(upbeat music) (music fades) >> Welcome to today's session of theCUBE's presentation of the AWS Startup Showcase, I'm your host Natalie Erlich. Today, we're going to feature Olive, in the life sciences track. And of course, this is part of the future of AI, security, and life sciences. Here we're joined by our very special guest Rohan D'Souza, the Chief Product Officer of Olive. Thank you very much for being with us. Of course, we're going to talk today about building the internet of healthcare. I do you appreciate you joining the show. >> Thanks, Natalie. My pleasure to be here, I'm excited. >> Yeah, likewise. Well tell us about AI and how it's revolutionizing health systems across America. >> Yeah, I mean, we're clearly living around, living at this time of a lot of hype with AI, and there's a tremendous amount of excitement. Unfortunately for us, or, you know, depending on if you're an optimist or a pessimist, we had to wait for a global pandemic for people to realize that technology is here to really come into the aid of assisting everybody in healthcare, not just on the consumer side, but on the industry side, and on the enterprise side of delivering better care. And it's a truly an exciting time, but there's a lot of buzz and we play an important role in trying to define that a little bit better because you can't go too far today and hear about the term AI being used/misused in healthcare. >> Definitely. And also I'd love to hear about how Olive is fitting into this, and its contributions to AI in health systems. >> Yeah, so at its core, we, the industry thinks of us very much as an automation player. We are, we've historically been in the trenches of healthcare, mostly on the provider side of the house, in leveraging technology to automate a lot of the high velocity, low variability items. Our founding and our DNA is in this idea of, we think it's unfair that healthcare relies on humans as being routers. And we have looked to solve the problem of technology not talking to each other, by using humans. And so we set out to really go in into the trenches of healthcare and bring about core automation technology. And you might be sitting there wondering, well why are we talking about automation under the umbrella of AI? And that's because we are challenging the very status quo of siloed-based automation, and we're building, what we say, is the internet of healthcare. And more importantly what we've done is, we've brought in a human, very empathetic approach to automation, and we're leveraging technology by saying when one Olive learns, all Olives learn, so that we take advantage of the network effect of a single Olive worker in the trenches of healthcare, sharing that knowledge and wisdom, both with her human counterparts, but also with her AI worker counterparts that are showing up to work every single day in some of the most complex health systems in this country. >> Right. Well, when you think about AI and, you know, computer technology, you don't exactly think of, you know, humanizing kind of potential. So how are you seeking to make AI really humanistic, and empathetic, potentially? >> Well, most importantly the way we're starting with that is where we are treating Olive just like we would any single human counterpart. We don't want to think of this as just purely a technology player. Most importantly, healthcare is deeply rooted in this idea of investing in outcomes, and not necessarily investing in core technology, right? So we have learned that from the early days of us doing some really robust integrated AI-based solutions, but we've humanized it, right? Take, for example, we treat Olive just like any other human worker would, she shows up to work, she's onboarded, she has an obligation to her customers and to her human worker counterparts. And we care very deeply about the cost of the false positive that exists in healthcare, right? So, and we do this through various different ways. Most importantly, we do it in an extremely transparent and interpretable way. By transparent I mean, Olive provides deep insights back to her human counterparts in the form of reporting and status reports, and we even, we even have a term internally, that we call is a sick day. So when Olive calls in sick, we don't just tell our customers Olive's not working today, we tell our customers that Olive is taking a sick day, because a human worker that might require, that might need to stay home and recover. In our case, we just happened to have to rewire a certain portal integration because a portal just went through a massive change, and Olive has to take a sick day in order to make that fix, right? So. And this is, you know, just helping our customers understand, or feel like they can achieve success with AI-based deployments, and not sort of this like robot hanging over them, where we're waiting for Skynet to come into place, and truly humanizing the aspects of AI in healthcare. >> Right. Well that's really interesting. How would you describe Olive's personality? I mean, could you attribute a personality? >> Yeah, she's unbiased, data-driven, extremely transparent in her approach, she's empathetic. There are certain days where she's direct, and there are certain ways where she could be quirky in the way she shares stuff. Most importantly, she's incredibly knowledgeable, and we really want to bring that knowledge that she has gained over the years of working in the trenches of healthcare to her customers. >> That sounds really fascinating, and I love hearing about the human side of Olive. Can you tell us about how this AI, though, is actually improving efficiencies in healthcare systems right now? >> Yeah, not too many people know that about a third of every single US dollar is spent in the administrative burden of delivering care. It's really, really unfortunate. In the capitalistic world, of, just us as a system of healthcare in the United States, there is a lot of tail wagging the dog that ends up happening. Most importantly, I don't know that the last time, if you've been through a process where you have to go and get an MRI or a CT scan, and your provider tells you that we first have to wait for the insurance company in order to give us permission to perform this particular task. And when you think about that, one, there's, you know the tail wagging the dog scenario, but two, the administrative burden to actually seek the approval for that test, that your provider is telling you that you need to perform. Right? And what we've done is, as humans, or as sort of systems, we have just put humans in the supply chain of connecting the left side to the right side. So what we're doing is we're taking advantage of massive distributing cloud computing platforms, I mean, we're fully built on the AWS stack, we take advantage of things that we can very quickly stand up, and spin up. And we're leveraging core capabilities in our computer vision, our natural language processing, to do a lot of the tasks that, unfortunately, we have relegated humans to do, and our goal is can we allow humans to function at the top of their license? Irrespective of what the license is, right? It could be a provider, it could be somebody working in the trenches of revenue cycle management, or it could be somebody in a call center talking to a very anxious patient that just learned that he or she might need to take a test in order to rule out something catastrophic, like a very adverse diagnosis. >> Yeah, really fascinating. I mean, do you think that this is just like the tip of the iceberg? I mean, how much more potential does AI have for healthcare? >> Yeah, I think we're very much in the early, early, early days of AI being applied in a production in practical sense. You know, AI has been talked about for many, many many years, in the trenches of healthcare. It has found its place very much in challenging status quos in research, it has struggled to find its way in the trenches of just the practicality on the application of AI. And that's partly because we, you know, going back to the point that I raised earlier, the cost of the false positive in healthcare is really high. You know, it can't just be a, you know, I bought a pair of shoes online, and it recommended that I buy a pair of socks, and I happen to get the socks and I returned them back because I realized that they're really ugly and hideous and I don't want them. In healthcare, you can't do that. Right? In healthcare you can't tell a patient or somebody else oops, I really screwed up, I should not have told you that. So, what that's meant for us, in the trenches of delivery of AI-based applications, is we've been through a cycle of continuous pilots and proof of concepts. Now, though, with AI starting to take center stage, where a lot of what has been hardened in the research world can be applied towards the practicality to avoid the burnout, and the sheer cost that the system is under, we're starting to see this real upwards tick of people implementing AI-based solutions, whether it's for decision-making, whether it's for administrative tasks, drug discovery, it's just, is an amazing, amazing time to be at the intersection of practical application of AI and really, really good healthcare delivery for all of us. >> Yeah, I mean, that's really, really fascinating, especially your point on practicality. Now how do you foresee AI, you know, being able to be more commercial in its appeal? >> I think you have to have a couple of key wins under your belt, is number one, number two, the standard, sort of outcomes-based publications that is required. Two, I think we need, we need real champions on the inside of systems to support the narrative that us as vendors are pushing heavily on the AI-driven world or the AI-approachable world, and we're starting to see that right now. You know, it took a really, really long time for providers, first here in the United States, but now internationally, on this adoption and move away from paper-based records to electronic medical records. You know, you still hear a lot of pain from people saying oh my God, I used an EMR, but try to take the EMR away from them for a day or two, and you'll very quickly realize that life without an EMR is extremely hard right now. AI is starting to get to that point where, for us, we, you know, we treat, we always say that Olive needs to pass the Turing test. Right? So when you clearly get this, this sort of feeling that I can trust my AI counterpart, my AI worker to go and perform these tasks, because I realized that, you know, as long as it's unbiased, as long as it's data-driven, as long as it's interpretable, and something that I can understand, I'm willing to try this out in a routine basis, but we really, really need those champions on the internal side to promote the use of this safe application. >> Yeah. Well, just another thought here is, you know, looking at your website, you really focus on some of the broken systems in healthcare, and how Olive is uniquely prepared to shine the light on that, where others aren't. Can you just give us an insight onto that? >> Yeah. You know, the shine the light is a play on the fact that there's a tremendous amount of excitement in technology and AI in healthcare applied to the clinical side of the house. And it's the obvious place that most people would want to invest in, right? It's like, can I bring an AI-based technology to the clinical side of the house? Like decision support tools, drug discovery, clinical NLP, et cetera, et cetera. But going back to what I said, 30% of what happens today in healthcare is on the administrative side. And so what we call as the really, sort of the dark side of healthcare where it's not the most exciting place to do true innovation, because you're controlled very much by some big players in the house, and that's why we we provide sort of this insight on saying we can shine a light on a place that has typically been very dark in healthcare. It's around this mundane aspects of traditional, operational, and financial performance, that doesn't get a lot of love from the tech community. >> Well, thank you Rohan for this fascinating conversation on how AI is revolutionizing health systems across the country, and also the unique role that Olive is now playing in driving those efficiencies that we really need. Really looking forward to our next conversation with you. And that was Rohan D'Souza, the Chief Product Officer of Olive, and I'm Natalie Erlich, your host for the AWS Startup Showcase, on theCUBE. Thank you very much for joining us, and look forward for you to join us on the next session. (gentle music)

(soft music) >> Welcome back, everyone. theCube's live coverage. Day two here at VMware Explore. Our 12th year covering VMware's annual conference formally called Vmworld, now it's VMware Explore. Exploring new frontiers multi-cloud and also bearing some of the fruit from all the investments in cloud native Tanzu and others. I'm John Furrier with Dave Vellante. We have the man who's in charge of a lot of that business and a lot of stuff coming out of the oven and hitting the market. Ajay Patel, senior vice president and general manager of the modern applications and management group at VMware, basically the modern apps. >> Absolutely. >> That's Tanzu. All the good stuff. >> And Aria now. >> And Aria, the management platform, which got social graph and all kinds of graph databases. Welcome back. >> Oh, thank you so much. Thanks for having me. >> Great to see you in person, been since 2019 when you were on. So, a lot's happened since 2019 in your area. Again, things get, the way VMware does it as we all know, they announce something and then you build it and then you ship it and then you announce it. >> I don't think that's true, but okay. (laughs) >> You guys had announced a lot of cool stuff. You bought Heptio, we saw that Kubernetes investment and all the cloud native goodness around it. Bearing fruit now, what's the status? Give us the update on the modern applications of the management, obviously the areas, the big announcement here on the management side, but in general holistically, what's the update? >> I think the first update is just the speed and momentum that containers and Kubernetes are getting in the marketplace. So if you take the market context, over 70% of organizations now have Kubernetes in production, not one or two clusters, but hundreds of clusters, sometimes tens of clusters. So, to me, that is a market opportunity that's coming to fruition. Sometimes people will come and say, Ajay, aren't you late to the market? I say, no, I'm just perfectly timing it. 'Cause where does our value come in? It's enterprise readiness. We're the company that people look to when you have complexity, you have scale, you need performance, you need security, you need the robustness. And so, Tanzu is really about making modern applications real, helping you design, develop, build and run these applications. And with Aria, we're fundamentally changing the game around multicloud management. So the one-two punch of Tanzu and Aria is I'm most excited about. >> Isn't it true that most of the Kubernetes, you know, today is people pulling down open source and banging away. And now, they're looking for, you know, like you say, more of a robust management capability. >> You know, last two years when I would go to many of the largest customers, like, you know, we're doing good. We've got a DIY platform, we're building this. And then you go to the customer a year later, he's got knocked 30, 40 teams and he has Log4j happen. And all of a sudden he is like, oh, I don't want to be in the business of patching this thing or updating it. And, you know, when's the next shoe going to fall? So, that maturity curve is what I was talking about. >> Yeah. Free like a puppy. >> Ajay, you know, mentioned readiness, enterprise readiness and the timing's perfect. You kind of included, not your exact words, but I'm paraphrasing. That's a lot to do with what's going on. I mean, I'll say Cloud Native, IWS, think of the hyper scale partner, big partner and Google and even Google said it today. You know, the market world's spinning in their direction. Especially with respect to VMware. You get the relationship with the hyperscalers. Cloud's been on everyone's agenda for a long time. So, it's always been ready. But enterprise, you are customer base at VMware, very cloud savvy in the sense they know it's there, there's some dabbling, there's some endeavors in the cloud, no problem. But from a business perspective and truly transforming the VMware value proposition, is already, they're ready and it's already time now for them, like, you can see the movement. And so, can you explain the timing of that? I mean, I get enterprise readiness, so we're ready to scale all that good stuff. But the timing of product market fit is important here. >> I think when Raghu talks about that cloud first to cloud chaos, to cloud smart, that's the transition we're seeing. And what I mean by that is, they're hitting that inflection point where it's not just about a single team. One of the guys, basically I talked to the CIO, he was like, look, let's assume hypothetically I have thousand developers. Hundred can talk about microservices, maybe 50 has built a microservice and three are really good at it. So how do I get my thousand developers productive? Right? And the other CIO says, this team comes to me and says, I should be able develop directly to the public cloud. And he goes, absolutely you can do that. You don't have to come through IT. But here's the book of security and compliance that you need to enforce to get that thing in production. >> Go for it. >> Go for it. >> Good luck with that. >> So that reality of how do I scale my dev developers is turning into a developer experience problem. We now have titles which says, head of developer experience. Imagine that two years ago. We didn't talk about it. People start, hey, containers Kubernetes. I'm good to go. I can go get all the open source technology you talked about. And now they're saying no. >> And also software supply chains, another board that you're think. This is a symptom of the growth. I mean, open source is the software industry. That is, I don't think debatable. >> Right. >> Okay. That's cool. But now integration becomes vetting, trust, trusting codes. It's very interesting software time right now. >> That's right. >> And how is that impacting the cloud native momentum in your mind? Accelerating it? What inning are we in? How would you peg the progress? >> You know, on that scale of 1 to 10, I think we're halfway marked now. And that moved pretty quickly. >> It really did. >> And if you sit back today, the kinds of applications we're involved in, I have a Chicago wealth management company. We're building the next generation wealth management application. It's a fundamental refactoring of the legacy application. If you go to a prescription company, they're building a brand new prescription platform. These are not just trivial. What they're learning is the lift and shift. Doesn't work for these major applications. They're having to refactor them which is the modernization. >> So how specifically, are they putting some kind of abstraction layer on that? Are they actually gutting it and rewriting it? >> There's always going to be brownfield. Remember the old days of SOA? >> Yeah, yeah. >> They are putting APIs in front of their main systems. They're not rewriting the core banking or the core platform, but the user experience, the business logic, the AIML capability to bring intelligence in the platform. It's surrounding the capability to make it much more intuitive, much more usable, much more declarative. That's where things are going. And so I'm seeing this mix of integration all over again. Showing my age now. But, you know, the new EAI so is now microservices and messaging and events with the same patterns. But again, being much more accelerated with cloud native services. >> And it is to the point, it's accelerated today. They're not having to freeze the code for six months or nine months and that which would kill the whole recipe for failure. So they're able to now to fast track their modernization. They have to prioritize 'cause they got limited resources. But how are you guys coming up to that? >> But the practice is changing as well, right? Well, the old days, it was 12, 18 months cycle or anything software. If you heard the CVS CIO, Rohan. >> Yeah. >> Three months where they started to engage with us in getting an app in production, right? If you look at the COVID, 10 days to get kind of a new application for getting small loans going with Pfizer, right? These are dramatically short term, but it's not rewriting the entire app. It's just putting these newer experiences, newer capability in front with newer modern developer practices. And they're saying, I need to do it not just once, but for 100, 200, 5,000 members. JPMC has 50,000 developers. Fifty thousand. They're not a bank anymore. >> We just have thousands of apps. >> Exactly. >> Ajay, I want to get your thoughts on something that we've been talking about on our super cloud event. I know we had an event a couple weeks ago, you guys were one of our sponsors, VMware was. It was called super cloud where we're defining that this next gen environment's a super cloud and every company will have a super cloud capability. And underneath that is cross cloud capabilities. So, super cloud is like a super set on top of a multi-cloud. And little word play or play on words is, ecosystem partners versus partners in the ecosystem. Because if you're coming down to the integration side of things, it's about knowing what goes what, it's almost like building an OS if you're a coder or an operating systems person. You got to put the pieces together right, not just go to the directory and say, okay, who's got the cheapest price in DR or air gaping or something or some solution. So ecosystem partners are truly partners. Partners in the ecosystem are a bunch of people out on a list. How do you see that? Because the trend we're seeing is, the development process includes partners at day one. >> That's right. Not bolt-on. >> Completely agree. >> Share your thoughts on that. >> So let's look at that. The first thing I'm hearing from my customers is, they're trying to use all the public clouds as a new IS. That's the first API or contract infrastructures code IS. From then on they're saying, I want more and more portable services. And if you see the success of some of the data vendors and the messaging vendors, you're starting to see best of breed becoming part of the platform. So you are to identify which of these are truly, you know, getting market momentum and are becoming kind of defacto leaders. So, Kafka goes hand in hand with streaming. RabbitMQ from my portfolio goes with messaging. Postgres for database. So these are the, in your definition, ecosystem partners, they're foundational. In the security space, you know, Snyk is a common player in terms of scanning or Aqua and Prisma even though we have Carbon Black. Those become partners from a container security perspective. So, what's happening is the industry stabilizing a handful of critical players that are becoming multi-cloud preference of choice in this. And our job is to bring it all together in a all coordinated, orchestrated manner to give them a platform. >> I mean, you guys always had ecosystem, but I think that priority more than ever. It wasn't really your job at VMware, even, Dave, 10 years ago to say, hey, this is the strategic role that you might play one partner. It was pretty much the partners all kind of fed off the momentum of VMware. Virtualization. And there's not a lot of nuance there. There's pretty much they plug in and you got. >> So what we're doing here is, since we're not the center of the universe, unfortunately, for the application world, things like Backstage is a developer portal from Spotify that became open source. That's becoming the place where everyone wants to provide a plugin. And so we took Backstage, we said, let's provide enterprise support for Backstage. If you take a technology like, you know, what we have with Spring. Every job where developer uses Spring, how do we make it modern with Spring cloud. We work with Microsoft to launch a service with Azure Spring Enterprise for Spring. So you're starting to see us taking communities where they have momentum and bringing the ecosystem around those technologies. Cluster API for Kubernetes, for have you managed stuff. >> Yeah. >> So it's about standard. >> Because the developers are voting with their clicks and their code repos. And so you're identifying the patterns that they like. >> That's right. >> And aligning with them and connecting with them rather than trying to sell against it. >> Exactly. It's the end story with everyone. I say stop competing. So people used to think Tanzu is Kubernetes. It's really Tanzu is the modern application platform that runs on any Kubernetes. So I've changed the narrative. When Heptio was here, we were trying to be a Kubernetes player. I'm like, Kubernetes is just another dial tone. You can use mine, you can use OpenShift. So this week we announced support for OpenShift by Tanzu application platform. The values moving up, it's around outcomes. So industry standards, taking lead and solving the problem. >> You know, we had a panel at super cloud. Dave, I know you got a question. I'll get to you in a second. But the panel was the innovator's dilemma. And then during the event, one of the panelists, Chris Hoff knows VMware very well, Beaker on Twitter, said it should be called the integrators dilemma. Because the innovations here, >> How do you put it all together? >> But the integration of the, putting the piece parts together, building the thing is the innovation. >> And we come back and say, it's a secure software supply chain. It starts with great content. Did you know, I published most of the open source content on every hyperscaler through my Bitnami acquisition. So I start with great content that's curated. Then I allow you to create your own golden images. Then I have a build service that secures and so on and so forth and we bring the part. So, that opinionated solution, but batteries included but you can change it is been one of our key differentiator. We recognize the roles is going to be modular, come back and solve for it. >> So I want to understand sort of relationship Tanzu and Aria, John was talking about, you know, super cloud before we had our event. We had an earlier session where we help people understand that Aria was not, you know, vRealize renamed. >> It's rebranded. >> And reason I bring that up is because we had said it around super cloud, that one of the defining characteristics was, sorry, super PaaS, which is a specific purpose built PaaS layer designed to support your objective for multi-cloud. And speaking to a lot of people this week, there's a federated architecture, there's graph relationships, there's real time ability to ingest and analyze. That's unique. And that's IP that is purpose built for what you're doing. >> Absolutely. When I think what came out of all that learning is after 20 years of Pivotal and BA and what we learned that you still need some abstraction layer. Kubernetes is too low level. So what are the developer problems? What are the delivery problems? What are the operations and management problems? Aria solves all the operations and management problem. Tanzu solves a super PaaS problems. >> Yes. Right. >> Of providing a consistent way to build great software and the secure software supply chain to run on any infrastructure. So the combination of Tanzu and Aria complete the value chain. >> And it's different. Again, we get a lot of heat for this, but we're saying, look, we're trying to describe, it's not just IAS, PaaS, and SaaS of last decade. There's something new that's happening. And we chose the name super cloud. >> And what's the difference? It's modular. It's pluggable. It fits into the way you operate. >> Whereas PaaS was very prescriptive. If you couldn't fit, you couldn't jump down to the next level. This is very much, you can stay at the abstraction level or go lower level. >> Oh, we got to add that to the attribute. >> We're recruiting him right now. (laughs) >> We'll give you credit. >> I mean, funny all the web service's background. Look at an app server. You well knew all about app servers. Basically the company is an app. So, if you believe that, say, Capital One is an application as a company and Amazon's providing all the CapEx, >> That's it. >> Okay. And they run all their quote, old IT spend millions, billions of dollars on operating expenses that's going to translate to the top line called the income statement. So, Dave always says, oh, it's on the balance sheet, but now they're going to go to the top line. So we're seeing dynamic. Ajay, I want to get your reaction to this where the business model shift if everything's tech enabled, the company is like an app server. >> Correct. >> So therefore, the revenue that's generated from the technology, making the app work has to get recognized in the income. Okay. But Amazon's doing all, or the cloud hyperscale is doing all the heavy lifting on the CapEx. So technically it's the cloud on top of a cloud. >> Yes and no. The way I look at it, >> I call that a super cloud. >> So I like the idea of super cloud, but I think we're mixing two different constructs. One is, the cloud is a new hardware, right? In terms of dynamic, elastic, always available, et cetera. And I believe when more and more customer I talk about, there's a service catalog of infrastructure services. That's emerging. This super cloud is the next set of PaaS super PaaS services. And the management service is to use the cloud. We spend so much time as VMware building clouds, the problem seems, how do you effectively use the cloud? What problems do we solve around digital where every company is a digital company and the product is this application, as you said. So everything starts with an application. And you look at from the lens of how you run the application, what it costs the application, what impact it's driving. And I think that's the change. So I agree with you in some way. That is a digital strategy. >> And that's the company. >> That's the company. The application is the company. >> That's the t-shirt. >> And API is the currency. >> So, Ajay, first of all, we love having you in theCube 'cause you're like a masterclass in multiple dimensions. So, I want to get your thoughts on the abstraction layer. 'Cause we were also talking earlier in theCube here as well as before. But abstraction layers happen when you have major movements in markets that are game changing or major inflection points because you've reached a complexity point where it's working so great, this new thing, that's too complex to reign it in. And we were quoting Andy Grove by saying, "let chaos reign then reign in the chaos". So, all major industry moments go back 30, 40 years happen with abstractions. So the question is is that, you can't be a vendor, we've observed you can't be a vendor and be the abstraction. Like, if Cisco's running routers, they can't be the abstraction layer. They have to be the benefit of the abstraction layer. And if you're on the other side of the abstraction layer, you can't be running that either. >> I like the way you're thinking about it. Yeah. Do you agree? >> I completely agree. And, you know, I'm an old middleware guy. And when I used to say this to my CEO, he's like, no, it's not middleware, it's just a new middleware. And what's middleware, right? It's a thing between app and infrastructure. You could define it whatever we want, right? And so this is the new distributed middleware. >> It's a metaphor and it's a good one because it does a purpose. >> It's a purpose. >> It creates a separation but then you have, it's like a DMZ zone or whatever you want to call it. It's an area that things happen. >> But the difference before last time was, you could always deploy it to a thing. The thing is now the cloud. The thing is a set of services. So now it's as much of a networking problem at the application layer is as much as security problem. It's how you build software, how we design. So APIs, become part of your development. You can't think of APIs after the fact, right? When you build an API, you got to publish API because the minute you publish it and if you change it, the API's out of. So you can't have it as a documentation process. So, the way you build software, you use software consume is all about it. So to me, digital product with an API as a currency is where we're headed towards. >> Yeah, that's a great observation. Want to make a mental note of that and make that a clip. I want to get your thoughts on software development. You mentioned that, obviously software development life cycles are changing. I'll say open sources now. I mean, it's unlimited codes, supply chain issue. What's in the code, I get that verified codes going to happen. Is software development coding as much or is coding changing the notion of writing code? Or is it more glue layer you're writing. >> I think you're onto something. I call software developments composition now. My son's at Facebook or Google. They have so many libraries. So you don't no longer start with the very similar primitive, you start with building blocks, components, services, libraries, open source technology. What are you really doing? You're composing these things from multiple artifacts. And how do you make sure those artifacts are good artifacts? So someone's not sticking in security in a vulnerability into it. So, the world is moving towards composition and there are few experts who build the core components. Most of the time we're just using those to build solutions. And so, the art here is, how do you provide that set of best practices? We call them patterns or building blocks or services that you can compose to build these next generation (indistinct) >> It's interesting. >> Cooking meals. >> I agree with you a hundred percent what you're thinking. I agree about that worldview. Here's a dilemma that I'm seeing. In the security world, you've got zero trust. You know, Which is, I don't know you, I don't trust you at all. And if you're going to go down this composed, we're going to have an orchestra of players with instruments, say to speak, Dave, metaphor. That's trust involved. >> Yes. >> So you have two spectrums of issues. >> Yes. >> If software's going trust and you're seeing Docker containers getting more verifications, software supply chain, and then you got hardware I call network guys, love zero trust. Where's the balance? How do you reconcile that? Is it just decoupled? Nuance? I mean, what's the point? >> No, no. I think it all comes together. And what I mean by that is, it starts with left shifting it all the way to hands of the developers, right? So, are you starting with good content? You have providence of the stuff you're using. Are you building it correctly? So you're not introducing bad things like solar winds along the process. Are you testing it along the way of the development process? And then once in production, do you know, half the time it's configurations of where you're running the stuff versus the software itself. So you can think of the two coming together. And the network security is protecting people from going laterally once they've got in there. So, a whole security solution requires all of the above, a secure software supply chain, the way to kind of monitor and look at configuration, we call posture management or workload management and the network security of SaaS-e for zero trust. That's a hard thing. And the boundary is the application. >> All right. >> So is it earned trust model sort of over time? >> No, it's designed in, it's been a thing. >> Okay. So it's not a, >> Because it developed. >> You can bolt in afterwards. >> Because the developers are driving it. They got to know what they're doing. >> And it's changing every week. If I'm putting a new code out every week. You can't, it can be changed to something else. >> Well, you guys got guardrails. The guardrails constant is a good example. >> It stops on the configuration side, but I also need the software. So, Tanzu is all about, the secure chain is about the development side of the house. Guardrails are on the operational side of the house. >> To make sure the developers don't stop. >> That's right. >> Things will always get out there. And I find out there's a CV that I use a library, I found after the fact. >> Okay. So again, while I got here again, this is great. I want to get test this thesis. So, we've been saying on theCube, talking about the new ops, the new kind of ops that emerging. DevOps, which we believe is cloud native. So DevOps moving infrastructure's code, that's happened, it's all good. Open source is growing. DevOps is done deal. It's done deal. Developers are doing that. That ops was IT. Then don't need the server, clouds my hardware. Check. That balances. The new ops is data and security which has to match up to the velocity of the developers. Do you believe that? >> Completely. That's why we call it DevSecOps. And the Sec is where all the action is. >> And data. And data too. >> And data is about making the data available where the app meets. So the problem was, you know, we had to move the logic to where the data is or you're going to move the data where the logic is. So data fabrics are going to become more and more interesting. I'll give you a simple example. I publish content today in a service catalog. My customer's saying, but my content catalog needs to be in 300 locations. How do I get the content to each of the repos that are running in 300 location? So I have a content distribution problem. So you call it a data problem. Yes, it's about getting the right data. Whether it's simple as even content, images available for use for deployment. >> So you think when I think about the application development stack and the analytics stack, the data stack, if I can call it that, they're separate, right? Are those worlds, I mean, people say, I want to inject data and AI intelligence into apps. Those worlds have deployment? I think about the insight from the historical being projected in the operational versus they all coming together. I have a Greenplum platform, it's a great analytics platform. I have a transactional platform. Do my customers buy the same? No, they're different buyers, they're different users. But the insight from that is being now plugged in so that at real time I can ask the question. So even this information is being made available on demand. So that's where I see it. And that's most coming together, but the insight is being incorporated in the operational use. So I can say, do I give the risk score? Do I give you credit? It's based on a whole bunch of historical analytics done. And at the real time, processing is happening, but the intelligence is behind it. >> It's a mind shift for sure because the old model was, I have a database, we're good. Now you have time series database, you got graphs. Each one has a role in the overall construct of the new thing. >> But it's about at the end. How do I make use of it? Someone built a smart AI model. I don't know how it was built, but I want to apply it for that particular purpose. >> Okay. So the final question for you, at least from my standpoint is, here at VMware Explore, you have a lot of the customers and so new people coming in that we've heard about, what's their core order of operations right now? Get on the bandwagon for modern apps. How do you see their world unfolding as they go back to the ranch, their places, and go back to their boss? Okay. We got the modern application. We're on the right track boss, full steam ahead. Or what change do they make? >> I think the biggest thing I saw was with some of the branding changes well and some of the new offerings. The same leader had two teams, the VMware team and the public cloud team. And they're saying, hey, maybe VMware's going to be the answer for both. And that's the world model. That's the biggest change I'm seeing. They were only thinking of us on the left column. Now they see us as a unifying player to play across cloud native and VMware, the uniquely set up to bring it all together. That's been really exciting this week. >> All right, Ajay, great to have you on. Great perspective. Worthy of great stuff. Congratulations on the success of all that investment coming to bear. >> Thank you. >> And on the new management platform. >> Yeah. Thank you. And thanks always for giving us all the support we need. It's always great. >> All right Cube coverage here. Getting all the data, getting inside the heads, getting all the specifics and all the new trends and actually connecting the dots here on theCube. I'm John Furrier with Dave Vellante. Stay tuned for more coverage from day two. Two sets, three days, Cube at VMware Explore. We'll be right back. (gentle music)

>> Live from Orlando, Florida It's the Cube covering Enterprise Connect twenty nineteen brought to you by five nine. >> Welcome back to Orlando, Florida. Lisa Martin. With the cues to minimum joining me, we are a day three of our coverage of enterprise connect nineteen. Thanks to our gracious hosts in the booth here, five nine, We're pleased to welcome from five nine to the program. Wendell Black, VP of Global Channels and international Business. Wendell, thank you so much for joining us today. >> Well, Lisa, thank you for having me on. >> I know you're a bit of a celebrity because you have now been a crn channel chief honoree three times, most recently last month. Congratulations. >> Well, thank you very much. It's absolutely a tribute to my team and the company's focus on building out our channel business over the last three years. So it's been, you know, a super time for five nights growth in this area on DH. It definitely is a team engage sport >> team that pulled you out of retirement. They're less >> Well, you know, we don't talk about that so much, but it is exciting to be back in the business and, you know, working here toe, you have to build something new for five nine and to help take us into the next Thira Business delivery and especially the expansion we're doing outside of North America. That's, uh, that's the really exciting part. >> So before we talk about the international peace, one of the things that's been really interesting to watch anybody that knows the channel is the cloud has had a dramatic effect on on them. If I walk around the show floor, many of the companies here in the channel that they did, where used to sell in boxes and then all I need to understand software and oh, jeez, this cloud, it's gonna put us out of a business. They'Ll all go direct, but I'm sure you've got a lot of perspectives on this. So maybe help walk us through some of that transformation. >> But it's interesting. I've been an evangelist in the cloud space since the late nineties senses peace. So we didn't call it cloud then it was multi tenant managed service technology. But you know, the really exciting part is, you know, the last four or five years when it really caught on and started to take off, you know, we've had a lot of good trailblazing companies out there that yo have won the minds of people for cloud and the C r m or the Air P and other spaces. Yeah, telecommunications is kind of the lagging, Uh, yeah. Technology area to be adopted, You know, his standards for cloud. But I believe today most buyers are trying to figure out why not cloud, rather than why go to cloud. And that's a game changer. >> Yes. Oh, I'm curious. Just from the channel perspective itself. We understand that customer journey, but the channel people was there. Do they have the skill set that they need to go? Was just some retraining. Was it partnerships like like yours, you know, how did that transition go? >> Yeah, that's a great question. And I really think that the channel has the skills. Yeah, they just have to adapt and re tune a little bit. Things just happen faster when you do the cloud and and we have get a MIDI discussions and experiences with partners where we're sitting around the table planning Ah, roll out. And you're just doing the basic discovery. And, you know, at the end of that, r P s team can say, Well, I've actually built it. Let me show you how it works, you know, rather than you know, the six month or twelve months rollout process that people were accustomed to in the past. So it's pretty exciting to be able to show people actionable results that kind of time frame very, very fun. >> Talk to us about the partnerships and the influence that your partners have had on such a big, successful close to f. Y eighteen. >> You know, the other partners were strong contributors in, you know, our cue for and we certainly value everything they're doing for us and with us out in the market are continuum of partners is get both in the master agent community. So referral oriented relationships where the five nine direct sales team is getting Carrie in the water and working with them to get a deal done, but also in our resale business. Uh, you know, it's great to see those partners doing more and more to build the business and their portfolio on DH delivered joint customers. So it's a very exciting, you know, kind of up lift everything we're doing. All right, >> So So Wendell, uh, one of things when we talked. A lot of companies, it's like, Well, there's North American. There's everything else I was promised by some of your team members. You can actually give us a little bit more granular view of, you know, Europe, Eastern Europe and some of the other global differences that are happening in the market Place would love if you could share some of your wisdom. It's >> your thing. And I believe that I don't want to be disparaging Tio my friends in Europe, but they're a little slower on the adoption rate. Um, it's interesting. In my history and contact center, there were times where Europe led the field with different technologies, and yet other times that they were kind of behind what North America was doing. Uh, this is one of behind times, and I think it is just, you know, an ongoing concern and their minds about you know, how security and management of a cloud based delivery model was going to affect their business and how they were going to be looked at by regulators. But I think we've overcome, uh, those hurdles and the last several years in twenty eighteen, our business in Europe doubled year over year. Uh, and it's inspired us God, ADM. Or sales and other departmental resource is in the region so that we can do that again here and twenty nineteen similar story in Latin America. And now there is, ah lot of growth, a lot of interest. And it's not just in the mid market anymore. We're talking big, big call centers on. They are all jumping on the bandwagon. Uh, for all of the economic reasons that people want to go to the cloud in the first place. You know it's less expensive to get started. You know, it's easier to be nimble and flexible and your staffing and costs, and, you know, they all need those benefits just as much as a mid market or s and be kind of a client. >> Well, dig in a little bit further, Wendell, on how five nine and your partners have helped some of these customers in Europe in Latin America become comfortable with. We need to move to the cloud and also help them understand some of the other implications. Besides costs and things like the opportunity to start taking advantage of a >> okay, Great, yeah, because in particular, one of our partners in the UK has specialized in the travel, vacation Liza kind of industry and yell when they work in those markets. Uh, distributed workforce is very much kind of the norm for them. And so, you know, one of their clients, in particular, has agents in the UK They have agents in Germany. They want to manage him, is a common group and be able Teo manage there, television advertising to be ableto staff and respond based on wherever the load is. You know, whenever things are going on in there, you know, marketing activity, that's that's a key flexibility win for them. And they get the right staff at the right time to be ableto you know, to cover the television advertising, which is pretty costly, but it's a big win for them. Gotta have that flexibility with five nine. >> You know, it's interesting. We actually have only talked a little bit this week about the distributed workforce, and I I'd love to get your perspective. You know, I think back there's, you know, a large apparel company in the Northeast that when they didn't have any of their agents, you know, in their headquarters, and, you know, it was something that got written up. You know when that had happened. So today you know what? What is that? That mix? And, you know, are there some geographic differences that you see in that? >> Yeah, there are some differences just based on the infrastructure that may be available. And, you know, we find that home based workforce is a little bit more challenging in Latin America than it is perhaps in Europe or in the US But then there's also cultural differences. Yeah, there are some countries that have actually regulate that employees have to show up in a physical building or you're violating the law because you might be taking advantage of your employees. So that's different. Different strokes for get up for different locations. We are finding it more and more desirable because of all the reasons that, yeah, I've been around for a long time. You can save on real estate. You can save on the wear and tear of your employees traveling, but probably the biggest one is the benefit of flex staffing that allows you to get the right number of people for a short shift to cover your peaks or your be ready for your valleys that you know if people have to drive to an office they're just not is likely to want to sign up for, But that business modeling is actually becoming more and more compelling. Driving around Orlando. You know, this week it was kind of a challenge. Get on I for and with the rain. And I'm sure there are a lot of people who want to be at home workers here, you know, based on the weather this week. >> Definitely. So this is the end of enterprise Connect Expo Hall anyway, today, three full days this Expo Hall one hundred forty vendors knew new products. New service is sixty five hundred attendees. So much excitement in this hot, hot contact center market. What are some of the things that excite you that you've heard from partners and customers that just think we're on the right track? The momentum, The wind is at our backs >> Well, and you mentioned a I and what do your earlier questions? And that's kind of the buzz. Everybody was to talk about automation and machine learning, and you can bring a I into, you know, interacting in the call center. I'm sure you've heard from other people that have been up here. The focus we see in the near term is on agent augmentation and, you know, enhancing. Yeah. Agent performance through those technologies on, you know, a lot of people would have approached this thinking like Ivy ours in the past. I can replace agents with interactive voice response. Well, we will. We want to make a smarter, better customer serving agent and bring that technology and to play to do it. That's to me. Going be the things I've been seen exciting new technologies that can be applied in real time transcription and Theo providing the ability to read that and data depth and serve things up for for agents to allow them, Tio go to be more on the ball, talking to a client. >> Yeah, that old mental Asian is definitely something that came up quite a bit. We even talked with your CEO, Rohan trollop about that and the importance of empathy and voice that as consumers I would love to know that you went to an augmented agent on the other end. Who knows? Okay, I understand the issue. I see how many times this person has reached out through different channels and they're actually going to use that technology to facilitate a resolution and hopefully drive up. See Elvi. >> I mean, that insight into the customer experience is key for the agent to be able to do Mohr and do it better. You know, we've been talking about that night of insight for years and years. You know, technology has caught up with desire. And so now that we have the technology to do it, you know, we can allow the agent focus more on their conversation with a customer and not have to be working the keyboard in order to retrieve the next thing that they need to take care of. And so better prepared agent, you know, knowing the background of the client, you know, is going to give them a much better experience. And, you know, that's what five nines trying to deliver in the market. >> We've heard that resoundingly throughout the re through your partners customers, and it's been fantastic. Wendell, congrats again on your three time channel, chief. Honoree. A record. And I'm sure there's got to be a fourth one around the corner. I won't jinx that, but I'm just gonna gas. >> Thank you. >> We thank you so much for your time. >> Appreciate it. >> Likewise forced to Mina. Man, I'm Lisa Martin. You're watching the Cube?

>> Hello, and welcome to the special. Keep conversation here in Palo Alto, California John Furrier, Co-Host of the Cube. We're here with Jonathan Rosenberg, CTO chief technology officer and head of AI for Five9. Jonathan. Great. Great to see you. Thanks for coming in. >> Thanks. My pleasure to be here. >> So you've had a stellar career? Certainly. Technical career going way back to Lucent Technologies. Now here at Five9, Cisco along the way. You've been a really technical guru. You've seen the movie before. This's happening. Every wave of innovation, multiple ways you've been on. Now you're on the next wave, which is cloud AI, CTO Five9. Rapidly growing company. Yes, it is. What attracted you to five? >> Yeah, Great question. There's actually a lot of things that brought me to Five9. I think probably the most important thing is that I've got this belief, and I'm very motivated for myself. A least to do technology and innovate and create new things. And this belief that were on the cusp of the next generation of technology in the collaboration industry. And that next generation is going to be powered by artificial intelligence, and one of the ways I sort of talked about this is that if you look at the entire history of collaboration, up til now meetings, telephony, messaging was to figure out, a way to get the bits of data from one person to another person fast enough to have a conversation. That's it. You know, once we got the audio connected, we just moved the audio packets in the video packets and messaging from one place to another. And we didn't actually analyze any of that because we couldn't. We didn't have the technology to do that. But now, with the arrival of artificial intelligence and particular speech recognition, natural language processing, we can apply those technologies to that content and take all this dark data that's been basically thrown away the instant it was received, to process it and do things. And that is going to completely transform every field of collaboration, from meetings to messaging, to telephony. And I believe that so strongly, that is, That's great. That's going to be my next job. I wanna work on that. And it's going to start in the Contact Center because a contact center is the ideal place to do that. It's the tip of the spear for AI in collaboration, >> and it's in a really great area. Disruptive innovation are absolutely so Take us through the impact was one of things I have observed in this industry is you have You know, I don't want to say mainframe clients served to go back to date myself, but there was that wave of client server computer >> mainframes. Cool again. We just called clout. Now, hey, is >> exactly. So you have these structural industry waves take us through the waves of how we got here and what's different now? And why can't the old guard or the older incumbents surviving if you're not out in front that next wave your driftwood. So what? What's What's his ways mean? Why is this important? What has to change to be successful? >> Exactly. So there's been this this whole like you said these waves. So the first wave of telecommunications was like hardware: circuit switching, big iron switches, sitting in telco data centers, you know, And then that era transitioned to software and that was with the arrival voiceover IP and technologies like SIP, and that made it more less expensive. And anyone could do it, and it transformed the industry. The next wave, the third wave were still like halfway through and in some areas, actually, just beginning contact, center was early here, the third wave is cloud, right is now we're moving that software to a totally new delivery vehicle that allows us to deliver innovation and speed. And that wave has now enabled us to start the next wave, which is on ly in its infancy, which is AI right, and the application of machine learning techniques to automate all kinds of aspects of how people communicate in collaborate. >> I think cloud is a great example of Seen a. I, which had been a concept around when I was in computer science. Back in the eighties, there was a guy you know theory, and it's the science of it is not so much change, but computing's available. The data to be analysed for the first time is available. Yeah, you mentioned analyzing the bits writings. There's now a key part. What does it actually mean? Teo. Someone who's has a contact center has a large enterprise. Says, you know what? I got to modernize. How does A I fit them? What is actually going on, >> right? Great question. So a I actually consult lots different problem at the end of the day again, Hey, eyes like this, Let's. It's the biggest buzz word right on. It's in my title. So, like I'm a little guilty, right? >> We'll get a pay raise for, But >> what? It comes down to this, really this Korean machine learning, which is really like a fancy new algorithmic technique for taking a bunch of data and sort of making a decision based on it. So And it turns out, as we've learned that if you have enough data and you can have enough computing and we optimize the algorithms, you could do some amazing things, right? And it's been applied to areas like speech recognition and image recognition and all these kind of things. Self driving cars that are all about decision process is, Do I go left? I go right? Is this Bob? Is this Alice? Did the users say and or did they say or write those air all decision process? Is that these tools economy? What does it mean? The Contact Center? It means everything in the context. And if you look at the conduct center. It's all about decision. Process is, you know, where should this call get routed? What's the right agent to handle the call right now? When the agent gets the call, what kind of things should they be saying? What I do with the call after the call is done, How should the agent use their time? All those things are decision processes and their key to the contact center. So so, aye, aye. And Emily going to transform every aspect of it and, most importantly, analyzing what the person is saying connecting with the customer, allowing the age to >> be more. You know, I think this is really one of the most cutting edge areas of the business. And the technology and throw in CEO was talking about an emotional cognitive recognition around. Yeah, connecting with customers and data certainly is going to be a part of that. But as machine learning continues to get it, Sea legs. Yeah, you seeing kind of two schools of thought? I call it the Berklee School. Hard core mathematics. Throw math at it. And then you've got this other side of a machine learning which is much more learning. Yeah, it's less math. More about adaptive and self learning. One's deterministic one's non deterministic is starting to see these use cases where Yeah, there's a deterministic outcome, right throw machine learning at a great exactly helped humans come curate, create knowledge, create value that you've got a new emerging use case of non deterministic, like machine learning environments where I could be driving my test Look down the road or my company's run the Contact Center. I gotto understand what's gonna happen before it happens. Right? Talkabout this. What's your thoughts on this is This isn't really new, pioneering area. What's your view on >> this? Yeah, so I think it actually straight sort of a key point. I wantto narrow enough from what she said, which is that a lot of these problems still, it's about the combination of man and machine, right? It's that there's things that you know are going to be hard for the machine to predict. So the human in their usage of the product, teaches the machine, and the machine, as it observes, helped the human achieved mastery. And that human part, by the way, is even more important in the conduct centre than anywhere else. At the end of the day, your customer and you call up, you're reaching for human connection. You're calling this. You want to talk, you've got a problem. You need someone to not just give you the answers, but empathize with youto understand you. Right? And if you go back to anything about the best experience you've ever had when you called up for support or get a question answered. He was like it was someone who understood you who's friendly, polite, empathetic, funny. And they knew exactly what they were doing, right? And they solve it for you. So the way I think about that, is that actually the future of the context. Dinner is a combination of human and machine, and the human delivers the heart, and the machine delivers the master. >> And I just noticed your I'm looking at Twitter, right? And you just tweeted this forty minutes to go the future of Contact Center. Nice. A combination of human and machine human delivers heart. The machines lose mastery. I think this is so important because unpacking that words like trust come out True relationship. So you asked about my experiences is when I've gotten what I needed, You know, all ledger, the outcome I wanted. Plus I felt good about right. I trusted it. I trusted the truth. It was. And he's seeing that in media today with fake news. You're seeing it with Digital has kind of almost created, anonymous, non trustworthy its data. There's been no real human. Yeah, packaging. So I think you're I'm hearing you You're on the side of humans and machines, not just machines being the silver bullet. >> Absolutely, absolutely. And again, it goes back to sort of the history of the contact centre has been this desire to, like, just make it cheaper, right? But as the world is changing, and as customer experience is more important than ever before and is now, technology is enabling us to allow agents and human beings to be more effective through this. The symbiotic relationship that we're going to form with each other, like we can actually deliver amazing customer experiences. And that's what really matters. And that idea of trust I want to come back to that word that's like super Central to this entire thing. You know, you have that as a user, you have to trust the brand you have to trust the information you're getting from the agent. You have to trust the product that you're calling them talking about, and that's central to everything that we need to do. In fact, it's a It's a fundamental aspect of our entire business. In fact, if you again think about it for a moment here, we're going to customers who are looking to buy a context, and we're saying, Trust us, we're going to put it in the cloud, We're going to run it, We're going to operate it for you and we're going to deliver a great, highly reliable experience that takes trust to sew one of things that back to your early early question. Why did come two, five, nine? One of the things it has done is build this amazing trust with its customers to its huge, amazing reliability. Up time, a great human process of how we go in work with our customers. It's about building trust in every single >> way. So I want to put in the spot because I know you've seen many ways of innovation. You've seen a lot of different times, but now it's more accelerated. Got cloud computing at a much more accelerated innovation cycle. So as users expect interact with certain kind of environment. Roman talked about this in his interview. CEO Control. So you just want to be served on the channels that they want to be served in. So having a system that they have to go to to get support, They wanted where they are. And so how is the future of the customer interaction? Whether it's support our engagement is going to take place in context to nonlinear discovery, progression, meaning or digging a service themselves in the organic digital space. I honestly want to go to a site per se. How do you see the future evolving around this notion of organic discovery? Talking to their friends, finding things out? Does that impact how Five9 sees the future? >> Yeah, absolutely. And I think it gets back to sort of an old idea of Omni channel. I mean, this is something that the context people been talking about for, like forever, like the last ten years, right? And and its original meeting was just this idea. Oh, you know, you can talk to us via chat, or you can send us an e mail or you can send us a text or you could call us right and we'll work with you on any of those, like you said. Actually, what's more interesting is as customers and users moved between those things, and it actually switches from reactive to proactive right where we actually treat those channels as well. Depending on what the situation is, we're going to gather information from all these different data sources, and then we're going toe, find the right way to reach out to you and allow you to reach out to us in the most official. >> So you see a real change in user expectation experience with relative rule contact? >> Yeah, I mean, I mean, the one thing that technology is delivered is a change in user expectations on how things work. And if you look at the way we as human beings communicate with each other, it's dramatically different today than it was really just just a few years ago. >> So, Johnny, let's look under the hood now in terms of the customer environment, because certainly I've seen Legacy after Legacy sisters being deployed. It's almost like cyber security kind of matches the same kind of trend that in your world, which is throw money at something and build it out. So there's a lot of sprawl of solutions out there and trying to solve these problems. How does the customer deal with that? And they're going forward there on this new wave. They want to be modernized, but they got legacy. They had legacy process, legacy, culture. What's the key technical architecture, How you see them deploying this? What's the steps of the patient and her opinion? >> It will surprise you not one drop when I say it's go to the cloud, all right, and there are real reasons for it and by the way, this is going to be going to be talking about this at Enterprise Connect. So, So tune in Enterprise Connect. I'm going to be talking about this. Um, there's a ton of reasons, five huge ones, actually, about why people need to get to the cloud. And one of them is actually one of the ones we've been talking about here, which is a lot of this. Modernization is rooted in artificial intelligence. It turns out you just cannot do artificial intelligence on promise you cannot. So the traditional gear, which used to be installed and operated by legacy vendors like a VIA, you know, they go in, and Genesis, they go in the install a thing and it works just for one customer at a time. The oly way artificial intelligence works is when it gathers data across multiple customers. So multi tendency and artificial intelligence go hand in hand. And so if you want to take any benefit from the stuff that we've been talking about this conversation, the first step is you gotta take your context int the cloud just to begin building and adding your data on the set and then leverage the technologies and they come out >> So data is the central equation And in all this because good data feed's good machine learning good machine learning feeds Great a. I So data is the heart of this, yes. So data making data in the cloud addressable seems to be a key. Thought Your reaction and what are you guys doing with? >> Absolutely, absolutely. And this is, by the way, another reason why I joined five nine, that I've been speculating here. I said, All right, if Date if ya if the future is about a I miss, I said, That's what I want to do in collaboration. You need data to do that. You actually have to work for a company that has a lot of data. So market leadership matters. And if you go look at the contact center and you go look at all the industry and analyst reports like it made it pretty obvious, like who to go to there is like the leader in cloud Conduct. Sonar with with tons of agents and tons of data is Five9 and ah, and so that's That's why you're so building the data aggregating data. That's one of the first things I'm working on here is how do we increase and utilize the data that we've been gathering for years. >> And and a lot of that we've had this conscious with many customs before about Silas Silas. Kill innovation When it comes to data address ability, your thoughts on that and what customs Khun due to start thinking about breaking down those silent >> exactly so In fact, Silas have been a big part of the history of especially on premise systems. Once in fact, Afghan one silo for inbound contacts and are different for outbound. Different departments, by the way, also had their own different comic centers. And then you had other tools that on the other data, if you don't like a separate tool over there for serum and a different tool over there for WFOR debut Fam and something else for Q M. And all these things were like barely integrated together in the cloud that becomes much more natural. Spring these technologies together and the data can begin to flow from the systems in and out of each other. And that means that we have a much greater access to data and correlated data across these different things that allows us to automate all over the place. So it's this positive reinforcement sile cycle that you only get one year when you've gone to the club. >> The question I want to ask you, it's more customers on pretend I'm a customer for second. I won't ask you, Jonathan, what's the core innovation for me to think about and bring to my organization? If I want to go down the modern monitors you. How do you answer that question? What is the core innovation? Stretch it. I should have Marcy moving through the cloud is one beyond that is itjust cloud. Then what else? What, Juanito? Be preaching internally and organizing my culture >> around. Yeah, great questions. So, I mean, I think the cloud is sort of the enabler of many of these different pieces of innovation. Right? So velocity and speed is one of them. And then setting up and adjusting these things used to be super super hard. Ah, you wanted to add agents seats? Oh, my gosh, enough to go binding hardware and racket stack boxes and whatever. So even simple things like reactive nous, right? That's something that's important to talk about is that many of our customers and our businesses are highly seasonal. Right? We've seen like someone showed me a graph. This was like, Oh, my gosh, it was It was a company that was doing ah, telethon. And they said, Here's how many agents they have over this year. It was like two agents, and then it shut up. It's like five hundred agents of phones. Two days exactly. Drop back down. And I'm like, if you think about a business like that, you could never even do that. And so the so cloud is nice, but the way you talk about it, and as an I t buyer of these technologies, you talk your business owners about reacted nous speed, velocity, right? That's what matters to a business and then customer experience. >> You're one of the things that just to kind of end of second, I want to get your thoughts on. I'm gonna bring kind of industry trend. That's I think, might be a way to kind of talk about some of these core problems on data. Most mainstream people look at Facebook and saying, Well, what a debacle. They used my data. These men against me. I'm not in control of my data. You're seeing that weaponization people saying elections were rigged. So weaponizing data for bad is this content, and this context ends right? An infrastructure that's right, >> that's right. >> But there's also the other side, which is, you actually make it for good. So you started thinking about this people starting to realize Wow, I should be thinking about my data and the infrastructure that I have to create a better outcome. That's right, Your thoughts on that as people start to think about II in terms of the business context, right? How did they get to that moment where they can saying, I don't want anyone weaponizing did against me. I want to use it for good. How did the head of the company comes back to >> trust, by the way, right? Is that you know, on and to some degree that's an uphill battle due to some of these debacles that you just talked about. But Contact Center is a different beast of the whole thing. And interestingly, it's an area where there's already been an assumption by users that when they interact with the contact center, that data is sort of used to improve the experience. I mean, every contacts and the first thing I say, by the way, this call may be recorded for training. Um, honoring purses, Captain, that they are right. It's it's already opt in. There's an assumption that that's exactly how that is being used. So it's This is another reason. By the way, what's a contact center is? It was the tip of the spear because it was a place where there was already permission, where the data is exactly the kind of stuff that had already been subject to analysis and Attock customer expectation that that's actually what was happening. The expectation was there they building action, that data what was missing. So now we're filling in the ability to action on that All that data with artificial intelligence >> and final question. What's your vision going forward? A CTO and aye, aye. What's the vision of Five9? What do what do you see? The twenty miles stair for Five9 within consciousness. We just talked about >> it. So? So it's It's about revolution. I'll be honest. Right on. I tell people like, I'm not like an incremental, steady Eddie CTo like I do things because I want to make big changes. And I believe that the context and R is on the cusp of a massive change. And my boss, Rohan said this and this has been actually central to how I'm thinking about this. The Contact Center in the next five years will be totally different than the twenty five years before that. It's a technologist. I say. Wow, five years like that's not very long in terms of softer development. That's what we were going pretty much rewrite our entire stack over the next five years. And show. What should that start to look like? So for me, it's about how do we completely reimagine every single aspect of the context center to revolutionize the experience by merging together, human and machine and totally new >> and the innovation strategies cloud in a cloud and and and data great job and great to have you on pleasure. Great, great conversation. Quick plug for you guys. Going to be a enterprise, connect to Cuba. Lbi. They're covering the event as well. What you going to talk about that? What? Some of the interactions? What will be the hallway conversations? What's your objective? What's your focus >> exactly? So so I'm going to be having my own session. We're going to be talking about the five reasons that you may not think about to goto context on the cloud. I've hinted already. A James of them. I think we're too well. That's you can you know, A. I is clearly central and I'm going to start to talk about the other four. >> Great, great conversation. A lot of change. Massive change happening. Great innovation Stretch. Great mission here at Five9. Great, great mission around. Changing and reimagine. More change the next five years in the past twenty five years. Again cloud computing eyes doing it will be winners. Will be losers will be following it here on the Cube. Jonathan Rosenberg, CTO ahead of AI at Five9. I'm John Furrier with the Cube. Thanks for watching.

Okay, this presentation includes forward looking statements that are subject to risks and uncertainties. Actual results may differ materially as a result of various risk factors including those described in the 10 k's 10 q's and eight ks. Vm ware files with the SEC, ladies and gentlemen, Sunjay Buddha for the jazz mafia from Oakland, California. Good to be with you. Welcome to late night with Jimmy Fallon. I'm an early early morning with Sanjay Poonen and two are set. It's the first time we're doing a live band and jazz and blues is my favorite. You know, I prefer a career in music, playing with Eric Clapton and that abandoned software, but you know, life as a different way. I'll things. I'm delighted to have you all here. Wasn't yesterday's keynote. Just awesome. Off the charts. I mean pat and Ray, you just guys, I thought it was the best ever keynote and I'm not kissing up to the two of you. If you know pat, you can't kiss up to them because if you do, you'll get an action item list at 4:30 in the morning that sten long and you'll be having nails for breakfast with him but bad it was delightful and I was so inspired by your tattoo that I decided to Kinda fell asleep in batter ass tattoo parlor and I thought one wasn't enough so I was gonna one up with. I love Vm ware. Twenty years. Can you see that? What do you guys think? But thank you all of you for being here. It's a delight to have you folks at our conference. Twenty 5,000 of you here, 100,000 watching. Thank you to all of the vm ware employees who helped put this together. Robin Matlock, Linda, Brit, Clara. Can I have you guys stand up and just acknowledge those of you who are involved? Thank you for being involved. Linda. These ladies worked so hard to make this a great show. Everybody on their teams. It's the life to have you all here. I know that we're gonna have a fantastic time. The title of my talk is pioneers of the possible and we're going to go through over the course of the next 90 minutes or so, a conversation with customers, give you a little bit of perspective of why some of these folks are pioneers and then we're going to talk about somebody who's been a pioneer in the world but thought to start off with a story. I love stories and I was born in a family with four boys and my parents I grew up in India were immensely creative and naming that for boys. The eldest was named Sanjay. That's me. The next was named Santosh Sunday, so if you can get the drift here, it's s a n, s a n s a n and the final one. My parents got even more creative and colon suneel sun, so you could imagine my mother going south or Sunday do. I meant Sanjay you and it was always that confusion and then I come to the United States as an immigrant at age 18 and people see my name and most Americans hadn't seen many Sundays before, so they call me Sanjay. I mean, of course it of sounds like v San, so sanjay, so for all of your V, San Lovers. Then I come to California for years later work at apple and my Latino friends see my name and it sorta sounds like San Jose, so I get called sand. Hey, okay. Then I meet some Norwegian friends later on in my life, nordics. The J is a y, so I get called San Year. Your my Italian friend calls me son Joe. So the point of the matter is, whatever you call me, I respond, but there's certain things that are core to my DNA. Those that people know me know that whatever you call me, there's something that's core to me. Maybe I like music more than software. Maybe I want my tombstone to not be with. I was smart or stupid that I had a big heart. It's the same with vm ware. When you think about the engines that fuel us, you can call us the VM company. The virtualization company. Server virtualization. We seek to be now called the digital foundation company. Sometimes our competitors are not so kind to us. They call us the other things. That's okay. There's something that's core to this company that really, really stands out. They're sort of the engines that fuel vm ware, so like a plane with two engines, innovation and customer obsession. Innovation is what allows the engine to go faster, farther and constantly look at ways in which you can actually make the better and better customer obsession allows you to do it in concert with customers and my message to all of you here is that we want to both of those together with you. Imagine if 500,000 customers could see the benefit of vsphere San Nsx all above cloud foundation being your products. We've been very fortunate and blessed to innovate in everything starting with Sova virtualization, starting with software defined storage in 2009. We were a little later to kind of really on the hyperconverged infrastructure, but the first things that we innovate in storage, we're way back in 2009 when we acquired nicer and began the early works in software defined networking in 2012 when we put together desktop virtualization, mobile and identity the first time to form the digital workspace and as you heard in the last few days, the vision of a multi cloud or hybrid cloud in a virtual cloud networking. This is an amazing vision couple that innovation with an obsession and customer obsession and an NPS. Every engineer and sales rep and everybody in between is compensated on NPS. If something is not going well, you can send me an email. I know you can send pat an email. You can send the good emails to me and the bad emails to Scott Dot Beto said Bmr.com. No, I'm kidding. We want all of you to feel like you're plugged into us and we're very fortunate. This is your vote on nps. We've been very blessed to have the highest nps and that is our focus, but innovation done with customers. I shared this chart last year and it's sort of our sesame street simple chart. I tell our sales rep, this is probably the one shot that gets used the most by our sales organization. If you can't describe our story in one shot, you have 100 powerpoints, you probably have no power and very The fact of the matter is that the data center is sort of like a human body. little point. You've got your heart that's Compute, you've got the storage, maybe your lungs, you've got the nervous system that's networking and you've got the brains of management and what we're trying to do is help you make that journey to the cloud. That's the bottom part of the story. We call it the cloud foundation, the top part, and it's all serving apps. The top part of that story is the digital workspace, so very simply put that that's the desktop, moving edge and mobile. The digital workspace meets the cloud foundation. The combination is a digital foundation Where does, and we've begun this revolution with a company. That's what we end. focus on impact, not just make an impression making an impact, and there's three c's that all of us collectively have had an impact on cost very clearly. I'm going to walk you through some of that complexity and carbon and the carbon data was just fascinating to see some of that yesterday, uh, from Pat, these fierce guarded off this revolution when we started this off 20 years ago. These were stories I just picked up some of the period people would send us electricity bills of what it looked like before and after vsphere with a dramatic reduction in cost, uh, off the tune of 80 plus percent people would show us 10, sometimes 20 times a value creation from server consolidation ratios. I think of the story goes right. Intel initially sort of fought vm ware. I didn't want to have it happen. Dell was one of the first investors. Pat Michael, do I have that story? Right? Good. It's always a job fulfilling through agree with my boss and my chairman as opposed to disagree with them. Um, so that's how it got started. And true with over the, this has been an incredible story. This is kind of the revenue that you've helped us with over the 20 years of existence. Last year was about a billion but I pulled up one of the Roi Charts that somebody wrote in 2006. collectively over a year, $50 million, It might've been my esteemed colleague, Greg rug around that showed that every dollar spent on vm ware resulted in nine to $26 worth of economic value. This was in 2006. So I just said, let's say it's about 10 x of economic value, um, to you. And I think over the years it may have been bigger, but let's say conservative. It's then that $50 million has resulted in half a trillion worth of value to you if you were willing to be more generous and 20. It's 1 trillion worth of value over the that was the heart. years. Our second core product, This is one of my favorite products. How can you not like a product that has part of your name and it. We sent incredible. But the Roi here is incredible too. It's mostly coming from cap ex and op ex reduction, but mostly cap x. initially there was a little bit of tension between us and the hardware storage players. Now I think every hardware storage layer begins their presentation on hyperconverged infrastructure as the pathway to the private cloud. Dramatic reduction. We would like this 15,000 customers have we send. We want every one of the 500,000 customers. If you're going to invest in a private cloud to begin your journey with, with a a hyperconverged infrastructure v sound and sometimes we don't always get this right. This store products actually sort of the story of the of the movie seabiscuit where we sort of came from behind and vm ware sometimes does well. We've come from behind and now we're number one in this category. Incredible Roi. NSX, little not so obvious because there's a fair amount spent on hardware and the trucks would. It looks like this mostly, and this is on the lefthand side, a opex mostly driven by a little bit of server virtualization and a network driven architecture. What we're doing is not coming here saying you need to rip out your existing hardware, whether it's Cisco, juniper, Arista, you get more value out of that or more value potentially out of your Palo Alto or load balancing capabilities, but what we're saying is you can extend the life, optimize your underlay and invest more in your overlay and we're going to start doing more and software all the way from the l for the elephant seven stack firewalling application controllers and make that in networking stack, application aware, and we can dramatically help you reduce that. At the core of that is an investment hyperconverged infrastructure. We find often investments like v San could trigger the investments. In nsx we have roi tools that will help you make that even more dramatic, so once you've got compute storage and networking, you put it together. Then with a lot of other components, we're just getting started in this journey with Nsx, one of our top priorities, but you put that now with the brain. Okay, you got the heart, the lungs, the nervous system, and the brain where you do three a's, sort of like those three c's. You've got automation, you've got analytics and monitoring and of course the part that you saw yesterday, ai and all of the incredible capabilities that you have here. When you put that now in a place where you've got the full SDDC stack, you have a variety of deployment options. Number one is deploying it. A traditional hardware driven type of on premise environment. Okay, and here's the cost we we we accumulate over 2,500 pms. All you could deploy this in a private cloud with a software defined data center with the components I've talked about and the additional cost also for cloud bursting Dr because you're usually investing that sometimes your own data centers or you have the choice of now building an redoing some of those apps for public cloud this, but in many cases you're going to have to add on a cost for migration and refactoring those apps. So it is technically a little more expensive when you factor in that cost on any of the hyperscalers. We think the most economically attractive is this hybrid cloud option, like Vm ware cloud and where you have, for example, all of that Dr Capabilities built into it so that in essence folks is the core of that story. And what I've tried to show you over the last few minutes is the economic value can be extremely compelling. We think at least 10 to 20 x in terms of how we can generate value with them. So rather than me speak more than words, I'd like to welcome my first panel. Please join me in welcoming on stage. Are Our guests from brinks from sky and from National Commercial Bank of Jamaica. Gentlemen, join me on stage. Well, gentlemen, we've got a Indian American. We've got a kiwi who now lives in the UK and we've got a Jamaican. Maybe we should talk about cricket, which by the way is a very exciting sport. It lasts only five days, but nonetheless, I want to start with you Rohan. You, um, brings is an incredible story. Everyone knows the armored trucks and security. Have you driven in one of those? Have a great story and the stock price has doubled. You're a cio that brings business and it together. Maybe we can start there. How have you effectively being able to do that in bridging business and it. Thank you Sanjay. So let me start by describing who is the business, right? Who is brinks? Brinks is the number one secure logistics and cash management services company in the world. Our job is to protect our customers, most precious assets, their cash, precious metals, diamonds, jewelry, commodities and so on. You've seen our trucks in your neighborhoods, in your cities, even in countries across the world, right? But the world is going digital and so we have to ratchet up our use of digital technologies and tools in order to continue to serve our customers in a digital world. So we're building a digital network that extends all the way out to the edges and our edges. Our branches are our messengers and their handheld devices, our trucks and even our computer control safes that we place on our customer's premises all the way back to our monitoring centers are processing centers in our data centers so that we can receive events that are taking place in that cash ecosystem around our customers and react and be proactive in our service of them and at the heart of this digital business transformation is the vm ware product suite. We have been able to use the products to successfully architect of hybrid cloud data center in North America. Awesome. I'd like to get to your next, but before I do that, you made a tremendous sacrifice to be here because you just had a two month old baby. How is your sleep getting there? I've been there with twins and we have a nice little gift for you for you here. Why don't you open it and show everybody some side that something. I think your two month old will like once you get to the bottom of all that day. I've. I'm sure something's in there. Oh Geez. That's the better one. Open it up. There's a Vm, wear a little outfit for your two month. Alright guys, this is great. Thank you all. We appreciate your being here and making the sacrifice in the midst of that. But I was amazed listening to you. I mean, we think of Jamaica, it's a vacation spot. It's also an incredible place with athletes and Usain bolt, but when you, the not just the biggest bank in Jamaica, but also one of the innovators and picking areas like containers and so on. How did you build an innovation culture in the bank? Well, I think, uh, to what rughead said the world is going to dissolve and NCB. We have an aspiration to become the Caribbean's first digital bank. And what that meant for us is two things. One is to reinvent or core business processes and to, to ensure that our customers, when they interact with the bank across all channels have a, what we call the Amazon experience and to drive that, what we actually had to do was to work in two moons. Uh, the first movement we call mode one is And no two, which is stunning up a whole set of to keep the lights on, keep the bank running. agile labs to ensure that we could innovate and transform and grow our business. And the heart of that was on the [inaudible] platform. So pks rocks. You guys should try it. We're going to talk about. I'm sure that won't be the last hear from chatting, but uh, that's great. Hey, now I'd like to get a little deeper into the product with all of you folks and just understand how you've engineered that, that transformation. Maybe in sort of the order we covered in my earlier comments in speech. Rohan, you basically began the journey with the private cloud optimization going with, of course vsphere v San and the VX rail environment to optimize your private cloud. And then of course we'll get to the public cloud later. But how did that work out for you and why did you pick v San and how's it gone? So Sunday we started down this journey, the fourth quarter of 2016. And if you remember back then the BMC product was not yet a product, but we still had the vision even back then of bridging from a private data center into a public cloud. So we started with v San because it helped us tackle an important component of our data center stack. Right. And we could get on a common platform, common set of processes and tools so that when we were ready for the full stack, vmc would be there and it was, and then we could extend past that. So. Awesome. And, and I say Dave with a name like Dave Matthews, you must have like all these musicians, like think you're the real date, my out back. What's your favorite Dave Matthew's song or it has to be crashed into me. Right. Good choice rash. But we'll get to music another time. What? NSX was obviously a big transformational capability, February when everyone knows what sky and media and wireless and all of that stuff. Networking is at the core of what you do. Why did you pick Nsx and what have you been able to achieve with it? So I mean, um, yeah, I mean there's, like I say, sky's yeah, maybe your organization. It's incredibly fast moving industry. It's very innovative. We've got a really clever people in, in, in, in house and we need to make sure our product guys and our developers can move at pace and yeah, we've got some great. We've got really good quality metric guys. They're great guys. But the problem is that traditional networking is just fundamentally slow is there's, there's not much you can do about it, you know, and you know to these agile teams here to punch a ticket, get a file, James. Yeah. That's just not reality. We're able to turn that round so that the, the, the devops ops and developers, they can just use terraform and do everything. Yeah, it's, yeah, we rigs for days to seconds and that's in the Aes to seconds with an agile software driven approach and giving them much longer because it would have been hardware driven. Absolutely. And giving the tool set to the do within boundaries. You have scenes with boundaries, developers so they can basically just do, they can do it all themselves. So you empower the developers in a very, very important way. Within a second you had, did you use our insight tools too on top of that? So yes, we're considered slightly different use case. I mean, we're, yeah, we're in the year. You've got general data protection regulations come through and that's, that's, that's a big deal. And uh, and the reality is from what an organization's compliance isn't getting right? So what we've done been able to do is any convenience isn't getting any any less, using vr and ai and Nsx, we're able to essentially micro segment off a lot of Erica our environments which have a lot, much higher compliance rate and you've got in your case, you know, plenty of stores that you're managing with visa and tens of thousands of Vms to annex. This is something at scale that both of you have been able to achieve about NSX and vsn. Pretty incredible. And what I also like with the sky story is it's very centered around Dev ops and the Dev ops use case. Okay, let's come to your Ramon. And obviously I was, when I was talking to the Coobernetti's, uh, you know, our Kubernetes Platform, team pks, and they told me one of the pioneer and customers was National Commercial Bank of Jamaica. I was like, wow, that's awesome. Let's bring you in. And when we heard your story, it's incredible. Why did you pick Coobernetti's as the container platform? You have many choices of what you could have done in terms of companies that are other choices. Why did you pick pks? So I think, well, what happened to, in our interviews cases, we first looked at pcf, which we thought was a very good platform as well. Then we looked at the integration you can get with pqrs, the security, the overland of Nsx, and it made sense for us to go in that direction because you offered 11 team or flexibility on our automation that we could drive through to drive the business. So that was the essence of the argument that we had to make. So the key part with the NSX integration and security and, and the PKS. Uh, and while we've got a few more chairs from the heckler there, I want you to know, Chad, I've got my pks socks on. That's how much I had so much fear. And if he creates too much trouble with security, we can be emotional. I'm out of the arena, you know. Anyway. Um, I wanted to put this chart up because it's very important for all of you, um, and the audience to know that vm ware is making a significant commitment to Coobernetti's. Uh, we feel that this is, as pat talked about it before, something that's going to be integrated into everything we do. It's going to become like a dial tone. Um, and this is just the first of many things you're going to see a vm or really take this now as a consistent thing. And I think we have an opportunity collectively because a lot of people think, oh, you know, containers are a threat to vm ware. We actually think it's a headwind that's going to become a tailwind for us. Just the same way public cloud has been. So thank you for being one of our pioneer and early customers. And Are you using the kubernetes platform in the context of running in a vsphere environment? Yes, we are. We're onto Venice right now. Uh, we have. Our first application will be a mobile banking APP which will be launched in September and all our agile labs are going to be on pbs moving forward medic. So it's really a good move for us. Dave, I know that you've, not yet, I mean you're looking in the context potentially about is your, one of the use cases of Nsx for you containers and how do you view Nsx in that? Absolutely. For us that was the big thing about t when it refresh rocked up is that the um, you know, not just, you know, Sda and on a, on vsphere, but sdn on openstack sdn into their container platform and we've got some early visibility of the, uh, of the career communities integration on there and yeah, it was, it was done right from the start and that's why when we talked to the pks Yeah, it's, guys again, the same sort of thing. it's, it's done right from the start. And so yeah, certainly for us, the, the NSX, everywhere as they come and control plane as a very attractive proposition. Good. Ron, I'd like to talk to you a little bit about how you viewed the public, because you mentioned when we started off this journey, we didn't have Mr. Cloud and aws, we approached to when we were very early on in that journey and you took a bet with us, but it was part of your data center reduction. You're kind of trying to almost to obliterate one data center as you went from three to one. Tell us that story and how the collaboration worked out on we amber cloud. What's the use case? So as I said, our vision was always to bridge to a So we wanted to be able to use public cloud environments to incubate new public cloud, right? applications until they stabilize to flex to the cloud. And ultimately disaster recovery in the cloud. That was the big use case for us. We ran a traditional data center environment where, you know, we run across four regions in the world. Each region had two to three data centers. One was the primary and then usually you had a disaster recovery center where you had all your data hosted, you had certain amount of compute, but it was essentially a cold center, right? It, it sat idle, you did your test once a year. That's the environment we were really looking to get out of. Once vmc was available, we were able to create the same vm ware environment that we currently have on prem in the cloud, right? The same network and security stack in both places and we were actually able to then decommission our disaster recovery data center, took it off, it's took it off and we move. We've got our, our, all of our mission critical data now in the, uh, in the, uh, aws instance using BMC. We have a small amount of compute to keep it warm, but thanks to the vm ware products, we have the ability now to ratchet that up very quickly in a Dr situation, run production in the cloud until we stabilized and then bring that workload back. Would it be fair to tell everybody here, if you are looking at a Dr or that type of bursting scenario, there's no reason to invest in a on premise private cloud. That's really a perfect use case of We, I know certainly we had breaks. this, right? Sorry. Exactly. Yeah. We will no longer have a, uh, a physical Dr a center available anywhere. So you've optimized your one data center with the private cloud stack will be in cloud foundation effectively starting off a decent and you've optimized your hybrid cloud journey, uh, with we cloud. I know we're early on in the journey with Nsx and branch, so we'll come back to that conversation may next year we discover new things about this guy I just found out last night that he grew up in the same town as me in Bangalore and went to the same school. So we will keep a diary of the schools at rival schools, but the last few years with the same school, uh, Dave, as you think about the future of where you want to this use case of network security, what are some of the things that are on your radar over the course of the next couple of months and quarters? So I think what we're really trying to do is, um, you know, computers, this is a critical thing decided technology conference, computers and networks are a bit boring, but rather we want to make them boring. We want to basically sweep them away from so that our people, our customers, our internal customers don't have to think about it were the end that we can make him, that, that compliance, that security, that whole, that whole framework around it. Um, regardless of where that work, right live as living on premise, off premise, everywhere you know. And, and even Aisha potentially out out to the edge. How big were your teams? Very quickly, as we wrap up this, how big are the teams that you have working on network is what was amazing. I talked to you was how nimble and agile you're with lean teams. How big was your team? The, the team during the, uh, the SDDC stack is six people. Six, six. Eight. Wow. There's obviously more that more. And we're working on that core data center and your boat to sleep between five and seven people. For it to brad to both for the infrastructure and containers. Yes. Rolling on your side. It's about the same. Amazing. Well, very quickly maybe 30 seconds. Where do you see the world going? Rolling. So, you know, it brings, I pay attention to two things. One is Iot and we've talked a little bit about that, but what I'm looking for there as digital signals continue to grow is injecting things like machine learning and artificial intelligence in line into that flow back so we can make more decisions closer to the source. Right. And the second thing is about cash. So even though cash volume is increasing, I mean here we are in Vegas, the number one cash city in the US. I can't ignore the digital payments and crypto currency and that relies on blockchain. So focusing on what role does blockchain play in the global world as we go forward and how can brings, continue to bring those services, blockchain and Iot. Very rare book. Well gentlemen, thank you for being with us. It's a pleasure and an honor. Ladies and gentlemen, give it up for three guests. Well, um, thank you very much. So as you saw there, it's great to be able to see and learn from some of these pioneering customers and the hopefully the lesson you took away was wherever your journey is, you could start potentially with the private cloud, embark on the journey to the public cloud and then now comes the next part which is pretty exciting, which is the journey off the desktop and removal what digital workspace. And that's the second part of this that I want to explore with a couple of customers, but before I do that, I wanted to set the context of why. What we're trying to do here also has economic value. Hopefully you saw in the first set of charts the economic value of starting with the heart, the lungs, any of that software defined data center and moving to the ultimate hybrid cloud had economic value. We feel the same thing here and it's because of fundamental shift that started off in the last seven, 10 years since iphone. The fact of the matter is when you look at your fleet of your devices across tablets, phones and laptops today is a heterogeneous world. Twenty years ago when the company started, it was probably all Microsoft devices, laptops now phones, tablets. It's a mixture and it was going to be a mixture for the rest of them. I think for the foreseeable time, with very strong, almost trillion market cap companies and in this world, our job is to ensure that heterogeneous digital workspace can be very easily managed and secured. I have a little soft corner for this business because the first three years of my five years here, I ran this business, so I know a thing about these products, but the fact of the matter is that I think the opportunity here is if you think about the 7 billion people in the world, a billion of them are working for some company or the other. The others are children or may not be employed or retired and every one of them have a phone today. Many of them phones and laptops and they're mixed and our job is to ensure that we bring simplicity to this place. You saw a little bit that cacophony yesterday and Pat's chart, and unfortunately a lot of today's world of managing and securing that disparate is a mountain of morass. Okay? No offense to any of the vendors named in there, but it shouldn't be your job to be that light piece of labor at the top of the mountain to put it all together, which costs you potentially at least $50 per user per month. We can make the significantly cheaper with a unified platform, workspace one that has all of those elements, so how have we done that? We've taken those fundamental principles at 70 percent, at least reduction of simplicity and security. A lot of the enterprise companies get security, right, but we don't get simplicity all always right. Many of the consumer companies like right? But maybe it needs some help and facebook, it's simplicity, security and we've taken both of those and said it is possible for you to actually like your user experience as opposed to having to really dread your user experience in being able to get access to applications and how we did this at vm ware, was he. We actually teamed with the Stanford Design School. We put many of our product managers through this concept of design thinking. It's a really, really useful concept. I'd encourage every one of you. I'm not making a plug for the Stanford design school at all, but some very basic principles of viability, desirability, feasibility that allow your product folks to think like a consumer, and that's the key goal in undoing that. We were able to design of these products with the type of simplicity but not compromise at all. Insecurity, tremendous opportunity ahead of us and it gives me great pleasure to bring onstage now to guests that are doing some pioneering work, one from a partner and run from a customer. Please join me in welcoming Maria par day from dxc and John Market from adobe. Thank you, Maria. Thank you Maria and John for being with us. Maria, I want to start with you. A DXC is the coming together of two companies and CSC and HP services and on the surface on the surface of it, I think it was $50,000, 100,000. If it was exact numbers, most skeptics may have said such a big acquisition is probably going to fail, but you're looking now at the end of that sort of post merger and most people would say it's been a success. What's made the dxc coming together of those two very different cultures of success? Well, first of all, you have to credit a lot of very creative people in the space. One of the two companies came together, but mostly it is our customers who are making us successful. We are choosing to take our customers the next generation digital platform. The message is resonating, the cultures have come together, the individuals have come together, the offers have come together and it's resonating in the marketplace, in the market and with our customers and with our partners. So you shouldn't have doubted it. I, I wasn't one of the skeptics, maybe others were. And my understanding is the d and the C Yes. If, and dxc is the digital and customer. if you look at the logo, it's, it's more of an infinity, so digital transformation for customers. But truthfully it's um, we wanted to have a new start to some very powerful companies in the industry and it really was a instead of CSC and HP, a new logo and a new start. And I think, you know, if this resonates very well with what I started off my keynote, which is talking about innovation and customers focused on digital and Adobe, obviously not just a household name, customers, John, many of folks who use your products, but also you folks have written the playbook on a transformation of on premise going cloud, right? A SAS products and now we've got an incredible valuations relative. How has that affected the way you think in it in terms of a cloud first type of philosophy? Uh, too much of how you implement, right? From an IT perspective, we're really focused on the employee experience. And so as we transitioned our products to the cloud, that's where we're working towards as well from an it, it's all about innovation and fostering that ability for employees to create and do some amazing products. So many of those things I talked about like design thinking, uh, right down the playbook, what adobe does every day and does it affect the way in which you build, sorry, deploy products 92. Yeah, I mean fundamentally it comes down to those basics viability and the employee experience. And we've believe that by giving employees choice, we're enabling them to do amazing work. Rhonda, Maria, you obviously you were in the process of rolling out some our technology inside dxc. So I want to focus less on the internal implementation as much as what you see from other clients I shared sort of that mountain of harassed so much different disparate tools. Is that what you hear from clients and how are you messaging to them, what you think the future of the digital workspaces. And I joined partnership. Well Sanjay, your picture was perfect because if you look at the way end user compute infrastructure had worked for years, decades in the past, exactly what we're doing with vm ware in terms of automation and driving that infrastructure to the cloud in many ways. Um, companies like yours and mine having the courage to say the old way of on prem is the way we made our license fees, the way move made our professional services in the past. And now we have to quickly take our customers to a new way of working, a fast paced digital cloud transformation. We see it in every customer that we're dealing with everyday of the week What are some of the keyboard? Every vertical. I mean we're, we're seeing a lot in the healthcare and in a variety of verticals. industry. I'm one of the compelling things that we're seeing in the marketplace right now is the next gen worker in terms of the GIG economy. I'm employees might work for one company at 10:00 in the morning and another company at We have to be able to stand those employees are 10 99 employees up very 2:00 in the afternoon. quickly, contract workers from around the world and do it securely with governance, risk and compliance quickly. Uh, and we see that driving a lot of the next generation infrastructure needs. So the users are going from a company like dxc with 160,000 employees to what we think in the future will be another 200, 300,000 of 'em, uh, partners and contract workers that we still have to treat with the same security sensitivity and governance of our w two employees. Awesome. John, you were one of the pioneer and customers that we worked with on this notion of unified endpoint management because you were sort of a similar employee base to Vm ware, 20,000 odd employees, 1000 plus a and you've got a mixture of devices in your fleet. Maybe you can give us a little bit of a sense. What percentage do you have a windows and Mac? So depending on the geography is we're approximately 50 percent windows 50 slash 50 windows and somewhat similar to how vm ware operates. What is your fleet of mobile phones look like in terms of primarily ios? We have maybe 80 slash 20 or 70 slash 20 a apple and Ios? Yes. Tablets override kinds. It's primarily ios tablets. So you probably have something in the order of, I'm guessing adding that up. Forty or 50,000 devices, some total of laptops, tablets, phones. Absolutely split 60 slash 60,000. Sixty thousand plus. Okay. And a mixture of those. So heterogeneities that gear. Um, and you had point tools for many of those in terms of managing secure in that. Why did you decide to go with workspace one to simplify that, that management security experience? Well, you nailed it. It's all about simplification and so we wanted to take our tools and provide a consistent experience from an it perspective, how we manage those endpoints, but also for our employee population for them to be able to have a consistent experience across all of their devices. In the past it was very disconnected. It was if you had an ios device, the experience might look like this if you had a window is it would look like go down about a year ago is to bring that together again, this. And so our journey that we've started to simplicity. We want to get to a place where an employee can self provision their desktop just like they do their mobile device today. And what would, what's your expectations that you go down that journey of how quickly the onboarding time should, should be for an employee? It should be within 15, 20 minutes. We need to, we need to get it very rapid. The new hire orientation process needs to really be modified. It's no longer acceptable from everything from the it side ever to just the other recruiting aspects. An employee wants to come and start immediately. They want to be productive, they want to make contributions, and so what we want to do from an it perspective is get it out of the way and enable employees to be productive as And the onboarding then could be one way you latch him on and they get workspace quickly as possible. one. Absolutely. Great. Um, let's talk a little bit as we wrap up in the next few minutes, or where do you see the world going in terms of other areas that are synergistic, that workspace one collaboration. Um, you know, what are some of the things that you hear from clients? What's the future of collaboration? We're actually looking towards a future where we're less dependent on email. So say yes to that real real time collaboration. DXC is doing a lot with skype for business, a yammer. I'll still a lot with citrix, um, our tech teams and our development teams use slack and our clients are using everything, so as an integrator to this space, we see less dependent on the asynchronous world and a lot more dependence on the synchronous world and whatever tools that you can have to create real time. Um, collaboration. Now you and I spoke a little last night talking about what does that mean to life work balance when there's always a demanding realtime collaboration, but we're seeing an uptick in that and hopefully over the next few years a slight downtick in, in emails because that is not necessarily the most direct way to communicate all the time. And, and in that process, some of that sort of legacy environment starts to get replaced with newer tools, whether it's slack or zoom or we're in a similar experience. All of the above. All of the above. Are you finding the same thing, John Environment? Yeah, we're moving away. There's, I think what you're going to see transition is email becomes more of the reporting aspect, the notification, but the day to day collaboration is me to products like slack are teams at Adobe. We're very video focused and so even though we may be a very global team around the world, we will typically communicate over some form of video, whether it be blue jeans or Jabber or Blue Jeans for your collaboration. Yeah. whatnot. We've internally, we use Webex and, and um, um, and, and zoom in and also a lot of slack and we're happy to announce, I think at the work breakouts, we'll hear about the integration of workspace one with slack. We're doing a lot with them where I want to end with a final question with you. Obviously you're very passionate about a cause that we also love and I'm passionate about and we're gonna hear more about from Malala, which is more women in technology, diversity and inclusion and you know, especially there's a step and you are obviously a role model in doing that. What would you say to some of the women here and others who might be mentors to women in technology of how they can shape that career? Um, I think probably the women here are already rocking it and doing what you need to do. So mentoring has been a huge part of my career in terms of people mentoring me and if not for the support and I'm real acceptance of the differences that I brought to the workplace. I wouldn't, I wouldn't be sitting here today. So I think I might have more advice for the men than the women in the room. You're all, you have daughters, you have sisters, you have mothers and you have women that you work every day. Um, whether you know it or not, there is an unconscious bias out there. So when you hear things from your sons or from your daughters, she's loud. She's a little odd. She's unique. How about saying how wonderful is that? Let's celebrate that and it's from the little go to the top. So that would be, that would be my advice. I fully endorse that. I fully endorse that all of us men need to hear that we have put everyone at Vm ware through unconscious bias that it's not enough. We've got to keep doing it because it's something that we've got to see. I want my daughter to be in a place where the tech world looks like society, which is not 25, 30 percent. Well no more like 50 percent. Thank you for being a role model and thank you for both of you for being here at our conference. It's my pleasure. Thank you Thank you very much. Maria. Maria and John. So you heard you heard some of that and so that remember some of these things that I shared with you. I've got a couple of shirts here with these wonderful little chart in here and I'm not gonna. Throw it to the vm ware crowd. Raise your hand if you're a customer. Okay, good. Let's see how good my arm is. There we go. There's a couple more here and hopefully this will give you a sense of what we are trying to get done in the hybrid cloud. Let's see. That goes there and make sure it doesn't hit anybody. Anybody here in the middle? Right? There we go. Boom. I got two more. Anybody here? I decided not to bring an air gun in. That one felt flat. Sorry. All. There we go. One more. Thank you. Thank you. Thank you very much, but this is what we're trying to get that diagram once again is the cloud foundation. Folks. The bottom part, done. Very simply. Okay. I'd love a world one day where the only The top part of the diagram is the digital workspace. thing you heard from Ben, where's the cloud foundation? The digital workspace makes them cloud foundation equals a digital foundation company. That's what we're trying to get done. This ties absolutely a synchronously what you heard from pat because everything starts with that. Any APP, a kind of perspective of things and then below it are these four types of clouds, the hybrid cloud, the Telco Cloud, the cloud and the public cloud, and of course on top of it is device. I hope that this not just inspired you in terms of picking up a few, the nuggets from our pioneers. The possible, but every one of the 25,000 view possible, the 100,000 of you who are watching this will take people will meet at all the vm world and before forums. the show on the road and there'll be probably 100,000 We want every one of you to be a pioneer. It is absolutely possible for that to happen because that pioneering a capability starts with every one of you. Can we give a hand once again for the five customers that were onstage with us? That's great.

>> Narrator: Live from Las Vegas, it's the Cube. Covering Informatica World 2018. Brought to you by Informatica. >> Hey, welcome back everyone. We're here live, it's the Cube. Exclusive coverage of Informatica World 2018. It's our fourth year, exclusive coverage. I'm John Furrier, your co-host of the Cube, with Peter Burris, my co-host and chief analyst at Wikibon, and SiliconANGLE, and the Cube. Our next guest is the CEO of Informatica, chief executive Anil Chakravarthy, who's back again for his fifth Cube appearance. We went back all the way to 2014 at AWS Reinvent when cloud was on the horizon. Now you running a really high growth company. Congratulations. It's great to see you. >> Thank you. It's great to see you. Great to be back on the Cube again. I appreciate it. >> One of the things I want to point out, you know, we're independent, we want to point all the things that you guys should be working on, but I got to say, you guys have done an amazing job. Executing on the product front in a market that's growing and changing erratically with data, and not a lot of people got that. Amazon was early on we saw them executing. They were misunderstood. You guys are not misunderstood anymore. >> Yep, I appreciate that. >> Data is at the center. Congratulations. >> Thank you. I think one of the things that we've learned over the last 25 years, 25 years old this year, and you got that in the sign behind you, is there is a few things we are really good at. Data management is what we are really good at. Now, it just so happens data is everywhere in all kinds of platforms, and we want to make sure that wherever our customers are we are there as well to help them in data management. >> So, let's talk about what's going on. So first of all, a lot of interesting things here going on. One last year, we talked about, data lakes, data swamps. This year it's about the enterprise catalog and all the goodness, MDM, and the things you guys have done, kind of check check. The catalog brings in the notion of the full visibility. And then you got the multi-cloud hybrid-cloud adoption and the announcement of Azure. This is bringing in a new era. You called it data 3.0 up on stage. What is data 3.0? Can you take a minute to describe the vision and what does it mean for your customers. >> Yeah, data 3.0 is the name we are using to talk about the generational market disruption that's going on right now. If you think of what's changing in the data world, there are multiple trends happening at the same time. Volume of data doubling every year. You have a lot of new types. >> Six months. >> Well, for us too, the cloud is six months, but across the industry it's about a year every year. Still faster than computing in fact. Faster than Moore's law. Then, you have the variety of data, all kinds of data. You have the velocity of data, all the speed at which data needs to get processed. All the new techniques of processing data, like AI and advanced analytics and so on. And if any single one of these was happening that would be a big trend in itself. Everything happening at the same time, that's the generational market disruption and that's what we call, I said look, it would be easier if we gave it a name, and that's what we call data 3.0. >> So, you know, you just made a really great point. And I want to highlight it and suggest, again, looking at the board, where are the next generation of innovations going to come from? It used to be that we relied Moore's Law, double performance every 18 months, and in so doing we could put more software into it. But what you just described is doubling the amount of data every year, faster than Moore's Law. Means that it's inevitable. We have to move more of the innovation up into software, especially software that manages data. >> Absolutely, right. I think there's, just like you had said, the rate of growth of data being so much faster than even the rate of processing power growth means a couple of things happen. First of all, you're going to move more data into the cloud because in the cloud you can expand horizontally must faster, so than you can ever do in your own on-premise. So that's going to happen. The second big thing that's going to happen is as data gets into the cloud and people are using all these different types of new data processing techniques to your point about the catalog, if you don't have a fundamental catalog that tells you where your data is, who's using it, what it is for etc., you just lose control. You just cannot keep in control of your data. And so what people are realizing is as they do new business initiatives they got to have the data catalog. They got to put in place the data catalog and then let the catalog expand. >> A horizontally scalable cloud. That's a really significant point. And this has been a customer challenge, right? So, we're now in the obvious mode of the cloud is there. Azure, you mentioned Microsoft is growing significant. The shift has been made, everyone kind of gets cloud. But the cloud scale is still the pressure. Now you got data coming in, into the cloud scale, and you got things like GDPR, which is a shot across the bow saying okay, now you got to start thinking about compliance and management, and growth. Kind of a lot of things being juggled there. How do you see that unfolding, because it's challenging for customers? I mean there's a lot of things going. A lot of moving parts. >> The way I think about it is, think of this way. Customers have been working with databases for a long time. Over 50 years right now. And the first generation of databases, customers used to say, "Look, I just need a database "that runs all the time. "I can't have a database that crashes "every two hours or so." It just needs reliability as the first thing in a database. The next thing people started thinking about, once reliability was a solved problem, was they said, "I need scale and performance. "The number of records are increasing, etc." Once these became design principles databases started to become more and more robust. The only way to solve the kinds of problems that you mentioned today is every new database that you think of, whether it's for structured data, unstructured data, any kind of data. And you think of a database, think not only of reliability, performance, scale, also think of connectivity, governance, security, privacy. All these need to become design principles for whoever is thinking about the database, and that's what we mean by the catalog. It's the catalog helps you put the discipline in place. When you start a new database, register it in the catalog. That way you know what you are doing with the database. When you set up a copy of a database, put in the catalog. That's what we mean by the discipline. That way you can track. Tomorrow if you say, look I want to know where my European customer data is, just go to the catalog and it will tell you. >> So, I want to build on that. Actually, many years ago when I was first screwing around with databases, one of the things that was explained to me was bring in a database the application developer no longer has to know as much about the underlying infrastructure. >> That's correct. >> Because the data base administrator will take responsibility for how the data got spread on disc and access paths and all that other stuff so the developer could focus on the development. Now when we think about the cloud and all these other technologies and raising things up the catalog allows developers to increasingly focus on how they're going to use data. As opposed to the process that they are going to build. So we were talking about his earlier with a couple of different guests. Microsoft and when Rohan was here. >> Right. >> And the idea that ultimately we're talking about a data-first approach to thinking about how we create application value. >> That's exactly right. And to your point, I think the principles have not changed. What has changed is the way that you apply those principles. Which is you take a data-first approach, but then that's what the APIs let you do. The APIs expose the data to different applications and users. They don't need to know how the processing is happening. So today the data might be processed through Spark. Tomorrow you might say I got a new engine that processes it. They don't need to know it at the application level. At the application level, it's exposed through APIs, and the get to use the APIs. >> So, if you think about, from our perspectives, sorry John, when you think about it from our perspectives, we've always believed that digital business means something, and the difference between business and digital business is digital businesses use data as an asset. And a digital business transformation is the degree to which you are transforming, re-institutionalizing your work, reorganizing around data as an asset. >> That's right. >> So very, very important concept. Challenging for a lot of CEOs. >> Yeah, exactly. >> So look. Informatica's a software business, which means in many respects it has a whole bunch of data assets associated with it, but you're engagement model hasn't always been data, your service model hasn't always been data-oriented. As a CEO, is Informatica more of a digital business today, >> Absolutely. >> And if it is, how would you advise other CEOs to think about this kind of a transformation? >> Yeah, let me just give you the kind of the intelligent disruption we've gone through, because we were a software business, we're a cloud business today. And that's the transformation of the digital business-- >> Peter: Product to a services-oriented approach. >> And even in the product, our business model used to be that we basically said look our goal is to try to sell software upfront, go work with customers, make the business case for software, and sell the software upfront. Today we're selling a service which means we not only want to self the software, we want to know how customers are using the software, are they successful with the software, is it doing what they expected, and that is the most notion of land, adapt, expand, and then renew. And that's a much better approach, because it works for the customer, it works for us. There's less shelf ware in this process. So a lot of people, everybody's happy with that. But in order to make that happen, we got to collect a lot of data on whether customers are being successful. >> The business model and the product model's got to be aligned completely and that's really what you guys have done. And is that where people are making mistakes, in your mind, when you see people going to the cloud? That they kind of do it with the cloud, then forget to change their... >> And that corporate, that's exactly right. When you think of this digital transformation or digital business you got to do three things all in sync. The new customer engagement models like ours change from upfront to ongoing. And then there's new products and services, which is all the stuff that we have done around the cloud portfolio. And then there's new operating models, new processes, customer success is a new process that we did not have four years ago. Which is we proactively reach out to customers to find out what they're doing with our software, are they successful with it, et cetera. We used to wait for them to call us. Now we do it proactively. >> But isn't that also one of the businesses of taking a product to services approach, is because you're now establish a relationship with a customer that says, it's not just proactively, you're exchanging data on a continuous basis. In the form of updates on the one hand, but also utilization information et cetera, build a better product, better engagement. >> Exactly. In fact, you'll see one of the packed events here has been what we call the the Ops Insight, or Operational Insight, that's the product we built to do exactly what you said. Get the telemetry data, help customers use our products better. And that's the transformation from a product to a service. >> And we had Toyota on earlier, and they were very complimentary. But the big ah-ha for them was we had this crisis, we weren't connected, but we actually had the data. They just didn't connect at all. So they kind of had it, the answer, couldn't get it. >> And then we're using data excellently in each of the different functions. >> Then we did the transformation, and then they realized, had they gone down a different route, they wouldn't have been prepared for the tsunami of telemetry data coming from the cars. >> That's exactly it. >> So now, again, this is not going away. This is going to to be the pattern. There's going to be a new set of inbound data coming in. How should customers prepare for that? Is there an ingestion mechanism? Is that where you guys do the cataloging? This is kind of the important, headroom question. Where's the... >> There's different points depending on the style of the organization. I often ask questions, what is the nature of the culture of your organization? Do you guys work top-down better, bottom-up better, how do you work? So somebody who says looking at it, we actually work bottom-up really well, right? Top-down dictates don't work really well. Then I say to them, why don't you start and profile the top hundred data elements that really matter for your business. So if they're an insurance company, a policy number. That's one of the top hundred data elements. A claim number, that's one of the top hundred data elements. Just identify the top hundred data elements, and then just tell yourself that you have a consistent business definition for that data element, you have a consistent technical definition, you know where the data resides, et cetera et cetera. Just start bottom-up. For some companies that works really well. Other companies are more like, no no no. We work more better top-down. Then you start with what is your strategy as a business? How are you going to transform yourself, who is your competitive threats, and so on. And then you go through what are you doing in terms of transformation, new operating models, new customer engagement, et cetera? And then translate that into a data strategy, and that becomes a data architecture. So I think it depends on the style of the organization. Some of them are trying both and meeting in the middle, but what I tell customers is based on your culture, based on your style, there's different models that work. >> Great relationship with Microsoft announced here. Scott Guthrie's on stage. How's that relationship going? I know it just didn't start yesterday, because there's deep production integration, shipping, it's not GA but it's previewed shipping soon. Couple weeks coming, or months. By September, I think that estimate is. Ballpark. Where'd this come from, how you guys doing, can you just give some color to the Informatica, Microsoft, Azure relationship? >> Absolutely. The relationship with Microsoft itself has been going on for a very long time. We have over 2,000 common customers with Microsoft, so it's something that especially on-premise, has been something that we have been working with SQL server and other Microsoft products for a very long time. The relationship specifically with Scott and with the Azure team started in 2014. So we went up there to Seattle just to learn about what they were doing with the cloud and so on. We were actually pretty impressed. We said, look, this is clearly the new Microsoft. This is the Microsoft that wants to work with partners, that wants to be a true enterprise player, and we said, you know what, this is the kind of partner that we want to bet on. So we made a few proactive investments initially. We, at that point, which was not clear that Azure would take off like it did. But just like you mentioned with Reinvent, we said these guys are really clearly betting on it. So 2014 was when we started making the bets on Azure, SQL data wheelhouse, et cetera. And that was when it started growing. And in the last, we have obviously seen the hockey stick now. We have 200 or so enterprises. >> Yeah, completely top-down, said we're doing that in cloud. Everyone's in line, it's beautiful. The growth has been there, the stock was the... I remember when it was trading at 26. I think it might have been about that time. >> Well you look at it now, exactly. >> So you're really confident that this is going to be a positive impact for customers? >> A very positive impact. Because with them, you see both the on-premise, we have clear synergy and partnerships with them, and in Azure as well, we have the clear partnership and value proposition with them. >> And let's be honest. There are not a lot of times when betting against Microsoft turned out to be the right thing to do. Maybe with phones, but that's about it. >> There's some things there, but anyway. I want to get to the company question. You're the chief executive officer, you're leading now a growing team, growing company. Talk about the culture, because you guys have always had a culture of innovation. Although private equity took you over, there was a story there, but I really want to get at the key points in the company, and talk about the R&D. Because you talked about bets. You bet on Amazon. We were there in 2014 with you. We say you there, and we saw Azure. You guys sniffing out the good tech. You guys are smart. But you got to put the rubber to the road for investment. Where's your priorities? Talk about the R&D. >> Yeah. Just to set the context, when we went private, we went private with the clear understanding that we would transform the company. We saw the potential for the company but we also knew that changing from a software company to the cloud company that we just talked about, that was not easy to do as a public company. Obviously there's a lot of investment required, plus there's some unpredictability. >> Earnings, and... >> We said look, we went private with the explicit aim of transforming the company. And the investors, our sponsors, had the same goal as well. You know, sometimes there's a misperception that all PE is about cost cutting. >> But most are. >> Exactly, and that's just not true. It's like you have to look at every PE form and every PE deal, and a number of PE deals that are growth-oriented. Because they know that, hey, with the investments we're making, ultimately if you can get a company to grow, the valuation is way better than you can ever get through just cost cutting. They saw that potential in Informatica. We worked closely with them to define the plan that we've been executing on since 2015. By the way, Microsoft and Salesforce.com came in as strategic investors, so when we went private that was a good endorsement for us. And so we've been executing on that front. And so we've never stopped investing in R&D. As a public company we invested about 15%, 16% on R&D. This year we're actually investing 17% on R&D, so we've really done what it takes to be continually best of breed and integrated, that's-- >> And I'll count cloud subscription models there, what are some other priorities can you share? Some of the priorities for you guys in terms of key areas you're getting out front on being proactive. >> Yeah, so biggest priorities for the company are continue to be a clear best of breed product line in everything we do That we believe that we should never ask any of our customers to sacrifice anything when they buy Informatica. It is best of breed. Second clear priority for the company, make sure that we have an integrated product suite. That's not easy to do, when you're both best of breed and integrated. But that's why we invest as much as we do in R&D. The third clear priority for the company is the transformation journey that we're on. All the key parts of the transformation, product portfolio, go to market, business model, customer success, brand. They all have to work in concert. That's where I mentioned the values and the culture of the company. We've really have always been a customer-focused company. But we said look, what really will take us for the next 25 years is what we call the values that are real data. >> I really appreciate your time, I know you're super busy. I have one final question, cause it's pretty obvious. We were kind of speculating on our intros, at our editorial overview is your ecosystem is, I won't say massive 'cause you're growing, but we predict it's going to be pretty big. Given if this continues, the trend continues, it's going to be a matter of time before you start rolling in developers and all kinds of new partners, just global system integrators, on and on and on. What's the strategy for the ecosystem, do you guys have clear visibility on how that's going to play out? Where is global partners or customers? How are people engaging with you guys in the ecosystem? >> We already have over 500 partners, and that's where this focus on being an API-driven, micro-services driven architecture really helps us. That way when you scale new partners, you don't have to do custom work for each partner. And that really helps us scale much faster. In the past we have a 100+ OEMs, and each OEM is to take a little more work because it was all custom interfaces. Now in this new API, micro-services driven world, we can scale to the kind of volume that you're talking about, and I'm pretty confident with-- >> In many respects that is the definition of horizontal scaling. >> Exactly. >> Horizontal scaling, it's the magic of the cloud. Certainly opening up and changing the game. Certainly changing the infrastructure with cloud-native. You're starting to see a shift to a new infrastructure on the internet is all happening with data, cloud, and who knows. Maybe blockchain and crypto will be in the conversation soon. How do you do the MDM on that? That's a hard one, we'll get to that later. Anil, thank you for coming on the Cube. Really appreciate it. Great to see you. >> Thank you for having me, I really appreciate it. >> Alright, John Furrier, Peter Burris here, the CEO of Informatica at Informatica World 2018. We'll be back. Stay with us for more coverage after this short break.

>> They are disruptive technologies. And if you think about the disruption that's happening in business, with IoT, with OT, and with big data, you can't get anything more disruptive to the whole of the business chain as this particular area. It's an area that I focused on myself, asking the question, should everything go to the cloud? Is that the new future? Is 90% of the computing going to go to the cloud with just little mobile devices right on the edge? Felt wrong when I did the math on it, I did some examples of real-world environments, wind farms, et cetera, it clearly was not the right answer, things need to be near the edge. And I think one of the areas to me that solidified it was when you looked at an area like video. Huge amounts of data, real important decisions being made on the content of that video, for example, recognizing a face, a white hat or a black hat. If you look at the technology, sending that data somewhere to do that recognition just does not make sense. Where is it going? It's going actually into the camera itself, right next to the data, because that's where you have the raw data, that's where you have the maximum granularity of data, that's where you need to do the processing of which faces are which, right close to the edge itself, and then you can send the other data back up to the cloud, for example, to improve those algorithms within that camera, to do all that sort of work on the batch basis over time, that's what I was looking at, and looking at the cost justification for doing that sort of work. So today, we've got a set people here on the panel, and we want to talk about coming down one level to where IoT and IT are going to have to connect together. So on the panel I've got, I'm going to get these names really wrong, Sanjeev Kumar? >> Yes, that's right. >> From FogHorn, could you introduce yourself and what you're doing where the data is meeting the people and the machines? >> Sure, sure, so my name is Sanjeev Kumar, I actually run engineering for a company called FogHorn Systems, we are actually bringing analytics and machine learning to the edge, and, so our goal and motto is to take computing to where the data is, than the other way around. So it's a two-year-old company that started, was incubated in the hive, and we are in the process of getting our second release of the product out shortly. >> Excellent, so let me start at the other end, Rohan, can you talk about your company and what contribution you're focusing on? >> Sure, I'm head product marketing for Maana, Maana is a startup, about three years old, what we're doing is we're offering an enterprise platform for large enterprises, we're helping the likes of Shell and Maersk and Chevron digitally transform, and that simply means putting the focus on subject matter experts, putting the focus on the people, and data's definitely an important part of it, but allowing them to bring their expertise into the decision flows, so that ultimately the key decisions that are driving the revenue for these behemoths, are made at a higher quality and faster. >> Excellent. Well, two software companies, we have a practitioner here who is actually doing fog computing, doing it for real, has been doing it for some time, so could you like, Janet George from Western Digital, can you introduce yourself, and say something from the trenches, of what's really going on? >> Okay, very good, thank you. I actually build infrastructure for the edge to deal with fog computing, and so for Western Digital, we're very lucky, because we are the largest storage manufacture, and we have what we call Internet of Things, and Internet of Test Equipment, and I process petabytes of data that comes out of the Internet of Things, which is basically our factories, and then I take these petabytes of data, I process them both on the cloud and then on the edge, but primarily, to be able to consume that data. And the way we consume that data is by building very high-profile models through artificial intelligence and machine learning, and I'll talk a lot more about that, but at the end of the day, it's all about consuming the data that you collect from anywhere, Internet of Things, computer equipment, data that's being produced through products, you have to figure out a way to compute that, and the cloud has many advantages and many trade-offs, and so we're going to talk about the trade-offs, that's where the gap for computing comes into play. >> Excellent, thanks very much. And last but not least, we have Val, and I can never pronounce your surname. >> Bercovici. >> Thank you. (chuckling) You are in the midst of a transition yourself, so talk about where you have been and where you're going. >> For the better part of this century, I've been with NetApp, working at various functions, obviously enterprise storage, and around 2008, my developer instinct kind of fired up, and this thing called cloud became very interesting to me. So I became a self-anointed cloud czar at NetApp, and I ended up initiating a lot of our projects which we know today as the NetApp Data Fabric, that culminated about 18 months ago, in acquisition of SolidFire, and I'm now the acting CTO of SolidFire, but I plan to retire from the storage industry at the end of our fiscal year, at the end of April, and I'm spending a lot of time with particularly the Cloud Native Compute Foundation, that is, the opensource home of Google's Kubernetes Technology and about seven other related projects, we keep adding some almost every month, and I'm starting to lose track, and spending a lot of time on the data gravity challenge. It's a challenge in the cloud, it's a particularly new and interesting challenge at the edge, and I look forward to talking about that. >> Okay, and data gravity is absolutely key, isn't it, it's extremely expensive and extremely heavy to move around. >> And the best analogy is workloads are like electricity, they move fairly easily and lightly, data's like water, it's really hard to move, particularly large bodies around. >> Great. I want to start with one question though, just in the problem, the core problem, particularly in established industries, of how do we get change to work? In an IT shop, we have enough problems dealing with operations and development. In the industrial world, we have the IT and the OT, who look at each other with less than pleasure, and mainly disdain. How do we solve the people problem in trying to put together solutions? You must be right in the middle of it, would you like to start with that question? >> Absolutely, so we are 26 years old, probably more than that, but we have very old and new mix of manufacturing equipment, it's a storage industry, and in our storage industry, we are used to doing things a certain way. We have existing data, we have historical data, we have trend data, you can't get rid of what you already have. The goal is to make connectors such that you can move from where you're at to where you're going, and so you have to be able to take care of the shift that is happening in the market, so at the end of the day, if you look at five years from now, it's all going to be machine learning and AI, right? Agent technology's already here, it's proven, we can see, Siri is out here, we can see Alexa, we can see these agent technologies out there, so machine learning is a getting a lot of momentum, deep learning and neural networks, things like that. So we got to be able to look at that data and tap into our data, near realistically, very different, and the way to do that is really making these connections happen, tapping into old versus new. Like for example, if you look at storage, you have file storage, you have block storage, and then you have object storage, right? We've not really tapped into the field of object storage, and the reason is because if you are going to process one trillion objects like Amazon is doing right now with S3, you can't do it with the file system level storage or with the blog system level storage, you have to go to objects. Think Internet of Things. How many trillions of objects are going to come out of these Internet of Things? So one, you have to be positioned from an infrastructure standpoint. Two, you have to be positioned from a use case prototyping perspective, and three, you got to be able to scale that very rapidly, very quickly, and that's how change happens, change does not happen because you ask somebody to change their behavior, change happens when you show value, and people are so eager to get that value out of what you've shown them in real life, that they are so quick to adapt. >> That's an excellent-- >> If I could comment on that as well, which is, we just got through training a bunch of OT guys on our software, and two analogies that actually work very well, one is sort of, the operational people are very familiar with circuit diagrams, and so, and sort of, flow of things through essentially black boxes, you can think of these as something that has a bunch of inputs and has a bunch of outputs. So that's one thing that worked very well. The second thing that works very well is the PLC model, and there are direct analogies between PLC's and analytics, which people on the floor can actually relate to. So if you have software that's basically based on data streams and time, as a first-class citizen, the PLC model again works very well in terms of explaining the new software to the OT people. >> Excellent, okay, would you want to come in on that as well? >> Sure, I think a couple of points to add to what Janet said, I couldn't agree more in terms of the result, I think Maana did a few projects, a few pilots to convince customers of their value, and we typically focus very heavily on operationalizing the output, so we are very focused on making sure that there is some measurable value that comes out of it, and it's not until the end user started seeing that value that they were willing and open to adopt the newer methodologies. A second point to that is, a lot of the more recent techniques available to solve certain challenges, there are deep learning neural nets there's all sorts of sophisticated AI and machine learning algorithms that are out there, a lot of these are very sophisticated in their ability to deliver results, but not necessarily in the transparency of how you got that, and I think that's another thing that Maana's learning, is yes, we have this arsenal of fantastic algorithms to throw at problems, but we try to start with the simplest approach first, we don't unnecessarily try to brute force, because I think an enterprise, they are more than willing to have that transparency in how they're solving something, so if they're able to see how they were able to get to us, how the software was able to get to a certain conclusion, then they are a lot happier with that approach. >> Could you maybe just give one example, a real-world example, make it a little bit real? >> Right, absolutely, so we did a project for a very large organization for collections, they have a lot of outstanding capital locked up and customers not paying, it's a standard problem, you're going to find it in pretty much any industry, and so for that outstanding invoice, what we did was we went ahead and we worked with the subject matter experts, we looked at all the historical accounts receivable data, we took data from a lot of other sources, and we were able to come up with models to predict when certain customers are likely to pay, and when they should be contacted. Ultimately, what we wanted to give the collection agent were a list of customers to call. It was fairly straightforward, of course, the solution was not very, very easy, but at least on a holistic level, it made a lot of sense to us. When we went to the collection agents, many of them actually refused to use that approach, and this is part of change management in some sense, they were so used to doing things their way, they were so used to trying to target the customers with the largest outstanding invoice, or the ones that hadn't paid for the longest amount of time, that it actually took us a while, because initially, what the feedback we got was that your approach is not working, we're not seeing the results. And when we dug into it, it was because it wasn't being used, so that would be one example. >> So again, proof points that you will actually get results from this. >> Absolutely, and the transparency, I think we actually sent some of our engineers to work with the collections agents to help them understand what approach is it that we're taking, and we showed them that this is not magic, we're actually, instead of looking at the final dollar value, we're looking, we're calculating time value lost, so we are coming up with a metric that allows us to incorporate not just the outstanding amount, or the time that they haven't paid for, but a lot of other factors as well. >> Excellent, Val. >> When you asked that question, I immediately went to more of a nontechnical business side of my brain to answer it, so my experience over the years has been particularly during major industry transitions, I'm old enough to remember the mainframe to client server transition, and now client server to virtualization and cloud, and really, sales reps have that well-earned reputation of being coin-operated, though it's remarkable how much you can adjust compensation plans for pretty much anyone, in a capitalist environment, and the IT/OT divide, if you will, is pretty easy to solve from a business perspective when you take someone with an IT supporting the business mentality, and you compensate them on new revenue streams, new business, all of a sudden, the world perspective changes sometimes overnight, or certainly when that contract is signed. That's probably the number one thing you can do from a people perspective, is incent them and motivate them to focus on these new things, the technology is, particularly nowadays is evolving to support them for these new initiatives, but nothing motivates like the right compensation plan. >> Excellent, a great series of different viewpoints. So the second question I have again coming down a bit to this level, is how do we architect a solution? We heard you got to architect it, and you've got less, like this, it seems to me that that's pretty difficult to do ahead of where you're going, that in general, you take smaller steps, one step at a time, you solve one problem, you go on to the next. Am I right in that? If I am, how would you suggest the people go about this decision-making of putting architectures together, and if you think I'm wrong and you have a great new way of doing it, I'd love to hear about it. >> I can take a shorter route. So we have a number of customers that are trying to adopt, are going through a phased way of adopting our technology and products, and so it begins with first gathering of the data, and replaying it back, to build the first level of confidence, in the sense that the product is actually doing what you're expecting it to do. So that's more from monitoring administration standpoint. The second stage is you should begin to capture analytical logic into the project, where it can start doing prediction for you, so you go into, so from operational, you go into a predictive maintenance, predictive maintenance, predictive models standpoint. The third part is prescriptive, where you actually help create a machine learning model, now, it's still in flux in terms of where the model gets created, whether it's on the cloud, in a central fashion, or some sort of a, the right place, the right context in a multi-level hierarchical fog layer, and then, you sort of operationalize that as close to the data again as possible, so you go through this operational to predictive to prescriptive adoption of the technology, and that's how people actually build confidence in terms of adopting something new into, let's say, a manufacturing environment, or things that are pretty expensive, so I give you another example where you have the case of capacitors being built on a assembly line, manufacturing, and so how do you, can you look at data across different stations and manufacturing on a assembly line? And can you predict on the second station that it's going to fail on the eighth one? By that, what you're doing is you are actually reducing the scrap that's coming off of the assembly line. So, that's the kind of usage that you're going to in the second and third stage. >> Host: Excellent. Janet, do you want to go on? >> Yeah, I agree and I have a slightly different point of view also. I think architecture's very difficult, it's like Thomas Edison, he spent a lot of time creating negative knowledge to get to that positive knowledge, and so that's kind of the way it is in the trenches, we spend a lot of time trying to think through, the keyword that comes to mind is abstraction layers, because where we came from, everything was tightly coupled, and tightly coupled, computer and storage are tightly coupled, structured and unstructured data are tightly coupled, they're tightly coupled with the database, schema is tightly coupled, so now we are going into this world of everything being decoupled. In that, multiple things, multiple operating systems should be able to use your storage. Multiple models should be able to use your data. You cannot structure your data in any kind of way that is customized to one particular model. Many models have to run on that data on the fly, retrain itself, and then run again, so when you think about that, you think about what suits best to stay in the cloud, maybe large amounts of training data, schema that's already processed can stay on the cloud. Schema that is very dynamic, schema that is on the fly, that you need to read, and data that's coming at you from the Internet of Things that's changing, I call it heteroscedastic data, which is very statistical in nature, and highly variable in nature, you don't have time to sit there and create rows and columns and structure this data and put it into some sort of a structured set, you need to have a data lake, you need to have a stack on top of that data lake that can then adapt, create metadata, process that data and make it available for your models, so, and then over time, like I totally believe that now we're running into near realtime compute bottleneck, processing all this pattern processing for the different models and training sets, so we need a stack that we can quickly replace with GPUs, which is where the future is going, with pattern processing and machine learning, so your architecture has to be extremely flexible, high layers of abstraction, ability to train and grow and iterate. >> Excellent. Do you want to go next? >> So I'll be a broken record, back to data gravity, I think in an edge context, you really got to look at the cost of processing data is orders of magnitude less than moving it or even storing it, and so I think that the real urgency, I don't know, there's 90% that think of data at the edge is kind of wasted, you can filter through it and find that signal through the noise, so processing data to make sure that you're dealing with really good data at the edge first, figuring out what's worth retaining for future steps, I love the manufacturing example, I have lots of customer examples ourselves where, for quality control in a high-moving assembly line, you want to take thousands of not millions of images and compare frame and frame exactly according to the schematics where the device is compared to where it should be, or where the components, and the device compared to where they should be, processing all of that data locally and making sure you extract the maximum value before you move data to a central data lake to correlate it against other anomalies or other similarities, that's really key, so really focus on that cost of moving and storing data, yeah. >> Yes, do you want the last word? >> Sure, Maana takes an interesting approach, I'm going to up-level a little bit. Whenever we are faced with a customer or a particular problem for a customer, we try to go over the question-answer approach, so we start with taking a very specific business question, we don't look at what data sources are available, we don't ask them whether they have a data lake, or we literally get their business leaders, their subject matter experts, we literally lock them up in a room and we say, "You have to define "a very specific problem statement "from which we start working backwards," each problem statement can be then broken down into questions, and what we believe is any question can be answered by a series of models, you talked about models, we go beyond just data models, we believe anything in the real world, in the case of, let's say, manufacturing, since we're talking about it, any smallest component of a machine should be represented in the form of a concept, relationships between people operating that machinery should be represented in the form of models, and even physics equations that are going into predicting behavior should be able to represent in the form of a model, so ultimately, what that allows us is that granularity, that abstraction that you were talking about, that it shouldn't matter what the data source is, any model should be able to plug into any data source, or any more sophisticated bigger model, I'll give you an example of that, we started solving a problem of predictive maintenance for a very large customer, and while we were solving that predictive maintenance problem, we came up with a number of models to go ahead and solve that problem. We soon realized that within that enterprise, there are several related problems, for example, replacement of part inventory management, so now that you figured out which machine is going to fail at roughly what instance of time from now, we can also figure out what parts are likely to fail, so now you don't have to go ahead and order a ton of replacement parts, because you know what parts are going to likely fail, and then you can take that a step further by figuring out which equipment engineer has the skillset to go ahead and solve that particular issue. Now, all of that, in today's world, is somewhat happening in some companies, but it is actually a series of point solutions that are not talking to each other, that's where our pattern technology graph is coming into play where each and every model is actually a note on the graph including computational models, so once you build 10 models to solve that first problem, you can reuse some of them to solve the second and third, so it's a time-to-value advantage. >> Well, you've been a fantastic panel, I think these guys would like to get to a drink at the bar, and there's an opportunity to talk to you people, I think this conversation could go on for a long, long time, there's so much to learn and so much to share in this particular information. So with that, over to you! >> I'll just wrap it up real quick, thanks everyone, give the panel a hand, great job. Thanks for coming out, we have drinks for the next hour or two here, so feel free to network and mingle, great questions to ask them privately one-on-one, or just have a great conversation, and thanks for coming, we really appreciate it, for our Big Data SV Event livestreamed out, it'll be on demand on YouTube.com/siliconangle, all the video, if you want to go back, look at the presentations, go to YouTube.com/siliconangle, and of course, siliconangle.com, and Wikibond.com for the research and content coverage, so thanks for coming, one more time, big round of applause for the panel, enjoy your evening, thanks so much.