than trying to hunt and Peck around within your ecosystem to find what it is that's important. Great. >>Thank you for that. So, Cindy, I wonder in hearing what Michelle just said, what are your thoughts on this? And when you work with customers at Cloudera, does, are there any that stand out that perhaps embody the fundamentals that Michelle just shared? >>Yeah, there's, there's quite a few. And especially as we look across, um, all the industries that we're actually working with customers in, you know, a few that stand out in top of mind for me is one is IQ via and what they're doing with real-world evidence and bringing together data across the entire, um, healthcare and life sciences ecosystems, bringing it together in different shapes and formats, making the ed accessible by both internally, as well as for their, um, the entire extended ecosystem. And then for SIA, who's working to solve some predictive maintenance issues within, there are a European car manufacturer and how do they make sure that they have, you know, efficient and effective processes when it comes to, uh, fixing equipment and so forth. And then also, um, there's, uh, an Indonesian based, um, uh, telecommunications company tech, the smell, um, who's bringing together, um, over the last five years, all their data about their customers and how do they enhance our customer experience? How do they make information accessible, especially in these pandemic and post pandemic times, um, uh, you know, just getting better insights into what customers need and when do they need it? >>Cindy platform is another core principle. How should we be thinking about data platforms in this day and age? I mean, where does, where do things like hybrid fit in? Um, what's cloud era's point >>Of view platforms are truly an enabler, um, and data needs to be accessible in many different fashions. Um, and also what's right for the business. When, you know, I want it in a cost and efficient and effective manner. So, you know, data needs to be, um, data resides everywhere. Data is developed and it's brought together. So you need to be able to balance both real time, you know, our batch historical information. It all depends upon what your analytical workloads are. Um, and what types of analytical methods you're going to use to drive those business insights. So putting and placing data, um, landing it, making it accessible, analyzing it needs to be done in any accessible platform, whether it be, you know, a public cloud doing it on-prem or a hybrid of the two is typically what we're seeing, being the most successful. >>Great. Thank you, Michelle. Let's move on a little bit and talk about practices and practices and processes as the next core principles. Maybe you could provide some insight as to how you think about balancing practices and processes while at the same time managing agility. >>Yeah, it's a really great question because it's pretty complex. When you have to start to connect your data to your business, the first thing to really gravitate towards is what are you trying to do? And what Cindy was describing with those customer examples is that they're all based off of business goals off of very specific use cases that helps kind of set the agenda about what is the data and what are the data domains that are important to really understanding and recognizing what's happening within that business activity and the way that you can affect that either in, you know, near time or real time, or later on, as you're doing your strategic planning, what that's balancing against is also being able to not only see how that business is evolving, but also be able to go back and say, well, can I also measure the outcomes from those processes and using data and using insight? >>Can I also get intelligence about the data to know that it's actually satisfying my objectives to influence my customers in my market? Or is there some sort of data drift or detraction in my, um, analytic capabilities that are allowing me to be effective in those environments, but everything else revolves around that and really thinking succinctly about a strategy that isn't just data aware, what data do I have and how do I use it, but coming in more from that business perspective to then start to be, data-driven recognizing that every activity you do from a business perspective leads to thinking about information that supports that and supports your decisions, and ultimately getting to the point of being insight driven, where you're able to both, uh, describe what you want your business to be with your data, using analytics, to then execute on that fluidly and in real time. And then ultimately bringing that back with linking to business outcomes and doing that in a continuous cycle where you can test and you can learn, you can improve, you can optimize, and you can innovate because you can see your business as it's happening. And you have the right signals and intelligence that allow you to make great decisions. >>I like how you said near time or real time, because it is a spectrum. And you know, one of the spectrum, autonomous vehicles, you've got to make a decision in real time, but, but, but near real-time, or real-time, it's, it's in the eyes of the holder, if you will, it's it might be before you lose the customer before the market changes. So it's really defined on a case by case basis. Um, I wonder Michelle, if you could talk about in working with a number of organizations, I see folks, they sometimes get twisted up and understanding the dependencies that technology generally, and the technologies around data specifically can have on critical business processes. Can you maybe give some guidance as to where customers should start, where, you know, where can we find some of the quick wins and high return, it >>Comes first down to how does your business operate? So you're going to take a look at the business processes and value stream itself. And if you can understand how people and customers, partners, and automation are driving that step by step approach to your business activities, to realize those business outcomes, it's way easier to start thinking about what is the information necessary to see that particular step in the process, and then take the next step of saying what information is necessary to make a decision at that current point in the process, or are you collecting information asking for information that is going to help satisfy a downstream process step or a downstream decision. So constantly making sure that you are mapping out your business processes and activities, aligning your data process to that helps you now rationalize. Do you need that real time near real time, or do you want to start grading greater consistency by bringing all of those signals together, um, in a centralized area to eventually oversee the entire operations and outcomes as they happen? It's the process and the decision points and acting on those decision points for the best outcome that really determines are you going to move in more of a real-time, uh, streaming capacity, or are you going to push back into more of a batch oriented approach? Because it depends on the amount of information and the aggregate of which provides the best insight from that. >>Got it. Let's, let's bring Cindy back into the conversation in your city. We often talk about people process and technology and the roles they play in creating a data strategy. That's that's logical and sound. Can you speak to the broader ecosystem and the importance of creating both internal and external partners within an organization? Yeah. >>And that's, uh, you know, kind of building upon what Michelle was talking about. If you think about datas and I hate to use the phrase almost, but you know, the fuel behind the process, um, and how do you actually become insight-driven? And, you know, you look at the capabilities that you're needing to enable from that business process, that insight process, um, you're extended ecosystem on, on how do I make that happen? You know, partners, um, and, and picking the right partner is important because a partner is one that actually helps under or helps you implement what your decisions are. Um, so, um, looking for a partner that has the capability that believes in being insight-driven and making sure that when you're leveraging data, um, you know, for within process on that, if you need to do it in a time fashion, that they can actually meet those needs of the business, um, and enabling on those, those process activities. So the ecosystem looking at how you, um, look at, you know, your vendors are, and fundamentally they need to be that trusted partner. Um, do they bring those same principles of value of being insight driven? So they have to have those core values themselves in order to help you as a, um, an end of business person enable those capabilities. So, so yeah, I'm >>Cool with fuel, but it's like super fuel when you talk about data, cause it's not scarce, right? You're never going to run out. So Michelle, let's talk about leadership. W w who leads, what does so-called leadership look like in an organization that's insight driven? >>So I think the really interesting thing that is starting to evolve as late is that organizations enterprises are really recognizing that not just that data is an asset and data has value, but exactly what we're talking about here, data really does drive what your business outcomes are going to be data driving into the insight or the raw data itself has the ability to set in motion. What's going to happen in your business processes and your customer experiences. And so, as you kind of think about that, you're now starting to see your CEO, your CMO, um, your CRO coming back and saying, I need better data. I need information. That's representative of what's happening in my business. I need to be better adaptive to what's going on with my customers. And ultimately that means I need to be smarter and have clearer forecasting into what's about ready to come, not just, you know, one month, two months, three months or a year from now, but in a week or tomorrow. >>And so that's, how is having a trickle down effect to then looking at two other types of roles that are elevating from technical capacity to more business capacity, you have your chief data officer that is shaping the exp the experiences, uh, with data and with insight and reconciling, what type of information is necessary with it within the context of answering these questions and creating a future fit organization that is adaptive and resilient to things that are happening. And you also have a chief digital officer who is participating because they're providing the experience and shaping the information and the way that you're going to interact and execute on those business activities, and either running that autonomously or as part of an assistance for your employees and for your customers. So really to go from not just data aware to data driven, but ultimately to be insight driven, you're seeing way more, um, participation, uh, and leadership at that C-suite level. And just underneath, because that's where the subject matter expertise is coming in to know how to create a data strategy that is tightly connected to your business strategy. >>Right. Thank you. Let's wrap. And I've got a question for both of you, maybe Cindy, you could start and then Michelle bring us home. You know, a lot of customers, they want to understand what's achievable. So it's helpful to paint a picture of a, of a maturity model. Uh, you know, I'd love to go there, but I'm not going to get there anytime soon, but I want to take some baby steps. So when you're performing an analysis on, on insight driven organization, city, what do you see as the major characteristics that define the differences between sort of the, the early, you know, beginners, the sort of fat middle, if you will, and then the more advanced, uh, constituents. >>Yeah, I'm going to build upon, you know, what Michelle was talking about as data as an asset. And I think, you know, also being data where, and, you know, trying to actually become, you know, insight driven, um, companies can also have data and they can have data as a liability. And so when you're data aware, sometimes data can still be a liability to your organization. If you're not making business decisions on the most recent and relevant data, um, you know, you're not going to be insight driven. So you've got to move beyond that, that data awareness, where you're looking at data just from an operational reporting, but data's fundamentally driving the decisions that you make. Um, as a business, you're using data in real time. You're, um, you're, you know, leveraging data to actually help you make and drive those decisions. So when we use the term you're, data-driven, you can't just use the term, you know, tongue in cheek. It actually means that I'm using the recent, the relevant and the accuracy of data to actually make the decisions for me, because we're all advancing upon. We're talking about, you know, artificial intelligence and so forth. Being able to do that, if you're just data where I would not be embracing on leveraging artificial intelligence, because that means I probably haven't embedded data into my processes. It's data could very well still be a liability in your organization. So how do you actually make it an asset? Yeah, I think data >>Where it's like cable ready. So, so Michelle, maybe you could, you could, you could, uh, add to what Cindy just said and maybe add as well, any advice that you have around creating and defining a data strategy. >>So every data strategy has a component of being data aware. This is like building the data museum. How do you capture everything that's available to you? How do you maintain that memory of your business? You know, bringing in data from your applications, your partners, third parties, wherever that information is available, you want to ensure that you're capturing and you're managing and you're maintaining it. And this is really where you're starting to think about the fact that it is an asset. It has value, but you may not necessarily know what that value is. Yet. If you move into a category of data driven, what starts to shift and change there is you're starting to classify label, organize the information in context of how you're making decisions and how you do business. It could start from being more, um, proficient from an analytic purpose. You also might start to introduce some early stages of data science in there. >>So you can do some predictions and some data mining to start to weed out some of those signals. And you might have some simple types of algorithms that you're deploying to do a next next best action for example. And that's what data-driven is really about. You're starting to get value out of it. The data itself is starting to make sense in context of your business, but what you haven't done quite yet, which is what insight driven businesses are, is really starting to take away. Um, the gap between when you see it, know it and then get the most value and really exploit what that insight is at the time when it's right. So in the moment we talk about this in terms of perishable insights, data and insights are ephemeral. And we want to ensure that the way that we're managing that and delivering on that data and insights is in time with our decisions and the highest value outcome we're going to have, that that insight can provide us. >>So are we just introducing it as data-driven organizations where we could see, you know, spreadsheets and PowerPoint presentations and lots of mapping to help make sort of longer strategic decisions, or are those insights coming up and being activated in an automated fashion within our business processes that are either assisting those human decisions at the point when they're needed, or an automated decisions for the types of digital experiences and capabilities that we're driving in our organization. So it's going from, I'm a data hoarder. If I'm data aware to I'm interested in what's happening as a data-driven organization and understanding my data. And then lastly being insight driven is really where light between business, data and insight. There is none it's all coming together for the best outcomes, >>Right? So people are acting on perfect or near perfect information or machines or, or, uh, doing so with a high degree of confidence, great advice and insights. And thank you both for sharing your thoughts with our audience today. It's great to have you. Thank you. Thank you. Okay. Now we're going to go into our industry. Deep dives. There are six industry breakouts, financial services, insurance, manufacturing, retail communications, and public sector. Now each breakout is going to cover two distinct use cases for a total of essentially 12 really detailed segments that each of these is going to be available on demand, but you can scan the calendar on the homepage and navigate to your breakout session for choice of choice or for more information, click on the agenda page and take a look to see which session is the best fit for you. And then dive in, join the chat and feel free to ask questions or contribute your knowledge, opinions, and data. Thanks so much for being part of the community and enjoy the rest of the day.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Welcome to the Virtual Cube and our coverage of aws reinvent 2020. I'm Lisa Martin. I'm joined by Ali Siddiqui, the chief product officer of BMC Software. We're gonna be talking about what BMC and A W s are doing together. Ali, it's great to have you on the Cube. Thank >>you, Lisa. Get great to be here and be part off AWS treatment. Exciting times. >>They are exciting times. That is true. No, never a dull moment these days, right? So all he talked to me a little bit. About what? A w what BMC is doing with AWS. Let's dig into what you're doing there on the technology front and unpack the benefits that you're delivering to customers. Great >>questions, Lisa. So at BMC, we really have a close partnership with AWS. It's really about BMC. Placido Blue s better together for our customers. That's what it's really about. We have a global presence, probably the largest, uh, off any window out there in this in our industry with 15 data centers, AWS data centers around the globe. We just announced five more in South Africa. Brazil Latin Um, a P J. A couple of them amia across the globe. Really? The presence is very strong with these, uh, data centers because that lets us offered local presence, Take care of GDP are and we have great certification. That is Aw, sock to fedramp. I'll four Haifa dram. We even got hip certifications as well as a dedicated Canada certifications for our customers. Thanks to our partnership, close partnership with the WS and on all these datas into the cross. In addition, for our customers, really visibility into aws seamless capability toe do multi cloud management is key and with a recent partnership with AWS around specifically AWS >>s >>S m, which gives customers cream multi cloud capabilities around multi cloud management, total visibility seamlessly in AWS and all their services whether it's easy toe s s s three sage maker, whatever services they have, we let them discover on syphilis. Lee give them visibility into that. >>That 360 degree visibility is really key to understand the dependencies right between the software in the services and help customers to optimize their investments in a W s assume correct. >>Exactly. With the AWS s s m and r E I service management integration. We really give deep visibility on the dependency, how they're being used, what services are being impacted and and really, AWS s system is a key, unique technology which we've integrated with them very, very happy with the results are customers are getting from it. >>Can you share some of those results? Operational efficiencies, Cost savings? Yeah, >>Yeah, least another great question. So when I look at the general picture off E I service management in the eye ops, which we run with AWS across all these global dinner senses and specifically with AWS S S M people are able to do customers. And this is like the talkto hyper scale, as we're talking about, as well as large telcos like Ericsson and and some of the leading, uh, industry retail Or or, you know, other customers we have They're getting great value because they're able to do service modeling, automatically use ascend to get true deep visibility seamlessly to do service discovery with for for for all the assets that they run or using our S service management in the eye ops capabilities. It really is the neck shin and it's disrupting the service idea Some traditional service management industry with what we offering now with the service management, AWS s, S M and other AWS Cloud needed capabilities such as sage Maker and AWS, Lex and connect that we leverage in our AI service management ai absolution. We recently announced that as a >>single >>unified platform which allows our customers to go on BMC customers and joined with AWS customers to go on this autonomous digital enterprise journey Uh, this announcement was done by our CEO of BMC. I'm in Say it in BMC Exchange recently, where we basically launched a single lady foundation, a single platform for observe ability, engagement with automation >>for the autonomous digital enterprise. I presume I'd like to understand to, from your perspective, this disruption that you're enabling. How is it helping your customers not just survive this viral disruption that we're all living with but be able thio, get the disability into their software and services, really maximize and optimize their cloud investments so that their business can operate well during these unprecedented times, meet their customer demands, exceed them and meet their customers. Where? There. How is this like an accelerator of that >>great question, Lisa. So when we say autonomous digital enterprise, this is the journey All our customers they're taking on its focus on three trips, agility, customer center, city and action ability. So if you think about our solutions with AWS, really, it's s of its management. AI ops enables these enterprises to go on this autonomous digital enterprise journey where they can offer great engagement to the employees. All CEOs really care about employee engagement. Happy employees make for more revenue for for those enterprises, as well as offer great customer experience for the customers. Uh, using our AI service management and AI ops combined. 80 found in this single platform, which we are calling 80 foundation. >>Yeah, go ahead. Sorry. >>No, go ahead, please. >>I was going to say I always look at the employee experience, and the customer experience is absolutely inextricably linked with the employee experience is hampered. That's bride default. Almost going to impact the customer experience. And right now, I don't know if it's even possible to say both the employee experience and the customer experience are even mawr essential to really get right because now we've got this. You know this big scatter That happened a few months ago with some companies that were completely 100% on site to remote being able, needing to give their employees access to the tools to do their jobs properly so that they can deliver products and services and solutions that customers need. So I always see those two employees. Customer experience is just inextricably linked. >>Absolutely. That's correct, especially in this time, even if the new pandemic these epidemics time, uh, the chief human resource offers. The CEOs are really thick focused on keeping the employees engaged and retaining top talent. And that's where our yes service management any other solution helps them really do. Use our digital assistance chat boards, which are powered by a W X and Lex and AWS connect and and and our integration with, uh, helix control them, which is another service we launched on AWS Helix Control them, which is our South version off a leading SAS product automation product out there, a swell as RP integrations we bring to the table, which really allows them toe take employing, give management to the next level And that's top of mind for all CEOs and being driven by line of business like chief human resource officers. Such >>a great point. Are you? Are you finding that mawr of your conversations with customers are at that sea level as they look to things like AI ops to help find you in their business that it's really that that sea level not concerned but priority to ensure that we're doing everything we can within our infrastructure, wherever where our software and services are to really ensure that we're delivering and exceeding customer expectations? That a very tumultuous time? >>Yes, What we're finding is, uh, really at the CEO level CEO level the sea level. It's about machine learning ai adopting that more than the enterprise and specifically in our capabilities when I say ai ops. So those are around root cause predictive I t. And even using ai NLP for self service for self service is a big part, and we offer key capabilities. We just did an acquisition come around, which lets them do knowledge management self service. So these are specific capabilities, predictability, ai ops and knowledge management. Self service that we offer that really is resonating very well with CEOs who are looking to transform their I T systems and in I t ops and align it with business is much better and really do innovation in this area. So that's what's happening, and it's great to see that we will do that. Exact capabilities that come with R E Foundation. The unified platform forms of ability and lets customers go on this autonomous digital enterprise journey without keeping capabilities. >>Do you see this facilitating the autonomous digital enterprise as as a way to separate the winners and losers of tomorrow as so much of the world has changed and some amount of this is going to be permanent, imagine that's got to be a competitive advantage to customers in any industry. >>We believe enterprises that have the growth mindset and and want to go into the next generation, and that's most of them. Toe, to be honest, are really looking at the ready autonomous digital price framework that we offer and work with our customers on the way to grow revenue to get more customer centric, increase employee engagement. That's what we see happening in the industry, and that's where our capabilities with 80 Foundation as well as Helix. Whether it's Felix Air Service management, he likes a Iot or now recently launched Helix Control them really enable them toe keep their existing, uh, you know, tools as well as keep their existing investments and move the ICTY ops towards the next generation off tooling and as well as increase employee engagement with our leading industry leading digital assistant chat board and and SMS management solution that that's what we see. And that's the journey we're taking with most of our customers and really, the ones with the growth mindset are really being distinguished as the front runs >>talk to me about some validation from the customer's perspective, the industry's perspective. What are you guys hearing about? What you're doing s BMC and with a w s >>so validation from customer that I just talked about great validation. As I said, talk to off the hyper skills users for proactive problem management. Proactive incident management ai ops a same time independent validation from Gardner we are back wear seven years and I don't know in a row So seven years the longest street in Gartner MQ for I t s m and we are a leader in that for seven years the longest run so far by any vendor. We are scoring the top in the top number one position in 12 of the 15 critical capabilities. As you know, Gardner, I d s m eyes really about the critical capability that where most customers look. So that's a big independent validation. Where we score 12 off the way were number one in 12 of the 15 capability. So that was the awesome validation from Gardner and I. D. S M. We also recently E Mei Enterprise Management Associates published a new report on AI Ops and BMT scored the top spot on the charts with Business impact and business alignment. Use cases categories for AI ops. So think about what that means. It's really about your business, right? So So we being the top of the chart for business impact and business alignment for ai ops radar report from Enterprise Management associated with a create independent validation that we can point toe off our solutions and what it is, really, because we partner very closely with our customers. We also got a couple of more awards than we want a lot more, but just to mention two more I break breakthrough, which is a nursery leading third party sources out there for chat boards and e i base chat board solution lamed BMC Helix Chat Board as the best chat board solution out there. Uh, SAS awards another industry analysts from independent from which really, uh really shows the how we're getting third parties and independents to talk about our solutions named BMC SAS per ticket and event management, which is really a proactive problem and proactive incident solution Revolution system as as the best solution out there for ticketing and event management. >>So a lot of accolades. A. Yes. It sounds like a lot of alcohol. A lot of validation. How do customers get How do you get started? So customers looking to come to BMC to really understand get that 3 60 degree visibility. How did they get started? >>Uh, well, they can start with our BMC Discovery, which integrates very tightly with AWS s s M toe. Basically get the full visibility off assets from network to storage toe aws services. Whether there s three. Uh, easy to, uh doesn't matter what services they did. A Kafka service they're using whatever. So the hundreds of services they're using weaken seamlessly do that. So that's one way to do that. Just start with BMC Helix Discovery. Thea Other one is with BMC Knowledge Management on BMC Self Service. That's a quick win for most of our customers. I ai service management, tooling That's the Third Way and I I, off stooling with BMC, Helix Monitor and AI ops that we offer pretty much the best in the industry in those that customers can start So the many areas, and now with BMC, control them. If they want to start with automation, that's a great way to start with BMC control them, which is our SAS solution off industry leading automation product called Controlling. >>And so, for just last question from a go to market perspective, it sounds like direct through BMC Channel partners. What about through a. W. S? >>Yes, absolutely. I mean again, we it's all about BMC and AWS better together we offer cloud native AWS services for our solutions, use them heavily, and I just mentioned whether that S S M or chat boards or any of the above or sage maker for machine learning I and customers can contact the local AWS Rep toe to start learning about BMC and AWS. Better together. >>Excellent. Well, Ali, thank you for coming on the program, talking to us about what BMC is doing to help your customers become that autonomous digital enterprise that we think up tomorrow. They're going to need to be to have that competitive edge. I've enjoyed talking to you >>same year. Thank you so much, Lisa. Really. It's about our customers and partnering with AWS. So very proud of Thank you so much. >>Excellent for Ali Siddiqui. I'm Lisa Martin and you're watching the Cube.

>>from around the globe. It's >>the Q with digital coverage of AWS Public sector online brought to you by Amazon Web services. Hello. I'm John for a host of the Cube. We're here covering A W. S s international public sector virtual event. We have a great guest. The star of the program is Max Peterson, Good friend of the Cube. Also Vice President of A W s International for Public Sector Max. Great to see you. Thanks for coming on this virtual remote interview. Cuban interview. Hey, >>John. Great to be back on the Cube, even if it is virtual >>well, you know, we're not face to face. We have to go virtual. So the cube virtual, you've got to public sector summit. Virtual. Um, this is the time of the year where normally we'd be out on the road in Bahrain, Japan, Asia, Pacific Europe. We'd be out on the summits talking to all the guests and presenting that the update on public sector. But we have to do it remotely. Um, a little bit of trade off. The good news is with cove it for at least you guys. It's a global media network. And with these remote interviews. Uh, public sector is seeing a lot more global activity, and that's what I want to get your thoughts on. What is the business update internationally for public sector? I'm sure that with CO over the pandemic, you're seeing a lot of activity. How is the public sector business doing internationally? >>John, You know, you mentioned one of the silver linings of a pretty bad situation with the Koven pandemic. And that's been that it has meant that people have to be resourceful. Governments have to be resourceful on DSO. There's been a tremendous amount of innovation people have gotten used to now using modern cloud technology to support remote work and remote war learning. Um, out of necessity, we've had to figure out how do we deliver far greater health care services using digital technology, telemedicine, digital social care, uh, chime rooms? Uh, it really, in a nutshell, has been a tough six months for people, but a relative relatively busy six months for innovation. And for i t for the public sector customers, >>you know, I did an interview a few months ago for one of the award programs in Canada. Um, with the center had a customer on disk customers. The classic customer, a Amazon. You know, I'm not sure we do it all internally. He deployed A W S Connect in literally days that saved the lives of many of his countrymen and women by getting the entitlement checks out. And he was a glowing endorsement because, he said, with Cove in 19 they were crippled. He said they will. They stood up a call center and literally he was converted. That's just one example again. That's Canada of the kind of solutions that you guys air, enabling with Cloud to quickly respond to the crisis, to use technology to solve other technology problems and also business problems. Can you give an example on the international front of where you're seeing some activity? Because this seems to be the same pattern we're seeing, People who have used in the cloud we cube virtual. Will there be no Cuba's wasn't for our cloud implementations, but this is, um, obvious, but I want to call it out. It's important. Can you share some examples of people internationally using the cloud to get and respond to the to the cove in 19 pandemic in delivering services? >>Yeah, In fact, John, we're focusing a lot on that at the public sector summit online that comes up here in October. Um, a couple of quick examples. In fact, one of the top learnings is speed matters. And so we have Eve Curry from Australia, who talks about social and health care and how they were able to get a complete digital suite up and running for supporting 5000 elderly patients and over 3000 employees in less than a week, and that included getting up and running a video conferencing and tele consultation capability using AWS chime. It involved getting up and running collaboration space for the remote workers using work work docks. And it involves setting up a complete call center on the cloud, using Amazon time and literally that was done in less than a week. Another example, really ambitious example, which again is a testament to the innovation and, uh, the capability, the capability that AWS brings to customers. I'm in India. They had a number of tele medicine applications. They were available for a fee, but they didn't have a universal way to reach the vast population in India. And so when the pandemic hit three organization that was responsible for the public health component was challenged to get a no cost tele consultation hella medicine system up and running for outpatient services that could scale to reach a billion people. Um, they did that in 19 days. They got the system up and running Now hasn't gotten to a billion people online at one time. But there right now, doing 6000 consultations a day with about 4000 doctors, and they're headed toward 100,000 consultations today. Eso just to your point, speed and scale. We're seeing it across the board from from our public sector customers. >>You know, it's just mind boggling just to kind of pinch myself from it in 19 days. It's crazy, right? I mean, crazy fast If you throw back to the eighties and nineties when I broke into the business, you know, young gun client server was all the rage back then. And if you wanted to do, like a big apt upon an oracle s a p, whatever it was years, it was months just to do planning. E mean, I mean, think about the telemedicine example 19 days. That's huge. I mean, just the scale is just off the charts. So So I mean, even if you're not a believer in cloud I don't feel should be should just go home and retire at this point because it's just obvious. Uh, the question I wanna ask you specifically because Theresa brought this up on my last interview with her. And I wanna ask you the same question is, what is AWS doing specifically to help customers? I know customers are helping themselves. You mentioned that. What are you guys doing? Toe? Accelerate this. How are you helping of you guys changed a little bit. Can you just share what you guys specifically doing to help customers pivot toe not only solving it, but having a growth strategy behind it? >>Yeah, John, that's a great question. Some of the things that we're doing our long standing programs and so customers from day one have had a need for skills and workforce development. We keep on doubling down on those programs. Things like a W s academy aws educate our restart programs in different countries. So number one is we continue to help customers double down on getting the right cloud skills to enable the digital workforce. The second thing, in fact, if I can, for just amendment, um, there is actually a section of the public sector online called the New Workforce, which talks about both the digital skills that are required and then also some of the remote working skills that we need to help folks with. So So workforce is a big one. Um, the second one. Yeah, and I'm super excited about this because we've opened up the opportunity, form or customers around the globe to participate in our city on the Cloud Challenge Onda That gives a great opportunity to showcase and highlight the innovation of public sector customers and, you know, win some AWS credits and technical assistance to help them build their programs. But I think one of the most the things I'm most proud about in the last 6 to 9 months was when the when this pandemic struck and we listen to our customers about what they needed. We came out with something called the AWS Diagnostic Development Initiative, and that was a program specifically aimed at providing technical assistance. Um, a ws cloud credits all to researchers to help them, um, tackle the tough questions that need to be answered to help us deal with and then hopefully resolve the pandemic. >>So on the international front, like I said earlier in the open, we would've been in Bahrain. That's a new region, only a couple of years old, Obviously the historic, um this, um, geopolitical things happening there, opening things up, that's been a very successful region. This is the playbook. Can you just give us an update on some of the successes in the different regions by rain and then a pack and other areas? What? Some of the highlights? >>Sure, John, One of the things that I think it's super exciting is that all of these customers are developing new capabilities right now. Um, one example from Egypt. Uh, they had to get literally an entire student population back to school. When the pandemic hit on DSO. They quickly pivoted to bringing a online learning management system or LMS up on the cloud on AWS. Um, and they have been able to continue to teach classes, literally to millions of students there. We've seen that same sort of distance learning online education across the globe. Another example would be when countries needed to figure out how to beam or effective in that sort of time tested, contact tracing process. So So when ah person has been found to have the the flu or the illness the subject illness, um, they typically have a lot of manual contact tracers that have to try to identify kind of where that person's been and see if they can. Then, um, helped to control the spread of whatever the diseases Kobe 19. In this case, um, we put together with governments across the world with a W s partners across the world again in very fast order, automated systems to help governments manage this, um, Singapore is a super example. India's a massively scaled example, but we did it in countries of across the globe, and we did it by working with them and the partners there to specifically respond to their needs. So everybody's case, while similar at a high level, you know, was unique in the way that they had to implement it. >>And it's been a great, great ride international us with co vid. You guys have ah current situation. You guys are providing benefits and I'll see the cloud itself for the customer to build those modern APS. The question I wanna ask you, Max, as an executive at eight of yourself. So you've been in the industry, Um, with public sector pre covert, it's, you know, it's before Cove. And there's after Govind is gonna be kind of like that demarcation line in the society. Um, it has become a global thing. I just did an event with Cal Poly was mentioned before we came on, um, small little symposium that would have been, you know, face to face. But because we did it virtually it's now global reinvents coming up. That's gonna be essentially virtual. So it's gonna be more global, less physical, space to face. Everything is introduced, no boundaries. So how >>does that >>impact? How do you How do you guys, How do you look at that? Because it impacts you, I guess a little bit because there's no boundaries, >>right? You know, John, I think this plays into what we're talking about in terms of people and governments and organizations getting used to new ways of working on de so some of our new workforce development is based around that, not just the digital skills in the cloud skills a couple of the things that we've recognized by the way, Um, it's different, but done well, there's new benefits. And so so one of the things that we've seen is where people employ chime, for instance, Uh, video conferencing solution or solutions from our partners like Zoom and others. Onda people have been able to actually be Maurin touch, for instance, with elder care. Um, there were a number of countries that introduced shielding. That meant that people couldn't physically go and visit their moms and dads. Um and so what we've seen is a number of systems on care organizations that have responded andare helping thing the elderly, uh, to use this new tech on. But it's really actually, uh, heartwarming, uh, to see those connections happen again, even in this virtual world. And the interesting thing is, you can actually step up the frequency on DSO. You don't have to be there physically, but you can be there, Andi and interact and support with the number of these thes tools. I think one of the other big learnings that we've seen for many organizations and just about every public sector group has toe work with, um uh, their constituents on the phone. Of course, we've got physical offices, you know, whether it's a hospital or a outpatient center or a social care center. Um, but you always have to have a way to work on phones. What's happened during the Cove in 19 Pandemic is there's been a surge is where information needed to get out to citizens or where citizens literally rushed the phone lines to be able to get the most current information back. Andi, the legacy called systems have been completely overwhelmed, their inadequate. And we've seen customers launch the online call center in the cloud piece, using Amazon connect as their starting point. But then, you know, continuously innovating. And so starting to use things like Lex to be able to deliver a chat box function, Um, in the in the US, for example, one of our partners, Smartronix, was able to automate the welfare and social care systems for a number of different states to the point now where 90 plus percent of those calls get initially handled, satisfied using a chat bots, which frees up agents the deal, you know, with the more difficult inbound calls that they get. >>I gotta ask you, where do we go from here? What's next for these organizations? Post Covad World. You know, if we're sitting at a cocktail party was sitting down having dinner or where he talking remotely here, how would you? How would you explain to me what's what's next? Where do we go from here? And how do organizations take that next post co vid recovery and growth? What's your take? >>And John? I think that's a fantastic question to ask. Let me tell you what we learn from our customers every day because we see them try and do new things. If I had to take my sort of crystal ball, I think we're in version one of figuring out How do we work in this new environment? I think there's a couple of key things that we're going to see. Number one. Um, resilience and continuity of service is not gonna be optional. Everybody is coming to expect that government care, not for profits. Education is going to be able to seamlessly continue to deliver the core services irrespective of these world events or emergencies on B C customers. Now you know, really getting that right. It used to take. You talked about it? Um, heck, you couldn't get a system up and running in 19 days. You'd be lucky if you cut a purchase order in 19 days and citizens and constituents that aren't going to accept that anymore, right? That's one big, uh, change that I think is with us. And we'll keep on driving cloud adoption. I think the next one is how do we start putting the pieces together in ways that make some of this invisible and an example? Um, you know, kind of starts with that with that example in the US with partner that was building systems to help, uh, welfare and social care call centers operate smoother. But if you think about the range of AWS services and the building blocks that customers have, we'll find customers starting to create that virtual experience in aversion to dot away where they tie the contact center into chat box and into transcription. Like, for instance, being able to have a conversation with the parents and using comprehend medical actually get a medically accurate transcription. So the doctor can focus on that patient interaction and not on actually data captured, right, and then if that patient asks. Well, g Doc, could you give me more information about, you know, X y z, uh, medication, or about what a course of treatment sounds like? Instead of tying up the doctors time, you could go and use a tool like Amazon Polly to then go text to speech and give all of that further rich information to that citizen. Um e think some of them things. Same scenarios, right? How do we go from this? This very fast version one dot response to a a mawr immersive, less tech evident capability that strings these things together that to meet kind of unique use cases or unique needs. >>Yeah, I think that's totally right. I think you know the 19 days. Yeah, I'm blown away by that. But I think you know, we thought about agility. That was a cloud term. Being more agile with your code business. Agility has come on the scene and then with business agility you have I call I call business latency. Andi, you went from years to months, months, two days. And I think now, as you get into the decks versions, it's days, two hours, hours, two minutes, hours two seconds Because when you look at the scale of the cloud some of things we were talking what's going on? Space force and globally around with space Leighton See, technically and business late and see this is the new dynamic and it's gonna be automation. Ai these air. This is the new reality. I think co vid points that out. Uh, what's your reaction to that? And give a final message to the AWS international community out there on on how to get through this and what you guys are doing? >>Yeah, John, I think your observation is you know that increasingly, uh, there needs to be a connectedness between the services that thes public sector customers deliver on dso Um, that connectedness can be in terms of making sure that a citizen who eyes on their life journey doesn't need to continuously explain to government where they're at. But rather, government learns how to create secure, scalable data stores so that so that they understand the journey of the citizen and can provide help through that journey. Eso it becomes mawr citizen centric. I think another example is in the entire healthcare arena where what we have found is that the ability thio to securely collaborate on very complex problems and complex data sets? Uh, like like genomes, um is increasingly important on DSO. I think what you'll find is you'll find we're seeing it today, right? With customers like, uh, Genomics England and the UK Bio Bank were there, in fact, creating these secure collaboration spaces so that the best researchers can work against these very important data sets in a secure, yet trusted collaboration environment. So I think we're seeing much more of that on I would say The third thing that we're probably learning from our customers is just how important that skills and workforce pieces. Um, with the accelerated pace, we continue to see pressure on smart skills, and resource is that our customers need. Fortunately, we've got a great global partner ecosystem, Um, but you'll see us continuing to push that forward as a zone agenda that will help customers with eso. I guess my parting comment would be how could it not be? I hope that the customers that attend the summit are from all over the world. I hope they find something that's useful to them in pursuing their mission and in their journey to the cloud. And John, I just This is always a pleasure to join the Cube. Thanks very much for the time today. Thank >>you, Max. Great. Call out. Just I'll call it out. One more time to amplify the learnings in the workforce development starting younger and younger. The path to get proficiency is quickly. You could be a cloud computing cybersecurity application, modern application development, all hot areas. Uh, the new playbook is cloud. It's all there online. And, of course, Max. Global footprint with the regions, the world has changed, and it's gonna be pretty busy. Time for you. We'll be covering it. Thanks for coming on. >>That's great. Thanks, John. >>Okay, I'm John. Free with the Cube. You're watching any of US? Public sector summit, The international online event. I'm John. Hard to keep your host. Thank you for watching

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape hello everyone and welcome to this week's episode of wiki bots cube insights powered by EGR in this breaking analysis we take a deeper dive into the world of robotic process automation otherwise known as RPA it's one of the hottest sectors in software today in fact Gartner says it's the fastest growing software sector that they follow in this session I want to break down three questions one is the RP a market overvalued - how large is the total available market for RP a and three who were the winners and losers in this space now before we address the first question here's what you need to know about RP a the market today is small but it's growing fast the software only revenue for the space was about 1 billion dollars in 2019 and it's growing it between 80 to a hundred percent annually RP a has been very popular in larger organizations especially in back-office functions really in regulated industries like financial services and healthcare RP a has been successful at automating the mundane repeatable deterministic tasks and most automations today are unattended the industry is very well funded with the top two firms raising nearly 1 billion dollars in the past couple of years they have a combined market value of nearly 14 billion now some people in the art community have said that RP a is hyped and looks like a classic pump and dump situation we're gonna look into that and really try to explore the valuation and customer data and really try to come to some conclusions there we see big software companies like Microsoft and sa P entering the scene and we want to comment on that a little later in this segment now RBA players have really cleverly succeeded in selling to the business lines and often a bypassed IT now sometimes that creates tension in or as I said customers are typically very large organizations who can shell out the hundred thousand dollar plus entry point to get into the RP a game the Tam is expanding beyond back office into broader on a broader automation agenda hyper automation is the buzzword of the day and there are varying definitions Gartner looks at hyper automation as the incorporation of RPA along with intelligent business process management I BPM and I pass or intelligent platform-as-a-service Gardner's definition takes a holistic view of the enterprise incorporating legacy on-prem app apps as well as emerging systems now this is good but I question whether the hyper term applies here as we see hyper automation as the extension of our PA to include process mining to discover new automations or new automation opportunities and the use of machine intelligence ml and a I applied to process data data where that combination drives intelligence analytics that further drives digital business process transformation across the enterprise so the point is that we envision a more agile framework and definition for hyper automation we see legacy BPM systems informing the transformation but not necessarily adjudicating the path forward we liken this to the early days of big data where legacy data warehouses and ETL processes provided useful context but organizations had to develop a new tech stack that broke the stranglehold of technical debt we're seeing this emerge in the form of new workloads powered by emerging analytic databases like redshift and snowflake with ml tools applied and cloud driving agile insights in that so-called Big Data space so we think a similar renaissance is happening here with with automation really driven by the money the mandate for digital business transformation along with machine intelligence and that tooling applied for a really driving automation across the enterprise in a form of augmentation with attended BOTS at scale becoming much much more important over time ok now let's shift gears a little bit question is the RP a market overhyped and overvalued now to answer this let's go through a bit of a thought exercise that we've put together and look at some data what this chart shows is some critical data points that will begin to help answer the question that we've posed in the top part of the chart we show the company the VC funding projected valuations and revenue estimates for 2019 and 2020 and as you can see uipath an automation any where are the hot companies right now they're private so much of this data is estimated but we know how much money they've raised and we know the valuations that have been reported so the RP a software market is around a billion dollars today and we have it almost doubling in 2020 now the bottom part of this chart shows the projected market revenue growth and the implied valuations for the market as a whole so you can see today we show a mark that is trading at about 15 to 17 times revenue which seems like a very high multiple but over time we show that multiple shrinking and settling in mid decade at just over 5x which for software is pretty conservative especially for high-growth software now what we've done on this next chart is we brought down that market growth and the implied valuation data and highlighted twenty twenty-five at seventy-five billion dollars the market growth will have slowed by then to twenty percent in this model and this thought exercise with a revenue multiple of five point four x for the overall market now eventually as growth slows RBA software will start to throw off profits at least it better so what we show here is a sensitivity analysis assuming a 20% 25% 30% and 35% for the market as a whole we're using that as a proxy and we show a 20/20 X even multiple which for a market growing the software market growing this fast you know we think is pretty reasonable consider the tech overall typically is gonna have a an even multiple of ten to fifteen you know X it really should be easy your enterprise value over a bit it's really a more accurate measure but but this is back in the Afghan on the balance sheet date and I'm a forecast all-out but we're trying to just sort of get to the question is is this market overvalued and as you can see in the Far column given these assumptions we're in the range of that seventy five billion dollar market valuation with that Delta now reality you're going to have some companies growing faster than the market overall and we'll see a lot of consolidation in this space but at the macro level it would seem that the company which can lead and when the Spoils is gonna really benefit okay so these figures actually suggest in my view that the market could be undervalued that sounds crazy right but look at companies like ServiceNow and work day and look at snowflakes recent valuation at twelve billion dollars so are the valuations for uipath and automation anywhere justified well in part it depends on the size of the market the TAM total available market in their ability to break out of back-office niches and deliver these types of revenue figures and growth you know maybe my forecasts are a little too aggressive in the early days but in my experience the traditional forecast that we see in the marketplace tend to underestimate transformative technologies you tend to have these sort of o guides where you know it takes off and really steep ins and it has a sharp curve and then tapers off so we'll see but let's take a closer look at the Tam but you know first I want to introduce a customer view point here's Eric's Lac Eric Lex who's an RPA pro at GE talking about his company's RPA journey play the clip I would say in terms of our journey 2017 was kind of our year to prove the technology we wanted to see if this stuff could really work long term and operate at scale given that I'm still here obviously we proved that was correct and then 2018 was kind of the year of scaling and operationalizing kind of a a sustainable model to support our business units across the board from an RPA standpoint so really building out a proper structure building out the governance that goes along with building robots and building a kind of a resource team to continue to support the bots that that you know we were at scale at that point so maintaining those bots is critically important that's the direction we're moving in 2019 we've kind of perfected the concept of the back office robot and the development of those and running those at scale and now we're moving towards you know a whole new market share when it comes to attended automation and citizen Development so this is a story we've heard from many customers and we've tried to reflect it in this graphic that we're showing here start small get some wins prove out the tech really in the back office and then drive customer facing activities we see this as the starting point for more SME driven digital transformations where business line pros are rethinking processes and developing new automations you know either in low code scenarios or with Centers of Excellence now this vision of hyper automation we think comes from the ability to do process mining and identify automation opportunities and then bring our PA to the table using machine learning and AI to understand text voice visual context and ultimately use that process data to transform the business this is an outcome driven model where organizations are optimizing on business KPIs and incentives are aligned accordingly so we see this vision as potentially unlocking a very large Tam that perhaps exceeds 30 billion dollars go now let's bring in some of these spending data and take a look at what the ETR data set tells us about the RPA market now the first thing that jumps out at you is our PA is one of the fastest growing segments in the data set you can see that green box and that blue dot at around 20% that's the change in spending velocity in the 2020 survey versus last year now the one caveat is I'm isolating on global 2000 companies in this data set and as you can see in in that red bar up on the left and remember our PA today is really hot in large companies but not nearly as fast growing when you analyze the overall respondent base and which includes smaller organizations nonetheless this chart shows net scores and market shares for our PA across all respondents remember net score is a measure of spending velocity and market share is a measure of pervasiveness in the survey and what you see here is that our PA net scores are holding steadily the nice rate and market shares are creeping up relative to other segments in the data set now remember this is across all companies but we want to use the ETR data understand who is winning in this space now what this chart shows is net score or spending velocity on the vertical axis and market share or pervasiveness on the horizontal axis for each individual player and as we run through this sequence from January 18 survey through today across the nine surveys look at uipath an automation anywhere but look at uipath in particular they really appear to be breaking away from the pack now here's another look at the data it shows net scores or spending velocity for uipath automation anywhere blue prism pegye systems and work fusion now these are all very strong net scores which are essentially calculated by subtracting the percent of customers spending less from those spending more the two leaders here uipath and automation anywhere August but the rest rest are actually quite good there in the green but look at this look what happens when you isolate on the 349 global 2,000 respondents in the survey uipath jumps into the 80 percent net score territory again spending velocity automation anywhere dips a little bit pegye systems interestingly jumps up nicely but look at blue prism they fall back in the larger global 2000 accounts which is a bit of a concern now the other key point on this chart is that 85% of UI customers and 70% of automation anywhere customers plan to spend more this year than they spent last year that is pretty impressive now as you can see here in this chart the global 2000 have been pretty consistent spenders on our PA for the past three survey snapshots uipath again showing net scores or spending intensity solidly in the 80% plus range and even though it's a smaller end you can see pay go with a nice uptick in the last two surveys within these larger accounts now finally let's look at what ETR calls market share which is a measure of pervasiveness in the survey this chart shows data from all 1000 plus respondents and as you can see UI path appears to be breaking out from the pack automation anywhere in pega are showing an uptick in the january survey and blue prism is trending down a little bit which is something to watch but you can see in the upper right all four companies are in the green with regard to net score or against pending velocity so let's summarize it and wrap up is this market overhyped well it probably is overhyped but is it overvalued I don't think so the customer feedback that we have in the community and the proof points are really starting to stack up so with continued revenue growth and eventually profits you can make the case that whoever comes out on top will really do well and see huge returns in this market space let's come back to that in a moment how large is this market I think this market can be very large at am of 30 billion pluses not out of the question in my view now that realization will be a function of RPAs ability to break into more use cases with deeper business integration RBA has an opportunity in our view to cross the chasm and deliver lower code solutions to subject matter experts in business lines that are in a stronger position to drive change now a lot of people poopoo this notion and this concept but I think it's something that is a real possibility this idea of hyper automation is buzzword e but it has meaning companies that bring RPA together with process mining and machine intelligence that tries process analytics has great potential if organizational stovepipes can be broken down in other words put process data and analytics at the core to drive decision-making and change now who wins let me say this the company that breaks out and hits escape velocity is going to make a lot of money here now unlike what I said in last week's braking analysis on cloud computing this is more of a winner-take-all market it's not a trillion dollar team like cloud it's tens of billions and maybe north to 30 billion but it's somewhat of a zero-sum game in my opinion the number one player is going to make a lot of dough number two will do okay and in my view everyone else is going to struggle for profits now the big wildcard is the degree to which the big software players like Microsoft and sa P poison the RPA well now here's what I think I think these big software players are taking an incremental view of the market and are bundling in RPA is a check off item they will not be the ones to drive radical process transformation rather they will siphon off some demand but organizations that really want to benefit from so-called hyper automation will be leaning heavily on software from specialists who have the vision the resources the culture in the focus to drive digital process transformation alright that's a wrap as always I really appreciate the comments that I get on my LinkedIn posts and on Twitter I'm at at D Volante so thanks for that and thanks for watching everyone this is Dave Volante for the cube insights powered by ETR and we'll see you next time

from New York it's the cube covering escape 19 okay welcome back to the cube coverage New York City for the inaugural multi-cloud conference the first one ever in the industry is called escape 2019 we're in New York so escapee from New York City from cloud that's the conversation all the thought leaders are here and executives people thinking about the next generation architecture and top tracks are all here if it's Wednesday who's the chief information security officer for Flextronics flex let's thank you for coming on love to have see so some because security seems to be there always a top conversation you got a very busy job I do yes you heard a lot of pressure all the time it's fun it's so fun for me so yeah as a Caesar and it's always like security stop in mind right of everyone out these days yeah and it's very sir one of the most interesting job I think most of the interesting for my trophies I learned so much about our business and they have insight into so many things that's actually really great you know one of the things I was just talking about on the kind of cube conversation was you know how date is really important part of it and how data backup and recovery was built on old thinking around you know data centers failing floods hurricanes electricity gets outages but the biggest disruption in business today is security security threats and so that's the cyber security pressure it's causing CISOs to to be mindful of the best architecture the best platform do we have the right tools so I wanna get your thoughts how are you thinking about that as an organization because you are you building in-house developers are you how you how are you organizing how are you gearing up to fight the battles that need to be fought so I am and I'm with the company so if Lex is a big manufacturing company right 26 billion so we have a lot of p2p business not consumer business which is I believe a different perspective of security versus actually like a consumer company facing so and I'm if in a security team for 15 years so we put it up like security operations and the orders kind of things really right we're old school I am what school learnt everything in that right but you a lot of IOT I mean you just really achieve oh yeah Industrial tea it's one of the topic but coming back to you you're right data is actually the center in Flour business data is getting more center right you collect data from the machine you collect data actually for the business actually to make more decisions right and could be predictive maintenance could be inventory management there could be a lot of things right you have to think about it so and the funny thing is I'm real I'm the seasonal for five years 15 years with the security team 20 years with the company so I rebuilt the team always like every three four years you like it's a kind of rebirth of the team we renew we add new skills right and cloud is one of the things which I think it's a fundamental change and the change is actually with it's actually on the development side what it means with that it's a security team has to move to serve the developers and the problem if the wood school was always like it's after sort so why I secured to such an issue because we had to do patching after we found vulnerabilities right and then old network is unsecure you need to wrap something around that like we did firewall so it was always an after sort now with the cloud it's changing because you have a lot of different things to do but basically we need to enable developers to be very quick and deploy their software very quickly so you know it is a fundamental change in the way you have to think the particular yeah and then that brings up the good question love to ask you because given you guys again not a consumer like Capital One yeah they don't challenge they got they weren't hacked Amazon actually the firewall was misconfigured an s3 bucket but that's a consumer company you have data though you're an industrial company got a lot of industrial IOT ransomware folks are targeting data yes and everyone's a target it's your surface area is large but you probably lock that down in the past so how are you thinking about all this new stuff so yeah I mean IOT it's I mean I would tease the problem as you said Industrial right it's not solved yet completely right because they still have to rethink a lot of the vendors providing this machinery which you've purchased for 25-30 years right this Silla wood school right sometimes like the one witness you can't upgrade or whatever such basic things they'd be lacking actually in terms of security there still has to be a shift in this you know not just in the industry but in a general thinking how you do that yes I have a big environment so we locked it down we use a lot of innovative technologies actually preventive measurements was also detected measuring and you need to create kind of mightily a concept where you actually start okay what is if this figures how we test it okay this face do we have other measurements where we can try to prevent measure stop those kind of things right but Wrentham is a big one there's other things as you know like hacking I mean they're kept in I was healing probably the capital one was an interesting money my I believe in that for the cloud its configuration issues right which I think it comes with cloud security it's about policy and configuration management right how you manage that and how you think about it but it's not it was not a nation gonna solve that I mean that's a open s3 bucket that's trivial I wasn't a big yes and no you look if you look at that it was a little bit more in detail so it was actually the back firewall was misconfigured which is a mod security running on a fresh air but the Miss configuration was actually a SS as server surgery force request issue which means like you tricked this firewall in giving you information you shouldn't give you so it was a little bit more granular as people think it was right just as free pocket configuration so it was a little bit more greener but I think that's the word the difficult comes about it which every security it's a complex problem right it's the many things you have - configuration error it was a configuration dumb as an s3 bucket no it was not rounded more sophisticated but not that sophisticated was it yellow what the change I would not sophisticated but something it's not easy to solve so you have to think about it but you're right it's still something exploit from a corner case it's still something you could have I mean I I'm careful to say you could have avoided yes you could because that's for sure but I know it's a complex environment right I'm not a human as humans involved and I know I don't know that eaters exactly we only know that once it's published right so it's very hard to to charge well let's bring some cloud security so let me ask you on multi-cloud this is a multi cloud conference what's your definition of multi-cloud how do you look at the multiple clouds for me more debris cloud is actually doesn't matter we had the good keynote where I said it's a bunch of service right that's how I see my two cloud it's a bunch of service could be my data centers in the public cloud data centers with different vendors that's what a cow is where I move my services should be actually independent from the public hybrid on-premise whatever it is right that's basically how I see it so it doesn't matter it's infrastructure on demand leverage it leverage it it could be say hey today I spin off this test server but you know what today it seems to be a cheaper all running on the Eva Lovelace versus CPC let's do it here next day next week we might do it somewhere else whatever you trigger whatever what is your requirements so you'd only look at that resource that like that how do you think about the cloud security then because the configurations compliance how do you how do you stay on top of that so that's an interesting thing because we a big enterprise but we as you said know consumer business so our problem is to find the right skill set to attract the right people to our company to do that right because this is our we have some cloud but it's not yet there's a journey we are trying to do as most of the enterprise so we're looking into startups managed services we say okay where are the gaps where we have to really have to outsource some of the things and gaps where we need to get information what's your advice to other CISOs out there that are in the b2b space of none other deal to consumer but I have to get serious that is now becoming more industrialized on the IOT side because you guys have been you know been there done that you have a big footprint on the IOT because you're history but as people get more facilities and they have more virtual offices more people working the edge is extending what's your advice to those CEOs who have to deal with this industrial and IOT edge I think you have to visibility is the key ingredient is first right if you don't know what you have it's very hard to understand what's the risk portfolios right so you need to find the right to set and don't believe you know what they have it's fantastic what you see when you use the right tool what this is everything is connected I mean basically even like I found like this coffee market I connect the devices right it's like like everyone just don't understand like it's kind of light poles get both wake multi-threaded processor what is that doing so there's I mean but visibility is a key ingredient so you have to understand and then you have to look into how you might take a terrace what is your risk about it right I mean if the coffee mug goes down I don't really care but if my testicles sound and I shut down the production I really care about that so you need to understand that risk and say how can i mitigating risk so while I got you here what's your final question what's your message to suppliers out there that all want to sell you something they want to sell you another tool you know an another tool you know I got a platform I got a tool you mean this here 750 which is existing now like the cybersecurity if you go to I say conferences unbelievable right it's like I want to sell you something you're the top dog I use shrinking suppliers down are you looking at some sort of standard API way to deal with them because you know you're obviously probably thinking about platforming and data visibility is critical what's your philosophy on how to support medieval suppliers so usually honestly the most time I really go in so for innovative technology we built in our company our so-called strategic partnership program were being it for startups and most of the time we engage we start of services or through other channels right but you get introduced and you review with a proof of concept of value the technology and we try to keep it like as a minimum value product very short time and say okay let's show what you can where your gaps are and can we get with you guys and come and get you but don't send me an email don't call me because I usually not react I have a job to do so that's most of the time where the disease were what comes all of the guys that hey I found another scissors tell me there's great technology you should look into that and what shows do you go to what events do you hang out and what are good events for you in this in the space RSA Red Hat black depth on are there certain events that you go to that you think are valuable I mean it's easily I go to the to the RSA Conference ership because actually it's very close to me as well yeah and being part being out of Santa C I recommend the b-sides actually I like the peace sign that these guys are great the pieces are great I think they are real value and then I try to a smaller circus I'd be a fun person around papers there's b-sides for folks watching is an alternative group of community industry participants they have kind of a b-side of a side like an album but it's essentially community event they do hackathons and variety of other cool things where people get together very unstructured kind of cool conference addition to bigger conferences I can't recommend desk yeah bitch thanks for coming on and sharing your insights there's pleasure there's a cube coverage here in New York City we're not escaping from the University escape conference the first multi-cloud conference in the industry we'll see how it goes if they're successful they might be back next year if not they won't be but I think multi-class here today what do you think okay great thanks for coming on I'm John Fourier thanks for watching

>> from Austin, Texas. It's Theo Cube, covering your storage. Accelerate 2019. Brought to you by pure storage. >> Welcome to Austin, Texas. This is the Cube. Live at the fourth annual pure accelerate. I'm Lisa Martin with David, Dante, Dave or in Texas, >> Texas again. >> Austin, Texas. Very interesting venue for this fourth annual hear stories. >> A lot of construction, >> music, a >> lot of music. >> So we just came from the keynote and news announcements, customers on stage. But the first thing to point out is, this is here is about to celebrate their 10th anniversary. Charlie Giancarlo, CEO and chairman who's coming on the program with us, and just a few minutes talking about what they have innovated and delivered these 10 X improvements and 10 years kind of this overnight success in 10 years and what's coming? What was with the things that really stuck out at you, Nicky Note. >> Well, first of all, ironically, this is the 10th year of the Cube, not our 10th anniversary, but it's the 10th year of doing the Cube. And so our fourth year, I think it's pure accelerate about what 3000 people here, >> you know, the keynotes >> pure was laying out what their vision is of the modern data experience and that I felt like the keynotes least there were sort of, ah, speed date of what's coming. There was a couple of major announcements that we'll talk about, >> Uh, but >> they really are trying to differentiate as the modern storage company turn a deep position. The competition, as the old guard is to use this term that Andy Jassy uses pure, didn't use that term. But they really talked about it's time to go Modern. And so they were an overnight success. It took him 10 years, was one of the comments that was on stage. So I think this is worth pointing out. A couple of things. I mean, let me lay out. Sort of my thoughts on Pure is a company. They were the only storage company Ah, in the past. Let's call a decade to reach what I'll call escape velocity. They achieved a billion dollars a couple years ago. They're doing their due about a billion and 1/2 on a trailing 12 month basis. They'll do 1.7 billion this year and evaluations about 4.5 billion. So they got a a three ex valuation in that fluctuates. That's pretty good for a storage company. Billy on Lee major storage company. That's really growing rapidly. They got 28% growth. I did a breaking analysis on Lincoln, and I'll just share with you some of the numbers. Dallas flat at 0%. So Del is actually gaining share with no growth has got a scary NetApp minus 16% in the quarter H P E minus 3% IBM minus 21%. And so it is pure A 28%. So they're really crushing it in terms of growth. They've also got a 69% gross gross margin, even if it's in its heyday. E emcees gross margins weren't that high, you know. They were in the sort of mid sixties, and so, and they've also got a good balance sheet. About a billion dollars in cash A little. A little more than that, they got some debt. They're shifting their model to a deferred revenue model. Now the only thing is, you know they're growing much, much faster than the competition. But they're throwing off a lot less cash because they're much smaller. Just as an example, they probably throw off 5 to 6% of their revenues in cash. Netapp probably throws about 23% of its revenues, often catch the big Delta there, so the point is long winded. But but pure storage is in growth mode. And until the market rewards more consistent with a cash flow, they're gonna, I think, stay in huge growth mode. >> There was a great analysis. Dave and I saw an analysis that you did with some spends data, just a couple of your reverence. A little bit of that. There's there seems to be a tailwind behind here you mention the 28% wrote that they announced in Q two, and some of the things that also they talked about were there. Adding about in Q two of F Y 2020 about seven net new customers every business day, adding about 450 new customers just in that quarter. Like you said, 3000 folks expected here today. The momentum is behind them, but they're also a company of firsts. You talked about this a number of times. The first, with all flashed the first with envy me on the back and a couple of additional firsts announced today. Talk about the as a service model and how that youth, in your opinion, you think might continue that trajectory that they're on. >> Yes, so basically pure laid out today, said that vast majority are Pouliot Portfolio is gonna be available as a service. That's the cloud consumption mall is important because pure has about $600 million in deferred revenue, largely coming from their evergreen service. But there they are, slowly shifting their model to a subscription model. It's gonna be very interesting to see how that plays out. Um, we've seen a number of companies do a tableau in Adobe kind of pulled the band Aid off and did it Splunk has taken years to do. It will be interesting to see how how pure goes. For that. I'll >> bring it >> back to the cloud up yours largely an on Prem storage company. That's where most of the revenues come from. But we heard the gentleman from Amazon today. I think it was E ethan whiner, not Ethan, anyway, Mr Whiner, he said. That gardener did A survey last year showed 88% of customers said they have a cloud for a strategy, but 86% of those customers continue to spend on prim. So here you have the cloud. Amazon gorilla wants everybody to go to the cloud pure would much rather they make much more money on Prem? But they realize customers air pulling them in. So they have to move to that as a service model. One of the interesting things that pure is done, which, you know, that's not really a first. But it certainly is for the large storage companies they've announced. Ah, block storage on AWS. So basically what they're doing is they're taking the pure experience. It all looks like pure software, and they're front ending cheap s3 storage from Amazon with E. C. To compute instances, and they've architected using Amazon service. Is this basically a block storage array in the cloud so Amazon gets paid, pure, gets paid? It's a little bit of a premium, but you get higher availability. You get great right performance and you get the pure cloud experience pretty interesting strategy, >> and they're talking about it really as this. This positioning it rather as a bridge, a bridge to hybrid cloud. This numbers that the Amazon gentlemen, share that you mentioned Gardner were really interesting both sides recognizing there's a forcing function there and that forcing function is the customers from the enterprise to the small business who need to have data available immediately wherever it is people to extract this insights from it quickly so that those companies, whether it's a capital one or a Delta Airlines or a smaller organization, can act on it quickly to Dr Competitive Advantage. Same kind of challenge that your storage has. But really that forcing function of the customer, clearly bringing the giant AWS together with yet another story >> so pure as they say reached escape velocity. They and Nutanix were the only on a new entrance that reached a billion dollars Nutanix. I really don't consider a storage company. They're kind of hyper converged. And the way they did that as they drove a truck through E emcees install base with flash. So they were the first within all flash array. Maybe maybe they weren't the first, but they were the first to really drive it. They hired a bunch of DMC sales reps. They knew where all the skeletons were buried and they really took out a lot of old Symmetric Se's and Claire eons and V. Max is and all the old sort of GMC install base, and that helped them catapult their way there 1st 10 years. Now they got to do that again. They got to get to get They're on their way to two billion. But how did they get to five billion? Um, and and so the way they do that is they have to expand their tam. I mean, we'll talk to Charlie Jean Carlo about this. My feeling is a big job of the CEO is to expand the Tamil. How do they do that? They go after new workloads like a i. They go for cloud. They go from multi cloud. These are all very large markets in which they don't participate. Data protection. They'll partner with Lex, Kohi City and Rubric and Beam to to have data protection software running on their flash. A raise with very, very fast restores. That's something that's taking off. It's gonna be really interested in seeing as they say, they've got this subscription model that's coming in. They've got all this deferred revenue that in a way, it's going to slow him down a little bit just from an accounting standpoint, cause when you recognize deferred revenue, you recognize that, you know over 12 months over 36 months, so that's a little bit of a transition. The other thing that pure is facing in a tactical basis is Nande pricing. It's like this countervailing effects nan pricing is coming down, which means lower prices, lower costs but also lower revenue. But at the same time, it becomes more competitive with spinning disk. This is something else. We'll talk to Charlie Jean. Cholera right about it opens up new markets. So this tam expansion is critical for pure in terms of driving this modern data experience into these new workloads and fighting the competition, the competition is not sitting still. All those companies that I mentioned the H P ease, the the Delhi emcees, et cetera, are basically taking a page out of your swords narrative, talking about the cloud experience, talking about, you know, flexible pricing models, building cloud products on prime and hybrid cloud and multi cloud. So it's hard sometimes for customers to squint through that. And really, no, I guess the bottom line, the last thing I'll say is pure. Doesn't have as many feet on the street is these other guys. So it's gotta leverage the channel increasingly, and that's how it gets beyond two billion on its way to five billion. >> And that was one of the factors that they attributed the second quarter. 28% year on year growth is to not just innovation, but also to the channel. So they've done a good job of really pivoting. There's large enterprise deals to be covered, direct and then bringing in the channel for those smaller mid size business customers. Adding a lot of momentum in cute to you mentioned the nan pricing that in some of the political climate with the start of China, most of their businesses in the Americas so they're not facing as many of those challenges. So they did lower guidance for the rest of it is >> the second time they've >> lowered 20. However, they kind of attributed that thio the nan supply oversupply and they say happy Matt to flatten out quickly, say they're >> not worried about the macro. I mean, look, if if the economy is good and is booming and people are spending money on cap ex. That's good for even a high growth company. They're basically positioning to the street that if if the economy does turn down and there's a softness at the macro, they'll actually gain share more rapidly. Which, by the way, is probably true. But look at the rising tide lifts all boats. Nobody wants to see Ah recession. Having said that, well, it's interesting. When you saw Pure Lower, its guidance stock took a hit, and then net app, I'd be him. All these other company you have to see a deli emcee they announced in the market said, Wow, pure must be doing really well compared to these other guys. So it's come back in a big way. My opinion pure is going to in the e. T. Our data shows this from a spending intentions Pure is going to continue to gain share at a much, much more rapid pace of the other. The other guys, from a product standpoint, delicacies consolidating its product portfolio, trying to lower its cost. H. P E is really focused on limbo. IBM needs a mainframe product cycle to get back going, Ned APS facing its challenges and its kind of tweaking its go to market model. So all these other companies air dealing with sort of some structural changes. Where is pure is like put the put the foot on the gas and accelerate no pun intended. And so I think they're gonna continue to gain share for quite quite a number of quarters. >> I want to talk about sustainability before we break. And one of the things that Charlie talked about on his keynote is in terms of the modern data experience, he said. It was three things. It was simple, seamless and sustainable, an inch sustainable. You really started talking about the evergreen model that they launched a while ago that seems to be really sticky with organizations. He also talked about sustainability is a lot of other organization I need to adjust in terms of, you know, waste and carbon emissions and things like that. But I'm just curious, since Pierre is much smaller than the competitors that you mentioned and a lot more focus, obviously all in on flash. Where does the evergreen model, in your opinion, give them that tail winter? That advantage? >> Well, the Evergreen model was first of all brilliant marketing strategy and a business strategy Because if you think about the traditional storage vendors, they make so much money on maintenance, they would never have done this unless pure force them to do it. Because they're making so much cash on the maintenance. You know, it's it's you. You put the storage array in and we're just gonna charge you maintenance. And if you're not on the maintenance contract, sorry. You don't get all the software upgrades, everything else. So it's just this, you know, this lock in strategy, which is work brilliantly for two decades pure, comes along and says, Hey, where? Software driven. We're gonna allow you to get all the modern software. As long as you're got a subscription with us, we'll swap out your controller for free. You know, the competitors hate that. There's all kinds of nuances and stuff, but it worked, and customers love it. And so it's very strong, and it's a fundamental as they said, they got $600 million in deferred revenue, largely from that evergreen model. So they, you know, Charlie mentioned first for non disruptive upgrades. First for cloud management, first for a I ops first for always on que Os first with always on encryption, and if they're really the first, we're probably the first big company. They got a lot of attention there. Last thing, it's it's a four big announcements today. There's a I ready infrastructure, airy. They're doing some stuff they were first to announce with video. You know, a year or so ago, they got cloud offerings. Ah, block storage for AWS. And they've got clout Snap for Azure, which is actually pretty hot. It's backup on Azure, and they got product extensions. They got cheaper flash with a flash or a C for capacity. And then they have extended their all flashy raise their flash played etcetera with storage class, memory and and storage memory. And in this, this as a service model. Those are really the four big announcements that were gonna dig into all this week. >> We are, and we're gonna be talking with This is a great event. Two days. The cube is going to be here. We have seven pure customers to talk to you that I think kind of a record, at least in my cube experience of the last >> AWS always puts a lot of customers up too. You know. All >> right, well, there's no better validation than the success of a brand, whether we're talking about Evergreen or their first or the reaction of the market to bringing flash down to satya prices. So excited to dig into customer stories with you, Dave. Course we'll talk to some partners who got c'mon slung Cisco somebody else and probably forgetting. And, of course, some of the pure, exactly gonna be exciting two days with you and looking for two days >> looking forward to at least a great >> all right stick around. Dave and I will be right back with our first guest, Charlie Giancarlo, chairman and CEO of Pier Storage. Stick around, come back Mawston in just a minute.

>> from Seattle Washington. It's the Q covering AWS. Imagine nonprofit brought to you by Amazon Web >> service is >> Hey, welcome back already. Jeffrey here with the Cube were in >> the waterfront, actually in Seattle, Washington. It's an absolutely gorgeous August day. We're here for the AWS. Imagine nonprofit event. It's the fourth year they've had. It is the first year's been kind of open to the public. It was invitation only. And we're excited to be here for our first time. Our >> guest is here for his first time, too. And >> we're excited to sit down with side L. Nash. He is the vice president. And of I t and C i o for the National Council on Aging. Say great to see you. >> Thank you. Good to see you. Yeah. So, first >> off, just kind of impressions on the event So far. Really good keynotes this morning. And they got a full two days planned for you. >> Yes, it was an excellent good note. Keynote speaks to the speech this morning and, uh, started off talking about impact and how nonprofit organizations make it make a difference in the world. >> Right. So National Council of Aging, the population is aging Maur Every day they keep sending me my my card in the mail that keep pretending I'm not old enough to get. But >> don't try to pretend exactly they are >> double AARP. Thank you very much for the car, but, um, there's a lot of unique challenges with as the population continues to get holding. What are some of your organisation's priorities? How do you address this kind of growing population in our society? >> So I'll share with you some statistics on aging. So there are about 72,000,060 and older adults in the U. S. 70 >> 1,000,000 to three on its growing >> and growing. It will be 92,000,000 in 2030. So it's a growing larger segment of the population. People are living longer, saving less about but half of those so are 60 plus have saving off about $30,000 about 80% off 60 plus have about maybe to chronic disease conditions. So people are living longer, saving less money, and obviously with that, there are a lot of challenges, and this is where we step in. So we step in. Our mission is to help people age healthier and wealthier, try to make sure that they planned correctly for their savings. And they plan correctly also for their convention there chronic diseases and managing their health in general. And so for that, we have a lot off just products, actually that help older adults figuring out there how to live in older and healthy life. One of them is our flagship product, helping people get access to ah, federal, state and local government benefits. It's called benefits. Checkup is the largest system decision support system in the country that helps older adults figuring out how what benefits take all 54 and how to apply. And we walked them through that whole process. >> So it's also not necessarily the most technically astute population, either, especially today seniors who didn't grow up his digital natives like a lot of the kids are today. And >> as you said, your your guys >> objective number one is economic security. Maybe not necessarily number one, but top of the list and then healthy living. And they don't have the benefit of of time for therefore one case and stuff to grow. So these air pretty unique challenges. How are you helping him? And then you know we're here in eight of us. What role has eight of us played in helping you reach your your constituent? >> Clear? You're asking a lot of questions in one. So let me try and answer them one by one. So let's take a >> look at the aging population, especially the older adults. 70 plus those who actually don't have. Ah, I don't know. They're not necessity technology savvy, but they have Ah, they have cell phone. It's over. 73% of them have cell phones and some have smartphones. S o. We looked at the different ways of trying to reach out to them. And one of the things that we experimented with is looking at an SMS texting pilot. So we actually started that pilot and was very successful. And well, now we're rolling out into a full production system. It's a we found out that it's a great channel. It's very simple asking simple questions. Did you apply yes or no? Just answer us if you were to do one or two. So tell us give us a very simple answer and we found that the engagement rates are way above the average industry. People tend to respond to text messages for better than actually telling them. Hey, there's the mobile app. Go download my mobile already So that's one aspect of it on the AWS Sod off it. So when I joined and see away about a year and 1/2 ago, we were in Private Cloud and in that situation we had a lot of single point of failures and disaster recovery was in bad shape. And so we realized that we needed to move into a new and more robust environment, one that solved the single all the risks that we had from disaster recovery. Single point of failures to also being able to innovate quickly and fast. And so we looked that we started the ah migration process to the cloud and we ended up on AWS back in February. This year would move 95% of our assets to the cloud to AWS Cloud and we medicated the two major risks. The single point of failure is disaster recovery and so on. And with that, we also have a lot of other tools that are out of the box that we're using right now with the AWS platform. >> That's great So, um, I want it back up to the S, the best comic cause That's really interesting. So how do you find your customers? How do you get people get engaged? Obviously, art center the card in the mail. You know, there's a lot of organizations that that we get involved with. How do you directly engage with your clients? >> So we do a lot of digital marketing, believe it or not. So we spent a lot off time money and energy into digital marketing on Facebook. So a good number of older adults are on Facebook. There's also a good percentage of them that are on YouTube. Unfortunately, older adults spend about 46 hours watching either TV or videos on the Web, those who have access to the Web. So that's one way we're trying to reach them. So these are our sort of marketing funnels. In addition to that, we have about close to 100 centers around the U. S. Where older those can actually go in and be helped and go walk through the process of applying for federal state local government benefits. And so we have. They're called benefits benefits centers. And so the those centers are open to the public. We also try to collaborate with different with different organizations around the country, through through whom we get older adults too engage with us and joined the benefits checkup program. And with that, we we ask people to our 10. So we take a very cautious and very respectful approach to data and privacy to ask people to opt in. And we tell them about how we're using the data. We encrypt the data address. We take very caring very good care of it. We don't share it outside of organization. So we have our own internal data privacy principles. So we take this matter very seriously again. Our objectives always the hope older adults live a better, healthier and wealthier life, >> right? I just love that the older people are now using Facebook and SMS like kids. >> 15 years ago, they moved on >> to other platforms. Thank goodness for the old folks keeping the Facebook and, uh >> so let's shift gears. A little >> bit of talk about your transformation in your movement to the cloud. How big of an effort was that? How long did it take? And, you know, hasn't really opened up the innovation because there's clearly cost savings. And as you talked about a single point of failure and kind of mitigating the negatives, but as well as we've seen over and over again, really, the benefits from from Cloud are really that innovation and delivering service is faster. So how's your experience? >> That's exactly right. So So let me talk a little bit about the traditional transformation. So about, I would say, year over year ago, we started our digital transformation initiative. It's really focused on customers, we call it, knowing our customers as individuals with individual needs. Traditionally organizations like ours looked at older adults. In the perspective, off percentages averages, on average is is how old they are on average, in this is their income. On average, this is their health. But in reality, every older adult is an individual that has specific and individual needs, and we need to really take a look at that and caters to those very specific needs that they actually changed over time. So the transformation really enabled it. We needed to move to a cloud where we can have products immediately that we can spend off and use a I machine learning products and so on. And so I'm gonna go back and talking more about our a digital transformation and the perspectives off it. So our objective long term is to build was recalling the the aging Well, aye aye. Engine. It's basically imagine an older adult waking up in the morning and trying to decide what are the top best three things for me to do. Stop the actions for me to do to improve my life. And we wanna help that older adult make those decisions easily and quickly through a frictionless interactions. Frictionless. Conversational. Aye, aye. Speaking to an Alexa like voice enabled smart speaker asking Alexa, what should I do today? Alexis, respond. The weather is nice out there. Call your friend. Go for a walk. Call your doctor, get the lab results and so on. And check your benefits on benefits. Check up and figure out and improve your life. So the idea is to really get the person to actively and the actively using technology and simple, frictionless way to be able to make those decisions that improve their lives. So for us to do this kind of work to build the aging. Well, Aye, aye. Engine. It is impossible without being on a cloud like >> a w. Interesting. So, uh, first time I've heard about Lexus since we've been here. A lot of talk about Lex at the education conference a couple of weeks back. So is Alexa. Pretty key piece of your strategy going forward, you really see voice as a different type of communication. You mentioned. That's a message. Just kind of old, but really effective. How do you see Alexa playing >> so absolutely so voice enabled communication channels. So we look at it as actually we look at our communication with older adults. We look at it as an Army channel communication. Every person have their own preference of the way they interact with technology. Some people prefer SMS. Others like to speak to Alexa. Others like to go through the web and so on. Some are on Facebook or YouTube, etcetera. So each we have our own choices. And that's exactly why we need to look at the older adults as individuals with their individual needs. And then our job is to deliver those to deliver all products through those different channels individually. So delivering the right product with the right customer at the right time and through the right channels. So lax is one of the channels it is. It's not the only channel or the voice channel I would call it is not the only channels. What we found out is that older adults find Alexis is very engaging. It reduces social isolation. It helps with the many other tests, especially for those who are visually inferred. The the complexity. The challenge for older adults is setting it up, so that's what we're trying to look at. Ways of trying to packages will be package so that it is possible for the older adult to plug it in and be able to use it. The other thing that we discovered, we probably need to look at family caregivers as the customer segment of the customer target that we would work with really enable looks, um, >> interesting. Let's see, it seems like a natural fit once you get kind of the tone and the and the comfort worked out, and I would imagine you're writing all types of specific things for to do and types of activities for Alexa to do for the specific needs of this older generation, >> so yeah. So we started >> a very small proof of concept project with Alexa trying to engage an experiment for me, everything that we do has to bring in value. And I need to also make sure that we are when we deliver a product or customers. That product actually delivers that value and engages the customers. So we know that there are there is the value in there were also working with partners on delivering this voice channel. So I know that we have, as a non profit organization with our, you know, a limited resource is. And so we look at partners as a way to enable those votes channels on the different channels that we have >> exciting, exciting times. And I look forward to watching that innovation pulls out at a high rate of speed. So thanks for taking a few minutes and safe travels home. >> Okay. Thank you, Seed. I'm Jeff. You're watching the keyboard aws. Imagine >> in Seattle. Thanks for watching. We'll see you next time

>> live from Washington, D. C. It's the Cube covering a ws public sector summit by Amazon Web services. >> Welcome back, everyone to our nation's capital. We are the Cube. We are live at A W s Public Sector summit. I'm your host Rebecca Night, along with my co host, John Farrier. We're joined by Ken Eisner Director Worldwide Educational programs at a WS Thanks so much for coming on the show >> you for having me. >> So tell our viewers a little bit. About what? What you do as the director of educational programs. Sure, I head >> up a program called a Ws Educate a ws educate is Amazon's global initiative to provide students and teachers around the world with the resource is that they need really to propel students into this awesome field of cloud computing. We launched it back in May of 2,015 and we did it to fill this demand. If we look at it today, what kind of right in the midst of this fourth industrial revolution is changing the means of production obviously in the digital on cloud space, But it's also creating this new worker class all around. Yeah, the cloud Advanced services like machine learning I robotics, I ot and so on. And if you looked at the employer demand, um, Cloud computing has been the number one linked in skill for the past four years in a row. We look at cloud computing. We kind of divide into four families. Software development, cloud architecture, the data world, you know, like machine learning I data science, business intelligence and Alex and then the middle school opportunities like technical customer support, age and cybersecurity, which can range all the way from middle school of Ph. D. But yet the timeto hire these people has grown up dramatically. Glass door as study of companies over there platform between two thousand 92 1,050 18 and show that the timeto higher had increased by 80%. Yet just think about that we talk about I mean, this conference is all about innovation. If you don't have builders, if you don't have innovators, how the heck Kenya Kenya innovate? >> Can I gotta ask you, Andy, just to have known him for over eight years and reporting on him and covering it was on when when everyone didn't understand yet what it was. Now everyone kind of does our congratulations and success. But to see him on stage, talk passionately about education. Yeah, mean and knowing Andy means it's kind of boiled up because he's very reserved, very conservative guy, pragmatic. But for him to be overtly projecting, his opinion around education, which was really yeah, pretty critical means something's going on. This is a huge issue not just in politics, riel, state, local areas where education, where >> the root of income inequality it's it's a lot of. >> There's a lot of challenges. People just aren't ready for these new types of jobs that are coming out that >> pay well, by the way. And this is Elliott >> of him out there that are unfilled for the first time, there are more jobs unfilled than there are candidates for them. You're solving this problem. Tell us what's going on in Amazon. Why the fewer what's going on with all this? Why everyone's so jacked up >> a great point. I, Andy, I think, said that education is at a crisis point today and really talked about that racial inequality piece way. Timeto hire people in the software development space Cloud architecture um technical called cloud Support Age. It's incredibly long so that it's just creating excess costs into the system, but were so passionate, like if you look at going to the cloud, Amazon wants to disrupt areas where we do not see that progress happening. Education is an area that's in vast need for disruption. There are people were doing amazing stuff. We've heard from Cal Poly. We've heard from Yeah, Arizona State. Carnegie Mellon. There's Joseph Alan at North Northeastern. >> People are >> doing great stuff. We're looking at you some places that are doing dual enrollment programs between high school and community in college and higher ed. But we're not moving fast enough, but you guys >> are provided with educate your program. This is people can walk in the front door without any kind of going through gatekeepers or any kind of getting college. This is straight up from the front, or they could be dropouts that could be post college re Skilling. Whatever it is, they could walk in the front door and get skilled up through educators that correct, >> we send people the ws educate dot com. All you need is some element of being in school activity, or you won't be going back from Re Skilling perspective and you came free access into resource is whether your student teacher get free access into content. That's map two jobs, because again, would you people warm from the education way? All want enlightenment contributors to sai all important, But >> really they >> want careers and all the stats gallop ransom good stats about both what, yet students and what industry wants. They want them to be aligned to jobs. And we're seeing that there's a man >> my master was specifically If I'm unemployed and I want to work, what can I do? I walk into you, You can go >> right on and we can you sign up, we'll give you access to these online cloud. Career pathways will give you micro credentials so we can bad you credential you against you We belong something on Samarian Robo maker. So individual services and full pathways. >> So this a >> direct door for someone unemployed We're going to get some work and a high paying job, >> right? Right. Absolutely. >> We and we also >> give you free access into a ws because we know that hands on practice doing real world applications is just vital. So we >> will do that end. By the way, at the end of >> this, we have a job board Amazon customer In part of our job, we're all saying >> these air >> jobs are super high in demand. You can apply to get a job as an intern or as a full time. Are you through our job? >> This is what people don't know about Rebecca. The war is not out there, and this is the people. Some of the problems. This is a solution >> exactly, but I actually want to get drilled down a little bit. This initiative is not just for grown ups. It's it's for Kimmie. This is for you. Kid starts in kindergarten, So I'm really interested to hear what you're doing and how you're thinking about really starting with the little kids and particularly underrepresented minorities and women who are not. There were also under representative in the in the cloud industry how you're thinking expansively about getting more of those people into these jacks. And actually, it's still >> Day one within all y'all way started with Way started with 18 and older because we saw that as the Keith the key lever into that audience and start with computer science but we've expanded greatly. Our wee last year reinvent, We introduced pathways for students 14 over and cloud literacy materials such as a cloud inventor, Cloud Explorer and Cloud Builder. Back to really get at those young audiences. We've introduced dual enrollment stuff that happens between high school community college or high school in higher ed, and we're working on partnerships with scratch First Robotics Project lead the way that introduced, whether it's blocked based coding, robotics were finding robotics is such a huge door opener again, not just for technically and >> get into it absolutely, because it's hands on >> stuff is relevant. They weren't relevant stuff that they can touch that. They can feel that they can open their browser, make something happen, build a mobile application. But they also want tohave pathways into the future. They want to see something that they can. Eventually you'll wind up in and a ws the cloud just makes it real, because you, Khun do real worlds stuff from a browser by working with the first robot. Biotics are using scratch toe develop Ai ai extensions in recognition and Lex and Polly and so on. So we've entered into partnerships with him right toe. Open up those doors and create that long term engagement and pipe on into the high demand jobs of tomorrow. >> What do you do in terms of the colleges that you mentioned and you mention Northeastern and Cal Poly Arizona State? What? What are you seeing? Is the most exciting innovations there. >> Yes. So, first of all, we happen to be it. We're in over 24 100 institutions around the world. We actually, by the way, began in the U. S. And was 65% us. Now it's actually 35% US 65% outside. We're in 200 countries and territories around the world. But institutions such as the doing amazing stuff Polo chow at a Georgia Tech. Things that he's doing with visual ization on top of a ws is absolutely amazing. We launched a cloud Ambassador program to reward and recognize the top faculty from around the world. They're truly doing amazing stuff, but even more, we're seeing the output from students. There was a student, Alfredo Cologne. He was lived in Puerto Rico, devastated by Hurricane Maria. So lost his, you know, economic mobility came to Florida and started taking classes at local schools. He found a ws educate and just dove headlong into it. Did eight Pathways and then applied for a job in Dev Ops at Universal Studios and received a job. He is one of my favorite evangelists, but and it's not just that higher ed. We found community college students. We launched a duel enrolment with between Santa Monica College and Roosevelt High School in Los Angeles, focusing again a majority minority students, largely Hispanic, in that community. Um, and Michael Brown, you finish the cloud computing certificate, applied for an internship, a mission clouds so again a partner of ours and became a God. Hey, guys, internship And they start a whole program around. So not only were seeing your excitement out of the institutions, which we are, but we're also seeing Simon. Our students and businesses all want to get involved in this hiring brigade. >> Can I gotta ask. We're learning so much about Amazon would cover him for a long time. You know all the key buzzwords. Yeah, raise the bar all these terms working backwards. So >> tell us about what's your >> working backwards plan? Because you have a great mission and we applaud. I think it's a super critical. I think it's so under promoted. I think we'll do our best to kind of promote. It's really valuable to society and getting people their jobs. Yeah, but it's a great opportunity, you know, itself. But what's your goal? What's your What's your objective? How you gonna get there, What your priorities, What do you what do you what do you need >> to wear? A pure educational workforce? And today our job is to work backwards from employers and this cloud opportunity, >> the thing that we >> care about our customers still remains or student on DH. So we want to give excessive mobility to students into these fields in cloud computing, not just today and tomorrow. That requires a lot that requires machine lurking in the algorithm that you that changed the learning objectives you based on career, so content maps to thes careers, and we're gonna be working with educational institutions on that recruited does. Recruiting doesn't do an effective job at matching students into jobs. >> Are we >> looking at all of just the elite institutions as signals for that? That's a big >> students are your customer and customer, but older in support systems that that support you, right? Like Cal Poly and others to me. >> Luli. We've also got governments. So we were down in Louisiana just some last month, and Governor Bel Edwards said, We're going to state why with a WS educates cloud degree program across all of their community college system across the University of Louisiana State system and into K 12 because we believe in those long term pathways. Never before have governors have ministers of country were being with the Ministry of Education for Singapore in Indonesia, and we're working deep into India. Never had they been more aligned toe workforce development. It creates huge unrest. We've seen this in Spain and Greece we see in the U. S. But it's also this economic imperative, and Andy is right. Education is at a crisis. Education is not solving the needs of all their constituents, but also industries to blame. We haven't been deeply partnered with education. That partnership is such a huge part of >> this structural things of involved in the educational system. It's Lanier's Internets nonlinear got progressions air differently. This is an opportunity because I think if the it's just like competition, Hey, if the U. S Department of Education not get their act together. People aren't going to go to school. I mean, Peter Thiel, another political spectrums, was paying people not to go to college when I was a little different radical view Andy over here saying, Look at it. That's why you >> see the >> data points starting to boil up. I see some of my younger son's friends all saying questioning right what they could get on YouTube. What's accessible now, Thinking Lor, You can learn about anything digitally now. This is totally People are starting to realize that I might not need to be in college or I might not need to be learning this. I can go direct >> and we pay lip >> service to lifelong education if you end. If you terminally end education at X year, well, you know what's what's hap happening with the rest of your life? We need to be lifelong learners. And, yes, we need to have off ramps and the on ramps throughout our education. Thie. Other thing is, it's not just skill, it's the skills are important, and we need to have people were certified in various a ws skills and come but we also need to focus on those competencies. Education does a good job around critical decision making skills and stuff like, um, collaboration. But >> do they really >> do a good job at inventing? Simplified? >> Do they teach kids >> to fam? Are we walking kids to >> social emotional, you know? >> Absolutely. Are we teaching? Were kids have tio think big to move >> fast and have that bias for action? >> I think that I want to have fun doing it way. Alright, well, so fun having you on the show. A great conversation. >> Thank you. I appreciate it. >> I'm Rebecca Knight for John. For your you are watching the cube. Stay tuned.

>> Hello, Room. Welcome back to London. You watching the Cube? The leader and tech coverage. My name is Dave Volante. We're here in a special program that we've constructed. It's the day before the eight of US London summit and we wanted to come and talk to some customers, some executives of startups, and really dig into what's going on in the public sector. Chris Heman is here. He's the director of UK and Ireland Public sector for eight of us. Chris, Thanks for coming on the Cube. >> Thanks for vitamins. Christ. >> Yeah. So you guys have a special public sector healthcare pre day that's going on downstairs? What's that all about? >> Yes. So obviously we'LL remain summit tomorrow expecting about twelve thousand people, which is phenomenal today that we could do something with one of our special industries, which is health care. So we've invited a number of customers and executives along for that today to learn more about cloud, how they can get going with the cloud and get, you know, start adopting a pace. So I believe you spoke with the missus about earlier on. So he misses a supplies the n hs, but also people and hs digital and so on her adopting the platform. So that's what today's all about. >> So health care is one of those sectors. It's ripe for disruption. It really hasn't been, you know, disrupted in a big way and digitized and it's starting. But the challenge is, how do you balance the cost of health care? Everybody's sensitized to that with the quality. Yeah, here. And so that's what really the problem. Show yourself. How does he ws in the cloud? Help solve that. >> Yeah, I think across the public sex. Really not just for the healthcare, but, you know, one of the things organizations are trying to do is reduce that large legacy footprint of infrastructure and really deliver against their mission, whether it be patients or citizens or whatever it may be. Ah, good example. In the in the case of the health care is we're working with a partner and I just school Business Services Authority on they have a large call center that was a really, you know, costly experience having traditional call center set up. So they've used our connect platform, our call center platform, and also some voice technologic called Lex. And they're able to reduce they stood up in about three weeks is a phenomenal effort, and they reduce their call volume by forty two percent. So basically getting the computer's towards some of the really easy queries, which, of course, meant that some of the tougher call center queries went to the actual humans and the call center handlers. So you know those sort things, I really think impact the bottom line for the HS and save some cost, but really helping to innovate a swell for for their patients and sis isn't so. >> Let's stay in health care for a second. So any just has, ah, nearly half a billion pound initiative to modernize. So if had they asked me, they didn't ask me. But had they ask me, I say, Well, part of that should be to get rid of the heavy lifting, so moved to the cloud and then really try toe transform your labor force to focus on more value added areas. It's actually helps to solve your problems. Is that essentially, what's happening? >> Understand, so that the contacts into very you know, that the people are now answering fines aren't doing those sort of Monday enquiries were it's just going to take four to six weeks. It's Maur, you know, transferring that. You know that's the computer and letting the humans do the heavy lifting. So I think that's you know, certainly one thing. But I think it's also enabling these organizations to really be closer to their citizens into their patients as well. With free liquor organizations like in the local authority, space, like else prevail. There are also using voice technology with Alexa to enable citizens to answer queries like You know who is my counselor or to update about various things within their sort of council record. And socially public sector organizations love that because they've now got this unique touch point with the sisters and at scale, whereas they would never have been able to do that previously. So that's a really good, you know, close engagement for them. >> So you hear the bromide people say data is the new oil. It's it's the it's the new natural resource. We actually think date is more valuable than oil because you can only use oil in one place. The data you can use many, many places, so data becomes increasingly important. But the problem that most traditional companies have is there, Their data is locked in silos. It's hardened into an application. And so so how are you guys attacking that problem? What do you see? A CZ trends in the customer base in terms of being able tto have sort of, ah, unified data model. And what role does the cloud >> play there? Yeah, I think it's really good questions. So there's a number of things that we're doing. First of all, we're very passionate about public date sets. So we host a number of public day sets like Lanza imagery and these sort of things, you know, fundamentally, we believe data has gravity, so, you know, for overto host and provide this data at scale for researchers and so on. That has tremendous huge benefit. But you're right about public sector organizations, and I silos a good example. Where we've we've worked is with transport for London. Obviously, if you want to get in and around the city of London, typically you go to tear filled look after UK, which runs on a dress, and you'LL say, I want to get from you know, Frank and to Liverpool Street, and that's all kind of running on top of a dress. But the really cool thing is they've opened up all that information so they don't have to develop. Those ups themselves are effectively crowd sourcing the development of those APS. So they've got some four thousand developers now working against all this data. Ah, Delight recently did a study. They reckon it's goingto generate economic benefits of one hundred thirty million pounds per annum just by making this really time data available. So So you're gaining unique business in size. But not only that, you've got organizations like city mapper who can commercialize that data develop, perhaps, and sell those apse on behalf of you know, you took to the community and so on. So you've got double bubble of s on the engagement, but also the public benefit as well. So that's really cool >> now, years ago Ah, in a past life, I had an opportunity when I worked for I d see the research company to run the government business. And when I went around and talked to the heads of military heads, the heads of agencies, there was a common theme. They were trying to close the gap between public sector and commercial. Yeah, and they never quite could get there. The cloud seems to me, Chris, to be changing that. I mean, to me, the CIA deal in twenty thirteen was a seminal moment for just the cloud and need of us specifically. But increasingly, you're seeing innovation. Yeah, it's still very difficult because you get turnover and agencies and administrations and so forth. But what are you seeing in terms of of those trends? Are you seeing public sector organizations leaning in modernizing? And again, what role does the cloud play there? >> Yeah, one hundred cent. I think you're absolutely rise. It is a unifier. In that sense we worked with, you know, we're moving mission systems to the cloud now with our customers. Ah, we worked with Dr Vehicle Stands Agency. So they're responsible for making sure our car's unroadworthy in the UK. They migrated their entire platform, which supports on thirty thousand small businesses. Try the rest in ten weeks. So it's amazing what public sector organizations are able to achieve with the pace of cloud. And a lot of it starts with experimentation. You know, that's the great thing is that you can try something. If it doesn't work, you can turn it off and you haven't lost anything but that that pace of being out to move, even mission systems. So the cloud is happening in public sexual across the board, >> and I mentioned the CIA before they start to be the American sort of parachuting in, and it's obviously a bias that I have. I'm working on my accent. But But But But the CIA was significant because everybody in the early days were so concerned about security that the head of tea in the CIA stood up last year at the D. C. Public sector Summit and said, My worst day of security in the cloud is better, far better than my client server ever. Wass. Yeah. So what about security concerns? Have they abated? They they still there? How is that evolving? >> Well, I think first of always, absolutely right that public sector organizations one hundred percent laser focused on security. But the good news is that we are to you know, its job. Zero for us is absolutely everything that we don't live and breathe by. And I think we've demonstrated that in a number of ways. I mean first of all, just the way in which we operate our physical infrastructure and everything that we do it physical pace, but then above the layer with the kind of the things that are a customer's responsible for. We have something called a shared responsibility model, so the responsibility for kind of everything above the physical infrastructure, but we provide the tools that they just never would've been able to get access to in a in a physical world, you know what our CEO's in public sector organizations do You know every servant you have, you know, just things like that. And they would just be like Now I've got no idea, but with a cloud, you have that visibility. You can see every single thing that's happening in the environment. So you get farm or visibility in control that he ever was ever were able to in a physical world. So I think that's first thing and obviously everything that we do around certification atter stations around. I so certification all the reporting and so on that we do Teo to assure our customers that we do a good job of that level as well. Ministry of Justice actually came out and said you could be more secure in the cloud than on premises and you have to focus on those areas where you're not in the cloud. So I think that was a huge testament by the UK. Come and say, Actually, this is this is secure, and this is fit for purpose, which is which is good. >> One of the things I've observed boat just technology adoption in general. You know, Silicon Valley's unique, obviously, And but, you know, outside of Silicon Valley, maybe technology adoption, you know, twenty years ago occurred more slowly. It seems like cloud adoption is very much consistent across the globe. I wonder if you could talk about that, But then specifically, public sector jobs in the cloud Do you see this Very similar sort of cadence from, you know, us rest of >> world? Yeah, I do. And I think you know, we were doing a fantastic job in the UK, Actually. Really fantastic job. Talked about some of stuff we're doing round. I I am machine learning. You know, some of these things are really leading edge on DH. If you speak to a miss earlier, they're investigating things like Blockchain for their tops of solution. So these sort of things are really pushing the boundary. But Paramount, All of that is this idea that you can experiment to try things. There's no longer there's a kind of is no longer a disparity around. Think something's fundamentally when you when you log into the console, you got access to one hundred sixty five different things and you can get going with you in the UK whether you're in the candor or in North America. So our customers are picking these things up on DH, accelerating a pace, which is which is fantastic trying all different types of things and work lights. >> Okay, if I were to ask Alexa what's gonna happen with Brexit, what would what would you tell me? I think first of >> almost, you know, with the way we think about it is it's just business as usual for us. You know, it's a fairly mundane answer, but fundamentally, you know, organization still need to adapt. This stone is transformed. They still need to evolve, and that's where we're helping and we're leaning in, you know, we're helping them with some of their EU accept programs around tooling and process and things like that. But I still came to adopt cloud a place which is which is also >> so come back to the session that you guys are running downstairs. I saw some of descriptions of it and I think there were three areas of focus. The public payers, the health care providers in the publicly funded research organizations is kind of what you guys are focused on today. So maybe close there and give us a vision for where you see eight of us public sector in the UK and >> I I think this were obviously healthcare's really fast growing vertical for us, which is fantastic upper across the board. Demand has never been greater, which is phenomenal on DH were really pushing the boundaries of what can be achieved. Yeah, we're working with, you know, I talked about some the public sector organizations with working with, you know, partners like he miss, but also small businesses as well as great example. Working with a company called Ad Zuna, which provides job search functionality. They run on a dress and they want a contract for Jobcentre Plus, which part of our department work and pensions. So it's not just the direct engagement we have with our customers. But it's also a ll the partners that we're working with to enable that in tow and functionality, which is which is really good. So we're doing a lot, lots of work in that space. And I could liken see Maura Mohr organizations not just customers in customers, but also partners technology providers coming to talk to us. Ah, and then across the spectrum, in health care, whether it's supplies to the chess or at the NSS himself, an individual trusts and and hospitals and so on, the kind of using our technology. So it's a real broad mixing spectrum of adoption. >> Outstanding, Chris, thanks so much for coming on. The Cube really appreciate it. And they were seeing the growth of a device is a DBS is actually astounding thirty billion dollars run rate company growing at forty plus percent a year. But more importantly, you're starting to see not only region expansion, but you're seeing expansion into specific verticals and ecosystems forming startups. And you guys are doing a great job of attracting these. Thanks very much for coming. Thanks. Thanks. Alright, Keep it right there. Buddy. This is David, Dante and the Cuba right back. Right after this short break. Wait

>> live from Mountain View, California. It's the queue covering definite create twenty nineteen. Brought to You by Cisco >> Welcome back to the cave. Lisa Martin with John Fourier. Live at Cisco Definite Create twenty nineteen at the Computer History Museum in Mountain View, California John Mayer, please to welcome to the Cube Jeff Levin, sailor collaboration Engineer from Presidio Jeff, It's great to have you joining us today. >> Yes, great to be here. >> So lots of energy. You can hear all this noise behind us. We heard this morning in the key note that the definite community is now well over half a million strong. You mentioned before we went line. This is your second definite creates before we get into our city and Cisco. Tell me a little bit about your involvement in the definite community. >> Uh, so I got >> started just looking for support, and it's not like it's a supported product. This is a new venture for everybody. So you go out and you find these little avenues to get questions answered. And WebEx teams has a great community support and just ask a question ended up answering more questions than I was asking, and, you know, that kind of like got me started down this path of, you know, people bounce ideas off each other So really, this is Ah, homecoming. And it's just people inspiring each other If you really want to learn And deep dive Obviously I'm a self learner, so I'll just sit down and really get into it. But I come here to get inspired and the Kino just >> Will you wait? Yeah. What was the key? What was the highlight for you on the Kino? What was >> anything Ashutosh has to talk about? Ashutosh is on the I guess, the incubator side. He comes up with these things, and his job is to get people excited about the FBI's. So today he had an augmented reality app with his phone and he would go around and show network coverage of a WiFi hot spot. You can go up to an access point and troubleshoot network of problems by seeing if on access, points registered or not. So my mind, I'm thinking how many times I go in the data center and look, I have to plug in a laptop to look to see what the lands on a port. Now, Aiken take that same approach too, you know, put my phone out in a data center, and okay, this witch has ah, this V lands here. I could plug it. Antonito even need to plug my laptop. >> I mean, he first introduced the beginning of that demo at Cisco Live in Barcelona. Totally blown away. He's a demo. God first. Yeah, he's amazing. But it shows the automation right and also shows the new kind of experiences. I think to me what is inspiring to me about this community. I'd love to get your reaction. This is that It kind of shows a new way to do work. And it's all about making life easier, But it's also more capability. You can see all the configurations and then ultimately writing new apse. That seems to be the theme. Create definite curiosity with all these capabilities. Is that kind of something that you're seeing as well? What's your reaction to that? That kind of this new way of doing things. >> Wow. I mean, it's we have a code competition are Presidio called Shark Tank, and it's really just to inspire people. Uh, tell me a business use case for this Use cases really ninety percent of it. You confined help you confined mentors your work. But, uh, really Just finding a use case and stuff like this coming here just thinking about new ways to do things and do things to create >> in collaboration What? Some of the things that you see that are low hanging fruit use cases of either mundane tasks or stuff that just needs to be kind of like, abstracted away. What are some of the things >> I have a ton of those s o. Somebody came to me, a law firm that had these attorney's secretary assignments, and they wanted Secretary is to be able to schedule meetings for attorneys. You could do that in a gooey, but we're seeing more and more is away from the buoy. And it's becoming this FBI first. So anything that's not in the gooey, it's in the AP, I So that's where our values integrators has really become. This gap between the jury and the FBI. So what we did, or what I did is going active directory, have some fields filled out because they're already populated. One thing for this I read from that, and then I goto WebEx a p I and I populated, and that runs a nightly basis. >> You automate thataway. Yeah, piece of cake. But this is the trend. This is kind of what we're seeing happening with Cloud the question that comes up in the enterprises. Look, att. Hey, you know, we've been doing this thing for long times the way we do it. We, You know, ten years ago we built out this system. Don't touch it. But I love the new stuff. How do I get the new stuff in? How do I deal the old stuff, The legacy. And we got containers. Got some news stuff. A p. I's a big part of this integration fabric composing APS. I think you have to show >> that the business value it's it's saving time. It's saving people ours, and it's really checking code into get is something you wouldn't think about. Checking network config. Thing to get is something you wouldn't really think about, Uh, just a year ago. But that's really becoming the trend and having a testable code and, uh, you know, kind of Ah, if something goes wrong, I have a backup. You have somebody you know exactly who did what before it was just people hacking away. >> So let's talk about unlocking value for a second. When you were talking with John about what some of the things that blew your mind during this morning's keynote one I was hearing from you and one senses how how much easier certain functions of yourjob are going to be because of this? What value are you seeing that even just a few things that we were announced this morning is going to bring, too? Not just you and your business, but for city and Cisco's customers? >> Well, I mean So, for instance, the Iraqi thing, uh, they released bulk actions. So AP eyes. Typically, if you write the code one of the time, that's goingto limit your ability to do certain functions. Having all these AP eyes in one and point immediately, I'm thinking cloud formation templates. Name is on but ism Iraqi solution, so you could take this entire network and copy and paste. It is one slice of code. That's tremendous. >> What's the community vibe here? Definite. I mean big invention. >> It's a homecoming. I know all these people have met so many people from other areas and people competitors. We're all friends here, you know, And it's not a marketing ventured all you don't see a lot of people you know, scanning badges and bugging you on email later. This is all about just people hurting out about What they've done >> is we're getting >> the show until >> I like >> that. It's not just the hacker fond, you know, Hey, revenue event. They throw a hackathon over it and it turns out the most these events trees, a marketing event. It's completely eyes that >> unorganized as I would want it to be. There's conversations just passing by in the hallway, and I get just as much out of that as I do in a workshop. >> So you're giving a breakout session later today. Contact center. A eye for more efficient governments. >> Yes, that's a twenty minute lightning talk on just a recent project I did and taking an arm from a solution and be able to do Mohr by moving it up to the cloud. This's Amazon connect could be another one, but just basically enabling through the cloud different functionalities we're using Alexe pot, reason, elastic search, reason Landa and we're we're taking the top ten tickets this help desk would receive and trying to automate this. So I need to reset my pen. I need to transfer me to this person that was an operator before in an Excel spreadsheet. So what we did was completely not change your workflow. They're going to upload it, excels for a cheat and has three. It's going to take a Landau function to separate that spread she into a dynamo database Elastic search, going to read that database. And then Lex Boss is goingto interact with elastic search >> and his all in real time. >> It's all in real time. >> And they thought, this all natural language talking together you're working together, >> working together >> to solve those customer problems or get well that And I guess, get the customer that the ticket routed appropriately. >> Yeah, so there's take a look ups to get creation to get clothes and anything that you would typically anything that you can automate. We've done it within the ivy are and we've measured containment rates. So >> yeah, this is exactly why we've been covering. This is our third year, but here in the beginning, at the creation of the event, because what you just described is so valuable and so kind of basic. If you think about it, the number one tickets that everyone that stack ranked haven't over and over again. But breaking towns this going database for this? I got a database for this. I got a database for this. The old world. You have a waterfall process, you have a product. Project manager. People would go in a round trip meeting after meeting, arguing aboutthe ski mus and databases. And I mean, what would it be like in the old days, if you like, went through the traditional models versus his agile? Hey, let's just put it together. Hackett string up. So maybe eyes sling the FBI's rolling up, wiring up >> siding. Me, you're moving from a static ivy are too self service. And then even more what I think you forget who coined the term. But selfie service. You know more about a user you're able to predictably say, I see you have a ticket open or go a step further and say, I see have email on this phone and we're having active sync issues and only alert those people of issues and not bother everybody else. I see you work out of this office and you're calling in. Are you calling about, uh, you know, your office closure? Because we have a temporary office for you over here, So being able to get ahead of anything and predict that's the next thing >> I know. This really also highlights when we tend to talk about us when these data conferences, where the underlying value being here is the creation and stitching together with solutions. But it's the data that's driving it right. The tickets that ranking the the task getting if these reasoning aspect of reasoning with the data predictive are prescriptive, is a personalization benefit thes air. The things that are exposed on this new way of creating >> there's there's some real exciting, very consumable AP eyes out there. One of them all name is in dico io, and this is something that you could just plug in some data. Then I'll make a prediction using just a bunch of learned data set that it already has, and I'LL give you an example WebEx team space way just chat away, and for months and months, I funnel that data to a simple FBI and it comes back and tells me Who's the angriest person who's the happiest person? There's an f b I for Who's a conservative who's a liberal. There's an A p I. For the Myers Briggs test. >> I'LL get all of this. You are the girl. What's the emiko dot io? Indeed, In dico dico i n d >> i c e o dot io >> Awesome. Well, thanks for sharing that on the AP. I think I want to get your expert opinion on this because this comes up a lot recently. At these conferences, we go to where some oh new way to develop modern applications. Blah, blah, blah, waterfalls going away. Fiber Clavell. That's good stuff. Check, check, Check. At the end of the day that the key ingredient all this is AP AP Eyes are becoming the centre point for one data sharing integration coding Middle, where a new kind of middleware evolving? What's your view on this? Because this is an essential part of integration to like If someone wants to adopt a new product, I want to bring it in. It's really >> recognizing that your use case isn't everybody's used case, so you come from a static, fully functioning product to an FBI first approach, you build the FBI, then you build things around it. So when WebEx teams is released, for instance, it had certain functionality there and certain functionality wasn't there. But you could do it to the FBI. So it's partners and Cisco kind of competing at the same time to come up with a better solution. Any time you compete, you know it's good in any time something is open. It's good. So you have these Open A P I's and you have a community trying to come up with the best solution on DH. It's >> and that's really where communities of shining too right now, because you're going to community. They're great at giving feedback. If something something's not right, raise their hand. Appoint honest >> feedback, right? >> Yeah, competition. So Cisco telling Cisco something's not working. You know, you bring in some other people that maybe they're mohr AP to tell you when something's not working. They don't have any dog in the fight. You know, they'LL tell you if something's not working, they'LL give you feedback, and it really enables a better in product and a product that's more form to tailor fit for that user. That use case, >> which is exactly how it should be. Right? So last question, Jeff, before we wrap up, you already talked about how excited you were with some of the things in the Kino was day one of to >> me >> kind of expectations or hopes and dreams for what you're going to learn the rest of today and tomorrow that will help evolve the Presidio Cisco partnership. >> I mean, one thing is just making connections out here, Uh, but learning? I think so. I'm a collab guy and I'm getting to be more of a developer, and that's making me more of a generalist again. Because as a developer, yu have to interact with more than just collab FBI's. I'm getting into wireless and enterprise and everything security. So what I get out of combat is like, this is going around seeing what's happening and other technologies and other verticals and once again, competitive ideas seeing what other people are doing. Adding to that telling them what I'm doing A >> lot of collaboration pun intended. >> Yeah, You like it If you like puns. The keynote tomorrow is gonna be amazing. >> Is it way watching? Excellent. Jeff, Thanks so much for joining. Joining me on the Cube today. We appreciate your time for Joe inferior. I'm Lisa Martin. You're watching the Cube live from Cisco Dove Net. Create twenty nineteen. Thanks for watching.

>> fly from San Francisco. It's the Cube covering Google Cloud. Next nineteen, right Tio by Google Cloud and its ecosystem partners. >> Welcome back to the cues live coverage Here in San Francisco, this is day two of Google Cloud. Next twenty nineteen cubes. Exclusive coverage. We're in the middle of the show floor. All the action Aquino's are still going on a little bit over. I'm John for David Law student and kicking off, breaking down the keynote analysis. Also breaking down Post Day one. All the action in the evening, where all the parties are all the action on alway conversations. Dave's to picking off day to day one was setting the table. New CEO on stage Date date. You gets into the into the products really about data data. I machine learning's all aboutthe data cloud data, and we're seeing a machine learning data management. Smart analytics say Aye and machine learning and collaborations. The four themes of Today Google. Clearly using data has a key value proposition. Big table, Big Queary machine learning the G A support for auto ml for tables, big announcements, your thoughts >> Yes. Oh, John, I think answering some of the things that we brought up yesterday is when When Google puts out their vision of why they should be your partner of choice, like customers choose way thought that data and I and M l would be let read upfront. So they kind of buried the lead a little bit. And, you know, question we had coming this week is and they reclaim that really thought leadership that, you know, a couple years ago, You know, data. You know, they really that G technical science stuff is what Google was really good at. So I thought they laid out some really good things. I think everybody was, you know, impressed. To see there was good diversity of customers as well as all the Google me. There were a lot of the women of Google that you've written about John here showing their sewing their chops here. So a lot of pieces to go through and everything from the G sweetened the chromebooks and sick security and privacy is something I like to talk a little bit about when we get into it here. But quite quite a lot of use that day. Today I at the center of it >> and one of the power Women dipped to use the big table you see and think we're all that stuff, Dave with >> big steam Us on the Kino also was B I with a II B. I think we've covered that do space going back to our ten years of doing the tube. It's the promise of Do Remember those days. Do came from Google about Eric. The emergent Borden works and do this kind of small little sliver of the ecosystem into Google's now showing what was once the promise. Big data. They're giving demos democratizing. Bring in for the masses. Wait stories on silicon engels dot com outlining this, But the reality is there. Now remember hitting the road with promise of big data? Now, with Cloud really changed the game? Your bosses, you've been covering this from Day one? >> Well, I think that there's no question that this is a date, a game, WeII said early on John on the Cube. That big data war was going to be one in the cloud. Data was going to reside in the cloud. And having now machine intelligence applied >> to that data is what's giving companies competitive >> advantage at scale and economics I was struck by the stats that Google gave >> at the beginning of the Kino today. Google in the last three years has spent forty seven billion dollars >> capital expenditures. This year to date alone, they've spent thirteen billion dollars in Cap Xidan Data Centers. Thirteen billion. It would take IBM three and a half years to spend that much in cap back there would take Oracle six years. So from an economic standpoint, in the scale standpoint, Google, Microsoft, Amazon are gonna win that game. There's no question in my mind. So, John, you know it is a game of scale and data and I What do you think? First >> of all, Google, they got the Cuban aunties two of the white paper. They wrote that they did commercialized communities in a way that I thought was really excellent, well executed. I like a Jew where they left out on the side of the road. You got picked up by a Cloudera Michaels and memorable Jeff. I'm a Wagner. We saw what happened do communities. It is true that up. They basically put it out there in the open source system, the way they get behind Ciencia really positive there. On the data front, Google's got so much in the tool shed all across Google from day one. Their legacy is data data driven, large scale. They built software and systems to manage data at scale at a hole on president. Well, I think that they have their well ahead of the marketplace on the technology that our inside Google proper Google Cloud will be proper alphabet, whatever you wanna call it. Self driving cars question for Google is, Can they bring it to get there? They >> need to hire a team of people, just >> go out and just get it all >> together, pull the jewels together and put it into a coherent platform. That's kind of the tea leaves that I see that we're reading here. Is that Curry and pointed down the keynote. We got tons of technology. The question is, can they pull it together in a package and make a consumable addressable programmable programing, FBI's? We've seen that movie that's happening right now. The next level of innovation for Google is, can they make data programmable? This is going to be a ten year opportunity. If they get that right, they will win. Big move the ball down the field to see Amazon going big on stage maker. It's all about data data, analytics at scale, auto machine learning. These are the tell signs do data program ability. They got all the things. Can >> they bring it to bear? >> Yeah, Well, John, one of the things I saw it got a lot of people excited is if I have, You know, I'm a G sweet. Customers were geese sweet customers, and I'm using spreadsheets. Now I can use Big Query with that. So the power of analytics and big data be able to plug that right in, make it really easy. And what's interesting is trying to squint through. You know what was kind of the Google consumer side of the house that many of us know. And if used for for lots of years versus the Enterprise G sweet chromebooks and mobile? Well, you know, under Diane Green, it was Google Enterprise, and now it's all part of Google Cloud. Just when we talk about Microsoft, it's like, Well, is it azure or is it au three sixty five? Well, it was a G sweet words. Is it Google and one that I want to, you know, get get your guys comment on is they talk about privacy way. No, Google as a whole alphabet is You know what, ninety five percent plus ad revenue and they were very strong out here is that we do not own your data. We will not sell it to a third party. Privacy, privacy, privacy. And it's great to hear them say that. But way all interacted work with Google. We know all the cloud providers. The data is an important thing. When I do Aye aye and ml type activities. I need to be able to anonymous isat and leverage it train on it. So data privacy issue is still something that, you know, I heard what they said, but you know, there's got to be some concerns. >> There is another angle here that I'd like to talk about, and that's the database. Google, Amazon, Microsoft, Oracle, IBM, Mike Attention, Alibaba. All the big cloud guys. They want your data. That's why Amazon spending so much effort on the database market. That's why you don't see Oracle having such a dominant position in database. You like Google's announcement yesterday they were basically doing a backhanded slap but Amazon, saying, We're more open. They didn't deal with Mongo. There's a lot of discussion in the community of software community about how how Amazon, obviously Bogart's open source. But But if you if you look, it's something that's true if you look at Amazon, they basically taken a lot of open source products. It built their own databases. But if you look at Google, Google's got relational databases. They got non relational databases. They got operational databases. So I wonder out loud, Is this a Trojan horse strategy? Because they need to own your data that databases so important now that I think that is I talked to one noise that yesterday was a executive VP at Oracle, and he said to me that the cloud providers basically looked at the data base as another application to run on top of servers in virtual machines, >> he said, Were Oracle we integrate, you know, they do all the exit data stuff, etcetera. So my point is, database is the war to be won. That's where it starts. And if you're going to go away, I you want to have the data proximate to the application. Well, >> I mean there's two ways to look at that day. I would say that what might take on >> the database war or a position in the stack is you look out from the old way the new way the old way would be an oracle. Well, we got to preserve the database. We license that we have the license agreements. The new way is to change the game with automation. Like what? Google showing where all this stuff is gonna be done on behalf of the customer. So the business model of how database and the impact of data is being used well dictated my opinion, the monetization. And that's the question that everyone that I've talked to on the show floor offline on email, on direct messages, how we're gonna make money with containers, how we're gonna make money with Cooper Netease. How am I going to make money with data? This is the fundamental question. Now, if you look at the success pattern of the partner ecosystem, moneymaking is about new economics, new price points and new services. So if you're Deloitte or you're a censure, you're saying wow of goo could automate all the stuff that used to be really hard to do, like data migration, moving application were close around. That was once a high profit yield activity for this system integrators or selling databases like Oracle. That's the old way. The smart partners are essential, saying, OK, I'LL take the new economics where all that cost is distracted away by the automation. And I'll lower my price point but still capture the margin margin. Opportunity for cloud is significant, and this is where the smart money is going. The smart monetization schemes are around leveraging what Google and Amazon are doing at scale and shifting their business model. Take advantage of the lower cost but then lowering the price not as much, so they still capture the margin. So this's the immigration, and these are things that were like months and months project going. Data migrations to Melrose projects are like could be months. So smart money is saying Okay, how dowe I make money on this. It's not the old way. So this classic you know what side his treaty on old way or new way that's going to define who wins and who loses >> weight. By the way, I mean it. Sue Ellen >> license selling database license, for instance, is an old way. Well, essentially, it was Ramadan. Amazon does databases of service. What is the license by as you go? But you don't have, You >> know, the Oracle sells a zit buys you go to mean they play that same game. To me, it's more about when it comes to database. It's more about workloads. How much of the world needs acid property databases? Because that's oracles game versus how much of the world needs you no less database data store for for Lex structure data. And that's really I think, what Google and to a certain extent, Amazon are betting on. Although both companies, especially Amazon, is making a bet on both transactional data bases and non relationship, I >> mean in the ideal world database would be free from the margin get shifted to another spot. That's not clear yet, but still it can make money on database but lower caught in lower price. So Google makes money at scale, so with clouds scale, they can lower the price of the database like this, whether it's it's a service or some fee. But it's the people implementing, like the integrators and the people that are building applications as they build that agility. And how are they going to monetize? How does a company out in this floor make money? >> I just remember data stacks and probably like twenty twelve. I was talking to Billy Bob's worth the CEO about the merits of being in the US marketplace, and he said, You know, I'm a little nervous about that. What do you think, Dave? Do you think? Do you think they're gonna like, own me at some point in time and compete with me? So And that's what Google's announcement yesterday said is, You know, you're our friends, we're not going. They don't really come out and say, We're not going to compete with you They just basically said We are more open than aided us without mentioning a W S >> s. So it's interesting, you know, I've only had a little bit of a chance to walk around, but it's a different ecosystem, then Amazon. I remember six years ago, when we first went to Amazon. It was like game developers and all these weird start ups that I couldn't understand what they do. And now it's like, you know, like VM world, but bigger with just that. A broad ecosystem here, you know, there's a big section on collaboration. I went toe Enterprise connect a couple of weeks ago, talking about contact centers and see a lot of the same companies here heard five nines mentioned on stage zooms. Here, you know howto they plug into Google Cloud hurt sales force talking very devout Contact center. So it's a diverse ecosystem, but it's different than than Amazon, and there's not and Amazon. There's always that underlying, you know thing. Oh, is Amazon going to take over this business here? You know, I haven't heard that concern at this show. Well, >> I mean, the bottom line is that there's a shift in the economics and his model technology back in the database. Question. The fact that Mongo D. B. Was once forecast to go out of business. Oh, Amazon's going kill Mongo Devi that dynamo d B. Google's got databases. The fact the matter is, there's no one database anymore. Every application at some level has a database. So if you think about that, then you're gonna have a a new model where everything's has a database and the database is going be characterises on the workload in application. So I do agree with that point. Question is, it's not mutually exclusive one database license for all versus databases everywhere. So if databases air everywhere, then the connective tissue becomes the opportunity. That's where I think you see somebody's data playing technologies with Cloud very compelling, because I can move data very quickly around, and that's where the machine learning really shines. That's going to be a latent see question that's going to be a data integrity question. This is the new model. This is what horizontal scale ability means in the cloud, not by Oracle database. And we're good. This is It's kind of that game is that game is slowly moving into the oblivion. >> Well, I think you know, I think Amazon would say, Hey, if you're a database vendor, you gotta innovate or because we're not going to stop innovating. Whereas I think Google's message to the database vendors is somewhat different is, you know we want to partner with you, and maybe that's because they're not coming from a position of enterprise strength. But that ice I'm sensing, too, apparently different strategies. I just don't know what the end game is. And I believe the endgame is on the data. >> The tell sign on the databases of the developer, right? If I want to run a document store because that's best for my Jason or my my feeds from using Sage, eh, John? A lot of drama script. I'LL use document store. I want to use a relational database. I'll use a relational David So the ideal world does not have to develop are forced into a tooling and database decision that data >> mongo changed its licensing policy as a direct result of what Amazon was doing. So they made their community edition Ah, licence terms more restrictive if you follow that. So what? They said anybody, any cloud service provider that distributes the our community edition has to open source their entire software stack associated with distributing that, or they got to pay us. So basically saying you have to pay an open source tax or you gonna pay us we'LL be looking very interesting change in their database. One of >> the one the announcements here on the day two was the data fusion thing, which essentially means tell sign as well that fusion data moving data integrating Data's a critical thing. Pray ay, ay, ay and machine machine learning in a eyes only as good as the data that it's working with. So the data is, if his missing data saying a retail transaction, you potentially missing out on an opportunity to better user experience. So address ability of data. Having that accessible is a critical feature for machine learning, an a I and again, it's garbage in garbage out relatives of the data equation. High quality data gets high quality machine learning. High quality machine learning is high quality. I. So let's do that's that's kind of cloud offers with large compute large horizontal scale ability. >> Well, I said yes, and I said yesterday was kind of disappointed. It wasn't of talk about a I will. Google certainly made up for that today, didn't they? Still, >> Yeah, sorry was their questions >> were what was your favorite keynote moment today? >> Look, it was it was good when they actually let a couple of customers go up there and talk was that was a little bit disappointed that, you know, some of the sessions field a little bit too scripted for my take, but they laid out a lot of pieces there It takes a little wild, uh, you know, squint through all of the adjustment, you know, and all the changes that they have their I'm still digging through, like on the Antos. We talked about it quite a bit yesterday, but, you know, had some good conversations afterwards. They've got the cloud run announcement that's coming out this afternoon. But But, you know, digging into that open source discussion that you were just talking about from the database is something that I have a lot of interested. I'm glad we're actually right had on today will get their opinion as to, you know, they know a thing or two about open source and communities. And how does something like open shift fit with aunt those? They can work together, but it's not a owe it. Everything works back and forth If I'm p k s if I'm open shift or from you know, the geek based Antos, it's not seamless, and it sure ain't free you >> for not customers so weird from UPS. Scotiabank Baker Hughes McCasland heard from Cole's yesterday. So it's pretty high level senior people from the customer side speaking on stage, which is progress in the C e >> o of ups. I thought was great. He really laid out, You know, the scale of their business and how they grow. >> All right, guys, we got dates. You were kicking off here on the show floor here in San Francisco for Google Cloud next twenty nineteen. They never got it all day. And every day, two of three days, a live coverage. Stay with us as we kick off a full day of great interviews. Executives, entrepreneurs and ecosystem parties here at Google next stay with us for more after this short break.