>>mhm Yes. Welcome back to the cubes coverage of red hat summit 2021 virtual john for your host of the cube paul. Comey who's here is the president and Ceo of red hat cube alumni paul always great to have you on the leader of red hat now President and Ceo for a year I think about a year now we're looking at under your belt now part of IBM Great to see you. >>You too nice to see you again john. >>So we've talked many times on the Cuban now. It's kind of playing out in real time. The software world with open source has gone mainstream. The conversation was moved to the cloud. Okay. People move to the cloud. Cloud native emerges devil has been around for a while. But now the conversation is cloud for the enterprise that uh, the enterprises, it's a tough world. You gotta, it's complicated is a lot of legacies, a lot of value and you want the new stuff. This is what the conversation is now. It's shifted to I got cloud, it's hybrid. What's your reaction to that? >>Well, you know, it really is, as you say, it's complicated but it's evolving and really, really fast. I mean, you know, I think you remember we've been here a lot. You first remember first software is eating the world and open source software is eating the world and in every every company is becoming a software company. All true. But that evolution continues today with the proliferation of hybrid cloud environments that it encompasses everything from data centers to public cloud services to And even now we'll talk about two for far flung edge deployments. That's all now part of the cloud. I mean, this is all what makes up hybrid. I like to always say that Hybrid really is the new data centers but now see IOS and I thi leaders, they need to reconsider what their roles, what their role here is and the way we look at it as every C I O now needs to be a cloud operator because because Hybrid is what their environment is now today, that used to be all in their data center. So, so but one of the things that really makes a choice even more important and its leaders, they need to address address specific needs, um not only to the organization, but even as they change and evolve in this because it really is a dynamic environment, I mean think about it and just mentioned edge and how how important that is to see IOS, we weren't even talking about that two years ago, so, so it's not a single answer here, right? Um and and you know, and there as there wasn't a single answer when it was all in one building or in one data center, but now it's even it's even more complex. So, so we need to enable really a new wave of cloud operators here with technologies that can be deployed as cloud services as well as on premises. We'll talk more about this too, but and we'll talk about this at the summit. We talked about the summit. Cloud services become really important, especially managed services, for example, because, um because we're so complex, Hybrid brings so much power, but it is complex. You know, see I need help with this, they need help managing this now. And so that's really where a lot of our focus is today. >>It's interesting you say there's no single answer. I would agree with you because it's now you can actually do a lot more customization with cloud and Hybrid. I think there's a general sentiment and directionally correct answer uh in the industry is that hybrid is operating model right? And I think you guys are have a whole division of SRS google talks about this all the time and their cloud site reliability engineers. And I think you're seeing that in educational institutions which we'll talk about. But I think this idea of cloud scale as the new I. T. And you mentioned hybrids, the new data center. You know, I don't I don't want to offend my I. T. Friends out there but they're kind of all realizing it to that if they don't understand how to operate cloud scale they'll be irrelevant and they're and they understand that their jobs are not just provisioning storage, networking and servers. Those are now involved in a hybrid architecture. And by the way, there is no one recipe, it's dependent. Each enterprise can have its own set of architecture based on their workloads again. So I buy that no single answer, but there is hybrid and I think it's pretty well understood. I mean, do you agree with that? >>I absolutely agree with that. But let's take a look at this, unpack it a little bit and take a look at the building blocks a bit. Right. Um, you know, we talked about open sources, what's driving all of this now and and everything we're talking about here is built in and around Lennox and it was only possible because Lennox was so open, so available and became so powerful, that's now been the platform that all this new innovation is built around. I mean, I oftentimes saying it's true the cloud just wouldn't be here had Lennox not only made its way in the open source development environment, but made its way into the enterprise to enable it to companies like us that make it enterprise ready, secure etcetera. So I think that's really an important thing to understand here. So when you talk about skills that the Ceos need certainly SRE skills, operation skills etcetera, but they also need Lennox skills and even open source skills. So so I think I think that's important, everything that's coming down the road and in in this space in um in his open source based and built in and around Lennox things like ai quantum computing, autonomous vehicles um IOT in and out to the edge all built on a foundation of Lennox and open source. So we see it in the enterprise everywhere now. I mean a survey where you know we did a survey out there and looking at the survey of C I O s out there, open is predominant out there, Lennox is predominant out there in hybrid is predominant and growing in a pretty big clip every year. >>You know, paul, I want to get your reaction to something because this may be kind of a dot connecting moment for me because I want to get your thoughts on this because it's a it's a pattern I'm seeing emerging now multiple times and usually I thought this was kind of a one off, but I'm starting to see it. So I'm going to get your thoughts on this. You guys have been super successful with open source in the enterprise, Super successful over decades, building a community and an ecosystem now with open source with with cloud Native, specifically we're seeing end users participating more in the, in the contribution starts out with the hyper scale ear's but now you're seeing kind of, I would call general purpose mainstream enterprises contributing projects, not necessarily their expertise, but they've been participating in taking the goodness of open source and bringing that into the into the enterprise. And I'll see you relying on you guys as well. But now I'm starting to see the pattern where people are relying on you to bring your community to them and they merge their communities with you guys and being kind of a steward there, is that a pattern? Do you see that evolving? Because we've heard that on multiple interviews on the cube where we've heard end users say we love the red hat ecosystem and and that seems to be more and more about they want to be building their ecosystem. So you did it for yourselves, you did it for the industry. Now, enterprises want this service is this is this is a pattern. And what's your reaction to that? >>It actually is a pattern because it's actually one of the reasons why innovation is moving so quickly right now. As I just said, you know, you know, this whole area here in infrastructure and cloud and development environments, Hybrid included. It's all built in and around, it's all built in and around Lennox. And in the past, what's happening and driven by open source development in the past? What happened? Look at the old fashioned way, right, where a company like us would be in a company, software company, not like us, but any old software company would be, you know, in their stovepipe, talking to their customers, getting their requirements and then bringing those requirements back from the customer base and then trying to work that into their products over time, get that back out to the customer to test it and try it, see it as it works. That's probably a five year, there's probably a five year journey, uh, for big, big requirements for big change requirements you look at now with, with actually end users now participating in upstream development, they're building their requirements into that upstream, which is our development environment. And actually that's what feeds our products. And so we've cut out the middleman, if you will completely in there now when we're building those requirements into our future future, R and D work in the upstream and then we bring that down into a product back into their enterprise for them to use in production. So it cuts out years of time for that innovation to get from concept to building to product, rising to production. And, and I think, you know, john, that's one of the big reasons why that customer base participating is one of the big reason why we're seeing innovation move like we've never seen it before in the enterprise, which in the old days that was a stodgy place where they didn't want to move very quickly. >>Yeah. And the values there, I mean I think it's clear what the pandemic we get to this towards the the last last talking track here. But with the pandemic I think it's pretty clear what the value is and the speed to capture opportunities and growth. I think enterprises are realizing that I think the power of the ecosystem is a modern error kind of phenomenon that is now kind of showing its its value and clearly in the market. And I think people who harness communities and ecosystems not try to fork them but connect them and and intersect them and kind of played well together. So again this is an open source concept kind of re imagined so we'll keep an eye on that. So, um, I want to get to your comment in the kino you mentioned at the top here every C I. O. It has to be a cloud operator. You know, that reminds me of all the start ups and all the positioning statements. Every company needs to be a software company. Every company needs to be a media company. Every company needs to be a cloud operator. So I love that. What does it mean? Because I could say, hey paul, I have a cloud, I'm working on amazon Or is that it? Or wait a minute as yours got, I got 365 over here and I'm using big query over here. I might use oracle over here. I mean all these multi cloud conversations. So it's confusing. >>Yeah. Tell me what, you know, if you look at, if you look at it, we were really one of the first ones to really build around this hybrid, this hybrid concept. And the reason why we were one of the first ones is because what amazon hit the world 12 or 13 years ago or something like that, They were the first major cloud and at the time that the narrative was that, you know, every application was going to move to the cloud tomorrow. Right well, because as I said earlier, everything is built in and in and around open source. And legs were very involved with our customers as they tried to move those first applications to the cloud. So certainly is a lot of value and moving to the cloud. But our customers quickly realized with us helping them, quickly realized that you know what, this is great. But not every application suited for the cloud, um for any cloud, but also I may want to run multiple clouds because another cloud provider over here might have a better service than this particular service over here, vice versa. And so we were in the middle of that. So one of the decisions we made seven or eight years ago, everything we did in that last seven or eight years around the portfolio, whether it was building products, m and A, requiring new companies etcetera, was built around that hybrid portfolio. What that means is a common platform that sits both on premise and bare metal machines. Virtual machines, private clouds on premise multiple clouds across out in the enterprise, that common platform so that developers, operators and the security people have that common platform to build with because just like in Lenox, even though they are all derived from open source upstream, they're all different, they all make different choices and how they're going to configure themselves. So, so that's important. So now we're out there with these multiple clouds. One of our surveys we see our Ceo is telling us now that You're using on the average I think six Clouds today and they expect that to go 8-10 over the next 3-5 years. So how are they going to manage that? How are they going to secure that? How are their operations people going to operate with that? That's all the things that we've been working on over the last number of years. So from that common platform, which is sort of the basis which is open shift to underneath it, which is the Linux operating system, which is well that spans all those footprints that I talked about. And then also you look at one of the latest trends is as well as manage services because what customers are now telling us is okay I got this environment that this hybrid is now my data center. It means I have to worry about these apps all in different footprints. Um I want to the platform to act like a cloud in some cases I don't want to I don't want to even manage it. I want you to manage it for me because for many reasons I want great up time. I might not have the right skill sets in my organization and so I want you to manage it. And so that's where we develop managed services and that's where we have set a large group today large SRE group that's providing those managed services no matter where our platform runs for our customers. Also, what I talked about in my keynote today is that to support that thought process is that we're doing a lot of research in this and so, you know, in a typical computer science research world, you know, of the past, you might really be into the into the real computer science of Research. We with the consortium around mass Open cloud with Boston University, MIT, Harvard Northeastern with this consortium. We're running mass Open cloud on all Red Hat with the collaboration of these universities and we're really focusing on the sorry aspect of it. What do we need to manage it? What do we need around automation to manage it? What do we need around ai to manage it? What do we need for tools to manage it? And and that's really goes down to what I fully briefly said in the beginning, is that every C I O N I T uh executive now has to be their own cloud operator because they are effectively stitching all these disparate clouds together. So that's where a big part of our focus takes us all the way from, You know, upstream development to product to the research we're doing for the next 3-5 plus years. >>You know, I gotta say the hybrid cloud is a new data center which is implying I T in the cloud operators with C X O S and C IOS is interesting because it's validated by Mckinsey's recent report that came out that said there's a trillion dollars of untapped value in one retrofitting existing infrastructure and operations and to net new operate use cases that the cloud enables. So there's clearly not two categories of value proposition that businesses are facing. One is, you know, kind of take care of the existing and then also bring in the new that cloud enables. So, you know, I think that's really key and that will drive the business leaders to foresight, if you will to be agile and adaptive to that. So so totally agree on that. I love this open cloud initiative, you mentioned the mass open cloud which I know is kind of like this beanpot for techies, um people who know what that means, uh it's in the boston area these institutions um this is gonna be a training and an opportunity to train the next generation and if you take it to the next level cybersecurity is also in this kind of net new novelty, interdisciplinary components. So you got engineering which is like devops engineering and then Systems Engineering and Computer Science intersecting together with kind of this data discipline. So it hits cybersecurity which is a board level conversation, it hits the new business model opportunities which is a driver, this is new, this is there's no pre existing curriculum. What how do you explain that to heads of the departments and the deans of these institutions saying, you know, it's an engineering thing. No, it's computer science thing. No, it's a it's a business school thing with data science. What's your what's your conversation with folks in the industry when you say this is a different thing? >>Uh you know, the university, you know, the university is getting, it was actually one of the one of the first things this is you know what you'll see. You know, I talked to uh dr bob Brown from President bu earlier in an interview and and this is what we imagined with them early on and even they brought those disciplines together now in in in what they call a harry institute, where to bring data, computer science engineering as you say. And now even operations, it's almost like, you know, systems engineering on steroids, it's a really big spanning system. And so so the universities are starting understand that's why these universities in the consortium, that's why we're working here. But also, you know, the industry's kind of learning it the hard way because now that they get some of their developers starting to move some of their application developments out into one, maybe two clouds and having the now they have to figure out how they're going to do all those things that we talked about, develop, secure operated. So they're they're learning the hard way that this is the new discipline because that's reality. I also think that, you know, as I said, like anything in tech, we always say this is going to happen tomorrow. I also think, like I said, when when cloud first came came out, everybody saying, I'm moving every app to the cloud tomorrow. We even had customers that bought into that said we're moving going full board but they realized once they get into it it wasn't practical. Don't take me wrong. Cloud brings a ton of value here but from a practical perspective it's going to be some apps and across many clouds and and so now they're having to deal with the I. T. Execs and the C. I. Was having to deal with it. So they're learning really fast because of the reality that they have to deal with. Now having said all that to it also brings up why managed services you're seeing so popular right now because as that's moving so fast they just don't have the skills necessary in many cases to really operate and run in this in this type of environment. It brings so much power but the skills aren't necessarily there in the industry. So that now you see the connection between the industry where we sit and even the university now looking at this whole big problem as as you put said, john, actually a new discipline, >>I think, I think, and I think one final leg of a three legged stool is at the business schools because when you think about systems programming, you mentioned that and you know, I love to go back in history and look at the history of operating systems. And you know, paul, we've talked us in the past and you guys know a lot about operating systems from a technology standpoint, it's not just about a productivity suite for a user or a department with the system, it's a company that needs to be programmed. So when people want to globally operate their business, that software defined this isn't now and this is now happening, right? So this the new leaders in these companies that want to run these global companies that scale operate them, just like operating the business not necessary. Operating a tech or shiny new toy, have to build the operating system for the business. To me, I think that's where I see IBM looking at cloud differently and saying, hey, this is an operating system under the covers for the business. The applications are multi fold from, you know, an application for productivity to an edge device, industrial or consumer user work at home. I mean it's a plethora of applications. What's your reaction to that? And you you see the same thing? >>I mean frankly, I think this is an area that a lot of the infrastructure players missed in the past. And I think I think this is what IBM saw with with bringing us in as well. It's all about the application. You know, I said earlier that, you know, we said every every company was a software company is true. And so that means the companies are running their businesses on these applications. So it's all about the app and I think a lot of infrastructure companies miss that. And and so with Hybrid now you have that ability to run the app wherever makes the most sense for for a whole host of reasons. And so now, but now comes the complexity of all of that. I think, I think IBM with bringing us in saw that that Hybrid was maybe as big, if not a bigger opportunity than cloud itself because of of the complexity it's going to bring, the power is going to bring. But also the complexity is gonna bring. I see that's why, you see Arvind, I sort of doubling down the entire IBM company on on hybrid services that are that are going to be really important here, that they provide these applications on top that are going to be really important, but that have to be architected in such a way that they can run in a hybrid environment. And finally there's all the infrastructure and tools and development pieces that we bring to the table. So, So yeah, I think I think are really, really understood that as they made the decision to bring redheaded, >>I talked to a center all the time and they also have this kind of concept of re factoring and reprogramming your business. Uh, it's not, it's a holistic view. This is kind of what's happening. So my final question for you is as as that becomes software enabled and programmed if you will with applications the business with many different subsystems in there. Um a lot of companies now looking at the light at the end of the tunnel with the pandemic and they're seeing vaccines coming out. Some say vaccines will be pretty much everywhere, everyone over 12 by the fall. So we're back to real life. There's gonna be a pullback of some projects on doubling down on others. As you as you mentioned, what are we doing? We're starting to see hybrid as companies come out of the pandemic, they're all jockeying to make sure that they have either done their work to re factor or reposition, reprogrammed their business and be set up for net new opportunities. >>What >>do you see as a growth model or growth opportunities for companies? You want to come out with a growth strategy out of the gate of the pandemic. What's your thoughts? >>Well, I mean, I think you have to plan for companies have to plan for your workforce to be anywhere, but in order to be anywhere in and to be productive, you need you need services like we're on right now for example, but you need the infrastructure to be able to do that. You need you need a way for your customers if you buy the fact that every company is a software company, you're running a business through their applications either way for your customers to be able to interact with you anywhere from where they are anywhere in a real time way. And so I think that's why from our perspective, things like that we're pushing a lot on the edge. Now, that's why you're seeing the hybrid cloud moved all the way out into the edge and you can see it in every vertical, you know, in the telco space. The edge means you gotta do, you have data and compute that needs to be done on the set on the cell tower in the manufacturing world. You have the state and compute that needs to be done on the factory floor, in the retail vertical. We see the edge really being significant in all these verticals, but but that edge is now extends that hybrid data center that we've been talking so much about. So even though you have all these edge devices way out there on the edge, it's a critical part of the business. So you have to have, your developers need need to be able to develop for it, you need to secure it, you need to and you need to operate it and manage it. So now, you know, in a very short period of time, hybrids taken on another dimension, bringing you out to all these points on the edge which is the same but slightly different in every vertical. Now comes complexity and that's why automation is so important because with that power comes complexity but it's going to take automation to keep it all running, >>paul. Great insight. Thanks for coming on the cube. Open innovation out in the open with with you guys again continue. And the focus of the evolution of software and the cloud with enterprise I. T. Clearly a lot of innovation and your contribution to academia and the mass open cloud and all the open cloud initiatives, phenomenal. The world's going. Open source and continues and continues. Doesn't stop. The operating system of businesses is coming and you guys are well positioned. Thanks for coming on. >>Thanks again john. Always a pleasure. >>Okay paul, Cormier, President Ceo of Red Hat here on the Cuban, john for your host. Thanks for watching. Yeah. Yeah. Mhm mm.

>>from around the globe. It's the Cube presenting innovation for good, brought to you by on shape. >>Hello, everyone, and welcome to Innovation for Good Program, hosted by the Cuban. Brought to You by on Shape, which is a PTC company. My name is Dave Valentin. I'm coming to you from our studios outside of Boston. I'll be directing the conversations today. It's a very exciting, all live program. We're gonna look at how product innovation has evolved and where it's going and how engineers, entrepreneurs and educators are applying cutting edge, cutting edge product development techniques and technology to change our world. You know, the pandemic is, of course, profoundly impacted society and altered how individuals and organizations they're gonna be thinking about an approaching the coming decade. Leading technologists, engineers, product developers and educators have responded to the new challenges that we're facing from creating lifesaving products to helping students learn from home toe how to apply the latest product development techniques and solve the world's hardest problems. And in this program, you'll hear from some of the world's leading experts and practitioners on how product development and continuous innovation has evolved, how it's being applied toe positive positively affect society and importantly where it's going in the coming decades. So let's get started with our first session fueling Tech for good. And with me is John Hirschbeck, who is the president of the Suffers, a service division of PTC, which acquired on shape just over a year ago, where John was the CEO and co founder, and Dana Grayson is here. She is the co founder and general partner at Construct Capital, a new venture capital firm. Folks, welcome to the program. Thanks so much for coming on. >>Great to be here, Dave. >>All right, John. >>You're very welcome. Dana. Look, John, let's get into it for first Belated congratulations on the acquisition of Von Shape. That was an awesome seven year journey for your company. Tell our audience a little bit about the story of on shape, but take us back to Day zero. Why did you and your co founders start on shape? Well, >>actually, start before on shaping the You know, David, I've been in this business for almost 40 years. The business of building software tools for product developers and I had been part of some previous products in the industry and companies that had been in their era. Big changes in this market and about, you know, a little Before founding on shape, we started to see the problems product development teams were having with the traditional tools of that era years ago, and we saw the opportunity presented by Cloud Web and Mobile Technology. And we said, Hey, we could use Cloud Web and Mobile to solve the problems of product developers make their Their business is run better. But we have to build an entirely new system, an entirely new company, to do it. And that's what on shapes about. >>Well, so notwithstanding the challenges of co vid and difficulties this year, how is the first year been as, Ah, division of PTC for you guys? How's business? Anything you can share with us? >>Yeah, our first year of PTC has been awesome. It's been, you know, when you get acquired, Dave, you never You know, you have great optimism, but you never know what life will really be like. It's sort of like getting married or something, you know, until you're really doing it, you don't know. And so I'm happy to say that one year into our acquisition, um, PTC on shape is thriving. It's worked out better than I could have imagined a year ago. Along always, I mean sales are up. In Q four, our new sales rate grew 80% vs Excuse me, our fiscal Q four Q three. In the calendar year, it grew 80% compared to the year before. Our educational uses skyrocketing with around 400% growth, most recently year to year of students and teachers and co vid. And we've launched a major cloud platform using the core of on shape technology called Atlas. So, um, just tons of exciting things going on a TTC. >>That's awesome. But thank you for sharing some of those metrics. And of course, you're very humble individual. You know, people should know a little bit more about you mentioned, you know, we founded Solid Works, co founded Solid where I actually found it solid works. You had a great exit in the in the late nineties. But what I really appreciate is, you know, you're an entrepreneur. You've got a passion for the babies that you you helped birth. You stayed with the salt systems for a number of years. The company that quiet, solid works well over a decade. And and, of course, you and I have talked about how you participated in the the M I T. Blackjack team. You know, back in the day, a zai say you're very understated, for somebody was so accomplished. Well, >>that's kind of you, but I tend to I tend Thio always keep my eye more on what's ahead. You know what's next, then? And you know, I look back Sure to enjoy it and learn from it about what I can put to work making new memories, making new successes. >>Love it. Okay, let's bring Dana into the conversation. Hello, Dana. You look you're a fairly early investor in in on shape when you were with any A And and I think it was like it was a serious B, but it was very right close after the A raise. And and you were and still are a big believer in industrial transformation. So take us back. What did you see about on shape back then? That excited you. >>Thanks. Thanks for that. Yeah. I was lucky to be a early investment in shape. You know, the things that actually attracted me. Don shape were largely around John and, uh, the team. They're really setting out to do something, as John says humbly, something totally new, but really building off of their background was a large part of it. Um, but, you know, I was really intrigued by the design collaboration side of the product. Um, I would say that's frankly what originally attracted me to it. What kept me in the room, you know, in terms of the industrial world was seeing just if you start with collaboration around design what that does to the overall industrial product lifecycle accelerating manufacturing just, you know, modernizing all the manufacturing, just starting with design. So I'm really thankful to the on shape guys, because it was one of the first investments I've made that turned me on to the whole sector. And while just such a great pleasure to work with with John and the whole team there. Now see what they're doing inside PTC. >>And you just launched construct capital this year, right in the middle of a pandemic and which is awesome. I love it. And you're focused on early stage investing. Maybe tell us a little bit about construct capital. What your investment thesis is and you know, one of the big waves that you're hoping to ride. >>Sure, it construct it is literally lifting out of any what I was doing there. Um uh, for on shape, I went on to invest in companies such as desktop metal and Tulip, to name a couple of them form labs, another one in and around the manufacturing space. But our thesis that construct is broader than just, you know, manufacturing and industrial. It really incorporates all of what we'd call foundational industries that have let yet to be fully tech enabled or digitized. Manufacturing is a big piece of it. Supply chain, logistics, transportation of mobility or not, or other big pieces of it. And together they really drive, you know, half of the GDP in the US and have been very under invested. And frankly, they haven't attracted really great founders like they're on in droves. And I think that's going to change. We're seeing, um, entrepreneurs coming out of the tech world orthe Agnelli into these industries and then bringing them back into the tech world, which is which is something that needs to happen. So John and team were certainly early pioneers, and I think, you know, frankly, obviously, that voting with my feet that the next set, a really strong companies are going to come out of the space over the next decade. >>I think it's a huge opportunity to digitize the sort of traditionally non digital organizations. But Dana, you focused. I think it's it's accurate to say you're focused on even Mawr early stage investing now. And I want to understand why you feel it's important to be early. I mean, it's obviously riskier and reward e er, but what do you look for in companies and and founders like John >>Mhm, Um, you know, I think they're different styles of investing all the way up to public market investing. I've always been early stage investors, so I like to work with founders and teams when they're, you know, just starting out. Um, I happened to also think that we were just really early in the whole digital transformation of this world. You know, John and team have been, you know, back from solid works, etcetera around the space for a long time. But again, the downstream impact of what they're doing really changes the whole industry. And and so we're pretty early and in digitally transforming that market. Um, so that's another reason why I wanna invest early now, because I do really firmly believe that the next set of strong companies and strong returns for my own investors will be in the spaces. Um, you know, what I look for in Founders are people that really see the world in a different way. And, you know, sometimes some people think of founders or entrepreneurs is being very risk seeking. You know, if you asked John probably and another successful entrepreneurs, they would call themselves sort of risk averse, because by the time they start the company, they really have isolated all the risk out of it and think that they have given their expertise or what they're seeing their just so compelled to go change something, eh? So I look for that type of attitude experience a Z. You can also tell from John. He's fairly humble. So humility and just focus is also really important. Um, that there's a That's a lot of it. Frankly, >>Excellent. Thank you, John. You got such a rich history in the space. Uh, and one of you could sort of connect the dots over time. I mean, when you look back, what were the major forces that you saw in the market in in the early days? Particularly days of on shape on? And how is that evolved? And what are you seeing today? Well, >>I think I touched on it earlier. Actually, could I just reflect on what Dana said about risk taking for just a quick one and say, throughout my life, from blackjack to starting solid works on shape, it's about taking calculated risks. Yes, you try to eliminate the risk Sa's much as you can, but I always say, I don't mind taking a risk that I'm aware of, and I've calculated through as best I can. I don't like taking risks that I don't know I'm taking. That's right. You >>like to bet on >>sure things as much as you sure things, or at least where you feel you. You've done the research and you see them and you know they're there and you know, you, you you keep that in mind in the room, and I think that's great. And Dana did so much for us. Dana, I want to thank you again. For all that, you did it every step of the way, from where we started to to, you know, your journey with us ended formally but continues informally. Now back to you, Dave, I think, question about the opportunity and how it's shaped up. Well, I think I touched on it earlier when I said It's about helping product developers. You know, our customers of the people build the future off manufactured goods. Anything you think of that would be manufacturing factory. You know, the chair you're sitting in machine that made your coffee. You know, the computer you're using, the trucks that drive by on the street, all the covert product research, the equipment being used to make vaccines. All that stuff is designed by someone, and our job is given the tools to do it better. And I could see the problems that those product developers had that we're slowing them down with using the computing systems of the time. When we built solid works, that was almost 30 years ago. If people don't realize that it was in the early >>nineties and you know, we did the >>best we could for the early nineties, but what we did. We didn't anticipate the world of today. And so people were having problems with just installing the systems. Dave, you wouldn't believe how hard it is to install these systems. You need toe speck up a special windows computer, you know, and make sure you've got all the memory and graphics you need and getting to get that set up. You need to make sure the device drivers air, right, install a big piece of software. Ah, license key. I'm not making this up. They're still around. You may not even know what those are. You know, Dennis laughing because, you know, zero cool people do things like this anymore. Um, and it only runs some windows. You want a second user to use it? They need a copy. They need a code. Are they on the same version? It's a nightmare. The teams change, you know? You just say, Well, get everyone on the software. Well, who's everyone? You know, you got a new vendor today? A new customer tomorrow, a new employee. People come on and off the team. The other problem is the data stored in files, thousands of files. This isn't like a spreadsheet or word processor, where there's one file to pass around these air thousands of files to make one, even a simple product. People were tearing their hair out. John, what do we do? I've got copies everywhere. I don't know where the latest version is. We tried like, you know, locking people out so that only one person can change it At the time that works against speed, it works against innovation. We saw what was happening with Cloud Web and mobile. So what's happened in the years since is every one of the forces that product developers experience the need for speed, the need for innovation, the need to be more efficient with their people in their capital. Resource is every one of those trends have been amplified since we started on shape by a lot of forces in the world. And covert is amplified all those the need for agility and remote work cove it is amplified all that the same time, The acceptance of cloud. You know, a few years ago, people were like cloud, you know, how is that gonna work now They're saying to me, You know, increasingly, how would you ever even have done this without the cloud. How do you make solid works work without the cloud? How would that even happen? You know, once people understand what on shapes about >>and we're the >>Onley full SAS solution software >>as a service, >>full SAS solution in our industry. So what's happened in those years? Same problems we saw earlier, but turn up the gain, their bigger problems. And with cloud, we've seen skepticism of years ago turn into acceptance. And now even embracement in the cova driven new normal. >>Yeah. So a lot of friction in the previous environments cloud obviously a huge factor on, I guess. I guess Dana John could see it coming, you know, in the early days of solid works with, you know, had Salesforce, which is kind of the first major independent SAS player. Well, I guess that was late nineties. So his post solid works, but pre in shape and their work day was, you know, pre on shape in the mid two thousands. And and but But, you know, the bet was on the SAS model was right for Crick had and and product development, you know, which maybe the time wasn't a no brainer. Or maybe it was, I don't know, but Dana is there. Is there anything that you would invest in today? That's not Cloud based? >>Um, that's a great question. I mean, I think we still see things all the time in the manufacturing world that are not cloud based. I think you know, the closer you get to the shop floor in the production environment. Um e think John and the PTC folks would agree with this, too, but that it's, you know, there's reliability requirements, performance requirements. There's still this attitude of, you know, don't touch the printing press. So the cloud is still a little bit scary sometimes. And I think hybrid cloud is a real thing for those or on premise. Solutions, in some cases is still a real thing. What what we're more focused on. And, um, despite whether it's on premise or hybrid or or SAS and Cloud is a frictionless go to market model, um, in the companies we invest in so sass and cloud, or really make that easy to adopt for new users, you know, you sign up, started using a product, um, but whether it's hosted in the cloud, whether it's as you can still distribute buying power. And, um, I would I'm just encouraging customers in the customer world and the more industrial environment to entrust some of their lower level engineers with more budget discretionary spending so they can try more products and unlock innovation. >>Right? The unit economics are so compelling. So let's bring it, you know, toe today's you know, situation. John, you decided to exit about a year ago. You know? What did you see in PTC? Other than the obvious money? What was the strategic fit? >>Yeah, Well, David, I wanna be clear. I didn't exit anything. Really? You >>know, I love you and I don't like that term exit. I >>mean, Dana had exit is a shareholder on and so it's not It's not exit for me. It's just a step in the journey. What we saw in PTC was a partner. First of all, that shared our vision from the top down at PTC. Jim Hempleman, the CEO. He had a great vision for for the impact that SAS can make based on cloud technology and really is Dana of highlighted so much. It's not just the technology is how you go to market and the whole business being run and how you support and make the customers successful. So Jim shared a vision for the potential. And really, really, um said Hey, come join us and we can do this bigger, Better, faster. We expanded the vision really to include this Atlas platform for hosting other SAS applications. That P D. C. I mean, David Day arrived at PTC. I met the head of the academic program. He came over to me and I said, You know, and and how many people on your team? I thought he'd say 5 40 people on the PTC academic team. It was amazing to me because, you know, we were we were just near about 100 people were required are total company. We didn't even have a dedicated academic team and we had ah, lot of students signing up, you know, thousands and thousands. Well, now we have hundreds of thousands of students were approaching a million users and that shows you the power of this team that PTC had combined with our product and technology whom you get a big success for us and for the teachers and students to the world. We're giving them great tools. So so many good things were also putting some PTC technology from other parts of PTC back into on shape. One area, a little spoiler, little sneak peek. Working on taking generative design. Dana knows all about generative design. We couldn't acquire that technology were start up, you know, just to too much to do. But PTC owns one of the best in the business. This frustrated technology we're working on putting that into on shaping our customers. Um, will be happy to see it, hopefully in the coming year sometime. >>It's great to see that two way exchange. Now, you both know very well when you start a company, of course, a very exciting time. You know, a lot of baggage, you know, our customers pulling you in a lot of different directions and asking you for specials. You have this kind of clean slate, so to speak in it. I would think in many ways, John, despite you know, your install base, you have a bit of that dynamic occurring today especially, you know, driven by the forced march to digital transformation that cove it caused. So when you sit down with the team PTC and talk strategy. You now have more global resource is you got cohorts selling opportunities. What's the conversation like in terms of where you want to take the division? >>Well, Dave, you actually you sounds like we should have you coming in and talking about strategy because you've got the strategy down. I mean, we're doing everything said global expansion were able to reach across selling. We got some excellent PTC customers that we can reach reach now and they're finding uses for on shape. I think the plan is to, you know, just go, go, go and grow, grow, grow where we're looking for this year, priorities are expand the product. I mentioned the breath of the product with new things PTC did recently. Another technology that they acquired for on shape. We did an acquisition. It was it was small, wasn't widely announced. It, um, in an area related to interfacing with electrical cad systems. So So we're doing We're expanding the breath of on shape. We're going Maura, depth in the areas were already in. We have enormous opportunity to add more features and functions that's in the product. Go to market. You mentioned it global global presence. That's something we were a little light on a year ago. Now we have a team. Dana may not even know what we have. A non shape, dedicated team in Barcelona, based in Barcelona but throughout Europe were doing multiple languages. Um, the academic program just introduced a new product into that space that z even fueling more success and growth there. Um, and of course, continuing to to invest in customer success and this Atlas platform story I keep mentioning, we're going to soon have We're gonna soon have four other major PTC brands shipping products on our Atlas Saas platform. And so we're really excited about that. That's good for the other PTC products. It's also good for on shape because now there's there's. There's other interesting products that are on shape customers can use take advantage of very easily using, say, a common log in conventions about user experience there, used to invest of all they're SAS based, so they that makes it easier to begin with. So that's some of the exciting things going on. I think you'll see PTC, um, expanding our lead in SAS based applications for this sector for our our target, uh, sectors not just in, um, in cat and data management, but another area. PTC's Big and his augmented reality with of euphoria, product line leader and industrial uses of a R. That's a whole other story we should do. A whole nother show augmented reality. But these products are amazing. You can you can help factory workers people on, uh, people who are left out of the digital transformation. Sometimes we're standing from machine >>all day. >>They can't be sitting like we are doing Zoom. They can wear a R headset in our tools, let them create great content. This is an area Dana is invested in other companies. But what I wanted to note is the new releases of our authoring software. For this, our content getting released this month, used through the Atlas platform, the SAS components of on shape for things like revision management and collaboration on duh workflow activity. All that those are tools that we're able to share leverage. We get a lot of synergy. It's just really good. It's really fun to have a good time. That's >>awesome. And then we're gonna be talking to John MacLean later about that. Let's do a little deeper Dive on that. And, Dana, what is your involvement today with with on shape? But you're looking for you know, which of their customers air actually adopting. And they're gonna disrupt their industries. And you get good pipeline from that. How do you collaborate today? >>That sounds like a great idea. Um, Aziz, John will tell you I'm constantly just asking him for advice and impressions of other entrepreneurs and picking his brain on ideas. No formal relationship clearly, but continue to count John and and John and other people in on shaping in the circle of experts that I rely on for their opinions. >>All right, so we have some questions from the crowd here. Uh, one of the questions is for the dream team. You know, John and Dana. What's your next next collective venture? I don't think we're there yet, are we? No. >>I just say, as Dana said, we love talking to her about. You know, Dana, you just returned the compliment. We would try and give you advice and the deals you're looking at, and I'm sort of casually mentoring at least one of your portfolio entrepreneurs, and that's been a lot of fun for May on, hopefully a value to them. But also Dana. We uran important pipeline to us in the world of some new things that are happening that we wouldn't see if you know you've shown us some things that you've said. What do you think of this business? And for us, it's like, Wow, it's cool to see that's going on And that's what's supposed to work in an ecosystem like this. So we we deeply value the ongoing relationship. And no, we're not starting something new. I got a lot of work left to do with what I'm doing and really happy. But we can We can collaborate in this way on other ventures. >>I like this question to somebody asking With the cloud options like on shape, Wilmore students have stem opportunities s Oh, that's a great question. Are you because of sass and cloud? Are you able to reach? You know, more students? Much more cost effectively. >>Yeah, Dave, I'm so glad that that that I was asked about this because Yes, and it's extremely gratified us. Yes, we are because of cloud, because on shape is the only full cloud full SAS system or industry were able to reach. Stem education brings able to be part of bringing step education to students who couldn't get it otherwise. And one of most gratifying gratifying things to me is the emails were getting from teachers, um, that that really, um, on the phone calls that were they really pour their heart out and say We're able to get to students in areas that have very limited compute resource is that don't have an I T staff where they don't know what computer that the students can have at home, and they probably don't even have a computer. We're talking about being able to teach them on a phone to have an android phone a low end android phone. You can do three D modeling on there with on shape. Now you can't do it any other system, but with on shape, you could do it. And so the teacher can say to the students, They have to have Internet access, and I know there's a huge community that doesn't even have Internet access, and we're not able, unfortunately to help that. But if you have Internet and you have even an android phone, we can enable the educator to teach them. And so we have case after case of saving a stem program or expanding it into the students that need it most is the ones we're helping here. So really excited about that. And we're also able to let in addition to the run on run on whatever computing devices they have, we also offer them the tools they need for remote teaching with a much richer experience. Could you teach solid works remotely? Well, maybe if the student ran it had a windows workstation. You know, big, big, high end workstation. Maybe it could, but it would be like the difference between collaborating with on shape and collaborate with solid works. Like the difference between a zoom video call and talking on the landline phone. You know, it's a much richer experience, and that's what you need. And stem teaching stem is hard, So yeah, we're super super. Um, I'm excited about bringing stem to more students because of cloud yond >>we're talking about innovation for good, and then the discussion, John, you just had it. Really? There could be a whole another vector here. We could discuss on diversity, and I wanna end with just pointing out. So, Dana, your new firm, it's a woman led firm, too. Two women leaders, you know, going forward. So that's awesome to see, so really? Yeah, thumbs up on that. Congratulations on getting that off the ground. >>Thank you. Thank you. >>Okay, so thank you guys. Really appreciate It was a great discussion. I learned a lot and I'm sure the audience did a swell in a moment. We're gonna talk with on shaped customers to see how they're applying tech for good and some of the products that they're building. So keep it right there. I'm Dave Volonte. You're watching innovation for good on the Cube, the global leader in digital tech event coverage. Stay right there. >>Oh, yeah, it's >>yeah, yeah, around >>the globe. It's the Cube presenting innovation for good. Brought to you by on shape. >>Okay, we're back. This is Dave Volonte and you're watching innovation for good. A program on Cuba 3 65 made possible by on shape of PTC company. We're live today really live tv, which is the heritage of the Cube. And now we're gonna go to the sources and talkto on shape customers to find out how they're applying technology to create real world innovations that are changing the world. So let me introduce our panel members. Rafael Gomez Furberg is with the Chan Zuckerberg bio hub. A very big idea. And collaborative nonprofit was initiative that was funded by Mark Zuckerberg and his wife, Priscilla Chan, and really around diagnosing and curing and better managing infectious diseases. So really timely topic. Philip Tabor is also joining us. He's with silver side detectors, which develops neutron detective detection systems. Yet you want to know if early, if neutrons and radiation or in places where you don't want them, So this should be really interesting. And last but not least, Matthew Shields is with the Charlottesville schools and is gonna educate us on how he and his team are educating students in the use of modern engineering tools and techniques. Gentlemen, welcome to the Cuban to the program. This should be really interesting. Thanks for coming on. >>Hi. Or pleasure >>for having us. >>You're very welcome. Okay, let me ask each of you because you're all doing such interesting and compelling work. Let's start with Rafael. Tell us more about the bio hub and your role there, please. >>Okay. Yeah. So you said that I hope is a nonprofit research institution, um, funded by Mark Zuckerberg and his wife, Priscilla Chan. Um, and our main mission is to develop new technologies to help advance medicine and help, hopefully cure and manage diseases. Um, we also have very close collaborations with Universe California, San Francisco, Stanford University and the University California Berkeley on. We tried to bring those universities together, so they collaborate more of biomedical topics. And I manage a team of engineers. They by joining platform. Um, and we're tasked with creating instruments for the laboratory to help the scientist boats inside the organization and also in the partner universities Do their experiments in better ways in ways that they couldn't do before >>in this edition was launched Well, five years ago, >>it was announced at the end of 2016, and we actually started operation with at the beginning of 2017, which is when I joined, um, So this is our third year. >>And how's how's it going? How does it work? I mean, these things take time. >>It's been a fantastic experience. Uh, the organization works beautifully. Um, it was amazing to see it grow From the beginning, I was employee number 12, I think eso When I came in, it was just a nem P office building and empty labs. And very quickly we had something running about. It's amazing eso I'm very proud of the work that we have done to make that possible. Um And then, of course, that's you mentioned now with co vid, um, we've been able to do a lot of very cool work attire being of the pandemic in March, when there was a deficit of testing, uh, capacity in California, we spun up a testing laboratory in record time in about a week. It was crazy. It was a crazy project, Um, but but incredibly satisfying. And we ended up running all the way until the beginning of November, when the lab was finally shut down. We could process about 3000 samples a day. I think at the end of it all, we were able to test about 100 on the order of 100 and 50,000 samples from all over the state. We were providing free testing toe all of the Department of Public Health Department of Public Health in California, which at the media pandemic, had no way to do testing affordably and fast. So I think that was a great service to the state. Now the state has created that testing system that would serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down. >>All right. Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe describe a little bit more about silver sod detectors and what your role is there and how it all works. >>Tour. So we make a nuclear bomb detectors and we also make water detectors. So we try and do our part thio keep the world from blowing up and make it a better place at the same time. Both of these applications use neutron radiation detectors. That's what we make. Put them out by import border crossing places like that. They can help make sure that people aren't smuggling. Shall we say very bad things. Um, there's also a burgeoning field of research and application where you can use neutrons with some pretty cool physics to find water so you could do things. Like what? A detector up in the mountains and measure snowpack. Put it out in the middle of the field and measure soil moisture content. And as you might imagine, there's some really cool applications in, uh, research and agronomy and public policy for this. >>All right, so it's OK, so it's a It's much more than, you know, whatever fighting terrorism, it's there's a riel edge or I kind of i o t application for what you guys >>do. We do both its's to plowshares. You might >>say a mat. I I look at your role is kind of scaling the brain power for for the future. Maybe tell us more about Charlottesville schools and in the mission that you're pursuing and what you do. >>Thank you. Um, I've been in Charlottesville City schools for about 11 or 12 years. I started their teaching, um, a handful of classes, math and science and things like that. But Thescore board and my administration had the crazy idea of starting an engineering program about seven years ago. My background is an engineering is an engineering. My masters is in mechanical and aerospace engineering and um, I basically spent a summer kind of coming up with what might be a fun engineering curriculum for our students. And it started with just me and 30 students about seven years ago, Um, kind of a home spun from scratch curriculum. One of my goals from the outset was to be a completely project based curriculum, and it's now grown. We probably have about six or 700 students, five or six full time teachers. We now have pre engineering going on at the 5th and 6th grade level. I now have students graduating. Uh, you know, graduating after senior year with, like, seven years of engineering under their belt and heading off to doing some pretty cool stuff. So it's It's been a lot of fun building a program and, um, and learning a lot in the process. >>That's awesome. I mean, you know, Cuba's. We've been passionate about things like women in tech, uh, diversity stem. You know, not only do we need more, more students and stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John Herstek and integrate gration about this is Do you do you feel is though you're I mean, first of all, the work that you do is awesome, but but I'll go one step further. Do you feel as though it's reaching, um, or diverse base? And how is that going? >>That's a great question. I think research shows that a lot of people get funneled into one kind of track or career path or set of interests really early on in their educational career, and sometimes that that funnel is kind of artificial. And so that's one of the reasons we keep pushing back. Um, so our school systems introducing kindergartners to programming on DSO We're trying to push back how we expose students to engineering and to stem fields as early as possible. And we've definitely seen the first of that in my program. In fact, my engineering program, uh, sprung out of an after school in Extracurricular Science Club that actually three girls started at our school. So I think that actually has helped that three girls started the club that eventually is what led to our engineering programs that sort of baked into the DNA and also our eyes a big public school. And we have about 50% of the students are under the poverty line and we e in Charlottesville, which is a big refugee town. And so I've been adamant from Day one that there are no barriers to entry into the program. There's no test you have to take. You don't have to have be taking a certain level of math or anything like that. That's been a lot of fun. To have a really diverse set of kids enter the program and be successful, >>that's final. That's great to hear. So, Philip, I wanna come back to you. You know, I think about maybe some day we'll be able to go back to a sporting events, and I know when I when I'm in there, there's somebody up on the roof looking out for me, you know, watching the crowd, and they have my back. And I think in many ways, the products that you build, you know, our similar. I may not know they're there, but they're keeping us safe or they're measuring things that that that I don't necessarily see. But I wonder if you could talk about a little bit more detail about the products you build and how they're impacting society. >>Sure, so There are certainly a lot of people who are who are watching, trying to make sure things were going well in keeping you safe that you may or may not be aware of. And we try and support ah lot of them. So we have detectors that are that are deployed in a variety of variety of uses, with a number of agencies and governments that dio like I was saying, ports and border crossing some other interesting applications that are looking for looking for signals that should not be there and working closely to fit into the operations these folks do. Onda. We also have a lot of outreach to researchers and scientists trying to help them support the work they're doing. Um, using neutron detection for soil moisture monitoring is a some really cool opportunities for doing it at large scale and with much less, um, expense or complication than would have been done. Previous technologies. Um, you know, they were talking about collaboration in the previous segment. We've been able to join a number of conferences for that, virtually including one that was supposed to be held in Boston, but another one that was held out of the University of Heidelberg in Germany. And, uh, this is sort of things that in some ways, the pandemic is pushing people towards greater collaboration than they would have been able to do. Had it all but in person. >>Yeah, we did. Uh, the cube did live works a couple years ago in Boston. It was awesome show. And I think, you know, with this whole trend toward digit, I call it the Force march to digital. Thanks to cove it I think that's just gonna continue. Thio grow. Rafael. What if you could describe the process that you use to better understand diseases? And what's your organization's involvement? Been in more detail, addressing the cove in pandemic. >>Um, so so we have the bio be structured in, Um um in a way that foster so the combination of technology and science. So we have to scientific tracks, one about infectious diseases and the other one about understanding just basic human biology, how the human body functions, and especially how the cells in the human body function on how they're organized to create tissues in the body. On Ben, it has this set of platforms. Um, mind is one of them by engineering that are all technology rated. So we have data science platform, all about data analysis, machine learning, things like that. Um, we have a mass spectrometry platform is all about mass spectrometry technologies to, um, exploit those ones in service for the scientist on. We have a genomics platform that it's all about sequencing DNA and are gonna, um and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and developed technologies to marry computation on microscopy. So, um, the scientists set the agenda and the platforms, we just serve their needs, support their needs, and hopefully develop technologies that help them do their experiments better, faster, or allow them to the experiment that they couldn't do in any other way before. Um And so with cove, it because we have that very strong group of scientists that work on have been working on infectious disease before, and especially in viruses, we've been able to very quickly pivot to working on that s O. For example, my team was able to build pretty quickly a machine to automatically purified proteins on is being used to purify all these different important proteins in the cove. It virus the SARS cov to virus Onda. We're sending some of those purified proteins all over the world. Two scientists that are researching the virus and trying to figure out how to develop vaccines, understand how the virus affects the body and all that. Um, so some of the machines we built are having a very direct impact on this. Um, Also for the copy testing lab, we were able to very quickly develop some very simple machines that allowed the lab to function sort of faster and more efficiently. Sort of had a little bit of automation in places where we couldn't find commercial machines that would do it. >>Um, eso Matt. I mean, you gotta be listening to this and thinking about Okay, So someday your students are gonna be working at organizations like like, like Bio Hub and Silver Side. And you know, a lot of young people they're just don't know about you guys, but like my kids, they're really passionate about changing the world. You know, there's way more important than you know, the financial angles and it z e. I gotta believe you're seeing that you're right in the front lines there. >>Really? Um, in fact, when I started the curriculum six or seven years ago, one of the first bits of feedback I got from my students is they said Okay, this is a lot of fun. So I had my students designing projects and programming microcontrollers raspberry, PiS and order we nose and things like that. The first bit of feedback I got from students was they said Okay, when do we get to impact the world? I've heard engineering >>is about >>making the world a better place, and robots are fun and all, but, you know, where is the real impact? And so um, dude, yeah, thanks to the guidance of my students, I'm baking that Maurin. Now I'm like day one of engineering one. We talk about how the things that the tools they're learning and the skills they're gaining, uh, eventually, you know, very soon could be could be used to make the world a better place. >>You know, we all probably heard that famous line by Jeff Hammer Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. I think we're really generally generationally, finally, at the point where young students and engineering a really, you know, a passionate about affecting society. I wanna get into the product, you know, side and understand how each of you are using on shape and and the value that that it brings. Maybe Raphael, you could start how long you've been using it. You know, what's your experience with it? Let's let's start there. >>I begin for about two years, and I switched to it with some trepidation. You know, I was used to always using the traditional product that you have to install on your computer, that everybody uses that. So I was kind of locked into that. But I started being very frustrated with the way it worked, um, and decided to give on ship chance. Which reputation? Because any change always, you know, causes anxiety. Um, but very quickly my engineers started loving it, Uh, just because it's it's first of all, the learning curve wasn't very difficult at all. You can transfer from one from the traditional product to entree very quickly and easily. You can learn all the concepts very, very fast. It has all the functionality that we needed and and what's best is that it allows to do things that we couldn't do before or we couldn't do easily. Now we can access the our cat documents from anywhere in the world. Um, so when we're in the lab fabricating something or testing a machine, any computer we have next to us or a tablet or on iPhone, we can pull it up and look at the cad and check things or make changes. That's something that couldn't do before because before you had to pay for every installation off the software for the computer, and I couldn't afford to have 20 installations to have some computers with the cat ready to use them like once every six months would have been very inefficient. So we love that part. And the collaboration features are fantastic, especially now with Kobe, that we have to have all the remote meetings eyes fantastic, that you can have another person drive the cad while the whole team is watching that person change the model and do things and point to things that is absolutely revolutionary. We love it. The fact that you have very, very sophisticated version control before it was always a challenge asking people, please, if you create anniversary and apart, how do we name it so that people find it? And then you end up with all these collection of files with names that nobody ever remembers, what they are, the person left. And now nobody knows which version is the right one. A mess with on shape on the version ING system it has, and the fact that you can go back in history off the document and go back to previous version so easily and then go back to the press and version and explore the history of the part that is truly, um, just world changing for us, that we can do that so easily on for me as a manager to manage this collection of information that is critical for our operations. It makes it so much easier because everything is in one place. I don't have to worry about file servers that go down that I have to administer that have to have I t taken care off that have to figure how to keep access to people to those servers when they're at home, and they need a virtual private network and all of that mess disappears. I just simply give give a person in accounting on shape and then magically, they have access to everything in the way I want. And we can manage the lower documents and everything in a way that is absolutely fantastic. >>Feel what was your what? What were some of the concerns you had mentioned? You had some trepidation. Was it a performance? Was it security? You know some of the traditional cloud stuff, and I'm curious as to how, How, whether any of those act manifested really that you had to manage. What were your concerns? >>Look, the main concern is how long is it going to take for everybody in the team to learn to use the system like it and buy into it? Because I don't want to have my engineers using tools against their will write. I want everybody to be happy because that's how they're productive. They're happy, and they enjoyed the tools they have. That was my main concern. I was a little bit worried about the whole concept of not having the files in a place where I couldn't quote unquote seat in some server and on site, but that That's kind of an outdated concept, right? So that took a little bit of a mind shift, but very quickly. Then I started thinking, Look, I have a lot of documents on Google Drive. Like, I don't worry about that. Why would I worry about my cat on on shape, right? Is the same thing. So I just needed to sort of put things in perspective that way. Um, the other, um, you know, the concern was the learning curve, right? Is like, how is he Will be for everybody to and for me to learn it on whether it had all of the features that we needed. And there were a few features that I actually discussed with, um uh, Cody at on shape on, they were actually awesome about using their scripting language in on shape to sort of mimic some of the features of the old cat, uh, in on, shaped in a way that actually works even better than the old system. So it was It was amazing. Yeah, >>Great. Thank you for that, Philip. What's your experience been? Maybe you could take us through your journey within shape. >>Sure. So we've been we've been using on shaped silver side for coming up on about four years now, and we love it. We're very happy with it. We have a very modular product line, so we make anything from detectors that would go into backpacks. Two vehicles, two very large things that a shipping container would go through and saw. Excuse me. Shape helps us to track and collaborate faster on the design. Have multiple people working a same time on a project. And it also helps us to figure out if somebody else comes to us and say, Hey, I want something new how we congrats modules from things that we already have put them together and then keep track of the design development and the different branches and ideas that we have, how they all fit together. A za design comes together, and it's just been fantastic from a mechanical engineering background. I will also say that having used a number of different systems and solid works was the greatest thing since sliced bread. Before I got using on shape, I went, Wow, this is amazing and I really don't want to design in any other platform. After after getting on Lee, a little bit familiar with it. >>You know, it's funny, right? I'll have the speed of technology progression. I was explaining to some young guns the other day how I used to have a daytime er and that was my life. And if I lost that daytime, er I was dead. And I don't know how we weigh existed without, you know, Google maps eso we get anywhere, I don't know, but, uh but so So, Matt, you know, it's interesting to think about, you know, some of the concerns that Raphael brought up, you hear? For instance, you know, all the time. Wow. You know, I get my Amazon bill at the end of the month that zip through the roof in, But the reality is that Yeah, well, maybe you are doing more, but you're doing things that you couldn't have done before. And I think about your experience in teaching and educating. I mean, you so much more limited in terms of the resource is that you would have had to be able to educate people. So what's your experience been with With on shape and what is it enabled? >>Um, yeah, it was actually talking before we went with on shape. We had a previous CAD program, and I was talking to my vendor about it, and he let me know that we were actually one of the biggest CAD shops in the state. Because if you think about it a really big program, you know, really big company might employ. 5, 10, 15, 20 cad guys, right? I mean, when I worked for a large defense contractor, I think there were probably 20 of us as the cad guys. I now have about 300 students doing cat. So there's probably more students with more hours of cat under their belt in my building than there were when I worked for the big defense contractor. Um, but like you mentioned, uh, probably our biggest hurdle is just re sources. And so we want We want one of things I've always prided myself and trying to do in this. Programs provide students with access two tools and skills that they're going to see either in college or in the real world. So it's one of the reason we went with a big professional cad program. There are, you know, sort of K 12 oriented software and programs and things. But, you know, I want my kids coding and python and using slack and using professional type of tools on DSO when it comes to cat. That's just that That was a really hurt. I mean, you know, you could spend $30,000 on one seat of, you know, professional level cad program, and then you need a $30,000 computer to run it on if you're doing a heavy assemblies, Um and so one of my dreams And it was always just a crazy dream. And I was the way I would always pitcher in my school system and say, someday I'm gonna have a kid on a school issued chromebook in subsidized housing, on public WiFi doing professional level bad and that that was a crazy statement until a couple of years ago. So we're really excited that I literally and you know, March and you said the forced march, the forced march into, you know, modernity, March 13th kids sitting in my engineering lab that we spent a lot of money on doing cad March 14th. Those kids were at home on their school issued chromebooks on public WiFi, uh, keeping their designs going and collaborating. And then, yeah, I could go on and on about some of the things you know, the features that we've learned since then they're even better. So it's not like this is some inferior, diminished version of Academy. There's so much about it. Well, I >>wanna I wanna ask you that I may be over my skis on this, but we're seeing we're starting to see the early days of the democratization of CAD and product design. It is the the citizen engineer, I mean, maybe insulting to the engineers in the room, But but is that we're beginning to see that >>I have to believe that everything moves into the cloud. Part of that is democratization that I don't need. I can whether you know, I think artists, you know, I could have a music studio in my basement with a nice enough software package. And Aiken, I could be a professional for now. My wife's a photographer. I'm not allowed to say that I could be a professional photographer with, you know, some cloud based software, and so, yeah, I do think that's part of what we're seeing is more and more technology is moving to the cloud. >>Philip. Rafael Anything you Dad, >>I think I mean, yeah, that that that combination of cloud based cat and then three d printing that is becoming more and more affordable on ubiquitous It's truly transformative, and I think for education is fantastic. I wish when I was a kid I had the opportunity to play with those kinds of things because I was always the late things. But, you know, the in a very primitive way. So, um, I think this is a dream for kids. Teoh be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino on all of these electronic things that live kids play at home very cheaply with things that back in my day would have been unthinkable. >>So we know there's a go ahead. Philip, please. >>We had a pandemic and silver site moved to a new manufacturing facility this year. I was just on the shop floor, talking with contractors, standing 6 ft apart, pointing at things. But through it all, our CAD system was completely unruffled. Nothing stopped in our development work. Nothing stopped in our support for existing systems in the field. We didn't have to think about it. We had other server issues, but none with our, you know, engineering cad, platform and product development in support world right ahead, which was cool, but also a in that's point. I think it's just really cool what you're doing with the kids. The most interesting secondary and college level engineering work that I did was project based, taken important problem to the world. Go solve it and that is what we do here. That is what my entire career has been. And I'm super excited to see. See what your students are going to be doing, uh, in there home classrooms on their chromebooks now and what they do building on that. >>Yeah, I'm super excited to see your kids coming out of college with engineering degrees because, yeah, I think that Project based experience is so much better than just sitting in a classroom, taking notes and doing math problems on day. I think it will give the kids a much better flavor. What engineering is really about Think a lot of kids get turned off by engineering because they think it's kind of dry because it's just about the math for some very abstract abstract concept on they are there. But I think the most important thing is just that hands on a building and the creativity off, making things that you can touch that you can see that you can see functioning. >>Great. So, you know, we all know the relentless pace of technology progression. So when you think about when you're sitting down with the folks that on shape and there the customer advisor for one of the things that that you want on shape to do that it doesn't do today >>I could start by saying, I just love some of the things that does do because it's such a modern platform. And I think some of these, uh, some some platforms that have a lot of legacy and a lot of history behind them. I think we're dragging some of that behind them. So it's cool to see a platform that seemed to be developed in the modern era, and so that Z it is the Google docks. And so the fact that collaboration and version ing and link sharing is and like platform agnostic abilities, the fact that that seems to be just built into the nature of the thing so far, That's super exciting. As far as things that, uh, to go from there, Um, I don't know, >>Other than price. >>You can't say >>I >>can't say lower price. >>Yeah, so far on P. D. C. S that work with us. Really? Well, so I'm not complaining. There you there, >>right? Yeah. Yeah. No gaps, guys. Whitespace, Come on. >>We've been really enjoying the three week update. Cadence. You know, there's a new version every three weeks and we don't have to install it. We just get all the latest and greatest goodies. One of the trends that we've been following and enjoying is the the help with a revision management and release work flows. Um, and I know that there's more than on shape is working on that we're very excited for, because that's a big important part about making real hardware and supporting it in the field. Something that was cool. They just integrated Cem markup capability. In the last release that took, we were doing that anyway, but we were doing it outside of on shapes. And now we get to streamline our workflow and put it in the CAD system where We're making those changes anyway when we're reviewing drawings and doing this kind of collaboration. And so I think from our perspective, we continue to look forward. Toa further progress on that. There's a lot of capability in the cloud that I think they're just kind of scratching the surface on you, >>right? I would. I mean, you're you're asking to knit. Pick. I would say one of the things that I would like to see is is faster regeneration speed. There are a few times with convicts, necessities that regenerating the document takes a little longer than I would like. It's not a serious issue, but anyway, I I'm being spoiled, >>you know? That's good. I've been doing this a long time, and I like toe ask that question of practitioners and to me, it It's a signal like when you're nit picking and that's what you're struggling to knit. Pick that to me is a sign of a successful product, and and I wonder, I don't know, uh, have the deep dive into the architecture. But are things like alternative processors. You're seeing them hit the market in a big way. Uh, you know, maybe helping address the challenge, But I'm gonna ask you the big, chewy question now. Then we maybe go to some audience questions when you think about the world's biggest problems. I mean, we're global pandemics, obviously top of mind. You think about nutrition, you know, feeding the global community. We've actually done a pretty good job of that. But it's not necessarily with the greatest nutrition, climate change, alternative energy, the economic divides. You've got geopolitical threats and social unrest. Health care is a continuing problem. What's your vision for changing the world and how product innovation for good and be applied to some of the the problems that that you all are passionate about? Big question. Who wants toe start? >>Not biased. But for years I've been saying that if you want to solve the economy, the environment, uh, global unrest, pandemics, education is the case. If you wanna. If you want to, um, make progress in those in those realms, I think funding funding education is probably gonna pay off pretty well. >>Absolutely. And I think Stam is key to that. I mean, all of the ah lot of the well being that we have today and then industrialized countries. Thanks to science and technology, right improvements in health care, improvements in communication, transportation, air conditioning. Um, every aspect of life is touched by science and technology. So I think having more kids studying and understanding that is absolutely key. Yeah, I agree, >>Philip, you got anything to add? >>I think there's some big technical problems in the world today, Raphael and ourselves there certainly working on a couple of them. Think they're also collaboration problems and getting everybody to be able to pull together instead of pulling separately and to be able to spur the ideas on words. So that's where I think the education side is really exciting. What Matt is doing and it just kind of collaboration in general when we could do provide tools to help people do good work. Uh, that is, I think, valuable. >>Yeah, I think that's a very good point. And along those lines, we have some projects that are about creating very low cost instruments for low research settings, places in Africa, Southeast Asia, South America, so that they can do, um, um, biomedical research that it's difficult to do in those place because they don't have the money to buy the fancy lab machines that cost $30,000 an hour. Um, so we're trying to sort of democratize some of those instruments. And I think thanks to tools like Kahn shape then is easier, for example, to have a conversation with somebody in Africa and show them the design that we have and discuss the details of it with them on. But it's amazing, right to have somebody, you know, 10 time zones away, Um, looking really life in real time with you about your design and discussing the details or teaching them how to build a machine, right? Because, um, you know, they have a three D printer. You can you can just give them the design and say like, you build it yourself, uh, even cheaper than and, you know, also billing and shipping it there. Um, so all that that that aspect of it is also super important. I think for any of these efforts to improve some of the hardest part was in the world for climate change. Do you say, as you say, poverty, nutrition issues? Um, you know, availability of water. You have that project at about finding water. Um, if we can also help deploy technologies that teach people remotely how to create their own technologies or how to build their own systems that will help them solve those forms locally. I think that's very powerful. >>Yeah, the point about education is right on. I think some people in the audience may be familiar with the work of Erik Brynjolfsson and Andrew McAfee, the second machine age where they sort of put forth the premise that, uh, is it laid it out. Look, for the first time in history, machines air replacing humans from a cognitive perspective. Machines have always replaced humans, but that's gonna have an impact on jobs. But the answer is not toe protect the past from the future. The answer is education and public policy that really supports that. So I couldn't agree more. I think it's a really great point. Um, we have We do have some questions from the audience. If if we could If I can ask you guys, um, you know, this one kind of stands out. How do you see artificial intelligence? I was just talking about machine intelligence. Um, how do you see that? Impacting the design space guys trying to infuse a I into your product development. Can you tell me? >>Um, absolutely, like, we're using AI for some things, including some of these very low cost instruments that will hopefully help us diagnose certain diseases, especially this is that are very prevalent in the Third World. Um, and some of those diagnostics are these days done by thes armies of technicians that are trained to look under the microscope. But, um, that's a very slow process. Is very error prone and having machine learning systems that can to the same diagnosis faster, cheaper and also little machines that can be taken to very remote places to these villages that have no access to a fancy microscope. To look at a sample from a patient that's very powerful. And I we don't do this, but I have read quite a bit about how certain places air using a Tribune attorneys to actually help them optimize designs for parts. So you get these very interesting looking parts that you would have never thought off a person would have never thought off, but that are incredibly light ink. Earlier, strong and I have all sort of properties that are interesting thanks to artificial intelligence machine learning in particular >>yet another. The advantage you get when when your work is in the cloud I've seen. I mean, there's just so many applications that so if the radiology scan is in the cloud and the radiologist is goes to bed at night, Radiologist could come in in the morning and and say, Oh, the machine while you were sleeping was using artificial intelligence to scan these 40,000 images. And here's the five that we picked out that we think you should take a closer look at. Or like Raphael said, I can design my part. My, my, my, my, my you know, mount or bracket or whatever and go to sleep. And then I wake up in the morning. The machine has improved. It for me has made it strider strider stronger and lighter. Um And so just when your when your work is in the cloud, that's just that's a really cool advantage that you get that you can have machines doing some of your design work for you. >>Yeah, we've been watching, uh, you know, this week is this month, I guess is AWS re invent and it's just amazing to see how much effort is coming around machine learning machine intelligence. You know Amazon has sage maker Google's got, you know, embedded you no ML and big query. Uh, certainly Microsoft with Azure is doing tons of stuff and machine learning. I think the point there is that that these things will be infused in tow R and D and in tow software product by the vendor community. And you all will apply that to your business and and build value through the unique data that your collecting, you know, in your ecosystems. And and that's how you add value. You don't have to be necessarily, you know, developers of artificial intelligence, but you have to be practitioners to apply that. Does that make sense to you, Philip? >>Yeah, absolutely. And I think your point about value is really well chosen. We see AI involved from the physics simulations all the way up to interpreting radiation data, and that's where the value question, I think, is really important because it's is the output of the AI giving helpful information that the people that need to be looking at it. So if it's curating a serious of radiation alert, saying, Hey, like these air the anomalies. You need to look at eyes it, doing that in a way that's going to help a good response on. In some cases, the II is only as good as the people. That sort of gave it a direction and turn it loose. And you want to make sure that you don't have biases or things like that underlying your AI that they're going to result in less than helpful outcomes coming from it. So we spend quite a lot of time thinking about how do we provide the right outcomes to people who are who are relying on our systems? >>That's a great point, right? Humans air biased and humans build models, so models are inherently biased. But then the software is hitting the market. That's gonna help us identify those biases and help us, you know? Of course. Correct. So we're entering Cem some very exciting times, guys. Great conversation. I can't thank you enough for spending the time with us and sharing with our audience the innovations that you're bringing to help the world. So thanks again. >>Thank you so much. >>Thank you. >>Okay. Welcome. Okay. When we come back, John McElheny is gonna join me. He's on shape. Co founder. And he's currently the VP of strategy at PTC. He's gonna join the program. We're gonna take a look at what's next and product innovation. I'm Dave Volonte and you're watching innovation for good on the Cube, the global leader. Digital technology event coverage. We'll be right back. >>Okay? Okay. Yeah. Okay. >>From around >>the globe, it's the Cube. Presenting innovation for good. Brought to you by on shape. >>Okay, welcome back to innovation. For good. With me is John McElheny, who is one of the co founders of On Shape and is now the VP of strategy at PTC. John, it's good to see you. Thanks for making the time to come on the program. Thanks, Dave. So we heard earlier some of the accomplishments that you've made since the acquisition. How has the acquisition affected your strategy? Maybe you could talk about what resource is PTC brought to the table that allowed you toe sort of rethink or evolve your strategy? What can you share with us? >>Sure. You know, a year ago, when when John and myself met with Jim Pepperman early on is we're we're pondering. Started joining PTC one of things became very clear is that we had a very clear shared vision about how we could take the on shape platform and really extended for, for all of the PTC products, particular sort of their augmented reality as well as their their thing works or the i o. T business and their product. And so from the very beginning there was a clear strategy about taking on shape, extending the platform and really investing, um, pretty significantly in the product development as well as go to market side of things, uh, toe to bring on shape out to not only the PTC based but sort of the broader community at large. So So So PTC has been a terrific, terrific, um, sort of partner as we've we've gonna go on after this market together. Eso We've added a lot of resource and product development side of things. Ah, lot of resource and they go to market and customer success and support. So, really, on many fronts, that's been both. Resource is as well a sort of support at the corporate level from from a strategic standpoint and then in the field, we've had wonderful interactions with many large enterprise customers as well as the PTC channels. So it's been really a great a great year. >>Well, and you think about the challenges of in your business going to SAS, which you guys, you know, took on that journey. You know, 78 years ago. Uh, it's not trivial for a lot of companies to make that transition, especially a company that's been around as long as PTC. So So I'm wondering how much you know, I was just asking you How about what PCP TC brought to the table? E gotta believe you're bringing a lot to the table to in terms of the mindset, uh, even things is, is mundane is not the right word, but things like how you compensate salespeople, how you interact with customers, the notion of a service versus a product. I wonder if you could address >>that. Yeah, it's a it's a really great point. In fact, after we had met Jim last year, John and I one of the things we walked out in the seaport area in Boston, one of things we sort of said is, you know, Jim really gets what we're trying to do here and and part of let me bring you into the thinking early on. Part of what Jim talked about is there's lots of, you know, installed base sort of software that's inside of PTC base. That's helped literally thousands of customers around the world. But the idea of moving to sass and all that it entails both from a technology standpoint but also a cultural standpoint. Like How do you not not just compensate the sales people as an example? But how do you think about customer success? In the past, it might have been that you had professional services that you bring out to a customer, help them deploy your solutions. Well, when you're thinking about a SAS based offering, it's really critical that you get customers successful with it. Otherwise, you may have turned, and you know it will be very expensive in terms of your business long term. So you've got to get customers success with software in the very beginning. So you know, Jim really looked at on shape and he said that John and I, from a cultural standpoint, you know, a lot of times companies get acquired and they've acquired technology in the past that they integrate directly into into PTC and then sort of roll it out through their products, are there just reached channel, he said. In some respects, John John, think about it as we're gonna take PTC and we want to integrate it into on shape because we want you to share with us both on the sales side and customer success on marketing on operations. You know all the things because long term, we believe the world is a SAS world, that the whole industry is gonna move too. So really, it was sort of an inverse in terms of the thought process related to normal transactions >>on That makes a lot of sense to me. You mentioned Sharon turns the silent killer of a SAS company, and you know, there's a lot of discussion, you know, in the entrepreneurial community because you live this, you know what's the best path? I mean today, You see, you know, if you watch Silicon Valley double, double, triple triple, but but there's a lot of people who believe, and I wonder, if you come in there is the best path to, you know, in the X Y axis. If if it's if it's uh, growth on one and retention on the other axis. What's the best way to get to the upper right on? Really? The the best path is probably make sure you've nailed obviously the product market fit, But make sure that you can retain customers and then throw gas on the fire. You see a lot of companies they burn out trying to grow too fast, but they haven't figured out, you know that. But there's too much churn. They haven't figured out those metrics. I mean, obviously on shape. You know, you were sort of a pioneer in here. I gotta believe you've figured out that customer retention before you really, You know, put the pedal to the >>metal. Yeah, and you know, growth growth can mask a lot of things, but getting getting customers, especially the engineering space. Nobody goes and sits there and says, Tomorrow we're gonna go and and, you know, put 100 users on this and and immediately swap out all of our existing tools. These tools are very rich and deep in terms of capability, and they become part of the operational process of how a company designs and builds products. So any time anybody is actually going through the purchasing process. Typically, they will run a try along or they'll run a project where they look at. Kind of What? What is this new solution gonna help them dio. How are we gonna orient ourselves for success? Longer term. So for us, you know, getting new customers and customer acquisition is really critical. But getting those customers to actually deploy the solution to be successful with it. You know, we like to sort of, say, the marketing or the lead generation and even some of the initial sales. That's sort of like the Kindle ing. But the fire really starts when customers deploy it and get successful. The solution because they bring other customers into the fold. And then, of course, if they're successful with it, you know, then in fact, you have negative turn which, ironically, means growth in terms of your inside of your install. Bates. >>Right? And you've seen that with some of the emerging, you know, SAS companies, where you're you're actually you know, when you calculate whatever its net retention or renew ALS, it's actually from a dollar standpoint. It's up in the high nineties or even over 100%. >>So >>and that's a trend we're gonna continue. See, I >>wonder >>if we could sort of go back. Uh, and when you guys were starting on shape, some of the things that you saw that you were trying to strategically leverage and what's changed, you know, today we were talking. I was talking to John earlier about in a way, you kinda you kinda got a blank slate is like doing another startup. >>You're >>not. Obviously you've got installed base and customers to service, but But it's a new beginning for you guys. So one of the things that you saw then you know, cloud and and sas and okay, but that's we've been there, done that. What are you seeing? You know today? >>Well, you know, So So this is a journey, of course, that that on shape on its own has gone through it had I'll sort of say, you know, several iterations, both in terms of of of, you know, how do you How do you get customers? How do you How do you get them successful? How do you grow those customers? And now that we've been part of PTC, the question becomes okay. One, There is certainly a higher level of credibility that helps us in terms of our our megaphone is much bigger than it was when we're standalone company. But on top of that now, figuring out how to work with their channel with their direct sales force, you know, they have, um, for example, you know, very large enterprises. Well, many of those customers are not gonna go in forklift out their existing solution to replace it with with on shape. However, many of them do have challenges in their supply chain and communications with contractors and vendors across the globe. And so, you know, finding our fit inside of those large enterprises as they extend out with their their customers is a very interesting area that we've really been sort of incremental to to PTC. And then, you know, they they have access to lots of other technology, like the i o. T business. And now, of course, the augmented reality business that that we can bring things to bear. For example, in the augmented reality world, they've they've got something called expert capture. And this is essentially imagine, you know, in a are ah, headset that allows you to be ableto to speak to it, but also capture images still images in video. And you could take somebody who's doing their task and capture literally the steps that they're taking its geo location and from their builds steps for new employees to be, we'll learn and understand how todo use that technology to help them do their job better. Well, when they do that, if there is replacement products or variation of of some of the tools that that they built the original design instruction set for they now have another version. Well, they have to manage multiple versions. Well, that's what on shape is really great at doing and so taking our technology and helping their solutions as well. So it's not only expanding our customer footprint, it's expanding the application footprint in terms of how we can help them and help customers. >>So that leads me to the tam discussion and again, as part of your strategist role. How do you think about that? Was just talking to some of your customers earlier about the democratization of cat and engineering? You know, I kind of joked, sort of like citizen engineering, but but so that you know, the demographics are changing the number of users potentially that can access the products because the it's so much more of a facile experience. How are you thinking about the total available market? >>It really is a great question, You know, it used to be when you when you sold boxes of software, it was how many engineers were out there. And that's the size of the market. The fact that matter is now when, When you think about access to that information, that data is simply a pane of glass. Whether it's a computer, whether it's a laptop, UH, a a cell phone or whether it's a tablet, the ability to to use different vehicles, access information and data expands the capabilities and power of a system to allow feedback and iteration. I mean, one of the one of the very interesting things is in technology is when you can take something and really unleash it to a larger audience and builds, you know, purpose built applications. You can start to iterate, get better feedback. You know there's a classic case in the clothing industry where Zara, you know, is a fast sort of turnaround. Agile manufacturer. And there was a great New York Times article written a couple years ago. My wife's a fan of Zara, and I think she justifies any purchases by saying, You know, Zara, you gotta purchase it now. Otherwise it may not be there the next time. Yet you go back to the store. They had some people in a store in New York that had this woman's throw kind of covering Shaw. And they said, Well, it would be great if we could have this little clip here so we can hook it through or something. And they sent a note back toe to the factory in Spain, and literally two weeks later they had, you know, 4000 of these things in store, and they sold out because they had a closed loop and iterative process. And so if we could take information and allow people access in multiple ways through different devices and different screens, that could be very specific information that, you know, we remove a lot of the engineering data book, bring the end user products conceptually to somebody that would have had to wait months to get the actual physical prototype, and we could get feedback well, Weaken have a better chance of making sure whatever product we're building is the right product when it ultimately gets delivered to a customer. So it's really it's a much larger market that has to be thought of rather than just the kind of selling A boxes software to an engineer. >>That's a great story. And again, it's gonna be exciting for you guys to see that with. The added resource is that you have a PTC, Um, so let's talk. I promise people we wanna talk about Atlas. Let's talk about the platform. A little bit of Atlas was announced last year. Atlas. For those who don't know it's a SAS space platform, it purports to go beyond product lifecycle management and you You're talking cloud like agility and scale to CAD and product design. But John, you could do a better job than I. What do >>we need to know about Atlas? Well, I think Atlas is a great description because it really is metaphorically sort of holding up all of the PTC applications themselves. But from the very beginning, when John and I met with Jim, part of what we were intrigued about was that he shared a vision that on shape was more than just going to be a cad authoring tool that, in fact, you know, in the past these engineering tools were very powerful, but they were very narrow in their purpose and focus. And we had specialty applications to manage the versions, etcetera. What we did in on shape is we kind of inverted that thinking. We built this collaboration and sharing engine at the core and then kind of wrap the CAD system around it. But that collaboration sharing and version ING engine is really powerful. And it was that vision that Jim had that he shared that we had from the beginning, which was, how do we take this thing to make a platform that could be used for many other applications inside of inside of any company? And so not only do we have a partner application area that is is much like the APP store or Google play store. Uh, that was sort of our first Stan Shih ation of this. This this platform. But now we're extending out to broader applications and much meatier applications. And internally, that's the thing works in the in the augmented reality. But there'll be other applications that ultimately find its way on top of this platform. And so they'll get all the benefits of of the collaboration, sharing the version ing the multi platform, multi device. And that's an extremely extremely, um, strategic leverage point for the company. >>You know, it's interesting, John, you mentioned the seaport before. So PTC, for those who don't know, built a beautiful facility down at the Seaport in Boston. And, of course, when PTC started, you know, back in the mid 19 eighties, there was nothing at the seaport s. >>So it's >>kind of kind of ironic, you know, we were way seeing the transformation of the seaport. We're seeing the transformation of industry and of course, PTC. And I'm sure someday you'll get back into that beautiful office, you know? Wait. Yeah, I'll bet. And, uh and but I wanna bring this up because I want I want you to talk about the future. How you how you see that our industry and you've observed this has moved from very product centric, uh, plat platform centric with sass and cloud. And now we're seeing ecosystems form around those products and platforms and data flowing through the ecosystem powering, you know, new innovation. I wonder if you could paint a picture for us of what the future looks like to you from your vantage point. >>Yeah, I think one of the key words you said there is data because up until now, data for companies really was sort of trapped in different applications. And it wasn't because people were nefarious and they want to keep it limited. It was just the way in which things were built. And, you know, when people use an application like on shape, what ends up happening is there their day to day interaction and everything that they do is actually captured by the platform. And, you know, we don't have access to that data. Of course it's it's the customer's data. But as as an artifact of them using the system than doing their day to day job, what's happening is they're creating huge amounts of information that can then be accessed and analyzed to help them both improve their design process, improve their efficiencies, improve their actual schedules in terms of making sure they can hit delivery times and be able to understand where there might be roadblocks in the future. So the way I see it is companies now are deploying SAS based tools like on shape and an artifact of them. Using that platform is that they have now analytics and tools to better understand and an instrument and manage their business. And then from there, I think you're going to see, because these systems are all you know extremely well. Architected allow through, you know, very structured AP. I calls to connect other SAS based applications. You're gonna start seeing closed loop sort of system. So, for example, people design using on shape, they end up going and deploying their system or installing it, or people use the end using products. People then may call back into the customers support line and report issues, problems, challenges. They'll be able to do traceability back to the underlying design. They'll be able to do trend analysis and defect analysis from the support lines and tie it back and closed loop the product design, manufacture, deployment in the field sort of cycles. In addition, you can imagine there's many things that air sort of as designed. But then when people go on site and they have to install it. There's some alterations modifications. Think about think about like a large air conditioning units for buildings. You go and you go to train and you get a large air conditioning unit that put up on top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of the particulars of that building. You know, with on shape and tools like this, you'll be able to not only take the design of what the air conditioning system might be, but also the all the adapter plates, but also how they installed it. So it sort of as designed as manufactured as stalled. And all these things can be traced, just like if you think about the transformation of customer service or customer contacts. In the early days, you used to have tools that were PC based tools called contact management solution, you know, kind of act or gold mine. And these were basically glorified Elektronik role in Texas. It had a customer names and they had phone numbers and whatever else. And Salesforce and Siebel, you know, these types of systems really broadened out the perspective of what a customer relationship? Waas. So it wasn't just the contact information it was, you know, How did they come to find out about you as a company? So all of the pre sort of marketing and then kind of what happens after they become a customer and it really was a 3 60 view. I think that 3 60 view gets extended to not just to the customers, but also tools and the products they use. And then, of course, the performance information that could come back to the manufacturer. So, you know, as an engineer, one of the things you learn about with systems is the following. And if you remember, when the CD first came out CDs that used to talk about four times over sampling or eight times over sampling and it was really kind of, you know, the fidelity the system. And we know from systems theory that the best way to improve the performance of a system is to actually have more feedback. The more feedback you have, the better system could be. And so that's why you get 16 60 for example, etcetera. Same thing here. The more feedback we have of different parts of a company that a better performance, The company will be better customer relationships. Better, uh, overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>It's a great vision in your point about the data is I think right on. It used to be so fragmented in silos, and in order to take a system view, you've gotta have a system view of the data. Now, for years, we've optimized maybe on one little component of the system and that sometimes we lose sight of the overall outcome. And so what you just described, I think is, I think sets up. You know very well as we exit. Hopefully soon we exit this this covert era on John. I hope that you and I can sit down face to face at a PTC on shape event in the near term >>in the seaport in the >>seaport would tell you that great facility toe have have an event for sure. It >>z wonderful >>there. So So John McElhinney. Thanks so much for for participating in the program. It was really great to have you on, >>right? Thanks, Dave. >>Okay. And I want to thank everyone for participating. Today we have some great guest speakers. And remember, this is a live program. So give us a little bit of time. We're gonna flip this site over toe on demand mode so you can share it with your colleagues and you, or you can come back and and watch the sessions that you heard today. Uh, this is Dave Volonte for the Cube and on shape PTC. Thank you so much for watching innovation for good. Be well, Have a great holiday. And we'll see you next time. Yeah.

>>from around the globe. It's the Cube presenting innovation for good. Brought to >>you by on shape. Okay, welcome back to innovation. For good. With me is John McElheny, who is one of the co founders of on Shape and is now the VP of strategy at PTC. John, good to see you. Thanks for making the time to come on the program. Thanks, Dave. So we heard earlier some of the accomplishments that you've made since the acquisition. How has the acquisition affected your strategy? Maybe you could talk about what resource is PTC brought to the table that allowed you toe sort of rethink or evolve your strategy? What can you share with us? >>Sure. You know, a year ago when John and myself met with Jim Hempleman early on is we're we're pondering started joining PTC. One of things became very clear is that we had a very clear shared vision about how we could take the on shape platform and really extended for for all of the PTC products, particular sort of their augmented reality as well as their their thing works or the i o. T business and their product. And so from the very beginning, there was a clear strategy about taking on shape, extending the platform and really investing, um, pretty significantly in the product development as well as go to market side of things, uh, toe to bring on shape out to not only the PTC based but sort of the broader community at large. So So So PTC has been terrific. Terrific, um, sort of partner as we've we've gonna go on after this market together. Eso we've added a lot of resource and product development side of things. Ah, lot of resource and to go to market and customer success and support. So really, on many fronts, that's with both resource is, as well a sort of support at the corporate level from from a strategic standpoint and then in the field, we've had wonderful interactions with many large enterprise customers as well as the PTC channels. So it's been really a great a great year. >>Well, and you think about the challenges of your business going to sas what you guys, you know, took on that journey, you know, 78 years ago. Uh, it's not trivial for a lot of companies to make that transition, especially company. That's been around as long as PTC. So So I'm wondering how much you know, I was just asking you what PC PTC brought the table. E gotta believe you're bringing a lot to the table to in terms of the mindset, uh, even things is, is mundane is not the right word. But things like how you compensate sales people, how you interact with customers, the notion of a service versus a product. I wonder if you could address >>that. Yeah, it's a It's a really great point. In fact, after we had met Jim last year, John and I one of the things we walked out in the seaport area in Boston one of things we sort of said is you know, Jim really gets what we're trying to do here and and part of let me bring you into the thinking early on. Part of what Jim talked about is there's lots of, you know, installed base sort of software that's inside of PTC base. That helped literally thousands of customers around the world. But the idea of moving to sass and all that it entails both from a technology standpoint, but also a cultural standpoint, like how do you not not just compensate the sales people as an example? But how do you think about customers? Success? In the past, it might have been that you had professional services that you bring out to a customer, help them deploy your solutions. Well, when you're thinking about a SAS based offering, it's really critical that you get customers successful with it. Otherwise, you may have turned, and you know it will be very expensive in terms of your business long term. So you've got to get customers success with software in the very beginning. So you know, Jim really looked at on shape and he said that John and I from a cultural standpoint, you know, a lot of times companies get acquired and they've acquired technology in the past that they integrate directly into into PTC and then sort of roll it out through their products or their distribution channels, he said. In some respects, John John, think about it as we're gonna take PTC and we want to integrate it into on shape because we want you to share with us both on the sales side and customer success on marketing on operations, you know, all the things because long term, we believe the world is a SAS world, that the whole industry is gonna move too. So, really, it was sort of an inverse in terms of the thought process related to normal transactions >>on that makes a lot of sense to me. You mentioned Sharon turns the silent killer of a SAS company. And you know, there's a lot of discussion, you know, in the entrepreneurial community because you live this, you know, what's the best path? I mean, today, you see, you know, you you watch Silicon Valley double, double, triple triple. But but there's a lot of people who believe, and I wonder, if you come in there is the best path to, you know, in the X Y axis. If if it's if it's, uh, growth on one and retention on the other axis, what's the best way to get to the upper right on? Really, the the best path is probably make sure you've nailed obviously the product market fit, but make sure that you can retain customers and then throw gas on the fire. You see a lot of companies they burn out trying to grow too fast, but they haven't figured out, you know that. But there's too much churn. They haven't figured out those metrics. I mean, obviously on shape. You know, you were sort of a pioneer in here. I gotta believe you've figured out that customer retention before you really? You know, put the pedal to the >>metal. Yeah. And you know, growth growth can mask a lot of things, but getting getting customers, especially the engineering space. Nobody goes and sits there and says, Tomorrow we're gonna go and and, you know, put 100 users on this and and immediately swap out all of our existing tools. These tools are very rich and deep in terms of capability, and they become part of the operational process of how a company designs and builds products. So any time anybody is actually going through the purchasing process, typically they will run a try along or they'll run a project where they look at Kind of What? What is this new solution gonna help them dio. How are we gonna orient ourselves for success? Longer term. So for us, you know, getting new customers and customer acquisition is really critical. But getting those customers to actually deploy the solution to be successful with it. You know, we like to sort of, say, the marketing or the lead generation and even some of the initial sales. That's sort of like the Kindle ing. But the fire really starts when customers deploy it and get successful with the solution because they bring other customers into the fold. And then, of course, if they're successful with it, you know, then in fact, you have negative turn which, ironically, means growth in terms of your inside of your install Bates. >>Right? And you've seen that with some of the emerging, you know, SAS companies, where you're you're actually you know, when you calculate whatever its net retention or renew ALS, it's actually from a dollar standpoint that's up in the high nineties or even over 100% >>so and >>that's a trend we're gonna continue. See, I wonder if we could sort of go back. Uh, and when you guys were starting on shape, some of the things that you saw that you were trying to strategically leverage and what's changed, you know, today we were talking. I was talking to John earlier about in a way, you kinda you kinda got a blank slate is like doing another startup. You're not. Obviously you've got installed base and customers to service, but but it's a new beginning for you guys. So one of the things that you saw then you know, cloud and and sas and okay, but that's we've been there, done that. What are you seeing? You know, today? >>Well, you know, So So this is a journey, of course, that that on shape on its own has gone through. And had, I'll sort of say, you know, several iterations, both in terms of of of, you know, how do you How do you get customers? How do you How do you get them successful? How do you grow those customers? And now that we've been part of PTC, the question becomes okay, One, there is certainly a higher level of credibility that helps us in terms of our our megaphone is much bigger than it was when we're standalone company. But on top of that now, figuring out how to work with their channel with their direct sales force, you know, they have, um, for example, you know, very large enterprises. Well, many of those customers are not gonna go in forklift out their existing solution to replace it with with on shape. However, many of them do have challenges in their supply chain and communications with contractors and vendors across the globe. And so, you know, finding our fit inside of those large enterprises as they extend out with their their customers is a very interesting area that we've really been sort of incremental to to PTC. And then, you know, they they have access to lots of other technology, like the i O. T business. And now, of course, the augmented reality business that that we can bring things to bear. For example, in the augmented reality world they've they've got something called expert capture. And this is essentially imagined, you know, in a are, ah, headset that allows you to be ableto to speak to it but also capture images, still images in video, and you could take somebody who's doing their task and capture literally the steps that they're taking its geo location and from their builds steps for new employees. We'll learn and understand how todo use that technology to help them do their job better. Well, when they do that if there is replacement products or variation of of some of the tools that that they built the original design instruction set for they now have another version. Well, they have to manage multiple versions. Well, that's what on shape is really great at doing and so taking our technology and helping their solutions as well. So it's not only expanding our customer footprint, it's expanding the application footprint in terms of how we can help them and help customers. >>So that leads me to the tam discussion. And again, it was part of your strategist role. How do you think about that? Was just talking to some of your customers earlier about the democratization of cat and engineering. You know, I kind of joked, sort of like citizen engineering, but but so that, you know, the demographics are changing the number of users potentially that can access the products because the it's so much more of a facile experience. How are you thinking about the total available market? >>It really is a great question, you know, It used to be when you when you sold boxes of software, it was how many engineers were out there, and that's the size of the market. The fact that matter is now when, When you think about access to that information, that data is simply a pane of glass. Whether it's a computer, whether it's a laptop, uh, a cell phone or whether it's a tablet, the ability to to use different vehicles, access information and data expands the capabilities and power of a system to allow feedback and iteration. I mean, one of the one of the very interesting things is in technology is when you can take something and really unleash it to a larger audience and builds, you know, purpose built applications. You can start to iterate, get better feedback. You know, there's a classic case in the clothing industry where Zara, you know, is a fast, sort of turnaround agile manufacturer. And there was a great New York Times article written a couple years ago. My wife's a fan of Zara, and I think she justifies any purchases by saying, you know, was Are you gotta purchase it now. Otherwise it may not be there the next time. Yet you go back to the store. They had some people in the store in New York that had this woman's throw kind of covering Shaw, and they said, Well, it would be great if we could have this little clip here so we could hook it through or something. And they sent a note back toe to the factory in Spain and literally two weeks later they had, you know, 4000 of these things in store, and they sold out because they had a closed loop and iterative process. And so if we could take information and allow people access in multiple ways through different devices and different screens, that could be very specific information that, you know, we remove a lot of the engineering data book, bring the end user products conceptually to somebody that would have had to wait months to get the actual physical prototype, and we could get feedback. Well, Weaken have a better chance of making sure whatever product we're building is the right product when it ultimately gets delivered to a customer. So it's really it's a much larger market that has to be thought of rather than just the kind of selling a boxes off where to an engineer, >>that's a great story, and and again, it's gotta be exciting for you guys to see that on day with the added resource is that you have a PTC eso. Let's talk. I promise people we want to talk about Atlas. Let's talk about the platform. A little bit of Atlas was announced last year. Atlas. For those who don't know it's a SAS space platform, it purports to go beyond product lifecycle management and you you're talking cloudlike agility and scale to CAD and product design. But, John, you could do a better job than I. What do >>we need to know about Atlas? Well, I think Atlas is a great description because it really is metaphorically, sort of holding up all of the PTC applications themselves. But from the very beginning, when John and I met with Jim, part of what we were intrigued about was that he shared a vision that on shape was more than just going to be a cad authoring tool that, in fact, you know, in the past, these engineering tools were very powerful, but they were very narrow in their purpose and focus, and we had specialty applications to manage diversions, etcetera. What we did in on shape is we kind of inverted that thinking we built this collaboration and sharing engine at the core and then kind of wrap the CAD system around it. But that collaboration sharing and version ING engine is really powerful. And it was that vision that Jim had that he shared that we had from the beginning, which was, how do we take this thing to make a platform that could be used for many other applications inside of inside of any company? And so not only do we have a partner application area that is is much like the APP store or Google play store. Uh, that was sort of our first misty initiation of this this this platform. But now we're extending out to broader applications and much meatier applications. And internally, that's the thing works in the in the augmented reality. But there'll be other applications that ultimately find its way on top of this platform, and so they'll get all the benefits of of the collaboration, sharing the version ing the multi platform multi device. And that's an extremely extremely, um, strategic leverage point for the company. >>You know, it's interesting, John, you mentioned the seaport before, So PTC For those who don't know built a beautiful facility down at the seaport in Boston. And of course, when PTC started back in the mid 19 eighties, this there was nothing at the seaport s. >>So it's >>kind of kind of ironic, you know, we were way seeing the transformation of the seaport. We're seeing the transformation of industry and of course, PTC. And I'm sure someday you'll get back into that beautiful office, you know? Wait. Yeah, I'll Bet. And, uh and but I wanna bring this up because I want I want you to talk about the future. How you how you see that our industry and you've observed this has moved from very product centric, uh, plat platform centric with sass and cloud. And now we're seeing ecosystems form around those products and platforms and in data flowing through the ecosystem, powering you new innovation. I wonder if you could paint a picture for us of what the future looks like to you from your vantage point. >>Yeah, I think one of the key words you said there is data because up until now, data for companies really was sort of trapped in different applications. And it wasn't because people with nefarious and they want to keep it limited. It was just the way in which things were built, and you know, when people use an application like on shape, what ends up happening is there their day to day interactions and everything that they dio is actually captured by the platform. And you know, we don't have access to that data. Of course it's it's the customer's data. But as as an artifact of them using the system than doing their day to day job, what's happening is they're creating huge amounts of information that can then be accessed and analyzed to help them both improve their design process, improve their efficiencies, improve their actual schedules in terms of making sure they can hit delivery times and be able to understand where there might be roadblocks in the future. So the way I see it is, companies now are deploying SAS based tools like an shape and an artifact of them. Using that platform is that they have now analytics and tools to better understand and an instrument and manage their business. And then from there, I think you're going to see, because these systems are all you know extremely well. architected allow through, you know, very structured AP. I calls to connect other SAS based applications. You're gonna start seeing closed loop sort of system. So, for example, people design using on shape. They end up going and deploying their system or installing it, or people use the end using products. People then may call back into the customers support line and report issues problems, challenges. They'll be able to do traceability back to the underlying design. They'll be able to do trend analysis and defect analysis from the support lines and tie it back and closed loop the product design, manufacture, deployment in the field sort of cycles. In addition, you can imagine there's many things that air sort of as designed. But then when people go on site and they have to install it, there's some alterations modifications. Think about think about like a large air conditioning units for buildings. You go and you go to train and you get a large air conditioning unit that put up on the top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of of of the particulars of that building. You know, with on shape and tools like this, you'll be able to not only take the design of what the air conditioning system might be, but also the all the adapter plates, but also how they installed it. So it sort of as designed as manufactured as stalled. And all these things can be traced just like if you think about the transformation of customer service or customer contacts. In the early days, you used to have tools that were PC based tools called contact management solution, you know, kind of act or gold mine. And these were basically glorified Elektronik role in Texas. It had a customer names, and they had phone numbers and whatever else. And Salesforce and Siebel, these types of systems really broadened out the perspective of what a customer relationship waas. So it wasn't just the contact information it was, you know, How did they come to find out about you as a company? So all the pre sort of marketing and then kind of what happens after they become a customer and it really was a 3 60 view. I think that 3 60 view gets extended to not just to the customers, but also tools and the products they use. And then, of course, the performance information that could come back to the manufacturer. So, you know, as an engineer, one of the things you learn about with systems is the following. And if you remember, when the 501st came out CDs that used to talk about four times over sampling or eight times over sampling and it was really kind of, you know, the fidelity the system. And we know from systems theory that the best way to improve the performance of a system is to actually have more feedback. The more feedback you have, the better system could be. And so that's why you got 16 60 for example, etcetera. Same thing here. The more feedback we have of different parts of a company that a better performance. The company will be better customer relationships, better overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>The great vision in your point about the data is, I think, right on. It used to be so fragmented in silos, and in order to take a system view, you've gotta have a system view of the data. Uh, for years we've optimized maybe on one little component of the system and that sometimes we lose sight of the overall outcome. And so what you just described, I think is, I think sets up. You know very well as we exit. Hopefully soon we exit this this covert era on John. I hope that you and I can sit down face to face at a PTC on shape event in the near term. Who's >>in the seaport in the >>seaport Would tell you that great facility toe have have an event for sure. It >>z wonderful >>there. So So, John McElhinney. Thanks so much for for participating in the program. It was really great to have you on. >>Right. Thanks, Dave. >>Okay. And I want to thank everyone for participating. Today. We have some great guest speakers. And remember, this is a live program, so give us a little bit of time. We're gonna flip this site over to on demand mode so you can share it with your colleagues and you, or you can come back and and watch the sessions that you heard today. Uh, this is Dave Volonte for the Cube and on shape PTC. Thank you so much for watching innovation for good. Be well, have a great holiday and we'll see you next time.

>>from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>And we're back with the data automation. Siri's. In this episode, we're gonna learn more about what I owe Tahoe is doing in the field of adaptive data governance how it can help achieve business outcomes and mitigate data security risks. I'm Lisa Martin, and I'm joined by a J. Bihar on the CEO of Iot Tahoe and Lester Waters, the CEO of Bio Tahoe. Gentlemen, it's great to have you on the program. >>Thank you. Lisa is good to be back. >>Great. Staley's >>likewise very socially distant. Of course as we are. Listen, we're gonna start with you. What's going on? And I am Tahoe. What's name? Well, >>I've been with Iot Tahoe for a little over the year, and one thing I've learned is every customer needs air just a bit different. So we've been working on our next major release of the I O. Tahoe product. But to really try to address these customer concerns because, you know, we wanna we wanna be flexible enough in order to come in and not just profile the date and not just understand data quality and lineage, but also to address the unique needs of each and every customer that we have. And so that required a platform rewrite of our product so that we could, uh, extend the product without building a new version of the product. We wanted to be able to have plausible modules. We also focused a lot on performance. That's very important with the bulk of data that we deal with that we're able to pass through that data in a single pass and do the analytics that are needed, whether it's, uh, lineage, data quality or just identifying the underlying data. And we're incorporating all that we've learned. We're tuning up our machine learning we're analyzing on MAWR dimensions than we've ever done before. We're able to do data quality without doing a Nen initial rejects for, for example, just out of the box. So I think it's all of these things were coming together to form our next version of our product. We're really excited by it, >>So it's exciting a J from the CEO's level. What's going on? >>Wow, I think just building on that. But let's still just mentioned there. It's were growing pretty quickly with our partners. And today, here with Oracle are excited. Thio explain how that shaping up lots of collaboration already with Oracle in government, in insurance, on in banking and we're excited because we get to have an impact. It's real satisfying to see how we're able. Thio. Help businesses transform, Redefine what's possible with their data on bond. Having I recall there is a partner, uh, to lean in with is definitely helping. >>Excellent. We're gonna dig into that a little bit later. Let's let's go back over to you. Explain adaptive data governance. Help us understand that >>really adaptive data governance is about achieving business outcomes through automation. It's really also about establishing a data driven culture and pushing what's traditionally managed in I t out to the business. And to do that, you've got to you've got Thio. You've got to enable an environment where people can actually access and look at the information about the data, not necessarily access the underlying data because we've got privacy concerns itself. But they need to understand what kind of data they have, what shape it's in what's dependent on it upstream and downstream, and so that they could make their educated decisions on on what they need to do to achieve those business outcomes. >>Ah, >>lot of a lot of frameworks these days are hardwired, so you can set up a set of business rules, and that set of business rules works for a very specific database and a specific schema. But imagine a world where you could just >>say, you >>know, the start date of alone must always be before the end date of alone and having that generic rule, regardless of the underlying database and applying it even when a new database comes online and having those rules applied. That's what adaptive data governance about I like to think of. It is the intersection of three circles, Really. It's the technical metadata coming together with policies and rules and coming together with the business ontology ease that are that are unique to that particular business. And this all of this. Bringing this all together allows you to enable rapid change in your environment. So it's a mouthful, adaptive data governance. But that's what it kind of comes down to. >>So, Angie, help me understand this. Is this book enterprise companies are doing now? Are they not quite there yet. >>Well, you know, Lisa, I think every organization is is going at its pace. But, you know, markets are changing the economy and the speed at which, um, some of the changes in the economy happening is is compelling more businesses to look at being more digital in how they serve their own customers. Eh? So what we're seeing is a number of trends here from heads of data Chief Data Officers, CEO, stepping back from, ah, one size fits all approach because they've tried that before, and it it just hasn't worked. They've spent millions of dollars on I T programs China Dr Value from that data on Bennett. And they've ended up with large teams of manual processing around data to try and hardwire these policies to fit with the context and each line of business and on that hasn't worked. So the trends that we're seeing emerge really relate. Thio, How do I There's a chief data officer as a CEO. Inject more automation into a lot of these common tax. Andi, you know, we've been able toc that impact. I think the news here is you know, if you're trying to create a knowledge graph a data catalog or Ah, business glossary. And you're trying to do that manually will stop you. You don't have to do that manually anymore. I think best example I can give is Lester and I We we like Chinese food and Japanese food on. If you were sitting there with your chopsticks, you wouldn't eat the bowl of rice with the chopsticks, one grain at a time. What you'd want to do is to find a more productive way to to enjoy that meal before it gets cold. Andi, that's similar to how we're able to help the organizations to digest their data is to get through it faster, enjoy the benefits of putting that data to work. >>And if it was me eating that food with you guys, I would be not using chopsticks. I would be using a fork and probably a spoon. So eso Lester, how then does iota who go about doing this and enabling customers to achieve this? >>Let me, uh, let me show you a little story have here. So if you take a look at the challenges the most customers have, they're very similar, but every customers on a different data journey, so but it all starts with what data do I have? What questions or what shape is that data in? Uh, how is it structured? What's dependent on it? Upstream and downstream. Um, what insights can I derive from that data? And how can I answer all of those questions automatically? So if you look at the challenges for these data professionals, you know, they're either on a journey to the cloud. Maybe they're doing a migration oracle. Maybe they're doing some data governance changes on bits about enabling this. So if you look at these challenges and I'm gonna take you through a >>story here, E, >>I want to introduce Amanda. Man does not live like, uh, anyone in any large organization. She's looking around and she just sees stacks of data. I mean, different databases, the one she knows about, the one she doesn't know about what should know about various different kinds of databases. And a man is just tasking with understanding all of this so that they can embark on her data journey program. So So a man who goes through and she's great. I've got some handy tools. I can start looking at these databases and getting an idea of what we've got. Well, as she digs into the databases, she starts to see that not everything is as clear as she might have hoped it would be. You know, property names or column names, or have ambiguous names like Attribute one and attribute to or maybe date one and date to s Oh, man is starting to struggle, even though she's get tools to visualize. And look what look at these databases. She still No, she's got a long road ahead. And with 2000 databases in her large enterprise, yes, it's gonna be a long turkey but Amanda Smart. So she pulls out her trusty spreadsheet to track all of her findings on what she doesn't know about. She raises a ticket or maybe tries to track down the owner to find what the data means. And she's tracking all this information. Clearly, this doesn't scale that well for Amanda, you know? So maybe organization will get 10 Amanda's to sort of divide and conquer that work. But even that doesn't work that well because they're still ambiguities in the data with Iota ho. What we do is we actually profile the underlying data. By looking at the underlying data, we can quickly see that attribute. One looks very much like a U. S. Social Security number and attribute to looks like a I c D 10 medical code. And we do this by using anthologies and dictionaries and algorithms to help identify the underlying data and then tag it. Key Thio Doing, uh, this automation is really being able to normalize things across different databases, so that where there's differences in column names, I know that in fact, they contain contain the same data. And by going through this exercise with a Tahoe, not only can we identify the data, but we also could gain insights about the data. So, for example, we can see that 97% of that time that column named Attribute one that's got us Social Security numbers has something that looks like a Social Security number. But 3% of the time, it doesn't quite look right. Maybe there's a dash missing. Maybe there's a digit dropped. Or maybe there's even characters embedded in it. So there may be that may be indicative of a data quality issues, so we try to find those kind of things going a step further. We also try to identify data quality relationships. So, for example, we have two columns, one date, one date to through Ah, observation. We can see that date 1 99% of the time is less than date, too. 1% of the time. It's not probably indicative of a data quality issue, but going a step further, we can also build a business rule that says Day one is less than date to. And so then when it pops up again, we can quickly identify and re mediate that problem. So these are the kinds of things that we could do with with iota going even a step further. You could take your your favorite data science solution production ISAT and incorporated into our next version a zey what we call a worker process to do your own bespoke analytics. >>We spoke analytics. Excellent, Lester. Thank you. So a J talk us through some examples of where you're putting this to use. And also what is some of the feedback from >>some customers? But I think it helped do this Bring it to life a little bit. Lisa is just to talk through a case study way. Pull something together. I know it's available for download, but in ah, well known telecommunications media company, they had a lot of the issues that lasted. You spoke about lots of teams of Amanda's, um, super bright data practitioners, um, on baby looking to to get more productivity out of their day on, deliver a good result for their own customers for cell phone subscribers, Um, on broadband users. So you know that some of the examples that we can see here is how we went about auto generating a lot of that understanding off that data within hours. So Amanda had her data catalog populated automatically. A business class three built up on it. Really? Then start to see. Okay, where do I want Thio? Apply some policies to the data to to set in place some controls where they want to adapt, how different lines of business, maybe tax versus customer operations have different access or permissions to that data on What we've been able to do there is, is to build up that picture to see how does data move across the entire organization across the state. Andi on monitor that overtime for improvement, so have taken it from being a reactive. Let's do something Thio. Fix something. Thio, Now more proactive. We can see what's happening with our data. Who's using it? Who's accessing it, how it's being used, how it's being combined. Um, on from there. Taking a proactive approach is a real smart use of of the talents in in that telco organization Onda folks that worked there with data. >>Okay, Jason, dig into that a little bit deeper. And one of the things I was thinking when you were talking through some of those outcomes that you're helping customers achieve is our ally. How do customers measure are? Why? What are they seeing with iota host >>solution? Yeah, right now that the big ticket item is time to value on. And I think in data, a lot of the upfront investment cause quite expensive. They have been today with a lot of the larger vendors and technologies. So what a CEO and economic bio really needs to be certain of is how quickly can I get that are away. I think we've got something we can show. Just pull up a before and after, and it really comes down to hours, days and weeks. Um, where we've been able Thio have that impact on in this playbook that we pulled together before and after picture really shows. You know, those savings that committed a bit through providing data into some actionable form within hours and days to to drive agility, but at the same time being out and forced the controls to protect the use of that data who has access to it. So these are the number one thing I'd have to say. It's time on. We can see that on the the graphic that we've just pulled up here. >>We talk about achieving adaptive data governance. Lester, you guys talk about automation. You talk about machine learning. How are you seeing those technologies being a facilitator of organizations adopting adaptive data governance? Well, >>Azaz, we see Mitt Emmanuel day. The days of manual effort are so I think you know this >>is a >>multi step process. But the very first step is understanding what you have in normalizing that across your data estate. So you couple this with the ontology, that air unique to your business. There is no algorithms, and you basically go across and you identify and tag tag that data that allows for the next steps toe happen. So now I can write business rules not in terms of columns named columns, but I could write him in terms of the tags being able to automate. That is a huge time saver and the fact that we can suggest that as a rule, rather than waiting for a person to come along and say, Oh, wow. Okay, I need this rule. I need this will thes air steps that increased that are, I should say, decrease that time to value that A. J talked about and then, lastly, a couple of machine learning because even with even with great automation and being able to profile all of your data and getting a good understanding, that brings you to a certain point. But there's still ambiguities in the data. So, for example, I might have to columns date one and date to. I may have even observed the date. One should be less than day two, but I don't really know what date one and date to our other than a date. So this is where it comes in, and I might ask the user said, >>Can >>you help me identify what date? One and date You are in this in this table. Turns out they're a start date and an end date for alone That gets remembered, cycled into the machine learning. So if I start to see this pattern of date one day to elsewhere, I'm going to say, Is it start dating and date? And these Bringing all these things together with this all this automation is really what's key to enabling this This'll data governance. Yeah, >>great. Thanks. Lester and a j wanna wrap things up with something that you mentioned in the beginning about what you guys were doing with Oracle. Take us out by telling us what you're doing there. How are you guys working together? >>Yeah, I think those of us who worked in i t for many years we've We've learned Thio trust articles technology that they're shifting now to ah, hybrid on Prohm Cloud Generation to platform, which is exciting. Andi on their existing customers and new customers moving to article on a journey. So? So Oracle came to us and said, you know, we can see how quickly you're able to help us change mindsets Ondas mindsets are locked in a way of thinking around operating models of I t. That there may be no agile and what siloed on day wanting to break free of that and adopt a more agile A p I at driven approach. A lot of the work that we're doing with our recall no is around, uh, accelerating what customers conduce with understanding their data and to build digital APS by identifying the the underlying data that has value. Onda at the time were able to do that in in in hours, days and weeks. Rather many months. Is opening up the eyes to Chief Data Officers CEO to say, Well, maybe we can do this whole digital transformation this year. Maybe we can bring that forward and and transform who we are as a company on that's driving innovation, which we're excited about it. I know Oracle, a keen Thio to drive through and >>helping businesses transformed digitally is so incredibly important in this time as we look Thio things changing in 2021 a. J. Lester thank you so much for joining me on this segment explaining adaptive data governance, how organizations can use it benefit from it and achieve our Oi. Thanks so much, guys. >>Thank you. Thanks again, Lisa. >>In a moment, we'll look a adaptive data governance in banking. This is the Cube, your global leader in high tech coverage. >>Innovation, impact influence. Welcome to the Cube. Disruptors. Developers and practitioners learn from the voices of leaders who share their personal insights from the hottest digital events around the globe. Enjoy the best this community has to offer on the Cube, your global leader in high tech digital coverage. >>Our next segment here is an interesting panel you're gonna hear from three gentlemen about adaptive data. Governments want to talk a lot about that. Please welcome Yusuf Khan, the global director of data services for Iot Tahoe. We also have Santiago Castor, the chief data officer at the First Bank of Nigeria, and good John Vander Wal, Oracle's senior manager of digital transformation and industries. Gentlemen, it's great to have you joining us in this in this panel. Great >>to be >>tried for me. >>Alright, Santiago, we're going to start with you. Can you talk to the audience a little bit about the first Bank of Nigeria and its scale? This is beyond Nigeria. Talk to us about that. >>Yes, eso First Bank of Nigeria was created 125 years ago. One of the oldest ignored the old in Africa because of the history he grew everywhere in the region on beyond the region. I am calling based in London, where it's kind of the headquarters and it really promotes trade, finance, institutional banking, corporate banking, private banking around the world in particular, in relationship to Africa. We are also in Asia in in the Middle East. >>So, Sanjay, go talk to me about what adaptive data governance means to you. And how does it help the first Bank of Nigeria to be able to innovate faster with the data that you have? >>Yes, I like that concept off adaptive data governor, because it's kind of Ah, I would say an approach that can really happen today with the new technologies before it was much more difficult to implement. So just to give you a little bit of context, I I used to work in consulting for 16, 17 years before joining the president of Nigeria, and I saw many organizations trying to apply different type of approaches in the governance on by the beginning early days was really kind of a year. A Chicago A. A top down approach where data governance was seeing as implement a set of rules, policies and procedures. But really, from the top down on is important. It's important to have the battle off your sea level of your of your director. Whatever I saw, just the way it fails, you really need to have a complimentary approach. You can say bottom are actually as a CEO are really trying to decentralize the governor's. Really, Instead of imposing a framework that some people in the business don't understand or don't care about it, it really needs to come from them. So what I'm trying to say is that data basically support business objectives on what you need to do is every business area needs information on the detector decisions toe actually be able to be more efficient or create value etcetera. Now, depending on the business questions they have to solve, they will need certain data set. So they need actually to be ableto have data quality for their own. For us now, when they understand that they become the stores naturally on their own data sets. And that is where my bottom line is meeting my top down. You can guide them from the top, but they need themselves to be also empower and be actually, in a way flexible to adapt the different questions that they have in orderto be able to respond to the business needs. Now I cannot impose at the finish for everyone. I need them to adapt and to bring their answers toe their own business questions. That is adaptive data governor and all That is possible because we have. And I was saying at the very beginning just to finalize the point, we have new technologies that allow you to do this method data classifications, uh, in a very sophisticated way that you can actually create analitico of your metadata. You can understand your different data sources in order to be able to create those classifications like nationalities, a way of classifying your customers, your products, etcetera. >>So one of the things that you just said Santa kind of struck me to enable the users to be adaptive. They probably don't want to be logging in support ticket. So how do you support that sort of self service to meet the demand of the users so that they can be adaptive. >>More and more business users wants autonomy, and they want to basically be ableto grab the data and answer their own question. Now when you have, that is great, because then you have demand of businesses asking for data. They're asking for the insight. Eso How do you actually support that? I would say there is a changing culture that is happening more and more. I would say even the current pandemic has helped a lot into that because you have had, in a way, off course, technology is one of the biggest winners without technology. We couldn't have been working remotely without these technologies where people can actually looking from their homes and still have a market data marketplaces where they self serve their their information. But even beyond that data is a big winner. Data because the pandemic has shown us that crisis happened, that we cannot predict everything and that we are actually facing a new kind of situation out of our comfort zone, where we need to explore that we need to adapt and we need to be flexible. How do we do that with data. Every single company either saw the revenue going down or the revenue going very up For those companies that are very digital already. Now it changed the reality, so they needed to adapt. But for that they needed information. In order to think on innovate, try toe, create responses So that type of, uh, self service off data Haider for data in order to be able to understand what's happening when the prospect is changing is something that is becoming more, uh, the topic today because off the condemning because of the new abilities, the technologies that allow that and then you then are allowed to basically help your data. Citizens that call them in the organization people that no other business and can actually start playing and an answer their own questions. Eso so these technologies that gives more accessibility to the data that is some cataloging so they can understand where to go or what to find lineage and relationships. All this is is basically the new type of platforms and tools that allow you to create what are called a data marketplace. I think these new tools are really strong because they are now allowing for people that are not technology or I t people to be able to play with data because it comes in the digital world There. Used to a given example without your who You have a very interesting search functionality. Where if you want to find your data you want to sell, Sir, you go there in that search and you actually go on book for your data. Everybody knows how to search in Google, everybody's searching Internet. So this is part of the data culture, the digital culture. They know how to use those schools. Now, similarly, that data marketplace is, uh, in you can, for example, see which data sources they're mostly used >>and enabling that speed that we're all demanding today during these unprecedented times. Goodwin, I wanted to go to you as we talk about in the spirit of evolution, technology is changing. Talk to us a little bit about Oracle Digital. What are you guys doing there? >>Yeah, Thank you. Um, well, Oracle Digital is a business unit that Oracle EMEA on. We focus on emerging countries as well as low and enterprises in the mid market, in more developed countries and four years ago. This started with the idea to engage digital with our customers. Fear Central helps across EMEA. That means engaging with video, having conference calls, having a wall, a green wall where we stand in front and engage with our customers. No one at that time could have foreseen how this is the situation today, and this helps us to engage with our customers in the way we were already doing and then about my team. The focus of my team is to have early stage conversations with our with our customers on digital transformation and innovation. And we also have a team off industry experts who engaged with our customers and share expertise across EMEA, and we inspire our customers. The outcome of these conversations for Oracle is a deep understanding of our customer needs, which is very important so we can help the customer and for the customer means that we will help them with our technology and our resource is to achieve their goals. >>It's all about outcomes, right? Good Ron. So in terms of automation, what are some of the things Oracle's doing there to help your clients leverage automation to improve agility? So that they can innovate faster, which in these interesting times it's demanded. >>Yeah, thank you. Well, traditionally, Oracle is known for their databases, which have bean innovated year over year. So here's the first lunch on the latest innovation is the autonomous database and autonomous data warehouse. For our customers, this means a reduction in operational costs by 90% with a multi medal converts, database and machine learning based automation for full life cycle management. Our databases self driving. This means we automate database provisioning, tuning and scaling. The database is self securing. This means ultimate data protection and security, and it's self repairing the automates failure, detection fail over and repair. And then the question is for our customers, What does it mean? It means they can focus on their on their business instead off maintaining their infrastructure and their operations. >>That's absolutely critical use if I want to go over to you now. Some of the things that we've talked about, just the massive progression and technology, the evolution of that. But we know that whether we're talking about beta management or digital transformation, a one size fits all approach doesn't work to address the challenges that the business has, um that the i t folks have, as you're looking through the industry with what Santiago told us about first Bank of Nigeria. What are some of the changes that you're seeing that I owe Tahoe seeing throughout the industry? >>Uh, well, Lisa, I think the first way I'd characterize it is to say, the traditional kind of top down approach to data where you have almost a data Policeman who tells you what you can and can't do, just doesn't work anymore. It's too slow. It's too resource intensive. Uh, data management data, governments, digital transformation itself. It has to be collaborative on. There has to be in a personalization to data users. Um, in the environment we find ourselves in. Now, it has to be about enabling self service as well. Um, a one size fits all model when it comes to those things around. Data doesn't work. As Santiago was saying, it needs to be adapted toe how the data is used. Andi, who is using it on in order to do this cos enterprises organizations really need to know their data. They need to understand what data they hold, where it is on what the sensitivity of it is they can then any more agile way apply appropriate controls on access so that people themselves are and groups within businesses are our job and could innovate. Otherwise, everything grinds to a halt, and you risk falling behind your competitors. >>Yeah, that one size fits all term just doesn't apply when you're talking about adaptive and agility. So we heard from Santiago about some of the impact that they're making with First Bank of Nigeria. Used to talk to us about some of the business outcomes that you're seeing other customers make leveraging automation that they could not do >>before it's it's automatically being able to classify terabytes, terabytes of data or even petabytes of data across different sources to find duplicates, which you can then re mediate on. Deletes now, with the capabilities that iota offers on the Oracle offers, you can do things not just where the five times or 10 times improvement, but it actually enables you to do projects for Stop that otherwise would fail or you would just not be able to dio I mean, uh, classifying multi terrible and multi petabytes states across different sources, formats very large volumes of data in many scenarios. You just can't do that manually. I mean, we've worked with government departments on the issues there is expect are the result of fragmented data. There's a lot of different sources. There's lot of different formats and without these newer technologies to address it with automation on machine learning, the project isn't durable. But now it is on that that could lead to a revolution in some of these businesses organizations >>to enable that revolution that there's got to be the right cultural mindset. And one of the when Santiago was talking about folks really kind of adapted that. The thing I always call that getting comfortably uncomfortable. But that's hard for organizations to. The technology is here to enable that. But well, you're talking with customers use. How do you help them build the trust in the confidence that the new technologies and a new approaches can deliver what they need? How do you help drive the kind of a tech in the culture? >>It's really good question is because it can be quite scary. I think the first thing we'd start with is to say, Look, the technology is here with businesses like I Tahoe. Unlike Oracle, it's already arrived. What you need to be comfortable doing is experimenting being agile around it, Andi trying new ways of doing things. Uh, if you don't wanna get less behind that Santiago on the team that fbn are a great example off embracing it, testing it on a small scale on, then scaling up a Toyota, we offer what we call a data health check, which can actually be done very quickly in a matter of a few weeks. So we'll work with a customer. Picky use case, install the application, uh, analyzed data. Drive out Cem Cem quick winds. So we worked in the last few weeks of a large entity energy supplier, and in about 20 days, we were able to give them an accurate understanding of their critical data. Elements apply. Helping apply data protection policies. Minimize copies of the data on work out what data they needed to delete to reduce their infrastructure. Spend eso. It's about experimenting on that small scale, being agile on, then scaling up in a kind of very modern way. >>Great advice. Uh, Santiago, I'd like to go back to Is we kind of look at again that that topic of culture and the need to get that mindset there to facilitate these rapid changes, I want to understand kind of last question for you about how you're doing that from a digital transformation perspective. We know everything is accelerating in 2020. So how are you building resilience into your data architecture and also driving that cultural change that can help everyone in this shift to remote working and a lot of the the digital challenges and changes that we're all going through? >>The new technologies allowed us to discover the dating anyway. Toe flawed and see very quickly Information toe. Have new models off over in the data on giving autonomy to our different data units. Now, from that autonomy, they can then compose an innovator own ways. So for me now, we're talking about resilience because in a way, autonomy and flexibility in a organization in a data structure with platform gives you resilience. The organizations and the business units that I have experienced in the pandemic are working well. Are those that actually because they're not physically present during more in the office, you need to give them their autonomy and let them actually engaged on their own side that do their own job and trust them in a way on as you give them, that they start innovating and they start having a really interesting ideas. So autonomy and flexibility. I think this is a key component off the new infrastructure. But even the new reality that on then it show us that, yes, we used to be very kind off structure, policies, procedures as very important. But now we learn flexibility and adaptability of the same side. Now, when you have that a key, other components of resiliency speed, because people want, you know, to access the data and access it fast and on the site fast, especially changes are changing so quickly nowadays that you need to be ableto do you know, interact. Reiterate with your information to answer your questions. Pretty, um, so technology that allows you toe be flexible iterating on in a very fast job way continue will allow you toe actually be resilient in that way, because you are flexible, you adapt your job and you continue answering questions as they come without having everything, setting a structure that is too hard. We also are a partner off Oracle and Oracle. Embodies is great. They have embedded within the transactional system many algorithms that are allowing us to calculate as the transactions happened. What happened there is that when our customers engaged with algorithms and again without your powers, well, the machine learning that is there for for speeding the automation of how you find your data allows you to create a new alliance with the machine. The machine is their toe, actually, in a way to your best friend to actually have more volume of data calculated faster. In a way, it's cover more variety. I mean, we couldn't hope without being connected to this algorithm on >>that engagement is absolutely critical. Santiago. Thank you for sharing that. I do wanna rap really quickly. Good On one last question for you, Santiago talked about Oracle. You've talked about a little bit. As we look at digital resilience, talk to us a little bit in the last minute about the evolution of Oracle. What you guys were doing there to help your customers get the resilience that they have toe have to be not just survive but thrive. >>Yeah. Oracle has a cloud offering for infrastructure, database, platform service and a complete solutions offered a South on Daz. As Santiago also mentioned, We are using AI across our entire portfolio and by this will help our customers to focus on their business innovation and capitalize on data by enabling new business models. Um, and Oracle has a global conference with our cloud regions. It's massively investing and innovating and expanding their clouds. And by offering clouds as public cloud in our data centers and also as private cloud with clouded customer, we can meet every sovereignty and security requirements. And in this way we help people to see data in new ways. We discover insights and unlock endless possibilities. And and maybe 11 of my takeaways is if I If I speak with customers, I always tell them you better start collecting your data. Now we enable this partners like Iota help us as well. If you collect your data now, you are ready for tomorrow. You can never collect your data backwards, So that is my take away for today. >>You can't collect your data backwards. Excellently, John. Gentlemen, thank you for sharing all of your insights. Very informative conversation in a moment, we'll address the question. Do you know your data? >>Are you interested in test driving the iota Ho platform kick Start the benefits of data automation for your business through the Iota Ho Data Health check program. Ah, flexible, scalable sandbox environment on the cloud of your choice with set up service and support provided by Iota ho. Look time with a data engineer to learn more and see Io Tahoe in action from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>In this next segment, we're gonna be talking to you about getting to know your data. And specifically you're gonna hear from two folks at Io Tahoe. We've got enterprise account execs to be to Davis here, as well as Enterprise Data engineer Patrick Simon. They're gonna be sharing insights and tips and tricks for how you could get to know your data and quickly on. We also want to encourage you to engage with the media and Patrick, use the chat feature to the right, send comments, questions or feedback so you can participate. All right, Patrick Savita, take it away. Alright. >>Thankfully saw great to be here as Lisa mentioned guys, I'm the enterprise account executive here in Ohio. Tahoe you Pat? >>Yeah. Hey, everyone so great to be here. I said my name is Patrick Samit. I'm the enterprise data engineer here in Ohio Tahoe. And we're so excited to be here and talk about this topic as one thing we're really trying to perpetuate is that data is everyone's business. >>So, guys, what patent I got? I've actually had multiple discussions with clients from different organizations with different roles. So we spoke with both your technical and your non technical audience. So while they were interested in different aspects of our platform, we found that what they had in common was they wanted to make data easy to understand and usable. So that comes back. The pats point off to being everybody's business because no matter your role, we're all dependent on data. So what Pan I wanted to do today was wanted to walk you guys through some of those client questions, slash pain points that we're hearing from different industries and different rules and demo how our platform here, like Tahoe, is used for automating Dozier related tasks. So with that said are you ready for the first one, Pat? >>Yeah, Let's do it. >>Great. So I'm gonna put my technical hat on for this one. So I'm a data practitioner. I just started my job. ABC Bank. I have, like, over 100 different data sources. So I have data kept in Data Lakes, legacy data, sources, even the cloud. So my issue is I don't know what those data sources hold. I don't know what data sensitive, and I don't even understand how that data is connected. So how can I saw who help? >>Yeah, I think that's a very common experience many are facing and definitely something I've encountered in my past. Typically, the first step is to catalog the data and then start mapping the relationships between your various data stores. Now, more often than not, this has tackled through numerous meetings and a combination of excel and something similar to video which are too great tools in their own part. But they're very difficult to maintain. Just due to the rate that we are creating data in the modern world. It starts to beg for an idea that can scale with your business needs. And this is where a platform like Io Tahoe becomes so appealing, you can see here visualization of the data relationships created by the I. O. Tahoe service. Now, what is fantastic about this is it's not only laid out in a very human and digestible format in the same action of creating this view, the data catalog was constructed. >>Um so is the data catalog automatically populated? Correct. Okay, so So what I'm using Iota hope at what I'm getting is this complete, unified automated platform without the added cost? Of course. >>Exactly. And that's at the heart of Iota Ho. A great feature with that data catalog is that Iota Ho will also profile your data as it creates the catalog, assigning some meaning to those pesky column underscore ones and custom variable underscore tents. They're always such a joy to deal with. Now, by leveraging this interface, we can start to answer the first part of your question and understand where the core relationships within our data exists. Uh, personally, I'm a big fan of this view, as it really just helps the i b naturally John to these focal points that coincide with these key columns following that train of thought, Let's examine the customer I D column that seems to be at the center of a lot of these relationships. We can see that it's a fairly important column as it's maintaining the relationship between at least three other tables. >>Now you >>notice all the connectors are in this blue color. This means that their system defined relationships. But I hope Tahoe goes that extra mile and actually creates thes orange colored connectors as well. These air ones that are machine learning algorithms have predicted to be relationships on. You can leverage to try and make new and powerful relationships within your data. >>Eso So this is really cool, and I can see how this could be leverage quickly now. What if I added new data sources or your multiple data sources and need toe identify what data sensitive can iota who detect that? >>Yeah, definitely. Within the hotel platform. There, already over 300 pre defined policies such as hip for C, C, P. A and the like one can choose which of these policies to run against their data along for flexibility and efficiency and running the policies that affect organization. >>Okay, so so 300 is an exceptional number. I'll give you that. But what about internal policies that apply to my organization? Is there any ability for me to write custom policies? >>Yeah, that's no issue. And it's something that clients leverage fairly often to utilize this function when simply has to write a rejects that our team has helped many deploy. After that, the custom policy is stored for future use to profile sensitive data. One then selects the data sources they're interested in and select the policies that meet your particular needs. The interface will automatically take your data according to the policies of detects, after which you can review the discoveries confirming or rejecting the tagging. All of these insights are easily exported through the interface. Someone can work these into the action items within your project management systems, and I think this lends to the collaboration as a team can work through the discovery simultaneously, and as each item is confirmed or rejected, they can see it ni instantaneously. All this translates to a confidence that with iota hope, you can be sure you're in compliance. >>So I'm glad you mentioned compliance because that's extremely important to my organization. So what you're saying when I use the eye a Tahoe automated platform, we'd be 90% more compliant that before were other than if you were going to be using a human. >>Yeah, definitely the collaboration and documentation that the Iot Tahoe interface lends itself to really help you build that confidence that your compliance is sound. >>So we're planning a migration. Andi, I have a set of reports I need to migrate. But what I need to know is, uh well, what what data sources? Those report those reports are dependent on. And what's feeding those tables? >>Yeah, it's a fantastic questions to be toe identifying critical data elements, and the interdependencies within the various databases could be a time consuming but vital process and the migration initiative. Luckily, Iota Ho does have an answer, and again, it's presented in a very visual format. >>Eso So what I'm looking at here is my entire day landscape. >>Yes, exactly. >>Let's say I add another data source. I can still see that unified 3 60 view. >>Yeah, One future that is particularly helpful is the ability to add data sources after the data lineage. Discovery has finished alone for the flexibility and scope necessary for any data migration project. If you only need need to select a few databases or your entirety, this service will provide the answers. You're looking for things. Visual representation of the connectivity makes the identification of critical data elements a simple matter. The connections air driven by both system defined flows as well as those predicted by our algorithms, the confidence of which, uh, can actually be customized to make sure that they're meeting the needs of the initiative that you have in place. This also provides tabular output in case you needed for your own internal documentation or for your action items, which we can see right here. Uh, in this interface, you can actually also confirm or deny the pair rejection the pair directions, allowing to make sure that the data is as accurate as possible. Does that help with your data lineage needs? >>Definitely. So So, Pat, My next big question here is So now I know a little bit about my data. How do I know I can trust >>it? So >>what I'm interested in knowing, really is is it in a fit state for me to use it? Is it accurate? Does it conform to the right format? >>Yeah, that's a great question. And I think that is a pain point felt across the board, be it by data practitioners or data consumers alike. Another service that I owe Tahoe provides is the ability to write custom data quality rules and understand how well the data pertains to these rules. This dashboard gives a unified view of the strength of these rules, and your dad is overall quality. >>Okay, so Pat s o on on the accuracy scores there. So if my marketing team needs to run, a campaign can read dependent those accuracy scores to know what what tables have quality data to use for our marketing campaign. >>Yeah, this view would allow you to understand your overall accuracy as well as dive into the minutia to see which data elements are of the highest quality. So for that marketing campaign, if you need everything in a strong form, you'll be able to see very quickly with these high level numbers. But if you're only dependent on a few columns to get that information out the door, you can find that within this view, eso >>you >>no longer have to rely on reports about reports, but instead just come to this one platform to help drive conversations between stakeholders and data practitioners. >>So I get now the value of IATA who brings by automatically capturing all those technical metadata from sources. But how do we match that with the business glossary? >>Yeah, within the same data quality service that we just reviewed, one can actually add business rules detailing the definitions and the business domains that these fall into. What's more is that the data quality rules were just looking at can then be tied into these definitions. Allowing insight into the strength of these business rules is this service that empowers stakeholders across the business to be involved with the data life cycle and take ownership over the rules that fall within their domain. >>Okay, >>so those custom rules can I apply that across data sources? >>Yeah, you could bring in as many data sources as you need, so long as you could tie them to that unified definition. >>Okay, great. Thanks so much bad. And we just want to quickly say to everyone working in data, we understand your pain, so please feel free to reach out to us. we are Website the chapel. Oh, Arlington. And let's get a conversation started on how iota Who can help you guys automate all those manual task to help save you time and money. Thank you. Thank >>you. Your Honor, >>if I could ask you one quick question, how do you advise customers? You just walk in this great example this banking example that you instantly to talk through. How do you advise customers get started? >>Yeah, I think the number one thing that customers could do to get started with our platform is to just run the tag discovery and build up that data catalog. It lends itself very quickly to the other needs you might have, such as thes quality rules. A swell is identifying those kind of tricky columns that might exist in your data. Those custom variable underscore tens I mentioned before >>last questions to be to anything to add to what Pat just described as a starting place. >>I'm no, I think actually passed something that pretty well, I mean, just just by automating all those manual task. I mean, it definitely can save your company a lot of time and money, so we we encourage you just reach out to us. Let's get that conversation >>started. Excellent. So, Pete and Pat, thank you so much. We hope you have learned a lot from these folks about how to get to know your data. Make sure that it's quality, something you can maximize the value of it. Thanks >>for watching. Thanks again, Lisa, for that very insightful and useful deep dive into the world of adaptive data governance with Iota Ho Oracle First Bank of Nigeria This is Dave a lot You won't wanna mess Iota, whose fifth episode in the data automation Siri's in that we'll talk to experts from Red Hat and Happiest Minds about their best practices for managing data across hybrid cloud Inter Cloud multi Cloud I T environment So market calendar for Wednesday, January 27th That's Episode five. You're watching the Cube Global Leader digital event technique

>>from around the globe. It's the Cube with digital coverage of enterprise data automation an event Siri's brought to you by Iot. Tahoe. >>Okay, we're back. Welcome back to data Automated. A J ahora is CEO of I o Ta ho, JJ. Good to see you. How have things in London? >>Big thing. Well, thinking well, where we're making progress, I could see you hope you're doing well and pleasure being back here on the Cube. >>Yeah, it's always great to talk to. You were talking enterprise data automation. As you know, with within our community, we've been pounding the whole data ops conversation. Little different, though. We're gonna We're gonna dig into that a little bit. But let's start with a J how you've seen the response to Covert and I'm especially interested in the role that data has played in this pandemic. >>Yeah, absolutely. I think everyone's adapting both essentially, um, and and in business, the customers that I speak to on day in, day out that we partner with, um they're busy adapting their businesses to serve their customers. It's very much a game of and showing the week and serve our customers to help their customers um, you know, the adaptation that's happening here is, um, trying to be more agile, kind of the most flexible. Um, a lot of pressure on data. A lot of demand on data and to deliver more value to the business, too. Serve that customer. >>Yeah. I mean, data machine intelligence and cloud, or really three huge factors that have helped organizations in this pandemic. And, you know, the machine intelligence or AI piece? That's what automation is all about. How do you see automation helping organizations evolve maybe faster than they thought they might have to >>Sure. I think the necessity of these times, um, there's there's a says a lot of demand doing something with data data. Uh huh. A lot of a lot of businesses talk about being data driven. Um, so interesting. I sort of look behind that when we work with our customers, and it's all about the customer. You know, the mic is cios invested shareholders. The common theme here is the customer. That customer experience starts and ends with data being able to move from a point that is reacting. So what the customer is expecting and taking it to that step forward where you can be proactive to serve what that customer's expectation to and that's definitely come alive now with they, um, the current time. >>Yes. So, as I said, we've been talking about data ops a lot. The idea being Dev Ops applied to the data pipeline. But talk about enterprise data automation. What is it to you and how is it different from data off? >>Yeah, Great question. Thank you. I am. I think we're all familiar with felt more more awareness around. So as it's applied, Teoh, uh, processes methodologies that have become more mature of the past five years around devil that managing change, managing an application, life cycles, managing software development data about, you know, has been great. But breaking down those silos between different roles functions and bringing people together to collaborate. Andi, you know, we definitely see that those tools, those methodologies, those processes, that kind of thinking, um, landing itself to data with data is exciting. We're excited about that, Andi shifting the focus from being I t versus business users to you know who are the data producers. And here the data consumers in a lot of cases, it concert in many different lines of business. So in data role, those methods those tools and processes well we look to do is build on top of that with data automation. It's the is the nuts and bolts of the the algorithms, the models behind machine learning that the functions. That's where we investors our R and D and bringing that in to build on top of the the methods, the ways of thinking that break down those silos on injecting that automation into the business processes that are going to drive a business to serve its customers. It's, um, a layer beyond Dev ops data ops. They can get to that point where well, I think about it is, Is the automation behind the automation we can take? I'll give you an example. Okay, a bank where we did a lot of work to do make move them into accelerating that digital transformation. And what we're finding is that as we're able to automate the jobs related to data a managing that data and serving that data that's going into them as a business automating their processes for their customer. Um, so it's it's definitely having a compound effect. >>Yeah, I mean I think that you did. Data ops for a lot of people is somewhat new to the whole Dev Ops. The data ops thing is is good and it's a nice framework. Good methodology. There is obviously a level of automation in there and collaboration across different roles. But it sounds like you're talking about so supercharging it, if you will, the automation behind the automation. You know, I think organizations talk about being data driven. You hear that? They have thrown around a lot of times. People sit back and say, We don't make decisions without data. Okay? But really, being data driven is there's a lot of aspects there. There's cultural, but it's also putting data at the core of your organization, understanding how it effects monetization. And, as you know, well, silos have been built up, whether it's through M and a, you know, data sprawl outside data sources. So I'm interested in your thoughts on what data driven means and specifically Hi, how Iot Tahoe plays >>there. Yeah, I'm sure we'll be happy. That look that three David, we've We've come a long way in the last four years. We started out with automating some of those simple, um, to codify. Um, I have a high impact on organization across the data, a data warehouse. There's data related tasks that classify data on and a lot of our original pattern. Senai people value that were built up is is very much around. They're automating, classifying data across different sources and then going out to so that for some purpose originally, you know, some of those simpler I'm challenges that we have. Ah, custom itself, um, around data privacy. You know, I've got a huge data lake here. I'm a telecoms business. I've got millions of six subscribers. Um, quite often the chief data office challenges. How do I cover the operational risk? Where, um, I got so much data I need to simplify my approach to automating, classifying that data. Recent is you can't do that manually. We can for people at it. And the the scale of that is is prohibitive, right? Often, if you had to do it manually by the time you got a good picture of it, it's already out of date. Then, starting with those those simple challenges that we've been able to address, we're then going on and build on that to say, What else do we serve? What else do we serve? The chief data officer, Chief marketing officer on the CFO. Within these times, um, where those decision makers are looking for having a lot of choices in the platform options that they say that the tooling they're very much looking for We're that Swiss army. Not being able to do one thing really well is is great, but more more. Where that cost pressure challenge is coming in is about how do we, um, offer more across the organization, bring in those business lines of business activities that depend on data to not just with a T. Okay, >>so we like the cube. Sometimes we like to talk about Okay, what is it? And then how does it work? And what's the business impact? We kind of covered what it is but love to get into the tech a little bit in terms of how it works. And I think we have a graphic here that gets into that a little bit. So, guys, if you bring that up, I wonder if you could tell us and what is the secret sauce behind Iot Tahoe? And if you could take us through this slot. >>Sure. I mean, right there in the middle that the heart of what we do It is the intellectual property. Yeah, that was built up over time. That takes from Petra genius data sources Your Oracle relational database, your your mainframe. If they lay in increasingly AP eyes and devices that produce data and that creates the ability to automatically discover that data, classify that data after it's classified them have the ability to form relationships across those different, uh, source systems, silos, different lines of business. And once we've automated that that we can start to do some cool things that just puts a contact and meaning around that data. So it's moving it now from bringing data driven on increasingly well. We have really smile, right people in our customer organizations you want do some of those advanced knowledge tasks, data scientists and, uh, quants in some of the banks that we work with. The the onus is on, then, putting everything we've done there with automation, pacifying it, relationship, understanding that equality policies that you apply to that data. I'm putting it in context once you've got the ability to power. A a professional is using data, um, to be able to put that data and contacts and search across the entire enterprise estate. Then then they can start to do some exciting things and piece together the tapestry that fabric across that different systems could be crm air P system such as s AP on some of the newer cloud databases that we work with. Snowflake is a great Well, >>yes. So this is you're describing sort of one of the one of the reasons why there's so many stove pipes and organizations because data is gonna locked in the silos of applications. I also want to point out, you know, previously to do discovery to do that classification that you talked about form those relationship to glean context from data. A lot of that, if not most of that in some cases all that would have been manual. And of course, it's out of date so quickly. Nobody wants to do it because it's so hard. So this again is where automation comes into the the the to the idea of really becoming data driven. >>Sure. I mean the the efforts. If we if I look back, maybe five years ago, we had a prevalence of daily technologies at the cutting edge. Those have said converging me to some of these cloud platforms. So we work with Google and AWS, and I think very much is, as you said it, those manual attempts to try and grasp. But it is such a complex challenge at scale. I quickly runs out of steam because once, um, once you've got your hat, once you've got your fingers on the details Oh, um, what's what's in your data estate? It's changed, you know, you've onboard a new customer. You signed up a new partner, Um, customer has no adopted a new product that you just Lawrence and there that that slew of data it's keeps coming. So it's keeping pace with that. The only answer really is is some form of automation. And what we found is if we can tie automation with what I said before the expertise the, um, the subject matter expertise that sometimes goes back many years within an organization's people that augmentation between machine learning ai on and on that knowledge that sits within inside the organization really tends to involve a lot of value in data? >>Yes, So you know Well, a J you can't be is a smaller company, all things to all people. So your ecosystem is critical. You working with AWS? You're working with Google. You got red hat. IBM is as partners. What is attracting those folks to your ecosystem and give us your thoughts on the importance of ecosystem? >>Yeah, that's that's fundamental. So I mean, when I caimans, we tell her here is the CEO of one of the, um, trends that I wanted us to to be part of was being open, having an open architecture that allowed one thing that was nice to my heart, which is as a CEO, um, a C I O where you've got a budget vision and you've already made investments into your organization, and some of those are pretty long term bets. They should be going out 5 10 years, sometimes with CRM system training up your people, getting everybody working together around a common business platform. What I wanted to ensure is that we could openly like it using ap eyes that were available, the love that some investment on the cost that has already gone into managing in organizations I t. But business users to before So part of the reason why we've been able to be successful with, um, the partners like Google AWS and increasingly, a number of technology players. That red hat mongo DB is another one where we're doing a lot of good work with, um, and snowflake here is, um it's those investments have been made by the organizations that are our customers, and we want to make sure we're adding to that, and they're leveraging the value that they've already committed to. >>Okay, so we've talked about kind of what it is and how it works, and I want to get into the business impact. I would say what I would be looking for from from this would be Can you help me lower my operational risk? I've got I've got tasks that I do many year sequential, some who are in parallel. But can you reduce my time to task? And can you help me reduce the labor intensity and ultimately, my labor costs? And I put those resources elsewhere, and ultimately, I want to reduce the end and cycle time because that is going to drive Telephone number R. A. Y So, um, I missing anything? Can you do those things? And maybe you could give us some examples of the tiara y and the business impact. >>Yeah. I mean, the r a y David is is built upon on three things that I mentioned is a combination off leveraging the existing investment with the existing state, whether that's home, Microsoft, Azure or AWS or Google IBM. And I'm putting that to work because, yeah, the customers that we work with have had made those choices. On top of that, it's, um, is ensuring that we have you got the automation that is working right down to the level off data, a column level or the file level so we don't do with meta data. It is being very specific to be at the most granular level. So as we've grown our processes and on the automation, gasification tagging, applying policies from across different compliance and regulatory needs, that an organization has to the data, everything that then happens downstream from that is ready to serve a business outcome. It could be a customer who wants that experience on a mobile device. A tablet oh, face to face within, within the store. I mean game. Would you provision the right data and enable our customers do that? But their customers, with the right data that they can trust at the right time, just in that real time moment where decision or an action is being expected? That's, um, that's driving the r a y two b in some cases, 20 x but and that's that's really satisfying to see that that kind of impact it is taking years down to months and in many cases, months of work down to days. In some cases, our is the time to value. I'm I'm impressed with how quickly out of the box with very little training a customer and think about, too. And you speak just such a search. They discovery knowledge graph on DM. I don't find duplicates. Onda Redundant data right off the bat within hours. >>Well, it's why investors are interested in this space. I mean, they're looking for a big, total available market. They're looking for a significant return. 10 X is you gotta have 10 x 20 x is better. So so that's exciting and obviously strong management and a strong team. I want to ask you about people and culture. So you got people process technology we've seen with this pandemic that processes you know are really unpredictable. And the technology has to be able to adapt to any process, not the reverse. You can't force your process into some static software, so that's very, very important. But the end of the day you got to get people on board. So I wonder if you could talk about this notion of culture and a data driven culture. >>Yeah, that's that's so important. I mean, current times is forcing the necessity of the moment to adapt. But as we start to work their way through these changes on adapt ah, what with our customers, But that is changing economic times. What? What we're saying here is the ability >>to I >>have, um, the technology Cartman, in a really smart way, what those business uses an I T knowledge workers are looking to achieve together. So I'll give you an example. We have quite often with the data operations teams in the companies that we, um, partnering with, um, I have a lot of inbound enquiries on the day to day level. I really need this set of data they think it can help my data scientists run a particular model? Or that what would happen if we combine these two different silence of data and gets the Richmond going now, those requests you can, sometimes weeks to to realize what we've been able to do with the power is to get those answers being addressed by the business users themselves. And now, without without customers, they're coming to the data. And I t folks saying, Hey, I've now built something in the development environment. Why don't we see how that can scale up with these sets of data? I don't need terabytes of it. I know exactly the columns and the feet in the data that I'm going to use on that gets seller wasted in time, um, angle to innovate. >>Well, that's huge. I mean, the whole notion of self service and the lines of business actually feeling like they have ownership of the data as opposed to, you know, I t or some technology group owning the data because then you've got data quality issues or if it doesn't line up there their agenda, you're gonna get a lot of finger pointing. So so that is a really important. You know a piece of it. I'll give you last word A J. Your final thoughts, if you would. >>Yeah, we're excited to be the only path. And I think we've built great customer examples here where we're having a real impact in in a really fast pace, whether it helping them migrate to the cloud, helping the bean up their legacy, Data lake on and write off there. Now the conversation is around data quality as more of the applications that we enable to a more efficiently could be data are be a very robotic process automation along the AP, eyes that are now available in the cloud platforms. A lot of those they're dependent on data quality on and being able to automate. So business users, um, to take accountability off being able to so look at the trend of their data quality over time and get the signals is is really driving trust. And that trust in data is helping in time. Um, the I T teams, the data operations team, with do more and more quickly that comes back to culture being out, supply this technology in such a way that it's visual insensitive. Andi. How being? Just like Dev Ops tests with with a tty Dave drops putting intelligence in at the data level to drive that collaboration. We're excited, >>you know? You remind me of something. I lied. I don't want to go yet. It's OK, so I know we're tight on time, but you mentioned migration to the cloud. And I'm thinking about conversation with Paula from Webster Webster. Bank migrations. Migrations are, you know, they're they're a nasty word for for organizations. So our and we saw this with Webster. How are you able to help minimize the migration pain and and why is that something that you guys are good at? >>Yeah. I mean, there were many large, successful companies that we've worked with. What's There's a great example where, you know, I'd like to give you the analogy where, um, you've got a lot of people in your teams if you're running a business as a CEO on this bit like a living living grade. But imagine if those different parts of your brain we're not connected, that with, um, so diminish how you're able to perform. So what we're seeing, particularly with migration, is where banks retailers. Manufacturers have grown over the last 10 years through acquisition on through different initiatives, too. Um, drive customer value that sprawl in their data estate hasn't been fully dealt with. It sometimes been a good thing, too. Leave whatever you're fired off the agent incent you a side by side with that legacy mainframe on your oracle, happy and what we're able to do very quickly with that migration challenges shine a light on all the different parts. Oh, data application at the column level or higher level if it's a day late and show an enterprise architect a CDO how everything's connected, where they may not be any documentation. The bright people that created some of those systems long since moved on or retired or been promoted into so in the rose on within days, being out to automatically generate Anke refreshed the states of that data across that man's game on and put it into context, then allows you to look at a migration from a confidence that you did it with the back rather than what we've often seen in the past is teams of consultant and business analysts. Data around this spend months getting an approximation and and a good idea of what it could be in the current state and try their very best to map that to the future Target state. Now, without all hoping out, run those processes within hours of getting started on, um well, that picture visualize that picture and bring it to life. You know, the Yarra. Why, that's off the bat with finding data that should have been deleted data that was copies off on and being able to allow the architect whether it's we're working on gcb or migration to any other clouds such as AWS or a multi cloud landscape right now with yeah, >>that visibility is key. Teoh sort of reducing operational risks, giving people confidence that they can move forward and being able to do that and update that on an ongoing basis, that means you can scale a J. Thanks so much for coming on the Cube and sharing your insights and your experience is great to have >>you. Thank you, David. Look towards smoking in. >>Alright, keep it right there, everybody. We're here with data automated on the Cube. This is Dave Volante and we'll be right back. Short break. >>Yeah, yeah, yeah, yeah

>>from around the globe. It's the Cube with digital coverage of enterprise data automation, an event Siri's brought to you by Iot. Tahoe, everybody, We're back. We're talking about enterprise data automation. The hashtag is data automated, and we're going to really dig into data migrations, data, migrations. They're risky. They're time consuming, and they're expensive. Yousef con is here. He's the head of partnerships and alliances at I o ta ho coming again from London. Hey, good to see you, Seth. Thanks very much. >>Thank you. >>So your role is is interesting. We're talking about data migrations. You're gonna head of partnerships. What is your role specifically? And how is it relevant to what we're gonna talk about today? >>Uh, I work with the various businesses such as cloud companies, systems integrators, companies that sell operating systems, middleware, all of whom are often quite well embedded within a company. I t infrastructures and have existing relationships. Because what we do fundamentally makes migrating to the cloud easier on data migration easier. A lot of businesses that are interested in partnering with us. Um, we're interested in parting with, So >>let's set up the problem a little bit. And then I want to get into some of the data. You know, I said that migration is a risky, time consuming, expensive. They're they're often times a blocker for organizations to really get value out of data. Why is that? >>Uh, I think I mean, all migrations have to start with knowing the facts about your data, and you can try and do this manually. But when that you have an organization that may have been going for decades or longer, they will probably have a pretty large legacy data estate so that I have everything from on premise mainframes. They may have stuff which is probably in the cloud, but they probably have hundreds, if not thousands of applications and potentially hundreds of different data stores. Um, now they're understanding of what they have. Ai's often quite limited because you can try and draw a manual maps, but they're outdated very quickly. Every time that data changes the manual that's out of date on people obviously leave organizations over time, so that kind of tribal knowledge gets built up is limited as well. So you can try a Mackel that manually you might need a db. Hey, thanks. Based analyst or ah, business analyst, and they won't go in and explore the data for you. But doing that manually is very, very time consuming this contract teams of people, months and months. Or you can use automation just like what's the bank with Iot? And they managed to do this with a relatively small team. Are in a timeframe of days. >>Yeah, we talked to Paul from Webster Bank. Awesome discussion. So I want to dig into this migration and let's let's pull up graphic it will talk about. We'll talk about what a typical migration project looks like. So what you see here it is. It's very detailed. I know it's a bit of an eye test, but let me call your attention to some of the key aspects of this Ah, and then use. If I want you to chime in. So at the top here, you see that area graph that's operational risk for a typical migration project, and you can see the timeline and the the milestones. That blue bar is the time to test so you can see the second step data analysis talking 24 weeks so, you know, very time consuming. And then Let's not get dig into the stuff in the middle of the fine print, but there's some real good detail there, but go down the bottom. That's labor intensity in the in the bottom and you can see high is that sort of brown and and you could see a number of data analysis, data staging data prep, the trial, the implementation post implementation fixtures, the transition toe B A B a year, which I think is business as usual. Those are all very labor intensive. So what do you take aways from this typical migration project? What do we need to know yourself? >>I mean, I think the key thing is, when you don't understand your data upfront, it's very difficult to scope to set up a project because you go to business stakeholders and decision makers and you say Okay, we want to migrate these data stores. We want to put them in the cloud most often, but actually, you probably don't know how much data is there. You don't necessarily know how many applications that relates to, you know, the relationships between the data. You don't know the flow of the data. So the direction in which the data is going between different data stores and tables, so you start from a position where you have pretty high risk and alleviate that risk. You could be stacking project team of lots and lots of people to do the next base, which is analysis. And so you set up a project which has got a pretty high cost. The big projects, more people, the heavy of governance, obviously on then there, then in the phase where they're trying to do lots and lots of manual analysis manage. That, in a sense, is, as we all know, on the idea of trying to relate data that's in different those stores relating individual tables and columns. Very, very time consuming, expensive. If you're hiring in resource from consultants or systems integrators externally, you might need to buy or to use party tools, Aziz said earlier. The people who understand some of those systems may have left a while ago. See you even high risks quite cost situation from the off on the same things that have developed through the project. Um, what are you doing with it, Ayatollah? Who is that? We're able to automate a lot of this process from the very beginning because we can do the initial data. Discovery run, for example, automatically you very quickly have an automated validator. A data map on the data flow has been generated automatically, much less time and effort and much less cars. Doctor Marley. >>Okay, so I want to bring back that that first chart, and I want to call your attention to the again that area graph the blue bars and then down below that labor intensity. And now let's bring up the the the same chart. But with a set of an automation injection in here and now. So you now see the So let's go Said Accelerated by Iot, Tom. Okay, great. And we're going to talk about this. But look, what happens to the operational risk. A dramatic reduction in that. That graph. And then look at the bars, the bars, those blue bars. You know, data analysis went from 24 weeks down to four weeks and then look at the labor intensity. The it was all these were high data analysis data staging data prep. Try a lot post implementation fixtures in transition to be a you. All of those went from high labor intensity. So we've now attack that and gone to low labor intensity. Explain how that magic happened. >>I think that the example off a data catalog. So every large enterprise wants to have some kind of repository where they put all their understanding about their data in its Price States catalog, if you like, um, imagine trying to do that manually. You need to go into every individual data store. You need a DB a business analyst, rich data store they need to do in extracted the data table was individually they need to cross reference that with other data school, it stores and schemers and tables. You probably were the mother of all lock Excel spreadsheets. It would be a very, very difficult exercise to do. I mean, in fact, one of our reflections as we automate lots of data lots of these things is, um it accelerates the ability to water may, But in some cases, it also makes it possible for enterprise customers with legacy systems um, take banks, for example. There quite often end up staying on mainframe systems that they've had in place for decades. Uh, no migrating away from them because they're not able to actually do the work of understanding the data g duplicating the data, deleting data isn't relevant and then confidently going forward to migrate. So they stay where they are with all the attendant problems assistance systems that are out of support. Go back to the data catalog example. Um, whatever you discover invades, discovery has to persist in a tool like a data catalog. And so we automate data catalog books, including Out Way Cannot be others, but we have our own. The only alternative to this kind of automation is to build out this very large project team or business analysts off db A's project managers processed analysts together with data to understand that the process of gathering data is correct. To put it in the repository to validate it except etcetera, we've got into organizations and we've seen them ramp up teams off 2030 people costs off £234 million a year on a time frame, 15 20 years just to try and get a data catalog done. And that's something that we can typically do in a timeframe of months, if not weeks. And the difference is using automation. And if you do what? I've just described it. In this manual situation, you make migrations to the cloud prohibitively expensive. Whatever saving you might make from shutting down your legacy data stores, we'll get eaten up by the cost of doing it. Unless you go with the more automated approach. >>Okay, so the automated approach reduces risk because you're not gonna, you know you're going to stay on project plan. Ideally, it's all these out of scope expectations that come up with the manual processes that kill you in the rework andan that data data catalog. People are afraid that their their family jewels data is not going to make it through to the other side. So So that's something that you're you're addressing and then you're also not boiling the ocean. You're really taking the pieces that are critical and stuff you don't need. You don't have to pay for >>process. It's a very good point. I mean, one of the other things that we do and we have specific features to do is to automatically and noise data for a duplication at a rover or record level and redundancy on a column level. So, as you say before you go into a migration process. You can then understand. Actually, this stuff it was replicated. We don't need it quite often. If you put data in the cloud you're paying, obviously, the storage based offer compute time. The more data you have in there that's duplicated, that is pure cost. You should take out before you migrate again if you're trying to do that process of understanding what's duplicated manually off tens or hundreds of bases stores. It was 20 months, if not years. Use machine learning to do that in an automatic way on it's much, much quicker. I mean, there's nothing I say. Well, then, that costs and benefits of guitar. Every organization we work with has a lot of money existing, sunk cost in their I t. So have your piece systems like Oracle or Data Lakes, which they've spent a good time and money investing in. But what we do by enabling them to transition everything to the strategic future repositories, is accelerate the value of that investment and the time to value that investment. So we're trying to help people get value out of their existing investments on data estate, close down the things that they don't need to enable them to go to a kind of brighter, more future well, >>and I think as well, you know, once you're able to and this is a journey, we know that. But once you're able to go live on, you're infusing sort of a data mindset, a data oriented culture. I know it's somewhat buzzword, but when you when you see it in organizations, you know it's really and what happens is you dramatically reduce that and cycle time of going from data to actually insights. Data's plentiful, but insights aren't, and that is what's going to drive competitive advantage over the next decade and beyond. >>Yeah, definitely. And you could only really do that if you get your data estate cleaned up in the first place. Um, I worked with the managed teams of data scientists, data engineers, business analysts, people who are pushing out dashboards and trying to build machine learning applications. You know, you know, the biggest frustration for lots of them and the thing that they spend far too much time doing is trying to work out what the right data is on cleaning data, which really you don't want a highly paid thanks to scientists doing with their time. But if you sort out your data stays in the first place, get rid of duplication. If that pans migrate to cloud store, where things are really accessible on its easy to build connections and to use native machine learning tools, you're well on the way up to date the maturity curve on you can start to use some of those more advanced applications. >>You said. What are some of the pre requisites? Maybe the top few that are two or three that I need to understand as a customer to really be successful here? Is it skill sets? Is it is it mindset leadership by in what I absolutely need to have to make this successful? >>Well, I think leadership is obviously key just to set the vision of people with spiky. One of the great things about Ayatollah, though, is you can use your existing staff to do this work. If you've used on automation, platform is no need to hire expensive people. Alright, I was a no code solution. It works out of the box. You just connect to force on your existing stuff can use. It's very intuitive that has these issues. User interface? >>Um, it >>was only to invest vast amounts with large consultants who may well charging the earth. Um, and you already had a bit of an advantage. If you've got existing staff who are close to the data subject matter experts or use it because they can very easily learn how to use a tool on, then they can go in and they can write their own data quality rules on. They can really make a contribution from day one, when we are go into organizations on way. Can I? It's one of the great things about the whole experience. Veritas is. We can get tangible results back within the day. Um, usually within an hour or two great ones to say Okay, we started to map relationships. Here's the data map of the data that we've analyzed. Harrison thoughts on where the sensitive data is because it's automated because it's running algorithms stater on. That's what they were really to expect. >>Um, >>and and you know this because you're dealing with the ecosystem. We're entering a new era of data and many organizations to your point, they just don't have the resources to do what Google and Amazon and Facebook and Microsoft did over the past decade To become data dominant trillion dollar market cap companies. Incumbents need to rely on technology companies to bring that automation that machine intelligence to them so they can apply it. They don't want to be AI inventors. They want to apply it to their businesses. So and that's what really was so difficult in the early days of so called big data. You have this just too much complexity out there, and now companies like Iot Tahoe or bringing your tooling and platforms that are allowing companies to really become data driven your your final thoughts. Please use it. >>That's a great point, Dave. In a way, it brings us back to where it began. In terms of partnerships and alliances. I completely agree with a really exciting point where we can take applications like Iot. Uh, we can go into enterprises and help them really leverage the value of these type of machine learning algorithms. And and I I we work with all the major cloud providers AWS, Microsoft Azure or Google Cloud Platform, IBM and Red Hat on others, and we we really I think for us. The key thing is that we want to be the best in the world of enterprise data automation. We don't aspire to be a cloud provider or even a workflow provider. But what we want to do is really help customers with their data without automated data functionality in partnership with some of those other businesses so we can leverage the great work they've done in the cloud. The great work they've done on work flows on virtual assistants in other areas. And we help customers leverage those investments as well. But our heart, we really targeted it just being the best, uh, enterprised data automation business in the world. >>Massive opportunities not only for technology companies, but for those organizations that can apply technology for business. Advantage yourself, count. Thanks so much for coming on the Cube. Appreciate. All right. And thank you for watching everybody. We'll be right back right after this short break. >>Yeah, yeah, yeah, yeah.

>>from around the globe. It's the Cube with digital coverage of enterprise data automation, an event Siri's brought to you by Iot. Tahoe Welcome everybody to Enterprise Data Automation. Ah co created digital program on the Cube with support from my hotel. So my name is Dave Volante. And today we're using the hashtag data automated. You know, organizations. They really struggle to get more value out of their data, time to data driven insights that drive cost savings or new revenue opportunities. They simply take too long. So today we're gonna talk about how organizations can streamline their data operations through automation, machine intelligence and really simplifying data migrations to the cloud. We'll be talking to technologists, visionaries, hands on practitioners and experts that are not just talking about streamlining their data pipelines. They're actually doing it. So keep it right there. We'll be back shortly with a J ahora who's the CEO of Iot Tahoe to kick off the program. You're watching the Cube, the leader in digital global coverage. We're right back right after this short break. Innovation impact influence. Welcome to the Cube disruptors. Developers and practitioners learn from the voices of leaders who share their personal insights from the hottest digital events around the globe. Enjoy the best this community has to offer on the Cube, your global leader. High tech digital coverage from around the globe. It's the Cube with digital coverage of enterprise, data, automation and event. Siri's brought to you by Iot. Tahoe. Okay, we're back. Welcome back to Data Automated. A J ahora is CEO of I O ta ho, JJ. Good to see how things in London >>Thanks doing well. Things in, well, customers that I speak to on day in, day out that we partner with, um, they're busy adapting their businesses to serve their customers. It's very much a game of ensuring the week and serve our customers to help their customers. Um, you know, the adaptation that's happening here is, um, trying to be more agile. Got to be more flexible. Um, a lot of pressure on data, a lot of demand on data and to deliver more value to the business, too. So that customers, >>as I said, we've been talking about data ops a lot. The idea being Dev Ops applied to the data pipeline, But talk about enterprise data automation. What is it to you. And how is it different from data off >>Dev Ops, you know, has been great for breaking down those silos between different roles functions and bring people together to collaborate. Andi, you know, we definitely see that those tools, those methodologies, those processes, that kind of thinking, um, lending itself to data with data is exciting. We look to do is build on top of that when data automation, it's the it's the nuts and bolts of the the algorithms, the models behind machine learning that the functions. That's where we investors, our r and d on bringing that in to build on top of the the methods, the ways of thinking that break down those silos on injecting that automation into the business processes that are going to drive a business to serve its customers. It's, um, a layer beyond Dev ops data ops. They can get to that point where well, I think about it is is the automation behind new dimension. We've come a long way in the last few years. Boy is, we started out with automating some of those simple, um, to codify, um, I have a high impact on organization across the data a cost effective way house. There's data related tasks that classify data on and a lot of our original pattern certain people value that were built up is is very much around that >>love to get into the tech a little bit in terms of how it works. And I think we have a graphic here that gets into that a little bit. So, guys, if you bring that up, >>sure. I mean right there in the middle that the heart of what we do it is, you know, the intellectual property now that we've built up over time that takes from Hacha genius data sources. Your Oracle Relational database. Short your mainframe. It's a lay and increasingly AP eyes and devices that produce data and that creates the ability to automatically discover that data. Classify that data after it's classified. Them have the ability to form relationships across those different source systems, silos, different lines of business. And once we've automated that that we can start to do some cool things that just puts of contact and meaning around that data. So it's moving it now from bringing data driven on increasingly where we have really smile, right people in our customer organizations you want I do some of those advanced knowledge tasks data scientists and ah, yeah, quants in some of the banks that we work with, the the onus is on, then, putting everything we've done there with automation, pacifying it, relationship, understanding that equality, the policies that you can apply to that data. I'm putting it in context once you've got the ability to power. Okay, a professional is using data, um, to be able to put that data and contacts and search across the entire enterprise estate. Then then they can start to do some exciting things and piece together the the tapestry that fabric across that different system could be crm air P system such as s AP and some of the newer brown databases that we work with. Snowflake is a great well, if I look back maybe five years ago, we had prevalence of daily technologies at the cutting edge. Those are converging to some of the cloud platforms that we work with Google and AWS and I think very much is, as you said it, those manual attempts to try and grasp. But it is such a complex challenges scale quickly runs out of steam because once, once you've got your hat, once you've got your fingers on the details Oh, um, what's what's in your data state? It's changed, You know, you've onboard a new customer. You signed up a new partner. Um, customer has, you know, adopted a new product that you just Lawrence and there that that slew of data keeps coming. So it's keeping pace with that. The only answer really is is some form of automation >>you're working with AWS. You're working with Google, You got red hat. IBM is as partners. What is attracting those folks to your ecosystem and give us your thoughts on the importance of ecosystem? >>That's fundamental. So, I mean, when I caimans where you tell here is the CEO of one of the, um, trends that I wanted us CIO to be part of was being open, having an open architecture allowed one thing that was close to my heart, which is as a CEO, um, a c i o where you go, a budget vision on and you've already made investments into your organization, and some of those are pretty long term bets. They should be going out 5 10 years, sometimes with the CRM system training up your people, getting everybody working together around a common business platform. What I wanted to ensure is that we could openly like it using AP eyes that were available, the love that some investment on the cost that has already gone into managing in organizations I t. But business users to before. So part of the reason why we've been able to be successful with, um, the partners like Google AWS and increasingly, a number of technology players. That red hat mongo DB is another one where we're doing a lot of good work with, um and snowflake here is, um Is those investments have been made by the organizations that are our customers, and we want to make sure we're adding to that. And they're leveraging the value that they've already committed to. >>Yeah, and maybe you could give us some examples of the r A y and the business impact. >>Yeah, I mean, the r a y David is is built upon on three things that I mentioned is a combination off. You're leveraging the existing investment with the existing estate, whether that's on Microsoft Azure or AWS or Google, IBM, and I'm putting that to work because, yeah, the customers that we work with have had made those choices. On top of that, it's, um, is ensuring that we have got the automation that is working right down to the level off data, a column level or the file level we don't do with meta data. It is being very specific to be at the most granular level. So as we've grown our processes and on the automation, gasification tagging, applying policies from across different compliance and regulatory needs that an organization has to the data, everything that then happens downstream from that is ready to serve a business outcome now without hoping out which run those processes within hours of getting started And, um, Bill that picture, visualize that picture and bring it to life. You know, the PR Oh, I that's off the bat with finding data that should have been deleted data that was copies off on and being able to allow the architect whether it's we're working on GCB or a migration to any other clouds such as AWS or a multi cloud landscape right off the map. >>A. J. Thanks so much for coming on the Cube and sharing your insights and your experience is great to have you. >>Thank you, David. Look who is smoking in >>now. We want to bring in the customer perspective. We have a great conversation with Paul Damico, senior vice president data architecture, Webster Bank. So keep it right there. >>Utah Data automated Improve efficiency, Drive down costs and make your enterprise data work for you. Yeah, we're on a mission to enable our customers to automate the management of data to realise maximum strategic and operational benefits. We envisage a world where data users consume accurate, up to date unified data distilled from many silos to deliver transformational outcomes, activate your data and avoid manual processing. Accelerate data projects by enabling non I t resources and data experts to consolidate categorize and master data. Automate your data operations Power digital transformations by automating a significant portion of data management through human guided machine learning. Yeah, get value from the start. Increase the velocity of business outcomes with complete accurate data curated automatically for data, visualization tours and analytic insights. Improve the security and quality of your data. Data automation improves security by reducing the number of individuals who have access to sensitive data, and it can improve quality. Many companies report double digit era reduction in data entry and other repetitive tasks. Trust the way data works for you. Data automation by our Tahoe learns as it works and can ornament business user behavior. It learns from exception handling and scales up or down is needed to prevent system or application overloads or crashes. It also allows for innate knowledge to be socialized rather than individualized. No longer will your companies struggle when the employee who knows how this report is done, retires or takes another job, the work continues on without the need for detailed information transfer. Continue supporting the digital shift. Perhaps most importantly, data automation allows companies to begin making moves towards a broader, more aspirational transformation, but on a small scale but is easy to implement and manage and delivers quick wins. Digital is the buzzword of the day, but many companies recognized that it is a complex strategy requires time and investment. Once you get started with data automation, the digital transformation initiated and leaders and employees alike become more eager to invest time and effort in a broader digital transformational agenda. Yeah, >>everybody, we're back. And this is Dave Volante, and we're covering the whole notion of automating data in the Enterprise. And I'm really excited to have Paul Damico here. She's a senior vice president of enterprise Data Architecture at Webster Bank. Good to see you. Thanks for coming on. >>Nice to see you too. Yes. >>So let's let's start with Let's start with Webster Bank. You guys are kind of a regional. I think New York, New England, uh, leave headquartered out of Connecticut, but tell us a little bit about the >>bank. Yeah, Webster Bank is regional, Boston. And that again in New York, Um, very focused on in Westchester and Fairfield County. Um, they're a really highly rated bank regional bank for this area. They, um, hold, um, quite a few awards for the area for being supportive for the community. And, um, are really moving forward. Technology lives. Currently, today we have, ah, a small group that is just working toward moving into a more futuristic, more data driven data warehouse. That's our first item. And then the other item is to drive new revenue by anticipating what customers do when they go to the bank or when they log into there to be able to give them the best offer. The only way to do that is you have timely, accurate, complete data on the customer and what's really a great value on off something to offer that >>at the top level, what were some of what are some of the key business drivers there catalyzing your desire for change >>the ability to give the customer what they need at the time when they need it? And what I mean by that is that we have, um, customer interactions and multiple weights, right? And I want to be able for the customer, too. Walk into a bank, um, or online and see the same the same format and being able to have the same feel, the same look and also to be able to offer them the next best offer for them. >>Part of it is really the cycle time, the end end cycle, time that you're pressing. And then there's if I understand it, residual benefits that are pretty substantial from a revenue opportunity >>exactly. It's drive new customers, Teoh new opportunities. It's enhanced the risk, and it's to optimize the banking process and then obviously, to create new business. Um, and the only way we're going to be able to do that is that we have the ability to look at the data right when the customer walks in the door or right when they open up their app. >>Do you see the potential to increase the data sources and hence the quality of the data? Or is that sort of premature? >>Oh, no. Um, exactly. Right. So right now we ingest a lot of flat files and from our mainframe type of runnin system that we've had for quite a few years. But now that we're moving to the cloud and off Prem and on France, you know, moving off Prem into, like, an s three bucket Where that data king, we can process that data and get that data faster by using real time tools to move that data into a place where, like, snowflake Good, um, utilize that data or we can give it out to our market. The data scientists are out in the lines of business right now, which is great, cause I think that's where data science belongs. We should give them on, and that's what we're working towards now is giving them more self service, giving them the ability to access the data in a more robust way. And it's a single source of truth. So they're not pulling the data down into their own like tableau dashboards and then pushing the data back out. I have eight engineers, data architects, they database administrators, right, um, and then data traditional data forwarding people, Um, and because some customers that I have that our business customers lines of business, they want to just subscribe to a report. They don't want to go out and do any data science work. Um, and we still have to provide that. So we still want to provide them some kind of read regiment that they wake up in the morning and they open up their email. And there's the report that they just drive, um, which is great. And it works out really well. And one of the things. This is why we purchase I o waas. I would have the ability to give the lines of business the ability to do search within the data, and we read the data flows and data redundancy and things like that and help me cleanup the data and also, um, to give it to the data. Analysts who say All right, they just asked me. They want this certain report and it used to take Okay, well, we're gonna four weeks, we're going to go. We're gonna look at the data, and then we'll come back and tell you what we dio. But now with Iot Tahoe, they're able to look at the data and then, in one or two days of being able to go back and say, Yes, we have data. This is where it is. This is where we found that this is the data flows that we've found also, which is what I call it is the birth of a column. It's where the calm was created and where it went live as a teenager. And then it went to, you know, die very archive. >>In researching Iot Tahoe, it seems like one of the strengths of their platform is the ability to visualize data the data structure, and actually dig into it. But also see it, um, and that speeds things up and gives everybody additional confidence. And then the other pieces essentially infusing ai or machine intelligence into the data pipeline is really how you're attacking automation, right? >>Exactly. So you're able to let's say that I have I have seven cause lines of business that are asking me questions. And one of the questions I'll ask me is, um, we want to know if this customer is okay to contact, right? And you know, there's different avenues so you can go online to go. Do not contact me. You can go to the bank And you could say, I don't want, um, email, but I'll take tests and I want, you know, phone calls. Um, all that information. So seven different lines of business asked me that question in different ways once said Okay to contact the other one says, You know, just for one to pray all these, you know, um, and each project before I got there used to be siloed. So one customer would be 100 hours for them to do that and analytical work, and then another cut. Another of analysts would do another 100 hours on the other project. Well, now I can do that all at once, and I can do those type of searches and say yes we already have that documentation. Here it is. And this is where you can find where the customer has said, You know, you don't want I don't want to get access from you by email, or I've subscribed to get emails from you. I'm using Iot typos eight automation right now to bring in the data and to start analyzing the data close to make sure that I'm not missing anything and that I'm not bringing over redundant data. Um, the data warehouse that I'm working off is not, um a It's an on prem. It's an oracle database. Um, and it's 15 years old, so it has extra data in it. It has, um, things that we don't need anymore. And Iot. Tahoe's helping me shake out that, um, extra data that does not need to be moved into my S three. So it's saving me money when I'm moving from offering on Prem. >>What's your vision or your your data driven organization? >>Um, I want for the bankers to be able to walk around with on iPad in their hands and be able to access data for that customer really fast and be able to give them the best deal that they can get. I want Webster to be right there on top, with being able to add new customers and to be able to serve our existing customers who had bank accounts. Since you were 12 years old there and now our, you know, multi. Whatever. Um, I want them to be able to have the best experience with our our bankers. >>That's really what I want is a banking customer. I want my bank to know who I am, anticipate my needs and create a great experience for me. And then let me go on with my life. And so that's a great story. Love your experience, your background and your knowledge. Can't thank you enough for coming on the Cube. >>No, thank you very much. And you guys have a great day. >>Next, we'll talk with Lester Waters, who's the CTO of Iot Toe cluster takes us through the key considerations of moving to the cloud. >>Yeah, right. The entire platform Automated data Discovery data Discovery is the first step to knowing your data auto discover data across any application on any infrastructure and identify all unknown data relationships across the entire siloed data landscape. smart data catalog. Know how everything is connected? Understand everything in context, regained ownership and trust in your data and maintain a single source of truth across cloud platforms, SAS applications, reference data and legacy systems and power business users to quickly discover and understand the data that matters to them with a smart data catalog continuously updated ensuring business teams always have access to the most trusted data available. Automated data mapping and linking automate the identification of unknown relationships within and across data silos throughout the organization. Build your business glossary automatically using in house common business terms, vocabulary and definitions. Discovered relationships appears connections or dependencies between data entities such as customer account, address invoice and these data entities have many discovery properties. At a granular level, data signals dashboards. Get up to date feeds on the health of your data for faster improved data management. See trends, view for history. Compare versions and get accurate and timely visual insights from across the organization. Automated data flows automatically captured every data flow to locate all the dependencies across systems. Visualize how they work together collectively and know who within your organization has access to data. Understand the source and destination for all your business data with comprehensive data lineage constructed automatically during with data discovery phase and continuously load results into the smart Data catalog. Active, geeky automated data quality assessments Powered by active geek You ensure data is fit for consumption that meets the needs of enterprise data users. Keep information about the current data quality state readily available faster Improved decision making Data policy. Governor Automate data governance End to end over the entire data lifecycle with automation, instant transparency and control Automate data policy assessments with glossaries, metadata and policies for sensitive data discovery that automatically tag link and annotate with metadata to provide enterprise wide search for all lines of business self service knowledge graph Digitize and search your enterprise knowledge. Turn multiple siloed data sources into machine Understandable knowledge from a single data canvas searching Explore data content across systems including GRP CRM billing systems, social media to fuel data pipelines >>Yeah, yeah, focusing on enterprise data automation. We're gonna talk about the journey to the cloud Remember, the hashtag is data automate and we're here with Leicester Waters. Who's the CTO of Iot Tahoe? Give us a little background CTO, You've got a deep, deep expertise in a lot of different areas. But what do we need to know? >>Well, David, I started my career basically at Microsoft, uh, where I started the information Security Cryptography group. They're the very 1st 1 that the company had, and that led to a career in information, security. And and, of course, as easy as you go along with information security data is the key element to be protected. Eso I always had my hands and data not naturally progressed into a roll out Iot talk was their CTO. >>What's the prescription for that automation journey and simplifying that migration to the cloud? >>Well, I think the first thing is understanding what you've got. So discover and cataloging your data and your applications. You know, I don't know what I have. I can't move it. I can't. I can't improve it. I can't build upon it. And I have to understand there's dependence. And so building that data catalog is the very first step What I got. Okay, >>so So we've done the audit. We know we've got what's what's next? Where do we go >>next? So the next thing is remediating that data you know, where do I have duplicate data? I may have often times in an organization. Uh, data will get duplicated. So somebody will take a snapshot of the data, you know, and then end up building a new application, which suddenly becomes dependent on that data. So it's not uncommon for an organization of 20 master instances of a customer, and you can see where that will go. And trying to keep all that stuff in sync becomes a nightmare all by itself. So you want to sort of understand where all your redundant data is? So when you go to the cloud, maybe you have an opportunity here to do you consolidate that that data, >>then what? You figure out what to get rid of our actually get rid of it. What's what's next? >>Yes, yes, that would be the next step. So figure out what you need. What, you don't need you Often times I've found that there's obsolete columns of data in your databases that you just don't need. Or maybe it's been superseded by another. You've got tables have been superseded by other tables in your database, so you got to kind of understand what's being used and what's not. And then from that, you can decide. I'm gonna leave this stuff behind or I'm gonna I'm gonna archive this stuff because I might need it for data retention where I'm just gonna delete it. You don't need it. All were >>plowing through your steps here. What's next on the >>journey? The next one is is in a nutshell. Preserve your data format. Don't. Don't, Don't. Don't boil the ocean here at music Cliche. You know, you you want to do a certain degree of lift and shift because you've got application dependencies on that data and the data format, the tables in which they sent the columns and the way they're named. So some degree, you are gonna be doing a lift and ship, but it's an intelligent lift and ship. The >>data lives in silos. So how do you kind of deal with that? Problem? Is that is that part of the journey? >>That's that's great pointed because you're right that the data silos happen because, you know, this business unit is start chartered with this task. Another business unit has this task and that's how you get those in stance creations of the same data occurring in multiple places. So you really want to is part of your cloud migration. You really want a plan where there's an opportunity to consolidate your data because that means it will be less to manage. Would be less data to secure, and it will be. It will have a smaller footprint, which means reduce costs. >>But maybe you could address data quality. Where does that fit in on the >>journey? That's that's a very important point, you know. First of all, you don't want to bring your legacy issues with U. S. As the point I made earlier. If you've got data quality issues, this is a good time to find those and and identify and remediate them. But that could be a laborious task, and you could probably accomplish. It will take a lot of work. So the opportunity used tools you and automate that process is really will help you find those outliers that >>what's next? I think we're through. I think I've counted six. What's the What's the lucky seven >>Lucky seven involved your business users. Really, When you think about it, you're your data is in silos, part of part of this migration to cloud as an opportunity to break down the silos. These silence that naturally occurs are the business. You, uh, you've got to break these cultural barriers that sometimes exists between business and say so. For example, I always advise there's an opportunity year to consolidate your sensitive data. Your P I. I personally identifiable information and and three different business units have the same source of truth From that, there's an opportunity to consolidate that into one. >>Well, great advice, Lester. Thanks so much. I mean, it's clear that the Cap Ex investments on data centers they're generally not a good investment for most companies. Lester really appreciate Lester Water CTO of Iot Tahoe. Let's watch this short video and we'll come right back. >>Use cases. Data migration. Accelerate digitization of business by providing automated data migration work flows that save time in achieving project milestones. Eradicate operational risk and minimize labor intensive manual processes that demand costly overhead data quality. You know the data swamp and re establish trust in the data to enable data signs and Data analytics data governance. Ensure that business and technology understand critical data elements and have control over the enterprise data landscape Data Analytics ENABLEMENT Data Discovery to enable data scientists and Data Analytics teams to identify the right data set through self service for business demands or analytical reporting that advanced too complex regulatory compliance. Government mandated data privacy requirements. GDP Our CCP, A, e, p, R HIPPA and Data Lake Management. Identify late contents cleanup manage ongoing activity. Data mapping and knowledge graph Creates BKG models on business enterprise data with automated mapping to a specific ontology enabling semantic search across all sources in the data estate data ops scale as a foundation to automate data management presences. >>Are you interested in test driving the i o ta ho platform Kickstart the benefits of data automation for your business through the Iot Labs program? Ah, flexible, scalable sandbox environment on the cloud of your choice with set up service and support provided by Iot. Top Click on the link and connect with the data engineer to learn more and see Iot Tahoe in action. Everybody, we're back. We're talking about enterprise data automation. The hashtag is data automated and we're going to really dig into data migrations, data migrations. They're risky, they're time consuming and they're expensive. Yousef con is here. He's the head of partnerships and alliances at I o ta ho coming again from London. Hey, good to see you, Seth. Thanks very much. >>Thank you. >>So let's set up the problem a little bit. And then I want to get into some of the data said that migration is a risky, time consuming, expensive. They're they're often times a blocker for organizations to really get value out of data. Why is that? >>I think I mean, all migrations have to start with knowing the facts about your data. Uh, and you can try and do this manually. But when you have an organization that may have been going for decades or longer, they will probably have a pretty large legacy data estate so that I have everything from on premise mainframes. They may have stuff which is probably in the cloud, but they probably have hundreds, if not thousands of applications and potentially hundreds of different data stores. >>So I want to dig into this migration and let's let's pull up graphic. It will talk about We'll talk about what a typical migration project looks like. So what you see, here it is. It's very detailed. I know it's a bit of an eye test, but let me call your attention to some of the key aspects of this, uh and then use if I want you to chime in. So at the top here, you see that area graph that's operational risk for a typical migration project, and you can see the timeline and the the milestones That Blue Bar is the time to test so you can see the second step. Data analysis. It's 24 weeks so very time consuming, and then let's not get dig into the stuff in the middle of the fine print. But there's some real good detail there, but go down the bottom. That's labor intensity in the in the bottom, and you can see hi is that sort of brown and and you could see a number of data analysis data staging data prep, the trial, the implementation post implementation fixtures, the transition to be a Blu, which I think is business as usual. >>The key thing is, when you don't understand your data upfront, it's very difficult to scope to set up a project because you go to business stakeholders and decision makers, and you say Okay, we want to migrate these data stores. We want to put them in the cloud most often, but actually, you probably don't know how much data is there. You don't necessarily know how many applications that relates to, you know, the relationships between the data. You don't know the flow of the basis of the direction in which the data is going between different data stores and tables. So you start from a position where you have pretty high risk and probably the area that risk you could be. Stack your project team of lots and lots of people to do the next phase, which is analysis. And so you set up a project which has got a pretty high cost. The big projects, more people, the heavy of governance, obviously on then there, then in the phase where they're trying to do lots and lots of manual analysis, um, manual processes, as we all know, on the layer of trying to relate data that's in different grocery stores relating individual tables and columns, very time consuming, expensive. If you're hiring in resource from consultants or systems integrators externally, you might need to buy or to use party tools. Aziz said earlier the people who understand some of those systems may have left a while ago. CEO even higher risks quite cost situation from the off on the same things that have developed through the project. Um, what are you doing with Ayatollah? Who is that? We're able to automate a lot of this process from the very beginning because we can do the initial data. Discovery run, for example, automatically you very quickly have an automated validator. A data met on the data flow has been generated automatically, much less time and effort and much less cars stopped. >>Yeah. And now let's bring up the the the same chart. But with a set of an automation injection in here and now. So you now see the sort of Cisco said accelerated by Iot, Tom. Okay, great. And we're gonna talk about this, but look, what happens to the operational risk. A dramatic reduction in that, That that graph and then look at the bars, the bars, those blue bars. You know, data analysis went from 24 weeks down to four weeks and then look at the labor intensity. The it was all these were high data analysis, data staging data prep trialling post implementation fixtures in transition to be a you all those went from high labor intensity. So we've now attacked that and gone to low labor intensity. Explain how that magic happened. >>I think that the example off a data catalog. So every large enterprise wants to have some kind of repository where they put all their understanding about their data in its price States catalog. If you like, imagine trying to do that manually, you need to go into every individual data store. You need a DB, a business analyst, reach data store. They need to do an extract of the data. But it on the table was individually they need to cross reference that with other data school, it stores and schemers and tables you probably with the mother of all Lock Excel spreadsheets. It would be a very, very difficult exercise to do. I mean, in fact, one of our reflections as we automate lots of data lots of these things is, um it accelerates the ability to water may, But in some cases, it also makes it possible for enterprise customers with legacy systems take banks, for example. There quite often end up staying on mainframe systems that they've had in place for decades. I'm not migrating away from them because they're not able to actually do the work of understanding the data, duplicating the data, deleting data isn't relevant and then confidently going forward to migrate. So they stay where they are with all the attendant problems assistance systems that are out of support. You know, you know, the biggest frustration for lots of them and the thing that they spend far too much time doing is trying to work out what the right data is on cleaning data, which really you don't want a highly paid thanks to scientists doing with their time. But if you sort out your data in the first place, get rid of duplication that sounds migrate to cloud store where things are really accessible. It's easy to build connections and to use native machine learning tools. You well, on the way up to the maturity card, you can start to use some of the more advanced applications >>massive opportunities not only for technology companies, but for those organizations that can apply technology for business. Advantage yourself, count. Thanks so much for coming on the Cube. Much appreciated. Yeah, yeah, yeah, yeah

>>Live from Barcelona, Spain. It's the Cube covering Cisco Live 2020 right to you by Cisco and its ecosystem partners. >>Welcome back to the Cube's live coverage here at Cisco Live 2020 in Barcelona, Spain. I'm jumpers student of cube coverage. We've got a lot of stuff going on in Cisco Multi cloud and cloud technology. Quantification of Cisco's happening in real time is happening right now. Cloud is here here to stay. We got two great guests unpack what's going on in cloud native and networking and applications as the modern infrastructure and software evolves. We got you. Gene Kim, global product marketing. Compute Storage at Cisco Global marketing manager and Rob Gori, senior director. Cloud Solution Marketing Guys come back. Thanks for coming back. Appreciate it. Great to see you Barcelona guys. So, Bobby, we've had multiple conversations and you see that from the sales force given kind of the the discussion in the motivation Cloud is big. It's here. It's here to stay. It's changing. Cisco AP I first week here in all the products, it's changing everything. What's the story now? What's going on? >>I would say you know the reason why we're so excited about the launch here in Barcelona is because this time it's all about the application of spirits. I mean, the last two years we've being announcing some really exciting stuff in the cloud space where I think about all the announcements with AWS is the Googles the azure, so the world. But this time it really boils down to making sure that is incredibly hyper distributive world. There is an application explosion. Ultimately, we will help for the right operation stools and infrastructure management tools to ensure that the right application experience will be guaranteed for the end customer. And that's incredibly important because at the end, what really really matters is that you will ensure the best possible digital experience to your customer. Otherwise, ultimately nothing's gonna work. And, of course, you're gonna lose your brand and your customers. >>One of the main stories that we're covering is the transformation of the industry. Also, Cisco and one of the highlights to me was the opening keynote. You had APP dynamics first, not networking. Normally it's like what's in the hood? Routers and the gear. No, it was about the applications. This is the story we're seeing. It's kind of a quiet unveiling. Its not get a launch, but it's evolving very quickly. Can you share what's going on behind this? All this? >>Absolutely. It's exactly along the lines of what I was saying a second ago, in the end that the reason why we're driving the announcement, if you want from the application experience side of the House, is because with Appdynamics, we already have very, very powerful application performance management, which it's evolving extremely rapidly. First of all, Appdynamics can correlate not just the application for four months to some technology, maybe eyes, but through actual business KP eyes. So app dynamics can give you, for instance, serial time visibility off, say, a marketing funnel conversion rates transactions that you're having in your in your business operation. Now we're introducing an incredibly powerful new capability that takes the bar to a whole new level. And that's the Appdynamics experience. Journey maps. What are those? It's actually the ability off, focusing not so much on front ends and back ends and the business performances, but really focusing on what the user is seen in front of his or her screen. And so what really matters is capturing the journey that given user of your application is being and understanding whether the experience is the one that you want to deliver or you have, like, a sudden drop off somewhere. And you know why this is important because in the end we've been talking about is the problem of the application, performance issues or performance. It could be a badly designed page. How do you know? And so this is a very precious information they were giving to application developers know, just through the idea. Ops, guys, that is incredibly gracious. >>Okay, you want to get this in. So you just brought up that journey. So that's part of the news. Just break down real quick. One minute what the news is. >>Yeah, so we have three components. The 1st 1 as you as you correctly pointed out, is really the introduction of the application. The journey maps, right. The experience journey maps. That's very, very important. The second he's way are actually integrating Appdynamics with the inter site. Actually, inter site the optimization manager, the workload optimization, workload, optimizer. And so because there is exchange of data between the two now, you are in a position to immediately understand whether you have an application problem. We have a worker problem for structure problem, which is after me, where you really need to do as quickly as you can. And thirdly, way have introduced a new version of our hyper flex platform, which is hyper converge flagship platform for Cisco with a fully containerized version, the tax free if you want as well, that is a great platform for containerized applications. >>So you do and what I've been talking to customers last few years. When they go through their transformational journey, there's the modernization they need to do. The pattern I've seen most successful is first, modernize the platform often HD I is, you know, an option for that. It really simplifies the environment, reduces the silos on, has more of that operational model that looks closer to what the cloud experience is. And then, if I've got a good platform, then I can modernize the applications on top of it. But often those two have been a little bit disconnected. It feels like the announcements now that they are coming together. What are you seeing? What're you hearing? How your solutions at solving this issue >>exactly. I mean, as we've been talking to our customers, a lot of them are going through a different application. Modernizations and kubernetes and containers is extremely important to them. And to build a container cloud on Prem is extremely one of their needs. And so there's three distinctive requirements that they've kind of talk to us about. A lot of it has to be ableto it's got to be very simple, very turnkey, fully integrated, ready to turn on the other. One is something that's very agile, right? Very Dev Ops friendly and the third being a very economic container cloud on prim. So as you mentioned, High Flex Application Platform takes our hyper converge system and build on top of it a integrated kubernetes platform to deliver a container as a service type capability. And it provides a full stack, fully supported element platform for our customers, and one of the best great aspects of it is it's all managed from inter site, from the physical infrastructure to the hyper converge layer to all the way to the container management. So it's very exciting to have that full stack management and inter site as well. >>It's great to see you, John and I have been following this kubernetes wave since the early early days. Fabio mentioned integrations with the Amazons and Googles of the world because, you know, a few years ago you talk to customers and they're like, Oh, well, I'm just going to build my own community. Nobody ever said that is easy now. Just delivering as a service seems to be the way most people want it. So if I'm doing it on Amazon or Google, they've got their manage service that I could do that or that there partners we're working with. So explain what you're doing to make it simpler in the data center environment. Because on Prem absolutely is a piece of that hybrid equation that customers need. >>Yes, so, essentially from the customer experience perspective, as I mentioned, very fairly turnkey right from the hyper flex application platform we're taking are happening for software were integrating a application virtualization layer on top of it analytics k VM based. And then on top of that, we're integrating the kubernetes stack on top of as well. And so, in essence, right? It's a fully curated kubernetes stack that has all the different elements from the networking from the storage elements and provide that in a very turnkey way. And as I mentioned, the inter site management is really providing that simplicity that customers need for that management. >>Fabio This is the previous announcements you've made with the public clouds. This just ties into those hybrid environments. That's exactly a few years ago. People like, Oh, is there going to be a distribution that wins in kubernetes? We don't think that's the answer, but still, I can't just move between kubernetes. You know seamlessly yet. But this is moving toward that >>direct. Absolutely. A lot of customers want to have a very simple implementation. At the same time, they weren't off course a multi cloud approach and I really care about marking the difference between multi cloud hybrid Cloud has been a lot of confusion. But if you think about a multi cloud is re routed into the business need or harnessing innovation from wherever it comes from, you know the different clouds capability from things, and you know what they do today. Tomorrow it could even change, so people want optionality, so they want a very simple implementation that's integrated with public cloud providers that simplifies their life in terms of networking, security and application of workload management. And we've been executing towards that goal so fundamentally simplify the operations of these pretty complex kind of hybrid apartments. >>And once you nail that operations on hybrid, that's where multi cloud comes in. That's really just a connection point. >>Absolutely, you know, you might know is an issue. So in order to fulfill your business, your line of business needs you. Then you have a hybrid problem, and you want to really kind of have a consistent production grade environment between things on Prem that you own and control versus things that you use and you want to control better. Now, of course, they're different school thoughts. But most of the customers who are speaking with really want to expand their governance and technology model right to the cloud, as opposed to absorb in different ways of doing things from each and every time. >>I want to unpack a little bit of what you said earlier about the knowing where the problem is, because a lot of times it's a point, the finger at the other first, it's the application promising the problem, so I want to get into that. But first I want to understand the hyper flex application platform. Eugene, if you could just share the main problem that you guys solve, what are some of the pain points that customers had? What problem does the AP solved? >>Yeah, as I mentioned, it's really the platform for our customers to modernize the applications on right, and it addresses those things that they're looking for as far as the economics right, really? The ability to provide a full stack container experience without having to, you know, but bringing any third party hyper visor licenses as well support costs that's well integrated. There you have your integrated, hyper converged storage capability. You have the cloud based management, and that's really developing. You provide that developer dev ops simplicity from that agility that they're looking for internally as well as for their production environments. And then the other aspect is the simplicity to manage all this right and the entire life cycle management >>as well. So it's the operational side of the hole in under the covers hobby on the application side where the problem is because this is where I'm a bit skeptical, Normal rightfully so. But I can see a problem where it's like Whose fault is it? Applications, problem or the network? I mean, it runs on where? Sears Workloads, Banking app. It's having trouble. How do you know where the problem is? And how do you solve that problem with what's going on for that specific issue? >>Absolutely. And you know, the name of the game here is breaking down this operational side, right? And I love what are appdynamics VP? GM Any? Whitaker said. You know, he has this terminology. Beast develops, which it may sound like an interesting acrobatics, but it's absolutely too. The business has to be part of this operational kind of innovation because, as you said, you know, developer just drops their containers and their code to the I T. Ops team, but you don't really know whether the problem a certain point is going to be in the code or in the application is actually deployed. Or maybe a server that doesn't have enough CPU. So in the end, it boils down to one very important thing. You have to have visibility, insights and take action at every layer of the stack. Instrumentation. Absolutely. There are players that only do it in their software overlay domain. The problem is, very often these kind of players assume they're underneath. Things are fine, and very often they're not. So in the end, this visibility inside in action is the loop that everybody's going after these days, too, Really get to the next. If you want a generational operation, where you gotta have a constant feedback loop and making it more faster and faster because in the end you can only win in the marketplace, right? So your I T ops, if you're faster than your competitors, >>will still still questioning the GM of APP Dynamics. Run, observe, ability. And he's like, No, it's not a feature, it's everywhere. So he's comment was observe. Abilities don't really talk about it because it's a big in. You agree with that? >>Absolutely. It has to be at every layer of the stack, and only if you have visibility inside an action through the entire stock, from the software all the way to the infrastructure level that you can solve the problems. Otherwise, the finger pointing quote unquote will continue, and you will not be able to gain the speed you need. >>Okay, so The question on my mind I want to get both of you guys could weigh in on this is that if you look at Cisco as a company, you got a lot going on. You guys huge customer base core routers to know applications. There's a lot going on a lot of a lot of complexity. You got I o. T. Security members talking about that. You got the WebEx rooms totally popular. It's got a lot of glam, too, and having the WebEx kind of, I guess, what virtual presence was telepresence kind of model. And then you get cloud. Is there a mind share within the company around how cloud is baked into everything? Because you can't do I ot edge without having some sort of cloud operational things. Stuff we're talking about is not just a division. It's kind of it's kind of threads everywhere across Cisco. What's the what's the mind share right now within the Cisco teams and also customers around cloud ification? >>Well, I would say it's it's a couple of dimensions. The 1st 1 is the cloud is one of the critical domains of this multi domain architecture. That, of course, is the cornerstone of Cisco's. The knowledge is strategy, right? If you think about it, it's all about connecting users to applications wherever they are and not just the users to the applications themselves. Like if you look at the latest US from I. D. C. 58% of workloads is heading to a public cloud, and the edge is like the data center is exploding many different directions. So you have this highly distributed kind of fabric. Guess what sits in between. All these applications and micro services is a secure network, and that's exactly what we're executing upon. Now that's the first kind of consideration. The second is if you look at the other civil line. Most of the Cisco technology innovation is also going a direction of absorbing cloud as a simplified way of managing all the components or the infrastructure. You look at the hyper flex. AP is actually managed by Inter site, which is a SAS kind of component. This journey started long time ago with Cisco Iraqi on then, of course, we have sass properties like WebEx. Everything else absolutely migrate borders. >>We've been reporting Eugene that five years ago we saw the movement where AP, eyes were starting to come in when you go back five years ago. Not a lot of the gear and stuff that Cisco had AP eyes. Now you got AP eyes building in all the new products that you see the software shift with you intent based networking to APP dynamics. It's interesting. It's you're seeing kind of the agile mindset. This is something you and I talk all the time. But agile now is the new model. Is it ready for customers? I mean, the normal enterprises still have the infrastructure and separated, and they're like, Okay, how do I bring it together? What do you guys see in the customer base? What's going on with that early adopters, Heavy duty hardcore pioneers out there. But you know, the general mainstream enterprise. Are they there yet? Have they had that moment of awakening? >>Yeah, I mean, I think they they are there because fundamentally, it's all about ensuring that application experience. And you could only ensure the application experience right by having your application teams and infrastructure teams work together. And that's what's exciting. You mentioned Ap eyes and what we've done. They were with APP dynamics, integrating with inner sight workload. Optimizer as you mentioned all the visibility inside in action and what APP Dynamics has provides. Provide that business and end user application performance experience. Visibility Inter site. It's giving you visibility on the underlining workload, and the resource is whether it's on prim in your private data center environment or in a different type of cloud providers. So you get that full stack visibility right from the application all the way down to the bottom and then inter site local optimizer is then also optimizing the resource is to proactively ensure that application experience. So before you know, if we talk about someone at a check out and they're about there's of abandonment because the function is not working, we're able to proactively prevent that and take a look at all that. So, you know, in the end, I think it's all about ensuring that application experience and what we're providing with APP Dynamics is for the application team is kind of that horizontal visibility of how that application performing and at the same time, if there's an issue, the infrastructure team could see exactly within the workload topology, where the issue is and entertain safely, whether it be manual intervention or even automatically our ops capability. Go ahead and provide that action so the action could be, you know, scaling out the VM that's on Prem or looking at new, different type of easy to template in the cloud. That's a very exciting about this. It's really the application experience is now driving and optimize the infrastructure in real >>time. And let me flip your question like, Do you even have a choice, John, when you think about in the next two years 50% more applications? If you're a large enterprise here, 5 to 7000 apps you have another 2 3000 applications just coming into into the and then 50% of the existing ones that are going to be re factor lifted and shifted the replace or retired by SAS application. It's just like a tsunami that's that's coming on you and oh, by the way, because again the micro services kind of effect the number of dependencies between all these applications is growing incredibly rapidly, Like last year, we were eight average interdependencies for applications. Now we have 20 so in Beijing imaginable happens as you are literally flooded with this can really you have to ensure that your application infrastructure fundamentally will get tied up as quickly as you can >>see. You and I have been talking for at least five years now, if not longer. Networking has been the key kind of last change over clarification. I would agree with you guys. I think last question because I wanted to get your perspective. But think about it. It's 13 years since the iPhone so mobile has shown people that mobile app can change business. But now you get the pressure of the networks. Bringing that pressure on the network or the pressure of the network to be better than programmable is the rise of video and data. I mean, you got mobile check now you got it. Video. I mean more people doing video now than ever before. Videos of consumer. Well, it's streaming. You got data? These two things absolutely forced customers to deal with it. >>But what really tipped the balance? John is actually the SAS effect is the cloud effect because, as you know, it's an I t. So the inflection points. Nothing gets a linear right. So once you reach a certain critical mass of cloud apps, and we're absolutely they're already all of a sudden your traffic pattern on your network changes dramatically. So why in the world are you continuing? Kind of, you know, concentrating all of your traffic in your data center and then going to the Internet. You have to absolutely open the floodgates at the branch level and as close to the users this possible, and that it implies a radical change of the >>way I would even add to that. And I think you guys are right on where you guys are going. It may be hard to kind of tease out with all the complexity with Cisco, but in the keynote, the business model shifts come from SAS. So you got all this technical stuff going on. You have the sass ification, or cloud changes the business models so new entrants can come in and existing players get better. So I think that whole business model conversation never was discussed at Cisco Live before in depth. Okay, run your business, connect your hubs campus move packets around Dallas applications in business model, >>but also the fact that there is increasing number off software capabilities and so fundamental. You want to simplify the life of your customers through subscription models that help the customer buying a using what they really need the right at any given point in time, all the way to having enterprise agreements. >>I also think that's about delivering these application experiences free for small, different experience. That's really what's differentiating you from your competitors, right? And so that's a different type of >>shift as well. Well, you guys have got a good That's a good angle on this cloud. I love it. I got to ask the question. What can we expect next from Cisco? More progression along cloud ification? What's next? >>Well, I would say we've been incredibly consistent, I believe in the last few years in executing on our cloud strategy, which again is sent around helping customers really gluing this mix, set off data centers and clouds to make it work as one right as much as possible. And so what we really deliver is networking security and application performance management, and we're integrating this more and more on the two sides of the equation, right? The data center side and the public cloud side and more more integrated in between all of these layers again, to fundamentally give you this operational capability to get faster and faster. We'll continue doing so and >>we'll get you set up before we came on camera that you were talking to sales teams. What are they? What's the vibe with sales team? They get excited by this. What's the >>oh yeah, feedback. And absolutely, from the inter site work optimizer and the app Dynamics side. It's very exciting for them. Switch the conversation they're having with their customers, really from that application experience and proactively ensuring it. And on the hyper flex application platform side, this is extreme exciting with providing a container cloud to our customers. And you know what's coming down is more and more capabilities for our customers to modernize the applications on hyper >>flex. You guys are riding a pretty big waves here at Cisco in a cloud way to get the i o t. Security wave. Great stuff. Thanks for coming in. Thanks for sharing the insights. Appreciate it. >>Thank you for having >>coverage here in Barcelona. I'm John. First, Minutemen back with more coverage. Fourth day of four days of cube coverage. Be right back after this short break. >>Yeah, yeah, yeah.

>> Hey, welcome back already, Jeffrey. Here with the Cube, we are high top San Francisco in the Salesforce Tower in the newest center offices. It's really beautiful and is part of that. They have their San Francisco innovation hubs, so it's five floors of maker's labs and three D printing and all kinds of test facilities and best practices Innovation theater and in this studio, which is really fun to be at. So we're talking about hybrid cloud in the development of cloud and multi cloud. And, you know, we're, you know, continuing on this path. Not only your customers on this path, but everyone's kind of on this path is the same kind of evolved and transformed. We're excited. Have a couple experts in the field. We got Larry Soccer. He's the global managing director of Intelligent Cloud Infrastructure Service's growth and strategy at a center. Very good to see you again. Great to be here. And the Jay Patel. He's the senior vice president and general manager, cloud provider, software business unit, being where enemies of the people are nice. Well, so, uh so first off, how you like the digs appear >> beautiful place and the fact we're part of the innovation team. Thank you for that. It's so let's just >> dive into it. So a lot of crazy stuff happening in the market place a lot of conversations about hybrid cloud, multi cloud, different cloud, public cloud movement of Back and forth from Cloud. Just wanted. Get your perspective a day. You guys have been in the Middle East for a while. Where are we in this kind of evolution? It still kind of feeling themselves out. Is it? We're kind of past the first inning, so now things are settling down. How do you kind of you. Evolution is a great >> question, and I think that was a really nice job of defining the two definitions. What's hybrid worse is multi and simply put hybrid. We look at hybrid as when you have consistent infrastructure. It's the same infrastructure, regardless of location. Multi is when you have disparate infrastructure. We're using them in a collective. So just from a level setting perspective, the taxonomy starting to get standardized industry starting to recognize hybrid is a reality. It's not a step in the long journey. It is an operating model that's gonna be exists for a long time, so it's no longer about location. It's a lot harder. You operate in a multi cloud and a hybrid cloud world and together, right extension BM would have a unique opportunity. Also, the technology provider Accenture, as a top leader in helping customers figure out where best to land their workload in this hybrid multicolored world, because workloads are driving decisions right and one of the year in this hybrid medical world for many years to come. But >> do I need another layer of abstraction? Cause I probably have some stuff that's in hybrid. I probably have some stuff in multi, right, because those were probably not much in >> the way we talked a lot about this, and Larry and I were >> chatting as well about this. And the reality is, the reason you choose a specific cloud is for those native different share capability. Abstraction should be just enough so you can make were close portable, really use the caper berry natively as possible right, and by fact, that we now with being where have a native VM we're running on every major hyper scaler, right? And on. Prem gives you that flexibility. You want off not having to abstract away the goodness off the cloud while having a common and consistent infrastructure. What tapping into the innovations that the public cloud brings. So it is a evolution of what we've been doing together from a private cloud perspective to extend that beyond the data center to really make it operating model. That's independent location, right? >> Solarium cures your perspective. When you work with customers, how do you help them frame this? I mean, I always feel so sorry for corporate CEOs. I mean, they got >> complexities on the doors are already going on >> like crazy that GDP are now, I think, right, The California regs. That'll probably go national. They have so many things to be worried about. They got to keep up on the latest technology. What's happening in containers away. I thought it was Dr Knight. Tell me it's kubernetes. I mean, it's really tough. So how >> do you help them? Kind of. It's got a shot with the foundation. >> I mean, you look at cloud, you look at infrastructure more broadly. I mean, it's there to serve the applications, and it's the applications that really drive business value. So I think the starting point has to be application lead. So we start off. We have are intelligent. Engineering guys are platform guys. You really come in and look And do you know an application modernisation strategy? So they'll do an assessment. You know, most of our clients, given their scale and complexity, usually have from 520,000 applications, very large estates, and they got to start to freak out. Okay, what's my current application's? You know, you're a lot of times I use the six R's methodology, and they say, OK, what is it that I I'm gonna retire. This I'm no longer needed no longer is business value, or I'm gonna, you know, replace this with sass. Well, you know, Yeah, if I move it to sales force, for example, or service now mattress. Ah, and then they're gonna start to look at their their workloads and say OK, you know, I don't need to re factor reform at this, you know, re hosted. You know, when one and things obviously be Emily has done a fantastic job is allowing you to re hosted using their softer to find a data center in the hyper scale er's environments >> that we called it just, you know, my great and then modernized. But >> the modern eyes can't be missed. I think that's where a lot of times you see clients kind of getting the trap Hammer's gonna migrate and then figure it out. You need to start tohave a modernisation strategy and then because that's ultimately going to dictate your multi and your hybrid cloud approaches, is how they're zaps evolve and, you know, they know the dispositions of those abs to figure out How do they get replaced? What data sets need to be adjacent to each other? So >> right, so a j you know, we were there when when Pat was with Andy and talking about, you know, Veum, Where on AWS. And then, you know, Sanjay has shown up, but everybody else's conferences a Google cloud talking about you know, Veum. Where? On Google Cloud. I'm sure there was a Microsoft show I probably missed. You guys were probably there to know it. It's kind of interesting, right from the outside looking in You guys are not a public cloud per se. And yet you've come up with this great strategy to give customers the options to adopt being We're in a public hot. And then now we're seeing where even the public cloud providers are saying here, stick this box in your data center and Frank, this little it's like a little piece of our cloud of floating around in your data center. So talk about the evolution of the strategy is kind of what you guys are thinking about because you know, you're cleared in a leadership position, making a lot of interesting acquisitions. How are you guys see this evolving? And how are you placing your bets? >> You know, that has been always consistent about this. Annie. Any strategy, whether it's any cloud, was any device, you know, any workload if you will, or application. And as we started to think about it, right, one of the big things be focused on was meeting the customer where he's out on its journey. Depending on the customer, let me simply be trying to figure out looking at the data center all the way to how the drive in digital transformation effort in a partner like Accenture, who has the breadth and depth and something, the vertical expertise and the insight. That's what customers looking for. Help me figure out in my journey. First tell me where, Matt, Where am I going and how I make that happen? And what we've done in a clever way, in many ways is we've created the market. We've demonstrated that VM where's the omen? Consistent infrastructure that you can bet on and leverage the benefits of the private or public cloud. And I You know, I often say hybrids a two way street. Now, which is you're bringing Maur more hybrid Cloud service is on Prem. And where is he? On Premise now the edge. I was talking to the centering folks and they were saying the mitral edge. So you're starting to see the workloads, And I think you said almost 40 plus percent off future workers that are gonna be in the central cloud. >> Yeah, actually, is an interesting stat out there. 20 years 2020 to 70% of data will be produced and processed outside the cloud. So I mean, the the edges about, you know, as we were on the tipping point of, you know, I ot finally taking off beyond, you know, smart meters. You know, we're gonna see a huge amount of data proliferate out there. So, I mean, the lines between public and private income literary output you look at, you know, Anthony, you know, as your staff for ages. So you know, And that's where you know, I think I am where strategy is coming to fruition >> sometime. It's great, >> you know, when you have a point of view and you stick with it >> against a conventional wisdom, suddenly end up together and then all of a sudden everyone's falling to hurt and you're like, This is great, but I >> hit on the point about the vertical ization. Every one of our client wth e different industries have very different has there and to the meeting that you know the customer, you know, where they're on their journey. I mean, if you talk to a pharmaceutical, you know, geekspeak compliance. Big private cloud started to dip their toes into public. You know, you go to minds and they're being very aggressive public. So >> every manufacturing with EJ boat back in >> the back, coming to it really varies by industry. >> And that's, you know, that's a very interesting here. Like if you look at all the ot environment. So the manufacturing we started see a lot of end of life of environment. So what's that? Next generation, you know, of control system's gonna run on >> interesting on the edge >> because and you've brought of networking a couple times where we've been talking it, you know, and as as, ah, potential gate right when I was still in the gates. But we're seeing Maura where we're at a cool event Churchill Club, when they had Xilinx micron and arm talking about, you know, shifting Maur that compute and store on these edge devices ti to accommodate, which you said, you know, how much of that stuff can you do at the adverse is putting in. But what I think is interesting is how are you going to manage that? There is a whole different level of management complexity when now you've got this different level of you're looting and security times many, many thousands of these devices all over the place. >> You might have heard >> recent announcements from being where around the carbon black acquisition right that combined with our work space one and the pulse I ot well, >> I'm now >> giving you a management framework with It's what people for things or devices and that consistency. Security on the client tied with the network security with NSX all the way to the data center, security were signed. A look at what we call intrinsic security. How do we bake and securing the platform and start solving these end to end and have a park. My rec center helped design these next generation application architectures are distributed by design. Where >> do you put a fence? You're you could put a fence around your data center, >> but your APP is using service now. Another SAS service is so hard to talk to an application boundary in the sea security model around that. It's a very interesting time. >> You hear a lot of you hear a >> lot about a partnership around softer to find data center on networking with Bello and NSX. But we're actually been spending a lot of time with the i o. T. Team and really looking at and a lot of our vision, the lines. I mean, you actually looked that they've been work similarly, agent technology with Leo where you know, ultimately the edge computing for io ti is gonna have to be containerized because you can need multiple middleware stacks supporting different vertical applications, right? We're actually you know what we're working with with one mind where we started off doing video analytics for predictive, you know, maintenance on tires for tractors, which are really expensive. The shovels, It's after we started pushing the data stream up it with a video stream up into azure. But the network became a bottleneck looking into fidelity. So we gotta process there. They're not looking autonomous vehicles which need eight megabits low laden C band with, you know, sitting at the the edge. Those two applications will need to co exist. And you know why we may have as your edge running, you know, in a container down, you know, doing the video analytics. If Caterpillar chooses, you know, Green Grass or Jasper that's going to co exist. So you see how the whole container ization that were started seeing the data center push out there on the other side of the pulse of the management of the edge is gonna be very difficult. I >> need a whole new frontier, absolutely >> moving forward. And with five g and telco. And they're trying to provide evaluated service is So what does that mean from an infrastructure perspective. Right? Right, Right. When do you stay on the five g radio network? Worse is jumping on the back line. And when do you move data? Where's his process? On the edge. Those all business decisions that need to be doing to some framework. >> You guys were going, >> we could go on. Go on, go. But I want to Don't fall upon your Segway from containers because containers were such an important part of this story and an enabler to the story. And, you know, you guys been aggressive. Move with hefty Oh, we've had Craig McCloskey, honor. He was still at Google and Dan great guys, but it's kind of funny, right? Cause three years ago, everyone's going to Dr Khan, right? I was like that were about shows that was hot show. Now doctors kind of faded and and kubernetes has really taken off. Why, for people that aren't familiar with kubernetes, they probably here to cocktail parties. If they live in the Bay Area, why's containers such an important enabler? And what's so special about Coburn? 80 specifically. >> Do you wanna go >> on the way? Don't talk about my products. I mean, if you >> look at the world is getting much more dynamics on the, you know, particularly you start to get more digitally to couple applications you started. You know, we've gone from a world where a virtual machine might have been up for months or years. Toe, You know, obviously you have containers that are much more dynamic, allowed to scale quickly, and then they need to be orchestrated. That's essential. Kubernetes does is just really starts to orchestrate that. And as we get more distributed workloads, you need to coordinate them. You need to be able to scale up as you need it for performance, etcetera. So kubernetes an incredible technology that allows you really to optimize, you know, the placement of that. So just like the virtual machine changed, how we compute containers now gives us a much more flexible portable. You know that, you know you can run on anything infrastructure, any location, you know, closer to the data, et cetera. To do that. And I >> think the bold movie >> made is, you know, we finally, after working with customers and partners like century, we have a very comprehensive strategy. We announced Project Enzo, a philosophy in world and Project tansy really focused on three aspects of containers. How do you build applications, which is pivotal in that mansion? People's driven around. How do we run these arm? A robust enterprise class run time. And what if you could take every V sphere SX out there and make it a container platform? Now we have half a million customers. 70 million be EMS, all of sudden that run time. We're continue enabling with the Project Pacific Soviets. Year seven becomes a commonplace for running containers, and I am so that debate of'em czar containers done gone well, one place or just spin up containers and resource is. And then the more important part is How do I manage this? You said, becoming more of a platform not just an orchestration technology, but a platform for how do I manage applications where I deploy them where it makes most sense, right? Have decoupled. My application needs from the resource is, and Coburn is becoming the platform that allows me to port of Lee. I'm the old job Web logic guy, right? >> So this is like distributed Rabb logic job on steroids, running across clouds. Pretty exciting for a middle where guy This is the next generation and the way you just said, >> And two, that's the enabling infrastructure that will allow it to roll into future things like devices. Because now you've got that connection >> with the fabric, and that's working. Becomes a key part of one of the key >> things, and this is gonna be the hard part is optimization. So how do we optimize across particularly performance, but even costs? >> You're rewiring secure, exact unavailability, >> Right? So still, I think my all time favorite business book is Clayton Christians. An innovator's dilemma. And in one of the most important lessons in that book is What are you optimizing four. And by rule, you can't optimize for everything equally you have to you have to rank order. But what I find really interesting in this conversation in where we're going in the complexity of the throughput, the complexity of the size of the data sets the complexity of what am I optimizing for now? Just begs for applied a I or this is not This is not a people problem to solve. This is this >> is gonna be all right. So you look at >> that, you know, kind of opportunity to now apply A I over the top of this thing opens up tremendous opportunity. >> Standardize infrastructural auditory allows you to >> get more metrics that allows you to build models to optimize infrastructure over time. >> And humans >> just can't get their head around me because you do have to optimize across multiple mentions. His performances cost, but then that performances gets compute. It's the network, I mean. In fact, the network's always gonna be the bottlenecks. You look at it even with five G, which is an order of magnitude, more bandwidth from throughput, the network will still lag. I mean, you go back to Moore's Law, right? It's Ah, even though it's extended to 24 months, price performance doubles. The amount of data potentially can kick in and you know exponentially grow on. Networks don't keep pays, so that optimization is constantly going to be tuned. And as we get even with increases in network, we have to keep balancing that right. >> But it's also the business >> optimization beyond the infrastructure optimization. For instance, if you're running a big power generation field of a bunch of turbines, right, you may wanna optimize for maintenance because things were running at some steady state. But maybe there's oil crisis or this or that. Suddenly the price, right? You're like, forget the maintenance. Right now we've got you know, we >> got a radio controlled you start about other >> than a dynamic industry. How do I really time change the behavior, right? Right. And more and more policy driven. Where the infrastructure smart enough to react based on the policy change you made. >> That's the world we >> want to get to. And we're far away from that, right? >> Yeah. I mean, I think so. Ultimately, I think the Cuban honeys controller gets an A I overlay and the operators of the future of tuning the Aye aye engines that optimizing, >> right? Right. And then we run into the whole thing, which we've talked about many times in this building with Dr Room, A child re from a center. Then you got the whole ethics overlay on top of the thing. That's a whole different conversation from their day. So before we wrap kind of just want to give you kind of last thoughts. Um, as you know, customers Aaron, all different stages of their journey. Hopefully, most of them are at least at least off the first square, I would imagine on the monopoly board What does you know, kind of just top level things that you would tell people that they really need just to keep always at the top is they're starting to make these considerations, starting to make these investments starting to move workloads around that they should always have kind of top >> of mind. For me, it's very simple. It's really about focused on the business outcome. Leverage the best resource for the right need and design. Architectures are flexible that give you a choice. You're not locked in and look for strategic partners with this technology partners or service's partners that alive you to guide because the complexities too high the number of choices that too high. You need someone with the breath in depth to give you that platform in which you can operate on. So we want to be the digital kind of the ubiquitous platform. From a software perspective, Neck Centuries wants to be that single partner who can help them guide on the journey. So I think that would be my ask. It's not thinking about who are your strategic partners. What is your architecture and the choices you're making that gave you that flexibility to evolve. Because this is a dynamic market. What should make decisions today? I mean, I'll be the one you need >> six months even. Yeah. And And it's And that that dynamic that dynamics is, um is accelerating if you look at it. I mean, we've all seen change in the industry of decades in the industry, but the rate of change now the pace, you know, things are moving so quickly. >> I mean, little >> respond competitive or business or in our industry regulations, right. You have to be prepared for >> Yeah. Well, gentlemen, thanks for taking a few minutes and ah, great conversation. Clearly, you're in a very good space because it's not getting any less complicated in >> Thank you. Thank you. All right. Thanks, Larry. Ajay, I'm Jeff. You're watching the Cube. >> We are top of San Francisco in the Salesforce Tower at the center Innovation hub. Thanks for watching. We'll see next time. Quick

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019. Brought to you by IBM Wear and its ecosystem partners. >> Welcome to our live coverage here in Mosconi North Lobby, Of'em World 2019. I'm John for a Student and a Volante celebrating our 10th VM World or 10 years of covering the M world. Dave's stew. What a run been Go back across Mosconi South 10 years ago with the green set. This is 10 years later. 10:10 p.m. World BMC Rule No longer the show, so that kind of folds in the Dell Technologies Man, The world's changed. Pat Nelson had just delivered his keynote as CEO Sanjay Poon and a CEO came on talk to customers stew. A lot of acquisitions, a lot of cloud native, a lot of cloud. 2.0, this is turning into VM. Wear 2.0, where vm zehr kind of only one part of the equation. So let's jump into the analysis, Dave. I mean, you put out some killer research on silken angle dot com, and we keep on dot com around customer spend still, we put out a lot of analysis on all the key trends that Vienna was playing into. Cloud two point. Oh, is what we're calling it. It's enterprise Cloud of fresh scale Day. What? What? What? What do you want? Your analysis, Latino >> John, when you go back. 10 VM Worlds ago, it was all about virtualization, completely changing the deployment dynamics. When when I first saw a VM deployed, I went, Oh, my God, This is gonna change everything. And it did. But while compared to now what's happening with cloud and a I we heard so much about five g. It was also the big, big difference in the ecosystem. Back when e. M. C owned VM wearing 2010 there was that sort of Chinese wall stew. You were working there, you know, just before that. And there wasn't a lot of, you know, swapping of I P, if you will. They were sort of treating them as unequal player to net app and everybody else out there. Tod Nielsen used to say, for every dollar spent on of'em were licensed, 15 spent an ecosystem. You don't hear that kind of narrative anymore, you hear we're crushing the HC. I vendor where number one basically a sort of backhand to Nutanix We heard on the on the keynote Very tight integration VX rail project Dimension So much, much tighter integration since Pat Tell Singer joined VM. Where from the emcee lots has changed >> will be a lot of research on reporting leading up to the show around Cloud two point. Oh, I'll see Dev. Ops is willing to home of the dimension on enterprise scale, the number of acquisitions of'em wears made and then, boom. They dropped two monsters on the table or the 11th hour pivotal for 2.7 billion carbon black for 2.1 billion. Lot of stories in those AK was other acquisitions, your analysis and how that played out today on the >> Kino. As Dave said when we started coming to this event back in 2010 you know, the virtual machine was the center of the universe. What were these servers that it lived on, how to storage and network and get fixed to be ableto live in that environment And the keynote. It was a lot of cloud, you know, John, we brought in a lot of the Cloud camp people that first year and some people were like, Why are we talking about Cloud? This is VM World, and we're like, Well, this is the future. And today we're not talking about V EMS at the center we're talking about containers were talking about cloud native applications, that multi cloud world absolutely something that pack l singer did. Front center actually felt it almost glossed over a little bit of the H C, I and NSX and all these wonderful things. Sure, there was some big del pieces in there. The M word cloud on Delhi emcee the Del Di are, you know, data protection, power protect, you know, into the VM where peace something that you definitely would not have seen under the old emcee Federation model. So Michael Dell, absolutely having his strong footprint here. Dave's done a lot of analysis talking about things like Pivotal getting pulled in and like so many different acquisitions, Pivotal came out of'em wear and, you know, carbon black Boston based companies so many different pieces here to get them talking about applications and where Veum, where the company sits in this multi cloud world where they're trying to be, you know, maintain their relationship with us. >> Let's get into the analysis on the whole ecosystems. I really want to dig into the work. Dave, you didn't and the team did. But let's go through the keynote first. So my personal opinion was it felt like, um, I'll give him a C plus Pat because it just didn't have a lot of meat. In my opinion, it felt like it was too much tech for good, although super important to have that mission driven stuff I think is really valuable as the market tends to look >> at tech >> as bad actors. I thought that was addressing. That was a positive thing, but it felt too much. I didn't see a lot of specifics. It felt do is and David, if they were hiding something, they were putting a lot of it didn't seem like there's a lot of substance coming out specifically around how Kubernetes was going to be impacted. Specifically, how Cooper is going to sit within the VM where ecosystem products specifically I just didn't feel like the product side was there. >> Well, you know what? I'll say it, John and General, I agree with you because Day one usually is here is the company vision. And if the vision is kubernetes, well, we've been hearing kubernetes for a bunch of years. Kubernetes is not the answer. Kubernetes is an enable ionizing technology job. Ada, who we up on stage? You know, we had him on the Cuban. He's like, look committed. This is not a magic layer. It's this thin layer that's gonna help us go between clouds. Getting into some of their future projects is something I usually would expect on Day two, the vision of V. M. Whereas a company, it feels like we're in that transition from who do you want a big tech for? Good? That that's great stuff. You know, Pat has a long history of talking about, you know, that moral compass that he has and wants the company to live. That which is a good change from many of the Silicon Valley companies. But, you know, I didn't get a strong feel for their vision and it was not >> a conservative. They didn't want to actually put a position down there because I think everyone in the hallway that I talked to wants to know how Cooper is gonna impact the sphere for instance, is gonna change the makeup of the sphere. And what's the impact on the product side the head that stat about bare metal being 8%. I was like, a little bit biased. Maybe there, So are they. They tiptoeing. Dave, you think? I mean, the spend numbers show that if you could just hold the line for 24 months and the new trends won't take away from that license, I mean, is it a tactical thing? Or do you think that here's the >> thing? I want to go back? I do want to give'em where? Props on one thing and you've used this term to If you go back to 8 4009 Paul Maritz talked about. We're building the software mainframe and passed them pretty consistent about that they used, they said, Any workload, any app? What's different today than back then is, he said, any workload, any up any cloud. Really. Cloud wasn't as much of a factor back then, but that vision has been fairly consistent it to you. Answer your question, Veum. We're spending remains strong, you know they're spending data that we shared with the GT R on silicon angle yesterday and today is that 41% of the VM were installed. Base is going to spend Maurine the second half of 2019 and only 7% are going to spend less. Okay, that's a real positive. But at the same time, the data clearly shows that cloud is negatively impacting VM wear spend and so that's a real threat. So multi club Pat said today technologists who Master Master Multi Cloud will own the next decade. He's talking to his audience. I'm not sure I agree with that. How much you're mastering Multi Cloud is what's gonna be the determining factor to own the next decade. >> Well, I'm stumped. Stick with my position. That multi cloud is not a reality. I think it's really more overhyped, and our actually just started to be hyped and probably will be then over hypes. And then seven years from now we'll start seeing multiple clouds truly interoperable. But I think multi cloud is we find on the Cuba simply enterprises have multiple vendors and multiple environments that happen to be those vendors have cloud, so I don't think it actually is an operating model yet. But again, just like on the Cube 2012 stew. We talked about hybrid Cloud. I called. I asked, yes. When was it a halfway house of the weigh station? He had a connection. >> So gassy. So, John, here's what I say. Number one is customers today absolutely have multiple clouds. But for multi cloud, to be a reality multi cloud must be greater than the sum of just the piece is that it's made up today and absolutely were not there. Today. VM wear has a strong reason why it should be at the center of that discussion. But they're gonna be right at loggerheads with Red Hat and Microsoft and Google and Cisco in that kind of debate at the multi cloud >> and we had, we had a story on our special report on silicon angle dot com. Check it out. It's called Coping With Multi Cloud. Were coping was by design. Coping as a mechanism used to deal with uncertainty. Coping strategies is what CEOs are going to deal with. But read that post. But in it I kind of see. I mean, I kind of agree and disagree. We have two perspectives, Dave developing. You want to get your thoughts butts do on this C I ose that come from a traditional I t background tend to like multi vendor things because they know they don't want lock. And they're afraid if you then swing to the progressive side si SOS, for instance, who are have a gun to their head in terms of security, they're all saying no, we're betting on one cloud and we'll have backup clouds, but our development staff is gonna build stacks. Have AP eyes, and we'll share those AP ice to our suppliers. Cloud vendors are saying Support our specs. So to spectrums the old school I t. Guys saying Multi vendor equals multi cloud. And then then, on the other end, See says to say, I'm gonna build technology and build a stack, exposed FBI's and let the clouds support my my tooling that not the other way around your thoughts. I >> pulled a quote in my piece That's on Silicon angle as well. From David. If lawyer and he was defining a hybrid multi cloud, he said, any application of application service can run on any note of the hybrid cloud without rewriting re compiling a re testing. My argument would be you're never gonna have that North Star without a high degree of homogeneity. And there's three examples of high degrees of homogeneity in hybrid Cloud. Today it's azure stack. It's clouded customer, and it's outposts. You're so this idea that we're gonna have this diverse set of clouds and yet they're all gonna run is one to me. I ask, Is it technically feasible? And is it Is it practical? >> Well, Steve, Steve Harry was on his Hey had announced the signal. FX has come. Portfolio can be sold on a big deal to split when he was on The Cube with me last week and he said one of them looking back on the 10 years that 1 may be M where great was virtual ization allowed for massive efficiencies and improvements without rewriting the apse. The question today's point is, is that a reality? Can what's next? So that that next gain that's not gonna require people to rewrite their APs >> well and that actually not rewriting the axes where VM or has its strength. Because, you know, I I made a joke during the keynote. It was like you have a V M insert magic. Congratulations. You now have a cloud workload because I just did. VM were cloud and it's the same app. But on the other hand, that's actually been my biggest dig on V M. Where is the long pole? In the tent and modernization is modernizing wraps. And that is that Tom Zoo that Veum were announced. They're taking bit Nami and pivotal because we do need to modernize the application. If you have an application, you've been running long enough that your users are complaining about it. We need to modernize that. VM wear has not been much of enabler of that pivotal. Yes, absolutely. That's what the cloud Foundry Labs, the pivotal Labs has been doing for years. It is a tough thing to do. That's what the developers we hear it Amazon. They're building new abs. I don't hear modern building new app at VM where, but they are moving in that >> direct question for you guys and John you in particular, but also used to as well followed AWS probably more closely than any two people I know, Pat said. Strength, lies and differences, not similarities. I've noted many differences in philosophy between A. W S and V M. where they're both winning in the market place. We know a divorce is growing much faster, but a divorce doesn't believe in multi cloud. A Devil's doesn't believe security is broken. That's that's VM wears narrative VM where says it wants to be the best infrastructure and develop our software company. That's kind of like eight of us is the platform for that. They both want to be the security cloud, and and VM were said today they have 10,000 cloud data centers, and I'm guessing that Andy Jassy wouldn't think that many of those data centers are cloud data centers. Your thoughts on the differences between between A. W S s philosophy and VM wears narrative. And can they both? Is there enough market for them both to win? >> Well, it's strikingly different. I mean, AWS is just in a breed of its own. VM wears hedging and playing there their bets. They're kind of putting, you know, bets on each horse, right? Interesting enough in the cloud thing. There was no mention of Google Cloud. I didn't see that mentioned there. Andi was speculation. Wouldn't Oracle be great partnering with Google? That's not a rumor. I'm just kind of put it out there. That would be a good combination partnership, given the Oracle's cloud is failing miserably, I think v M. Where because of the operating leverage in the enterprise, has that operational layer down to me, Amazon is the model, the future, because they are clearly born with a dev ops mindset. They have an environment where developers can build applications and they could operate. It scale with all the efficiencies of operations. So I think cloud to foreigners were calling. It is all about having developers and operational excellence without a lot of disruption or re platforming. So I think that's where the differences are. You have company that have toe have to work with this world of legacy applications, and that requires first lift and shift, which doesn't become attractive. Then you add containers on the game changes. So I think container ization really was, I think, the seminal moment in the shift where where you got kubernetes and containers. So let the enterprise cloud. Native guys get in and have an operational framework that takes advantage of the horsepower of public cloud, which is computing storage, which is why we think networking and security will be the absolute focus areas for Cloud two point. Oh, and Amazon is just dominating the depth and the ops. And I don't think anyone is coming close. >> I'd love to hear your thoughts, too, but I just got caught. I don't think Oracles Cloud is failing miserably. I think it's I wouldn't say it that way. I think their infrastructures of service is irrelevant and the cloud is all about SAS. But just, you know, that's what I think. Waken debate that somebody >> has been great for the Oracle customers. But in terms of all metrics in terms of public and enterprise, cloud with multiple environments nonstarter. >> So there's a bit of a schism out there if you talk to customers. There are many customers when they deploy in Public Cloud, although uses, you know, compute storage and, like the identity management and that's it. And they'll stop and I talkto you con many customers that are using kubernetes so that if they want to hit the eject button, but they're all on Amazon today, so it's not like they're all fleeing Amazon or doing it. But we talked to lots of developers that are deep in aws they're using those service is they're using Lambda and they're building it. So how deep will they go? And that's where I look at this VM we're offering. And it's if I'm gonna take the sphere and extend that with kubernetes. I saw Cuba. Well, um, actually in the Twitter stream said it is, you know, cloud lock in to Dato is what we get if we do that. Because the whole reason VM were originally created called Foundry. So they didn't have to take that entire V's fear colonel and put it everywhere. So it's a nice bridge. That van, where has the partnership they have with AWS is a great strategy. But I still think it is a bridge to an ultimate solution where they'll still use the M where the embers not going anyway. But that shift of where my application live in what service is I do is going to change a lot over the next 3 to 5. >> Let's not lose sight, Dave, of where we are in the industry. I mean, we're at VM World 2019. We go to reinvents coming up. We kind of live in a tech bubble in the sense that all this stuff is all kind of great skating to where the puck is gonna be. But the reality is in most I tea shops, and again, I use ceases as a proxy in my mind, because they're in the cutting edge of all the real critical nature of security, of the impact that harm that could happen to a company. So I look at sea. So she's more of a canary in the coal mine for trends than the nutritional CEO. At this point, most enterprises are just trying to rationalize kubernetes, generally speaking like never mind, like making a centerpiece of their entire architecture. They're looking at their existing environment saying, Hey, I got V EMS that did great for me. Serve a consolidation enabled more efficiency, not rewriting code. Now what? I gotta do kubernetes and do all this other stuff. How do I suspect my VM with kubernetes? Is it on bare metal? So I think we're way ahead right now. In the narrative, I think the reality is that people catch up. That's where the proof is gonna come into. That's why the customer survey numbers are interesting. >> Keep keep. Townsend is set on the Cube VM, where moves at the speed of the CEO, so they're not moving too far ahead of them, but they are key heating up with them. >> Let me share some data to share some data so you could go to Silicon Angle. Look at the V M World 2019 90 spending survey containers, Cloud NSX and pivotal its data from Enterprise Technology Research that we analyzed. There's no evidence right now that Container's air hurting VM wear. But then that was the narrative that containers are gonna kill the M where but long term. There's real threats there. So that's what the pivotal acquisition, at least in part was about. I want to address the pivotal acquisition cause we haven't dug into it a little bit a cz, Much as I'd like to see. There's really three things there. One pivotal was struggling. You look at the stock price, you look at their buying patterns, you know the stock was down that not even close to their original AIPO price, so they wanted to get out of the public eye right now would not be on that 30 day shot clock. The second is it's a hedge on containers. And the third is it's a financial scheme. I mean, I'll call it that VM wears paying $800 million in cash for an asset that's worth $4 billion. How can that be? Well, they already owned 15% of pivotal there. Give. They're exchanging stock. So their trade trading paper to Adele in exchange for Dell's 70% ownership in Pivotal. So they pick up this asset, and it's basically a forced migration by Michael Del, who controls 96% of the voting shares. So there's all kinds of inside nuance going on there that nobody's really talked about it a >> great deal for Of'em. Where and Michael Dell? It's >> a very good deal for VM wear and Michael Dell. >> Let's unpack that are rapidly. >> Just did the one piece on that, right, because kubernetes it was the elephant, the room that was damaging what Pivotal was doing. VM were made a couple of acquisitions VM where needs to react at, so it made sense to pull out back in. Even if it does go against some of the original mission, that Cloud Foundry and Pivotal had to be able to be that cloud native without that full strong time, >> it's all about building apse, right? It's all about enabling developers. >> Let's on that note. Let's go around the horn and talk about what we expect from the emerald this year. And then we'll kick off three days of wall to wall coverage. I'll start, I expect. And I'm not looking for is how VM wear and its ecosystem and who's really deep in the ecosystem, who's kind of independent and neutral, what they're doing with their containers and kubernetes play. Because I think the container revolution that was started with Dr Absolutely is very relevant to the C i o and the Sea. So so and then how they're using data in that in their applications. So you know how VM Way wants to position themselves on the control plane, how that fits in the NSX. I think containers in the container ization is going to change. I think bare metal is gonna be a super important topic in the next couple of years. Dio I'm kind of swinging back to the my feeling that you know, hyper convergence what it did for server storage networking back when you were calling those those moves. I think that kind of hyper convergence mentality is coming up the stack, and I think Containers and the Kubernetes Chess Board will will play out. >> I think if you my feelings, if you don't own a public cloud, you better convince your customers in your ecosystem that the future is in our definition of cloud, which is multi cloud. And that's what this VM world to me is all about. >> Yeah, you know, Veum wears taking their software state and trying to live in all of those cloud world. So you know, V. Amar has 600,000 customers and they want to be the ones to educate them on the kubernetes containers. You know you're at modernization, but there's a lot of other places customers can learn about this. No one understand where VM wear really adds value beyond all of those pieces, because all the cloud platforms have their kubernetes. >> A lot of other places, like the public cloud. That's where all the action >> exactly comes back down the cloud 2.0 Dev and ops developers and operations all come together with software. Thank you. Breaking it down here for three days. Wall to wall coverage here in Moscow north to set celebrating our 10th year covering VM World. Thanks for watching stay with us from or action after this short break.

>> live from New York. It's the Q covering AWS Global Summit 2019 brought to you by Amazon Web service, is >> welcome back here in New York City on stew Minimum. My co host is Corey Quinn. In the keynote this morning, Warner Vogel's made some new announcements what they're doing and also brought out a couple of customers who are local and really thrilled and excited to have on the program the C i O and E V P from Finn Ra here in New York City. Steve Randall, thanks so much for joining us. You're welcome. Thank you. All right, so, you know, quite impressive. You know when when I say one of those misunderstood words out there to talk about scale and you talk about speed and you know, you were you know, I'm taking so many notes in your keynote this 1 500,000 compute note. Seven terabytes worth of new data daily with half a trillion validation checks per day, some pretty impressive scale, and therefore, you know, it's I t is not the organ that kind of sits in the basement, and the business doesn't think about it business and I t need to be in lobster. So, you know, I think most people are familiar with in Rome. But maybe give us the kind of bumper sticker as Thio What dinner is today and you know, the >> the organization. Yeah, I started it Fender and 2013. I thought I was gonna come into a typical regulator, which is, as you alluded to technologies, kind of in the basement. Not very important, not strategic. And I realized very quickly two things. Number one, The team was absolutely talented. A lot of the people that we've got on her team came from start ups and other technology companies. Atypical financial service is and the second thing is we had a major big data challenge on our hands. And so the decision to go to the cloud S I started in March 2013. By July of that year, I was already having dialogue with our board of directors about having to go to the cloud in orderto handle the data. >> Yeah, so you know, big data was supposed to be that bit flip that turned that. Oh, my God. I have so much data to Oh, yea, I can monetize and do things with their data. So give us a little bit of that, That data journey And what? That that you talk about the flywheel? The fact that you've got inside Finneran. >> Yeah. So we knew that we needed the way were running at that time on data warehouse appliances from E, M. C. And IBM. And which a data warehouse appliance. You go back 10 15 years. That was where big data was running. But those machines are vertically scalable, and when you hit the top of the scale, then you've got to buy another bigger one, which might not be available. So public cloud computing is all about horizontal scale at commodity prices to things that those those data data warehouse appliance didn't have. They were vertical and proprietary, inexpensive. And so the key thing was to come up to select the cloud vendor between Google, IBM, You know, the usual suspects and architect our applications properly so that we wouldn't be overly vendor dependent on the cloud provider and locked in if you will, and that we could have flexibility to use commodity software. So we standardized in conjunction with our move to the public cloud on open source software, which we continue today. So no proprietary software for the most part running in the cloud. And we were just very smart about architect ing our systems at that point in time to make sure that those opportunities prevailed. And the other thing I would say, this kind of the secret of our success Is it because we were such early adopters we were in the financial service industry and a regulator toe boots that we had engineering access to the cloud providers and the big, big date open source software vendors. So we actually had the engineers from eight of us and other firms coming in to help us learn how to do it, to do it right. And that's been part of our culture ever since. >> One thing that was, I guess a very welcome surprise is normally these keynotes tend to fall into almost reductive tropes where first, we're gonna have some Twitter for pet style start up talking about all the higher level stuff they're doing, and then we're gonna have a large, more serious company. Come in and talk about how we moved of'em from our data center into the cloud gay Everyone clap instead, there was it was very clear. You're using higher level, much higher level service is on top of the cloud provider. It's not just running the M somewhere else in the same way you would on premise. Was that a transitional step that you went through or did you effectively when you went all in, start leveraging those higher service is >> okay. It's a great question. And ah, differentiator for us versus a lot. A lot of the large organizations with a legacy footprint that would not be practical to rewrite. We had outsourced I t entirely in the nineties E T s and it was brought back in source in in house early in this decade. And so we had kind of a fresh, fresh environment. Fresh people, no legacy, really other than the data warehouse appliances. So we had a spring a springboard to rewrite our abs in an agile way to be fully cloud enabled. So we work with eight of us. We work with Cloudera. We work with port works with all the key vendors at that time and space to figure out how to write Ah wraps so they could take most advantage of what the cloud was offering at that time. And that continues to prevail today. >> That that's a great point because, you know so often it's that journey to cloud. But it's that application modernization, that journey. Right. So bring us in little inside there is. You know how it is. You know, what expertise did Finn Ra have there? I mean, you don't want to be building applications. It is the open stuff source. The things wasn't mature enough. How much did they have toe help work, you know, Would you call it? You know, collaboration? >> Yeah. The first year was hard because I would have, you know, every high performance database vendor, and I see a number of them here today. I'm sure they're paddling their AWS version now, but they had a a private, proprietary database version. They're saying if you want to handle the volumes that you're seeing and predicting you really need a proprietary, they wouldn't call it proprietary. But it was essentially ah, very unique solution point solution that would cause vendor dependency. And so and then and then my architects internally, we're saying, No way, Wanna go open source because that's where the innovation and evolution is gonna be fastest. And we're not gonna have vendor Lock in that decision that that took about a year to solidify. But once we went that way, we never looked back. So from that standpoint, that was a good bad, and it made sense. The other element of your question is, how How much of this did we do on our own, rely on vendors again? The kind of dirty little secret of our beginnings here is that we ll average the engineer, you know, So typically a firm would get the sales staff, right. We got the engineers we insisted on in orderto have them teach our engineers how to do these re architectures to do it right. Um and we use that because we're in the financial service industry as a regulator, right? So they viewed us as a reference herbal account that would be very valuable in their portfolio. So in many regards, that was way scratch each other's back. But ultimately, the point isn't that their engineers trained our engineers who trained other engineers. And so when I when I did the, uh um keynote at the reinvented 2016 sixteen one of my pillars of our success was way didn't rely overly on vendors. In the end, we trained 2016 1 5 to 600 of our own staff on how to do cloud architectures correctly. >> I think at this point it's very clear that you're something of an extreme outlier in that you integrate by the nature of what you do with very large financial institutions. And these historically have not been firms that have embraced the cloud with speed and enthusiasm that Fenner has. Have you found yourself as you're going in this all in on the cloud approach that you're having trouble getting some of those other larger financial firms to meet you there, or is that not really been a concern based upon fenders position with an ecosystem? >> Um, I would say that five years ago, very rare, I would say, You know, we've had a I made a conscious effort to be very loud in the process of conferences about our journey because it has helped us track talent. People are coming to work for us as a senior financial service. The regulator that wouldn't have considered it five years ago, and they're doing it because they want to be part of this experience that we're having, but it's a byproduct of being loud, and the press means that a lot of firms are saying, Well, look what Fender is doing in the cloud Let's go talk to them So we've had probably at this 50.200 firms that have come defender toe learn from our experience. We've got this two hour presentation that kind of goes through all the aspects of how to do it right, what, what to avoid, etcetera, etcetera. And, um, you know, I would say now the company's air coming into us almost universally believe it's the right direction. They're having trouble, whether it's political issues, technology dat, you name it for making the mo mentum that we've made. But unlike 45 years ago, all of them recognize that it's it's the direction to go. That's almost undisputed at this point. And you're opening comment. Yeah, we're very much an outlier. We've moved 97 plus percent of our APS 99 plus percent of our data. We are I mean, the only thing that hasn't really been moved to the cloud at this point our conscious decisions, because those applications that are gonna die on the vine in the data center or they don't make sense to move to the cloud for whatever reason. >> Okay, You've got almost all your data in the cloud and you're using open source technology. Is Cory said if I was listening to a traditional financial service company, you know, they're telling me all the reasons that for governance and compliance that they're not going to do it. So you know, why do you feel safe putting your your data in the cloud? >> Uh, well, we've looked at it. So, um, I spent my first year of Finn run 2013 early, 2014 but mostly 2013. Convincing our board of directors that moving our most critical applications to the public cloud was going to be no worse from the information security standpoint than what we're doing in our private data centers. That presentation ultimately made it to other regulators, major firms on the street industry, lobbyist groups like sifma nephi. AP got a lot of air time, and it basically made the point using logic and reasoning, that going to the cloud and doing it right not doing it wrong, but doing it right is at least is secure from a physical logical standpoint is what we were previously doing. And then we went down that route. I got the board approval in 2015. We started looking at it and realizing, Wait a minute, what we're doing here encrypting everything, using micro segmentation, we would never. And I aren't doing this in our private data center. It's more secure. And at that point in time, a lot of the analysts in our industry, like Gardner Forrester, started coming out with papers that basically said, Hey, wait a minute, this perception the cloud is not as safe is on Prem. That's wrong. And now we look at it like I can't imagine doing what we're doing now in a private data center. There's no scale. It's not a secure, etcetera, etcetera. >> And to some extent, when you're dealing with banks and start a perspective now and they say, Oh, we don't necessarily trust the cloud. Well, that's interesting. Your regulator does. In other cases, some tax authorities do. You provided tremendous value just by being as public as you have been that really starts taking the wind out of the sails of the old fear uncertainty and doubt. Arguments around cloud. >> Yeah, I mean, doubts around. It's not secure. I don't have control over it. If you do it right, those are those are manageable risks, I would argue. In some cases, you've got more risk not doing it. But I will caution everything needs to be on the condition that you've got to do it right. Sloppy migration in the cloud could make you less secure. So there there are principles that need to be followed as part of >> this. So Steve doing it right. You haven't been sitting still. One of the things that really caught my attention in the keynote was you said the last four years you've done three re architectures and what I want. Understand? You said each time you got a better price performance, you know, you do think so. How do you make sure you do it right? Yet have flexibility both in an architect standpoint, and, you know, don't you have to do a three year reserves intense for some of these? How do you make sure you have the flexibility to be able to take advantage of you? Said the innovation in automation. >> Yeah. Keep moving forward with. That's Ah, that's a deep technical question. So I'm gonna answer it simply and say that we've architected the software and hardware stack such. There's not a lot of co dependency between them, and that's natural. I t. One on one principle, but it's easier to do in the cloud, particularly within AWS, who kind of covers the whole stacks. You're not going to different vendors that aren't integrated. That helps a lot. But you also have architect it, right? And then once you do that and then you automate your software development life cycle process, it makes switching out anyone component of that stack pretty easy to do and highly automated, in some cases completely automated. And so when new service is our new versions of products, new classes of machines become available. We just slip him in, and the term I use this morning mark to market with Moore's Law. That's what we aspire to do to have the highest levels of price performance achievable at the time that it's made available. That wasn't possible previously because you would go by ah hardware kit and then you'd appreciate it for five years on your books at the end of those five years, it would get kind of have scale and reliability problems. And then you go spend tens of millions of dollars on a new kit and the whole cycle would start over again. That's not the case here. >> Machine learning something you've been dipping into. Tell us the impact, what that has and what you see. Going forward. >> It's early, but we're big believers in machine learning. And there's a lot of applications for at Venera in our various investigatory and regulatory functions. Um, again, it's early, but I'm a big believer that the that the computer stored scale, commodity costs in the public cloud could be tapped into and lever it to make Aye aye and machine learning. Achieve what everybody has been talking about it, hoping to achieve the last several decades. We're using it specifically right now in our surveillance is for market manipulation and fraud. So fraudsters coming in and manipulating prices in the stock market to take advantage of trading early days but very promising in terms of what it's delivered so far. >> Steve want to give you the final word. You know, your thank you. First of all for being vocal on this. It sounds like there's a lot of ways for people to understand and see. You know what Fenner has done and really be a you know, an early indicator. So, you know, give us a little bit. Look forward, you know what more? Where's Finn Ra going next on their journey. And what do you want to see more from, You know, Amazon and the ecosystem around them to make your life in life, your peers better. >> Yes. So some of the kind of challenges that Amazon is working with us and partnering Assan is getting Ah Maur, automated into regional fell over our our industries a little bit queasy about having everything run with a relatively tight proximity in the East Coast region. And while we replicate our data to the to the other East region, we think AIM or co production environment, like we have across the availability zones within the East, would be looked upon with Maur advocacy of that architecture. From a regulatory standpoint, that would be one another. One would be, um, one of the big objections to moving to a public cloud vendor like Amazon is the vendor dependency and so making sure that we're not overly technically dependent on them is something that I think is a shared responsibility. The view that you could go and run a single application across multiple cloud vendors. I don't think anybody has been able to successfully do that because of the differences between providers. You could run one application in one vendor and another application in another vendor. That's fine, but that doesn't really achieve the vendor dependency question and then going forward for Finn or I mean, riel beauty is if you architected your applications right without really doing any work at all, you're going to continuously get the benefits of price performance as they go forward. You're not kind of locked into a status quo, So even without doing much of any new work on our applications, we're gonna continue to get the benefits. That's probably outside of the elastic, massive scale that we take advantage of. That's probably the biggest benefit of this whole journey. >> Well, Steve Randall really appreciate >> it. >> Thank you so much for sharing the journey of All right for Cory cleanups to minimum back with lots more here from eight Summit in New York City. Thanks for watching the cue

(light music) >> Hi, I'm Peter Burris and welcome to another CUBE Conversation. This one is part of a very, very special digital community event sponsored by Datrium. What are we gonna be talking about today? Well, Datrium's here with a special product announcement that's intended to help customers do a better job at matching their technology needs with the speed and opportunities to use their data differently within their business. This is a problem that every single customer faces, every single enterprise faces and it's one that's become especially acute as those digital natives increasingly hunt down and take out some of those traditional businesses that are trying to better understand how to use their data. Now, as we have with all digital community events, at the end of this one, we're gonna be running a crowd chat, so stay with us. We'll go through a couple of Datrium and Datrium customer conversations and then it'll be your turn to weigh in on what you think is important, ask the questions of Datrium and others in the community that you think need to be addressed. Let's hear what you have to say about this increasingly special relationship between data, technology and storage services. So, without further ado, let's get it kicked off. Tim Page is the CEO of Datrium. Tim, welcome to theCUBE. >> Thank you, Peter. >> So, Datrium, give us a quick take on where you guys are. >> Yeah, Datrium's formulated as a software defined converged infrastructure company that takes that convergence to the next level, and the purpose of us is to give the user the same experience whether you're working on-prem or across multicloud. >> Great, so let's start by saying that's the vision, but you've been talking to a lot of customers. What's the problem that you keep hearing over and over that you're pointing towards? >> Yeah, it's funny, meeting with a number of CIOs over the years and specifically as related to Datrium, they'll tell you we're on an on-demand economy that expects instant outcomes, which means you have to digitally transform and to do that, you've gotta transform IT, which means it's gotta be easy, it's gotta be consistent. You've gotta get rid of a lot of the management issues and it's gotta feel or take advantage of the services that cloud has to offer. >> All right, so that's the nature of the problem. You've also done a fair amount of research looking into the specifics of what they're asking for. Give us some insight into what Datrium's discovering as you talk to customers about what the solutions are gonna look like. >> It's interesting, if you look at how to resolve that, you've gotta converge to transform in some form or fashion. If you look at the first level of convergence a lot of people have done, it's been directly as it relates to hardware architecture. We've taken that to a whole new level to a point where we're saying how do you actually automate those mundane tasks that take multiple groups to solve. Specifically, primary, backup, disaster recovery, all the policies involved in that. There's a lot of work that goes into that across multiple groups and we set out to solve those issues. >> So, there's still a need for performance, there's still the need for capacity, to reduce management time and overhead, et cetera, but, Tim, as we move forward, how are customers responding to this? Are you getting some sense of what percentage of them are going to say, yeah, that's it? >> Yeah, so interesting, we just ran a survey and got over 500 people, IT leaders to respond to it and it's interesting 'cause they talk about performance, management, security, but they're also talking about consistency of that experience. Specifically, we asked how many of you is it important to have your platform have built-in backup and policy services with encryption built-in, et cetera and we got a 70% rate of those applicants, of those people interviewed saying it's really important for that to be part of a platform. >> Now, it sounds like you're really talking about something more than just a couple of products. You're really talking about forcing customers or you're not forcing, but customers are starting the process of rethinking their data infrastructure. Have I got that right? >> That's right. If you look at how infrastructure's grown over the last 20 years, 20 years ago, SAN technology was related and every time you threw up an app, you had to put different policies to that app or put different LUN type management to how much of my resources can go to certain things. We set out to actually automate that, which is why it took us four years to build this platform with 100 programmers is, well, how do we actually make you not think about how you're gonna back up. How do you set a policy and know disaster recovery is gonna run? And to do that, you gotta have it in one code base. And we know we're on to something even based on our survey because the old array vendors are all buying bolt-ons because they know users want an experience, but you can't have that experience with a bolt-on. You have to have it in your fundamental platform. >> Well, let me step in here. I've been around for a long time, Tim and heard a lot of people talk about platforms and if I have one rule, companies that introduce platforms that just expand typically fail. Companies that bring an opinion and converge more things so it's simpler, tend to be more successful. Which direction is Datrium going? >> Yeah, definitely, that's why we took time. If you wanna be an enterprise class company, you can't build a cheap platform in 18 months and hit the market, 'cause where you architect, you stay. Our purpose from the beginning was purposefully to spend four years building an enterprise platform that did away with a lot of the mundane tasks, SAN management. That's 20 years old technology, LUN management. If you're buying your multi-cloud type technology experience in cages, you're just buying old stuff. We took an approach saying we want that consistent approach that whether you're running your services on prem or in any type of cloud, you could instantly take advantage of that and it feels the same. That's a big task 'cause you're looking to run the speed of storage with the resiliency of backup, which is a whole different type of technology, which is how our founders who have built the first version of this went to the second and almost third version of that type of instantiation of a platform. >> All right, so we know what the solution's gonna look like. It's gonna look like a data platform that's rethought to support the needs of data assets and introduces a set of converged services that really focus the value proposition to what the enterprise needs. So, what are you guys announcing? >> That's exactly right. So, we've finalized what we call our AutoMatrix platform. AutoMatrix inherently in it will have primary backup, disaster recovery, DR solution, all the policies within that and encryption built-in from the very beginning. To have those five things, we believe to actually have the next generation experience across true multicloud, you're not bolting on hardware technologies, you're bolting on software technologies that operate in the same manner. Those five things have to be inherent or you're a bolt-on type company. >> So, you're not building a platform out by acquisition. You're building a platform out by architecture and development. >> That's right and we took four years to do it with 100 guys building this thing out. It's released, it's out and it's ready to go. So our first we're announcing is that first instantiation of that is a product we're calling Control Shift, which is really a data mobility orchestrator, true SaaS based. You can orchestrate prem to prem, prem to cloud, cloud to cloud and our first iteration of that is disaster recovery. So, truly, to be able to set up your policies, check those policies and make sure you're gonna have true disaster recovery with an RTO of zero. It's a tough thing. We've done it. >> That's outstanding. Great to hear, Tim Page, CEO Datrium talking about some of the announcements that we're gonna hear more about in a second. Let's now turn our attention to a short video. Let's hear more about it. (light music) >> Lead Bank is focused on small businesses and helping them achieve their success. We want through and redesigned the customer engagement in defining the bank in the future. This office is our first implementation of that concept. As you can see, it's a much more open floor plan design that increases the interaction between our Lead Bank associates and our clients. With Datrium's split provisioning, all of our data is now on the host. So, we have seen 80 times lower application latency. This gives our associates instant responses to their queries, so they can answer client questions in real-time. Down time is always expensive in our business. In the past, we had a 48 hour recovery plan, but with Datrium, we were able to far exceed that plan. We've been able to recover systems in minutes now. Instead of backing up once per day, with that backup time taking 18 hours, now we're doing full system snapshots hourly and we're replicating those offsite. Datrium is the only vendor I know of that can provide this end-to-end encryption. So, any cyber attacks that get into our system are neutralized. With the Datrium solution, we don't have to have storage consultants anymore. We don't have to be storage experts. We're able to manage everything from a storage perspective through vCenter, obviously spending less time and money on infrastructure. We continue to leverage new technologies to improve application performance and lower costs. We also wanna automate our DR failover, so we're looking forward to implementing Datrium's product that'll allow us to orchestrate and automate our DR failover process. (light music) >> It is always great to hear from a customer. Once again, I'm Peter Burris, this a CUBE Conversation, part of a digital community event sponsored by Datrium. We've been talking about how the relationship between the new digital business outcomes highly dependent upon data and the mismatch of technology to be able to support those new classes of outcomes. It's causing problems in so many different enterprises. So, let's dig a little bit more deeply into some of Datrium's announcements to try to find ways to close those gaps. We've got Sazzala Reddy, who's the CTO of Datrium with us today. Sazzala, welcome to theCUBE. >> Hey Peter, good to see you again. >> So, AutoMatrix, give us a little bit more detail and how it's creating value for customers. >> Yeah, if you go to any data center today, you notice that for the amount of data they have, they have five different vendors and five different products to manage that data. There is the primary storage, there is the backup and there is the DR and then there's mobility and then there is the security you have to think about. So, these five different products are causing friction for you. If you wanna be in the on-demand economy and move fast in your business, these things are causing friction. You cannot move that fast. What we have done is we took a step back and we built this Automatrix platform. It has this data services which is gonna provide autonomous data services. The idea is that you don't have to do much for it. By converging all these functions into one simple platform will remove all the friction you need to manage all your data and that's what we call Automatrix platform. >> As a consequence, I gotta believe then, your customers are discovering that not only is it super easy to use, perhaps a little bit less expertise required, but they also are more likely to be operationally successful with some of the core functions like DR that they have to work with. >> Yeah, so the other thing about these five different functions and products you need is that if you wanna imagine a future where you're gonna leverage the cloud for a simple thing like DR for example, the thing is that if you wanna move this data to a different place, with five different products, how does it move? 'Cause all these five products must move together to some other place. That's not how it's gonna operate for you. So, by having these five different functions converged into one platform is that when the data moves to any other place, the functions move with it giving you the same exact consistent view for your data. That's what we have built and on top of all this stuff is something we have, this global data management applications to control all the data you have in your enterprise. >> So, how are customers responding to this new architecture of AutoMatrix, converged services and a platform for building data applications? >> Yeah, so our customers consistently tell us one simple thing is that it's the most easiest platform they ever used in their entire enterprise life. So, that's what we aimed for simplicity of the customer experience. Autonomous data services give you exactly that experience. So, as an example, last quarter, we had about 40 proof of concepts out in the field. Out of them, about 30 have adopted it already and we're waiting for the 10 of them for results to come out in this quarter. So, generally we found that our proof of concepts don't come back because once you touch it, you experience the simplicity of it and how you get all these service and support, then people don't tend to send it back. They like to keep it and operate it that way. >> So, you mentioned earlier and I summarized the notion of applications, data services applications. Tell us a little bit about those and how they relate to AutoMatrix. >> Right, so once you have data in multiple places, people are adopt multi-cloud and we are going to also be in all these different clouds and we provide that uniform experience, you need this global data management applications to extract value out of your data and that's the reason why we built some global data management applications as SAAS products. Nothing to install, nothing to manage them, then they sit outside and then they help you manage globally all the data you have. >> So, as a result, the I&O people, the infrastructure and operations administrators, do things in terms of AutoMatrix's platform, the rest of the business can look at it in terms of services and applications that you're using in support. >> That's exactly right, so you get the single dashboard to manage all the data you have in your enterprise. >> Now, I know you're introducing some of these applications today. Can you give us a little peek into those? >> Yeah, firstly, our AutoMatrix platform is available on prem as a software defined converged infrastructure and you can get that. We call it DVX. And then we also offer in the cloud our services. It's called Cloud DVX. You can get these. And we're also announcing the release of Control Shift. It's one of our first data management applications, which helps you manage data in two different locations. >> So, go a little bit more specific into or detail into Control Shift. Specifically, which of those five data services you talk about is Control Shift most clearly associated with? >> Right, so to go to again back to this question about if you have five different services, if you have to think about DR. DR is a necessity for every business. It's digital protection, you need it, but the challenge is that there are three or four challenges you generally run into with most common people talk about is that one is that you have to plan. You have to have a proper plan. It's challenging to plan something and then you have to think about the file drill we have to run when there's a problem. And then lastly, when you eventually push the button to fail over, does it really work for you. How fast is it gonna come up? Those are three problems we wanted to solve really solidly, so we call our services, our DR services as failproof DR. That's actually takes a little courage to say failproof. ControlShift is our service which actually does this DR orchestration. It does mobility across two different places. It could be on-prem to on-prem, on-prem to the cloud and because we have this end-to-end data services ourselves, it's easy to then do compliance checks all the time. So, we do compliance checks every few minutes. What that gives you, that gives you the confidence that your DR plan's gonna work for you when you need it. And then secondly, when you push the button because you want some primary storage and backup, it's then easy to bring up all your services at once like that. And the last one is that because we are able to then work across the clouds and provide a seamless experience, so when you move the data to the cloud and have some backups there, you're gonna push a button to fail over, we'll bring up your services in VMware cloud, so that the idea is that it look exactly the same no matter where you are, in DR or not in DR and then watch the video, watch some demos. I think that you can see that you can't tell the difference. >> Well, that's great, so give us a little bit of visibility into how Datrium intends to extend these capabilities, give us a little visibility on your road map. What's up next? >> We are already on Amazon with the cloud. The next thing we're gonna be delivering is Azure, that's the next step, but if you step back a little bit and how do we think about ourselves? If you look at as an example Google, Google federates all the data, the internet data and processes an instant search, provides that instant click and access to all the data at your fingertips. So, we wanna do something similar for enterprise data. How do we federate, how do we aggregate data and provide the customer that instant management they can get from all the data they have. How do you extract value from the data? These set of applications are building towards some examples are we're building deep search. How do you find the things you want to find in a very nice intuitive way? And how do you do compliance, GDPR and also how do you think about some deep analytics on your data? So, we also wanna extend our Control Shift not to just manage the data on our platform, but also to manage data across different platforms. So, those are the kind of things we're thinking about as a future. >> Excellent stuff. Sazzala Reddy, CTO of Datrium, thanks so much for talking with us about AutoMatrix, Control Shift and the direction that you're taking with this. Very, very interesting new vision about how data and business can more easily be brought together. You know, I'll tell you what, let's take a look at a demo. Hi and welcome back to another CUBE Conversation. Once again, I'm Peter Burris and one of the biggest challenges that every user faces is how do they get more out of their technology suppliers, especially during periods of significant transformation. So, to have that conversation, we've got Bryan Bond who is Director of IT Infrastructure at eMeter, A Siemens Business. Bryan, welcome to theCUBE. >> Thanks for having me. >> So, tell us a little bit about eMeter and what you do there. >> So, eMeter is a developer and supplier of smart grid infrastructure software for enterprise level clients, utilities, water, power, energy. My team is charged with managing infrastructure for that entire business units, everything from dev tests, QA and sales. >> Well, the intelligent infrastructure as it pertains to the electronic grid, that's not a small set of applications, a small set of use cases. What kinds of pressure is that putting on your IT infrastructure? >> A lot of it is the typical pressures that you would see with do more with less, do more faster. But a lot of it is wrapped around our customers and our other end users in needing more storage, needing more app performance and needing things delivered faster. On a daily basis, things change and keeping up with the Jones' gets harder and harder to do as time moves on. >> So, as you think about Datrium's AutoMatrix, how is it creating value for you today? Give us a peek into what it's doing to alleviate some of these scaling and other sorts of pressures. >> So, the first thing it does is it does allow us to do a lot more with less. We get two times the performance, five times the capacity and we spend zero time managing our storage infrastructure. And when I say zero time, I mean zero time. We do not manage storage anymore with the Datrium product. We can deploy things faster, we can recover things faster. Our RTO and our RPO matrix is down to seconds instead of minutes or hours. And those types of things really allow us to provide a much better level of service to our customers. >> And it's especially for infrastructure like the electronic grid, it's good to hear that the RTO, RPO is getting as close to zero as possible, but that's the baseline today. Look out and as you envision where the needs are of these technologies are going for improving protection, consolidating, converging data services and overall providing a better experience for how a business uses data, how do you anticipate that you're going to evolve your use of AutoMatrix and relate it to Datrium technologies? >> Well, we fully intend to expand our use of the existing piece that we have, but then this new AutoMatrix piece is going to help us not with just deployments, but it's also gonna help us with compliance testing, data recovery, disaster recovery and also being able to deploy into any type of cloud or any type of location without having to change what we do in the back end, being able to use one tool across the entire set of the infrastructure that we're using. >> So, what about the tool set, you're using the whole thing consistently, but what about the tool set went in easiest for you within your shop? >> Installing the infrastructure pieces themselves in its entirety were very, very easy. So, putting that into what we had already and where we were headed was very, very simple. We were able to do that on the fly in production and not have to do a whole lot of changes with the environments that we were doing at the time. The operational pieces within the DVX, which is the storage part of the platform, were seamless as far as vCenter and other tools that we were using went and allowed us to just extend what we were doing already and be able to just apply that as we went forward. And we immediately found that again, we just didn't manage storage anymore and that wasn't something we were intending and that made our ROI just go through the roof. >> So, it sounds like time value for the platform was very, very quick and also it fit into your overall operational practices. You didn't have to do a whole bunch of unnatural acts to get there. >> Right, we did not have to change a lot of policies, we did not have to change a lot of procedures. A lot of times, we just shortened them, we took a few steps out in a lot of cases. >> So, how is it changing, being able to do things like that, changing your conversation with your communities that you're serving as they ask for more capabilities? >> First off, it's making me say no a lot less and that makes them very, very happy. The answer usually is less and the answer to the question of how long will it take changes from oh, we can get that done in a couple of days or oh, we can get that done in a couple hours to I did that while I was sitting here in the meeting with you and it's been handled and you're off to the races. >> So, it sounds like you're placing a pretty big bet on Datrium. What's it like working with them as a company? >> It's been a great experience. From the start in the initial piece of talking to them and going through the POC process, they were very helpful, very knowledgeable SCs and since then, they've been very, very helpful in allowing us to tell them what our needs are rather than them telling us what our needs are and going through and working through the new processes and the new procedures within our own environments. They've been very instrumental in performance testing and deployment testing with things that a lot of other storage providers didn't have any interest in talking with us about, so they've been very, very helpful with that and very, very knowledgeable. The people that are there are actually really smart, which is not surprising, but the fact that they can relay that into solutions to what my actual problems are and give me something that I can push forward onto my business and have a positive impact from day one has been absolutely without question one of the better things. >> Well, that's always one of the biggest challenge when working with a company that's just getting going is how do you get the smarts of that organization into the business outcomes and really succeed. It sounds like it's working well. >> Absolutely. >> All right, Bryan Bond, Director of IT Infrastructure at eMeter, A Siemens Business. Thanks again for being on theCUBE. >> Bryan: It's been great. >> And once again, this has been a CUBE Conversation. Now, what we'd like to do is don't forget this is your opportunity to participate in the crowd chat immediately after this video ends and let's hear your thoughts. What's important in your world as you think about new classes of data platforms, new roles of data, new approaches to taking greater advantage of the data assets that are differentiating your business. Have those conversations, make those comments, ask those questions. We're here to help. Once again, Peter Burris, let's crowd chat. (light music)

>> Live from San Francisco. It's theCUBE covering Google Cloud Next 2018. Brought to you by Google Cloud and its ecosystem partners. (electronic music) >> Hey, welcome back everyone. Live here in San Francisco it's theCUBE's coverage of Google Cloud and their big conference Google Next #GoogleNext18. I'm John Furrier, Dave Vellante. Our next guest is Adam Seligman, Vice President of Developer Relations at Google. Man, making it all happen, keeping the trains on time, keeping everyone motivated, welcome to theCUBE. Thanks for joining us. >> Thanks, glad to be here. >> So, first of all, take a step back, what is your job at Developer Relations? Are you herding cats, are you feeding them great code, are you overseeing a big team? Google's been very big on open-source, you've been part of the code program going back many many years. Google's always been a steward of open-source and developers are just devouring open-source in a big way right now. What's your job? >> I look after Developer Relations. There's around 20, 22 million developers in the world and we want to make every single one of them successful and build cool things, learn new technology, be part of community. That's something that's super important. I try to rally all of Google to sort of stand for developers. >> One of the big trends we're seeing now at open-source is that it's becoming such a good norm. I remember the days when I was getting into the business back in the late '80s, early '90s. Open-source, we'd kind of steal some code here and it kind of was radical. It's so normal now, and you start to see the clean, upstream etiquette, upstream projects, everyone's contributing, co-creating for a common good, monetizing downstream has been really well defined. There's some examples of probably where that could be better but for the most part, I think people are generally seeing a positive contribution. That's a community dynamic. How do you go to the next level for developers? Because this has turned out to be quite an opportunity to one: learn, meet new people, learn new skills and take advantage of some new technologies. How do you foster that community? What are you guys doing? Because no-one wants vendors to put their fingers in these upstream projects (laughs) but they're super important, they're all participating. What's the formula? How is that evolving? How do you see that? >> Google's been an open-source for maybe 20 years. Some big contributions early days, things like GCC, foundational compiler technology. And we have whole businesses that build around open-source, Chrome on the Web, Android for mobile, and now we see kubernetes in cloud and TensorFlow and AI and new things like Knative and Istio, so I think there's a course there where open-source can really shape whole ecosystems and create a lot of opportunity and a lot of innovation. And I think the challenge in all that is to do it in a really healthy, positive, community-centric way. And I think that's some real learning we've had in the last couple of years, is great leaders like Sarah Novotny have really helped guide us and her interface with open-source communities and foster the right kind of community interactions, and that's a big focus. We're trying to bring that here also. >> So, you had a keynote coming up, I know you got a hard stop and we want to try and get as many questions as we can. But I want to ask you, what are you going to be talking about at your keynote, what's the topic? 'Cos this is a, I won't say coming-out party for Google Cloud in particular, but clearly setting a couple stakes in the ground on what's going on. Enterprise focus, checking the boxes, table stakes are being met. And real tech: high performance, large-scale, really a good developer environment. What are you going to talk about at the keynote? >> Well, I think customers like HSBC and Target and others are coming to us, not for table stakes, they're coming to us for what's next. They're coming to us for massive-scale kubernetes, they're coming to us for AI. So, I think that the introductions we've had so far, things like the Cloud Services Platform, Istio 1.0, Knative, it really shows a bright future of service and AI-driven applications. What we're going to talk in the developer keynote, tomorrow, in day three, is really three themes: innovation, openness and open-source, and then that community theme that we were just talking about. And one area of innovation that we're going to talk about is Melody Meckfessel, who I think you talked to earlier, is going to talk about our approach to Cloud Build and integrated toolchains. We have a lot of technology we're going to open up in the DevOps space. But it's really a mentality, and this is the thing that I think is really needed coming to Google, is it's not just about pushing code down the waterfall to production, it's about building services for users and building services that the developers consume. And really flowing from code right out to running services, and then when you're done, the service is a turn on for everybody, you start routing traffic to it, you run canaries. So, it's a big step-change in how we think about continuous delivery and DevOps, we really want to land that in the keynote tomorrow. >> So I got to give some props to my partner, John Furrier, in 2010, John, you said, "Data is the new development kit." It was a while ago, and it's turned out, in my view anyway, to be true, but, Adam, it's also changed the profile of the developer. Data hackers, statisticians, mathematicians, artists. And so it's changed the way in which we think about a developer. I wonder, if you could talk about that, in terms of, how that's changed Developer Relations? >> Yufeng Guo is going to do a section AI in the keynote and he does these videos on YouTube that literally millions of people watch about how to get started on machine learning. And he's got a great line in there, which I think is attributed to him, that says, "AI is programming with data." And so I think we're in a world where all this data of user interactions and event streams and interactive things and mobile applications, we now have a lot of data to program the world on. And I think it's an incredible opportunity for developers. But the flip side, if we just restrict it to a couple thousand data scientists, it doesn't open up the world to everyone. So I think beyond that 20 million, what are the next 20 million we could pull in with AutoML? The next 20 million that can do SQL queries and can use BigQuery and do ML in BigQuery? So that's the vision of opening it up to more people, more developers. >> And the democratization of software, I mean, it's interesting, that's my background in software engineering, computer science, in the '80s you were called software engineering. Then it became software developer, then it became a software hacker. Now we're hearing words like software artisan. I interviewed Aparna, she said, "You don't need three PhDs, three degrees "in computer science, to do development anymore." The aperture's widening, big-time, because now craft is coming back to development. Because a lot of these abstractions, both on the business and tech side, are enabling different personas to come in. >> It's not legacy development anymore, it's heritage development, right?. (John laughs) I love that developers have the freedom to define their own titles and define their own tools they want to work with, and do a mix of the old and the new, and mix it up. So I think it's really important that we're not too narrow in how we define people and you don't have to be this tall to ride the ride, we really welcome everybody in to be a part of the community and if your entrance to ML is AutoML, but then eventually you graduate to TPUs, that's just fantastic. >> And how about crypto developers? They've exploded with innovation, what do you see in there? >> I could just go back to security, I think every company is really wrestling with security right now. How do they get two-factor everywhere? How do they stop phishing? How do they keep their employees safe? How do they have shielded VMs at every level of security? And it's a challenge to get developers to think about security sometimes. It's the operators that have to live with it, and so understanding your dependencies, way back up with developers are like, "Oh, I'll just use this library, "and I'll just use this library." How do you ensure you're using trusted dependencies back there, you don't have vulnerabilities you're introducing by taking dependencies in other codes. So I think there's a lot of education and best practice to share with developers to get them to care about security. >> My final question, I know you got to go. I just want to get it out there, years ago, when David and I used to hear on theCUBE, people come on, "We want to win the developers," no, they're not winnable. You don't win developers, you earn trust and you earn relationships and they might work with you and enjoy the services that they might provide to them. So I always kind of used to poo-poo that. But now with the Cloud you're seeing again, more range with developers. So, how do you keep developers happy? That might be a better question, because in order to earn and have a relationship with people who are going to be contributing IP and building IP, how do you keep harmonious relations? How do you keep people happy if you have things, like technical debt bothers people and people are like, "Oh, technical debt," you know, shipping codes, times. How do you think about that because keeping people happy is a broad answer, but in general, what's your view on keeping developers happy, harmonious, loving, working together, doing the things they love to do? >> It's a little different at Google, it's an interesting place, because there's never an "us and them" with developers, this is a company with tens of thousands of engineers on staff, most of the senior leadership team have an engineering background. So it's more like we live in the community of developers, my engineers are all over the world, living in developer communities. And so I think it really does matter how we show up and how we interact. But we sort of live it every day. So I don't think we have a hill to climb, so much as get to developers, I think we just have to have a really clear narrative, and then a really keen ear to listen to what they need and that's what I'm trying to orient them around. >> Listening, I think that's a great answer, listening. "What do you want?" you know, "What's important to you?" And then you have that perspective yourselves. Yeah, I mean, we're sort of a developer-centric company and I think the important thing is we put them at the center of everything we do, I use the word with my team, it's empathy. We have empathy for developers, you know, they have great jobs, great opportunities, but also great challenges, and as humans, can't we have empathy for them. >> I was hosting a panel one time, a night event, it was all out of fun, bunch of nerds on there were talking tech, getting on the hood, talking developers, all this stuff, range of questions, and one guy introduced himself as the, "I'm the CTO, I'm the Chief Toy Officer." (Adam laughs) Because we play with technology then we turn it into product. And you guys brought a lot of toys out here with Google, all this open-source. >> And then if we can amplify that for all the amazing talent that's in the world, at Google I/O, we host the developers' student clubs from Indonesia, and these young Indonesian women are teaching other college kids how to do android development. So, if we could bring that kind of magic to all of our assets, to the Cloud assets, I think there's this amazing, receptive community out there that could give us a bunch of whole new ideas that we don't just get in South of Market, San Francisco. >> It's inspiring to see people build things with open-source, pay it forward, contribute upstream, be part of a community, this is what it's all about, Developer Relations. Congratulations, thanks for coming on theCUBE. >> Thank you, so glad to be here, thanks guys! >> This is theCUBE paying it forward with content here from Google Next, all out in the open, co-creating with Google, Google's team, Google's customers, the best engineers, the best talent here at Google Cloud, I'm with theCUBE. I'm John Furrier, Dave Vellante, thanks for watching. Stay with us, more coverage after this short break. (electronic music)

>> Announcer: Live from Las Vegas, it's the Cube. Covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome to day three of Knowledge18. You're watching the Cube, the leader in live tech coverage. Day three is when ServiceNow brings together its audience and talks about its platform, the creators, the developers, the doers get together in the room. Jeff Frick and I, my co-host, we've seen this show now, Jeff, for many, many years. I joked on Twitter today, it's not often you see a full room and this room was packed on day three. Unless Larry Ellison is speaking. Well, Larry Ellison is not here, but Pat Casey is. He's the Senior Vice President of DevOps at ServiceNow and a Cube alum, Pat, great to see you again. >> Absolutely, just glad to be back. >> So, my head is exploding. With all the innovation that's comin' out. I feel like I'm at a AWS re:Invent with Andy Jassy up on stage with all these features that are coming out. But wow, you guys are on it. And part of that is because of the platform. You're able to put out new features, but how's the week going? >> So far it's been great. But you're sort of right, we are super proud of this year. I think there's more new stuff that's valuable for our customers coming out this year than probably the three years prior to this. I mean you got the chat bot designer, and you got some great application innovation, you got Flow Designer, you've got the entire integration suite coming online, and then in addition to that you've got a whole new mobile experience coming out. Just all stuff that our customers can touch. You can go downstairs and see all that and they can get their hands on it. Super exciting. >> So consistent too with the messaging. We've been coming here, I this is our sixth year, with kind of the low-code and no-code vision that Fred had way at the beginning. To let lots of people build great workflows and then to start taking some of these crazy new applications like chat bots and integration platform, pretty innovative. >> Yeah, I think it's a mindset when you get down to it. I mean we, the weird failure mode of technology is technology tends to get built by by technologists. And I do this for a living. There's a failure mode where you design the tool you want to use. And those tend to be programmer tools 'cause they tend to get designed by programmers. It does take an extra mental shift to say no, my user is not me. My user is a different person. I want to build the tool that they want to use. And that sort of user empathy, you know Fred had that in spades. That was his huge, huge, huge strength. Among other things. One of his huge strengths. It's something that we're really trying to keep foreground in the company. And you see that in some of the new products we released as well. It's really aimed at our customers not at our developers. >> The other thing I think that's been consistent in all the interviews we've done, and John talked on the day one keynote one of his kind of three keys to success was try to stay with out of the box as much as you can as a rule, and we've had all the GMs of the various application stacks that you guys have, they've all talked consistently we really try to drive, even as a group our specific requests back into development on the platform level so we can all leverage it. So even though then the vertical applications you guys are building, it's still this drive towards leverage the common platform. >> Yeah, absolutely. And there is, what's the word I'm looking for? There's a lot of value in using the product the way it was shipped. For easiest thing is when it advances or when we ship you new features you can just turn 'em on, and it doesn't conflict with anything else you got going in there. There's always an element of, you know, this is enterprise software. Every customer's a little bit different. GE does not work the same way as Bank of America. So you probably never get away entirely from configuring, but doing the minimum that you can get away with, the minimum that'll let you put your business-specific needs in there, and being really sure of it, you need to do it, it's the right approach to take. The failure mode of technologists, the other one, is we like writing technology. So give me a platform and I'm going to just write stuff. Applying that only when it makes sense to the business is where you really need to be. Especially in this day and age. >> Well I wanted to ask you about that 'cause you guys talk about many applications one platform. But you used to be one platform one app. >> Pat: Yep. >> So as you have more, and more, and more apps, how are you finding it regarding prioritization of features, and capabilities? I imagine the GMs like any company are saying, hey, this is a priority. >> Sure. >> And because you have a platform there's I'm sure a lot more overlap than if you're a stovepipe development organization. But nonetheless you still got to prioritize. Maybe talk about that a little bit. >> Sure, you end up with two different levels of it though. At one level, you tend to want to pick businesses to go into, which you're aligned with the technology stack you have. I don't think we're going to go into video streaming business. It's a good business, but it's not our business. >> Too bad, we could use some of that actually. >> Well, maybe next year. (laughs) But when you get down to it we mostly write enterprise business apps. So HR is an enterprise business app, CSM, SecOps, ITSM, they're all kind of the same general application area. So we don't tend to have something which is totally out to lunch. But you're right in the sense that A, what's important to CSM might be less important to ITSM. And so we do prioritize. And we prioritize partly based on what the perceived benefit across the product line is. If something that a particular BU wants that five other BUs are going to benefit from that's pretty valuable. If only them, not so much. And part of it too is based on how big the BUs are. You know if you're an emerging product line you probably get few less features than like Feryl Huff. Like she has a very big product line. Or Pabla, he has a very big product line. But there's also an over-investment in the emerging stuff. Because you have to invest to build the product lines out. >> The other thing I think is you guys have been such a great opportunity is I just go back to those early Fred interviews with the copy room and the color paper 'cause nobody knows what that is anymore. >> Pat: Yep. >> But workflow just by its very nature lends itself so much to leveraging, AI, and ML, so you've already kind of approached it while trying to make work easier with these great workflow tools, but what an opportunity now to apply AI and machine learning to those things over time. So I don't even have to write the rules and even a big chunk of that workflow that I built will eventually go away for me actually having to interact with it. >> Yeah, there's a second layer to it too, which I'll call out. The workflows between businesses are different. But we have the advantage that we have the data for each of the businesses. So we can train AI on this is the way this particular workflow works at General Electric and use that bot at GE and train a different bot at maybe at Siemens. You know it's still a big industrial firm. It's a different way of doing it. That gives us a really big advantage over people who commingle the data together. Because of our architecture, we can treat every customer uniquely and we can train the automation for the unique workflows for that particular customer. It gives a much more accurate result. >> So thinking about, staying on the theme of machine intelligence for a moment, you're not a household name in the world of AI, so you've done some acquisitions and-- >> Pat: Yep. >> But it's really becoming a fundamental part of your next wave of innovation. As a technologist, and you look out at the landscape, you obviously you see Google, Apple, Facebook, IBM, with Watson, et cetera, et cetera, as sort of the perceived leaders, do you guys aspire to be at that level? Do you need to be? What's the philosophy and strategy with regard to implementing AI in the road map? >> Well if you cast your eyes forward to where we think the future's going to be, I do think there are going to be certain core AI services that they're going to call their volume plays. You need a lot of engineers, a lot of resources, a lot of time to execute them. Really good voice-to-text is an example. And that's getting pretty good. It's almost solved at this point. A general case conversational agent, not solved yet. Even the stuff you see at Google I/O, it's very specialized. It does one thing really well and it's a great demo, but ask it about Russian history, no idea what to talk about. Whereas, maybe you don't know a lot about Russian history, you as a human would at least have something interesting to say. We expect that we will be leveraging other people's core AI services for a lot of stuff out there. Voice-to-text is a good example. There may well be some language parsing that we can do out there. There may be other things we never even thought of. Maybe stuff that'll read text for you and give you back summaries. Those are the kinds of things that we probably won't implement internally. Where you never know, but that's my guess, where you look at where we think we need to write our own code or own our own IP, it's where the domain is specific to our customers. So when I talked about General Electric having a specific workflow, I need to be able to train something specific for that. And if you look at some other things like language processing, there's a grammar problem. Which is a fancy way of saying that the words that you use describing a Cube show are different than the words that I would use describing a trade show. So if I teach a bot to talk about the Cube, it can't talk about trade shows. If you're Amazon, you train your bot to talk in generic language. When you want to actually speak in domain-specific language, it gets a lot harder. It's not good at talking about your show. We think we're going to have value to provide domain-specific language for our customers' individualized domains. I think that's a big investment. >> But you don't have to do it all as well. We saw two actually interesting use cases talking to some of your customers this week. One was the hospital in Australia, I don't know if you're familiar with this, where they're using Alexa as the interface, and everything goes into the ServiceNow platform for the nurses. >> Yep. >> And so that's not really your AI, it's kind of Amazon's AI, that's fine. And the other was Siemens taking some of your data and then doing some stuff in Azure and Watson, although the Watson piece was, my take away was it was kind of a fail, so there's some work to be done there, but customers are going to use different technologies. >> Pat: Oh, they will. >> You have to pick your spots. >> You know we're, as a vendor, we're pretty customer-centric. We love it when you use our technology and we think it's awesome, otherwise we wouldn't sell it. But fundamentally we don't expect to be the only person in the universe. And we're also not, like you've seen us with our chat bot, our chat bot, you can use somebody else's chat client. You can use Slack, you can use Teams, you can use our client, we can use Jabber. It's great. If you were a customer and want to use it, use it. Same thing on the AI front. Even if you look at our chat bot right now, there's the ability to plug in third-party AIs for certain things even today. You can plug it in for language processing. I think out of box is configured for Google, but you can use Amazon, you can use Microsoft if you want to. And it'll parse your language for you at certain steps in there. We're pretty open to partnering on that stuff. >> But you're also adding value on top of those platforms, and that's the key point, right? >> The operating model we have is we want it to be transparent to our customers as to what's going on in the back end. We will make their life easy. And if we're going to make their life easy by behind the scenes, integrating somebody else's technology in there, that's what we're going to do. And for things like language processing, our customers never need to know about that. We know. And the customers might care if they asked because we're not hiding it. But we're not going to make them do that integration. We're going to do it for them, and just they click to turn it on. >> Pat, I want to shift gears a little bit in terms of the human factors point of all this. I laugh, I have an Alexa at home, I have a Google at home, and they send me emails suggesting ways that I should interact with these things that I've never thought of. So as you see kind of an increase in chat bots and you see it increase in things like voice-to-text and these kind of automated systems in the background, how are you finding people's adoption of it? Do they get it? Do the younger folks just get it automatically? Are you able to bury it such where it's just served up without much thought in their proc, 'cause it's really the behavior thing I think's probably a bigger challenge than the technology. >> It is and frankly it's varied by domain. If you look at something like Voice that's getting pretty ubiquitous in the home, it's not that common in a business world. And partly there frankly is just you've got a background noise problem. Engineering-wise, crowded office, someone's going to say Alexa and like nobody even knows what they're talking about. >> Jeff: And then 50 of 'em all-- >> Exactly. There's ways to solve that, but this is actual challenge. >> Right. >> If you look at how people like to interact with technologies, I would argue we've already gone through a paradigm shift that's generational. My generation by default is I get out a laptop. If you're a millennial your default is you get out your phone. You will go to a laptop and the same says I will go to a phone, but that's your default. You see the same thing with how you want to interact. Chat is a very natural thing on the phone. It's something you might do on a full screen, but it's a less common. So you're definitely seeing people shifting over to chat as their preferred interaction paradigm especially as they move onto the phones. Nobody wants to fill out a form on a phone. It's miserable. >> Jeff: Right. >> I wonder if we could, so when Jeff and I have Fred on, we always ask him to break out his telescope. So as the resident technologist, we're going to ask you. And I'm going to ask a bunch of open-ended questions and you can pick whatever ones you want to answer, so the questions are, how far can we take machine intelligence and how far should we take machine intelligence? What are the things that machines can do that humans really can't and vice versa? How will humans and machines come together in the future? >> That's a broad question. I'll say right now that AI is probably a little over-marketed. In that you can build really awesome demos that make it seem like it's thinking. But we're a lot further away from an actual thinking machine, which is aware of itself than I think it would seem from the demos. My kids think Alexa's alive, but my son's nine, right? There's no actual Alexa at the end of it. I doubt that one's going to get solved in my lifetime. I think what we're going to get is a lot better at faking it. So there's the classical the Turing test. The Turing test doesn't require that you be self-aware. The Turing test says that my AI passes the Turing test if you can't tell the difference. And you can do that by faking it really well. So I do think there's going to be a big push there. First level you're seeing it is really in the voice-to-text and the voice assistance. And you're seeing it move from the Alexas into the call centers into the customer service into a lot of those rote interactions. When it's positive it's usually replacing one of those horrible telephone mazes that everybody hates. It gets replaced by a voice assist, and as a customer you're like that is better. My life is better. When it's negative, it might replace a human with a not-so-good chat. The good news on that front is our society seems to have a pretty good immune system on that. When companies have tried to roll out less good experiences that are based on less good AI, we tend to rebel, and go no, no, we don't want that. And so I haven't seen that been all that successful. You could imagine a model where people were like, I'm going to roll out something that's worse but cheaper. And I haven't seen that happening. Usually when the AI rolls out it's doing it to be better at something for the consumer perspective. >> That's great. I mean we were talking earlier, it's very hard to predict. >> Pat: Of course. >> I mean who would have predicted that Alexa would have emerged as a leader in NLP or that, and we said this yesterday, that the images of cats on the internet would lead to facial recognition. >> I think Alexa is one example though. The thing I think's even more amazing is the Comcast Voice Remote. Because I used to be in that business. I'm like, how could you ever have a voice remote while you're watching a TV and watching a movie with the sound interaction? And the fact that now they've got the integration as a real nice consumer experience with YouTube and Netflix, if I want to watch a show, and I don't know where it is, HBO, Netflix, Comcast, YouTube, I just tell that Comcast remote find me Chris Rock the Tamborine man was his latest one, and boom there it comes. >> There's a school of thought out there, which is actually pretty widespread that feels like the voice technologies have actually been a bit of a fail from a pure technologies standpoint. In that for all the energy that we've spent on them, they're sort of stuck as a niche application. There's like Alexa, my kids talk to Alexa at home, you can talk to Siri, but when these technologies were coming online, I think we thought that they would replace hard keyboard interactions to a greater degree than they have. I think there's actually a bit of a learning in there that people are not as, we don't mandatorily, I'm not sure if that's a real word, but we don't need to go oral. There's actually a need for non-oral interfaces. And I do think that's a big learning for a lot of the technology is that there's a variety of interface paradigms that actual humans want to use, and forcing people into any one of them is just not the right approach. You have to, right now I want to talk, tomorrow I want to text, I might want to make hand gestures another time. You're mostly a visual media, obviously there's talking too, but it's not radio, right? >> You're absolutely right. That's a great point because when you're on a plane, you don't want to be interacting in a voice. And other times that there's background noise that will screw up the voice reactions, but clearly there's been a lot of work in Silicon Valley and other places on a different interface and it needs to be there. I don't know if neural will happen in our lifetime. I wanted to give you some props on the DevOps announcement that you sort of pre-announced. >> We did. >> It's, you know CJ looked like he was a little upset there. Was that supposed to be his announcement? >> In my version of the script, I announced it and he commented on my announcement. >> It's your baby, come on. So I love the way you kind of laid out the DevOps and kind of DevOps 101 for the audience. Bringing together the plan, dev, test, deploy, and operate. And explaining the DevOps problem. You really didn't go into the dev versus the ops, throwing it over the wall, but people I think generally understand that. But you announced solving a different problem. 500 DevOps tools out there and it gets confusing. We've talked to a bunch of customers about that. They're super excited to get that capability. >> Well, we're super, it's one of those cases where you have an epiphany, 'cause we solved it internally. >> Dave: Right. >> And we just ran it for like three years, and we kept hearing customers say, hey, what are you guys going to do about DevOps? And we're never like quite sure what they mean, 'cause you're like, well what do you mean? Do you want like a planning tool? And then probably about a year ago we sort of had this epiphany of, oh, our customers have exactly the same problem we do. Duh. And so from that it kind of led us to go down the product road of how can we build this kind of management layer? But if you look across our customer base and the industry, DevOps is almost a rebellion. It's a rebellion against the waterfall development model which has dominated things. It's a rebellion against that centralized control. And in a sense it's good because there's a lot of silliness that comes out of those formal development methodologies. Slow everybody down, stupid bureaucracy in there. But when you apply it in an enterprise, okay some of the stuff in there, you actually did need that. And you kind of throw the baby out with the bathwater. So adding that kind of enterprise DevOps layer back in, you still do get that speed. Your developers get to iterate, you get the automated tests, you get the operating model, but you still don't lose those kind of key things you need at the top enterprise levels. >> And most of the customers we've talked to this week have straight up said, look, we do waterfall for certain things, and we're not going to stop doing waterfall, but some of the new cool stuff, you know. (laughs) >> Well if you look at us, it's at the, if you take the microscope far enough away from ServiceNow, we're waterfall in that every six months we release. >> Dave: Yeah, right. >> But if you're an engineer, we're iterating in 24-hour cycles for you. 24-hour cycles, two-week sprints. It's a very different model when you're in the trenches than from the customer perspective. >> And then I think that's the more important part of the DevOps story. Again, there's the technology and the execution detail which you outlined, but it's really more the attitudinal way that you approach problems. We don't try to solve the big problems. We try to keep moving down the road, moving down the road. We have a vision of where we want to get, but let's just keep moving down the road, moving down the road. So it's a very, like you said, cumbersome MRD and PRD and all those kind of classic things that were just too slow for 2018. >> Nobody goes into technology to do paperwork. You go into technology to build things to create, it's a creative outlet. So the more time you can spend doing that, and the less time you're spending on overhead, the happier you're going to be. And if you fundamentally like doing administration, you should move into management. That's great. That's the right job for you. But if you're a hands on the keyboard engineer, you probably want to have your hands on the keyboard, engineering. That's what you do. >> Let's leave on a last thought around the platform. I mentioned Andy Jassy before and AWS. He talks about the flywheel effect. Clearly we're seeing the power of the platform and it feels like there's the developer analog to operating leverage. And that flywheel effect going from your perspective. What can we expect going forward? >> Well, I mean for us there's two parallel big investment vectors. One is clearly we want to make the platform better for our apps. And you asked earlier about how do we prioritize from our various BUs, and that is driving platform enhancements. But the second layer is, this is the platform our customers are using to automate their entire workflow across their whole organization. So there's a series of stuff we're doing there to make that easier for them. In a lot of cases, less about new capabilities. You look at a lot of our investments, it's more about taking something that previously was hard, but possible, and making it easier and still possible. And in doing that, that's been my experience, is Fred Luddy's experience, the easier you can make something, the more successful people will be with it. And Fred had an insight that you could almost over-simplify it sometimes. You could take something which had 10 features and was hard to use, and replace with something that had seven features and was easy to use, everyone would be super happy. At some level, that's the iPhone story, right? I could do more on my Blackberry, it just took me an hour of reading the documentation to figure out how. >> Both: Right, right. >> But I still miss the little side wheel. (laughs) >> Love that side wheel. All right, Pat, listen thanks very much for coming. We are humbled by your humility. You are like a rock star in this community, and congratulations on all this success and really thanks for coming back on the Cube. >> Thank you very much. It's been a pleasure meeting you guys again. >> All right, great. Okay, keep it right there, everybody. We'll be back with our next guest. You're watching the Cube live from ServiceNow Knowledge K18, #know18. We'll be right back. (upbeat music)