(upbeat music) >> We're back at the ARIA in Las Vegas you're watching theCUBE's coverage of Veeamon 2022 live in person, but there's a big hybrid event going on. Close to 40,000 people watching online. This is the CEO segment. The newly minted CEO Anand Eswaran is here. And it's great to see you. Thanks for coming on. First time on theCUBE. >> Yeah, first time on theCUBE, excited to be here. Newly minted, those words, I haven't heard those for a long time. But thank you for the warm introduction, Dave. >> So why Veeam? What did you see that attracted you to Veeam? You have a great career, awesome resume. Why Veeam? >> A lot of different things. You know, it started with when I spent a good bit of time... I spent months with, you know, Insight, with Bill Largent who is now the chair of the board. And for me a few things, one, it started with the company culture. I absolutely loved... I spent time with our engineering team that it's an innovation-focused culture. It's an engineering-focused culture, which is so critical to any software company. And so that was the first place. And I spent a good bit of time with customers, reading, research, you know, brilliant products, always innovating. You know, even though it's a category you would think is fairly mature. I mean, when Veeam for example, did instant recovery. I mean, that was extreme innovation. And so that was the first thing which was appealing. The second thing was, you know, yes, we've reached a billion, but it still has that, you know, feel of a start up. It still has that feel of a... Jeff Bezos says this best, "A day one culture." Which is super critical, you know, we scale but you don't want to lose your soul and what made you special in the first place. And then you come down to the rest of the stuff, it's an execution machine. You know, it's an absolutely interesting category, especially in the day and the world we live in right now. You know, the proliferation of bad actors, security, backup, recovery, you know, everything you... Ransomware is starting to become you know, a meaningful threat to every company. So many different things coming together. This category is an interesting place. But that's not all, I feel that we are going to see this category evolve and shape very differently. You're going to see adjacencies coming and you're going to see in a couple of years or three years you're not going to just look at this and say, "Hey, it's backup and recovery." And so it's an opportunity to shape what is going to be a very important inflection point in this whole space. So a whole bunch of things. Excited about it. >> So flip question, why Anand? What did Insight see and the board see? What do you see as your key skills that they wanted here? Go after that opportunity- >> You should also get insight on this man. And you should ask them this question. I know Peter and Sokolov (laughs) >> So, you know, I don't know... I'll tell you where I think there's relevant experience is if I look at the future of Veeam. I think the first thing is we've got to think through what the next evolution of Veeam is. You know, there's a ton of work to do even in the path we are on, on data protection. And the team is absolutely brilliant at that. But how do you start to think ahead? How do you think about data management? How do you think about, you know, where are the adjacencies and how does it... How do you shape and reshape the category? You know, and I have some experiences in that. As I look at growth, Veeam has done a phenomenal job you know, 35,000 partners, an execution machine. I mean, just last year we grew ARR, you know, 27% we are sustaining that growth. But as I look ahead, you know there's huge opportunities to further accelerate our share in the enterprise to actually go work with creating multiple layers of partnerships beyond the very successful partnerships we already have. You know, how do you start to get GSIs in the mix? How do you start to get MSPs in the mix? How do you start to actually get to being a core part of the portfolio and platform of our primary storage partners, HPE, Pure Storage and so on. So reinvigorating and creating a multidimensional partnership strategy is key as well. And then just my experience in, you know I ran the enterprise for Microsoft and so those sort of experiences sort of are very relevant to our next step of the journey as well. And finally, you know I think the one thing which matters most for me and yeah, you realize... Again, I think we've forgotten what it means to have a microphone on. But culture, you know, I spent a lot of time in every company I've worked in, in contributing to the culture of what shapes and you know how do you create a purpose-led company and how do you get on that path? Which is a very, very important conversation inside Veeam. you know, and we already do that... You know, there's a huge focus on purpose. There's a huge focus on diversity. There's a huge focus on inclusion, but you know, the cultural aspect of Veeam attracted me to it. And I think my work and my passion for it attracted me to Veeam as well. So just a few of those things. >> Yeah, you speak from the heart, you can sense that. Dave and I were talking with Zias about platform versus product. Now you've got some experience with platforms, obviously, Microsoft, you know the amazing platform. RingCentral Zias brought up. And then I brought up HP, which actually never could figure out its software platform. So you've seen some successes. You've seen some, you know, couldn't ever get there. Do you see Veeam as a platform company? >> You know, the way I look at it is this. I mean, I may actually not answer your question directly but I'll answer the question. >> Dave: Okay. >> Which is, if you look at the biggest successes in the industry, call it Microsoft, Adobe now- >> Dave: Sure. >> Salesforce, eventually the path from a high growth startup to scale is platform and partners. That is the key. >> Dave: Ecosystem- >> So yeah. Platform and the ecosystem. So it all comes together. And so, yes, I mean, I think we already do that. I mean, we have a singular platform today for the multiple workloads we protect from, you know physical to cloud, to Kubernetes to the hybrid architectures the ability to actually, you know restore your data into any cloud, you know, back up from AWS restore into Azure or a physical data center. So we already have a robust platform in place but the scale or the growth from where we are a billion to the next set of milestones 2, 3, 5, 10 is going to be an absolute maturity and amp of platform partnerships ecosystem. >> That's a high wire act. When you talk about platform and scaling, you know, think about moving forward, when you have pressure to grow, often the easiest thing to grow is to acquire and add adjacencies that might not be as core to your core value proposition as they could be. How do you navigate that as you move forward in a world where... Look, Veeam was founded in an age when it was all about meantime between failure, recovery point, recovery time objectives. Now the big concern is malicious actors. So Veeam has been able to navigate that transition very well so far, but how do you do that? How do you balance that moving forward? This idea of platform is a desirous state to be in but you don't want to be a fake platform where you just glue a bunch of things on. >> It all comes down to thinking through where we see the world going from this point in time. How do you see technology evolving? How do you see the outside's, you know influences evolving. And when I say influences, it's, you know, just a euphemism for all the bad actors we expect to see getting even more active. So, you know, the way I think about it is either platform or acquisitions are not things you do piecemeal or point in time. It all needs to accrue to a larger strategy of how you create the ability for all of your customers to own protect, secure, you know their data and eventually create intelligence from it so that they can actually be proactive about it. So that, you know, if that's the thing, you know, our ambition is starting to become how do we sort of secure the world's data and help companies create intelligence from it so they can be proactive about it? You know, everything else sort of accrues from there the platform we evolve from the platform we already have, you know, stems from it. The acquisitions we may do, will do evolves from it. It all are... You know, its pieces coming together to the overall puzzle framework we've already created. >> Yeah. I have so many questions for you. And I want to get into a little bit of your philosophy, but before we do it, I want touch on the TAM a little bit more. You mentioned in the analyst discussion this morning that the market's fragmented. A lot of people think, "Oh, backup, storage, we'll just put it together. You know, Dell now or EMC brought it all together." But they're just dramatically different markets. You're seeing some of your competitors. One in particular is now kind of pivoting to security. It's an adjacency, but it's, yeah, I'm not sure you want to walk into that mess but it's clearly part of a data protection strategy. And you said you want your... My words, legacy to be a significant increase in market share, dominant position in the market. Even if it's number two, whatever, number one's nice, great. But much larger share than what is your 10, 12% today. How do you think about the TAM? It's so undercounted, I think. You know, we used to look at purpose built backup appliances, "Oh, it's a couple billion dollar market and it's a ceiling there." It reminds me of service management with ServiceNow. It's virtually unlimited TAM because it's data. How do you look at the TAM? >> How much time do you have? >> I know, I got so many questions- >> But I'll tell you this, right? You got to piece this question very carefully because I'll look at it in a variety of different ways. Number one, if you do nothing, if you just do nothing. I mean, today, as I shared in IDCs latest report last week we were joined number one, you know, for the first time we actually got- >> Dave: Yeah. Congratulations. That's a big milestone. >> That's huge, that's exciting. >> Dave: And that's revenue by the way. That's not licenses- >> Yeah. That's in share. But the thing is this, right? If, if you look at share, we are at 12%, you know as is the... You know, so 12% is not representative of how I think about number one. When you look at a market with a clear winner you expect to see 40 to 60% market share. So doing nothing is an opportunity to actually continue the path we are on which is taking share from every one of the top five significantly and growing as fast as we are. I mean, we are going to be on a path to, you know doubling our market share in the next two to three years. So there's share to gain doing nothing. And this is... You know what? This is the first and the most simplest aspect of TAM. Now layer in other aspects of TAM but just still stay in data protection. You know, talk about every single SaaS workload coming on. I mean, I shared 270 million Teams' users right now monthly actives. The TAM, if you were able to secure every one of those Teams' users and protect the data, I mean that's close to 6 or $7 billion. It's not factored in into any of the TAM numbers you see right now. Gartner talked about 13. You know, others talked about TAM being 40. I mean, but SaaS workloads, you know each of them are not factored in as much as it could be right now. So, you know, we are bringing in Salesforce, Microsoft 365. We secure 11 million paid users with Microsoft 365 backup. And so add all of them on, execute. We see a path to taking share and getting from here 12 to 25 to 40 and being an outsize number one. And then you'd come down to what you said, which is how do you think about adjacencies? Now, at Veeam, yeah, messaging is important, but unlike some of the competitors, we don't use words frivolously. If we say something, data protection, modern data protection, ransomware attacks, we mean it. And there's product truth behind it. We do not use frivolous security words to create a message and get attention and have no product truth behind it. That's where we are. We expect to see adjacencies come up. We expect Veeam to beyond execution and bringing in more SaaS workloads to look at the next layer of data management. We expect us to create partnerships which allow us to go do that meaningfully. And as time goes, you should expect us to be the prime influencer in reshaping this category with other adjacencies coming in. But we talk about it and there's product truth behind it. >> I wanted to get into your philosophy of management a little bit. I went to your LinkedIn recently and I loved the little graphic that you had. But I know a lot of people put up a picture of a pretty lake or mountains. I got theCUBE up there. You had a number of items. I wonder if I could read. You had a rocket ship, which was very cool. You had teamwork, you had innovation. I wrote down ABC, always be closing, Alec Baldwin. But everybody sells, I think is what it was and then keep it simple. >> Anand: Yep. >> I really like that. I mean, people going to... If they're going to evaluate Veeam they're going to go to your LinkedIn page. So tell us where that came from what your philosophy is as a manager. >> Yeah, no. So there's a few things and this is the philosophies which I put on is a meld of what I believe in and what Veeam believes in and has believed in for a long time which is life starts with a customer. For us, everything starts with a customer. You know, even the product creation philosophy 15 years back was, "Hey let's not just create some check marks and create a feature because someone, you know thought it's an important check mark to have." What is the value it creates for the customer? And is it different enough, unique enough, where, you know, it actually creates a moment where the customer sees the value impact their core business. That's where it all starts for us at Veeam. And then everything we do relates back to, "Is this moving the ball enough for our customers and for our partners and for our developers and users?" Everything comes back to there. Are we easy enough to do business with? You know, are we keeping it simple? Simple to use. A product should be really simple. It should be brain dead simple, you know are our processes such that, you know it's easy for us to connect with our partners, connect with our customers, connect with our users, you know it all comes back to keeping it really simple. And then, you know, I come down to a set of personal philosophies, which matters as well, which is, you know, how do we make sure that, you know, we used to say everyone is in sales, but we got to evolve it. Everyone is in customer success because we all know that it's not just the first sale which matters which was true 15 years back, what matters today is, yeah, the sale matters, everybody is there to sell. But what matters even more is the whole company rallies behind the customer's success at every step along the way. Because when you do that, you don't need to sell. You know, you get in through BBR and then we have a world of workloads to actually create value for the customer with, from, you know Microsoft 365 backup or, you know soon to come Salesforce backup cost. And we see that on net retention or, you know... And it's manifested in numbers, right? It's manifested in growth. It's manifested in net retention and it's manifested in NPS. I mean, Dave, I'm hugely excited about that, man. NPS of 80 where we are. I mean, you guys have been around for quite a bit. I mean, that's huge numbers. I mean, that's- >> Apple's- >> Apple was 76 or 77. And so eventually that is what matters more for me because it's... Share is important. And I'm excited about, you know, IDC saying, "You're joint number one." Hugely important, but that is a consequence. Growth is important. 25% ARR growth in Q1, super important but that is a consequence. What really matters is value for your customers. And the number one metric I look at is NPS, you know and NPS at 80, all the other things start to happen pair it with the engineering culture the innovation culture we have, long roadmap ahead. >> Veeam has made some... What appear to be, from the outside anyway, pretty successful acquisitions. Kasten is an obvious one. I remember it wasn't the first time I met Ratmir. It was maybe the third or fourth time we were at like a late night, Peter Bell party this Highland Capital at VMware. And we were walking down Howard Street. I see Ratmir and some of his colleagues, we start chatting. We, you know, got into a good conversation. I'm like, "What about an IPO?" He goes, "We're not doing an IPO. We don't need to do an IPO." And then several years later on theCUBE, he's like, "No, I'd be open to an IPO." And then of course the big acquisition happened. So you've got an opportunity here M and A obviously is a possibility. But what about the IPO in your future? Presumably, that's something Insight wants to do. What can you tell us about that? >> No, it's a great question. I was waiting when you were going to ask me that question. But this is what I would say which is, by the way, Veeam, at today's numbers, I mean, we shared numbers at the end of last year. 1.1 billion in ARR, 1.2 in revenues, 99.99% organic, right? You know, Kasten was the only acquisition we shared how Kasten is a blip at this point in time. And so the philosophy has always been organic. And as I look ahead, this is how I think about it. I think the pace of market change is going to be extreme. And so we will be a lot more open-minded, thinking about acquisitions for complimentary technologies which allow us to expand TAM and think about adjacencies, more to come there. IPO, see the good thing is this, a lot of companies want to enter the public markets to raise money, create liquidity. That's not the primary lens for us. And so the good news is that, you know we are incredibly profitable. We shared, you know, 30% EBITDA, you know, for 2021. So money is not the issue, but we do think that we entering the public markets is a good thing for a variety of other reasons, because when you are public and it comes with the, you know, transparency, which we believe we're already transparent. But it puts the focus on you. And that creates even better growth impetus. Especially as you go work with large enterprise customers they are a lot more amenable and you know and so we feel that it's a strategy of growth not a strategy of liquidity for us, but stay tuned. You know, I fully expect for something like that to happen sometime towards the middle of next year, to the end of next year. >> Yeah, we had a similar conversation with Frank Slootman they obviously were able to raise money. But wow, what a change since the snowflake IPO in terms of just the brand value. And again, so many questions. I thought your keynote was great, by the way. >> Anand: Thank you. I love the focus on, you know, ransomware, of course. I thought the bot jokes were great. Keep 'em coming. I mean, I really did enjoy- >> (laughs) Absolutely. >> It lightens things up. So thanks so much for coming on theCUBE, really appreciate your time. >> Absolutely appreciate it, Dave and Dave. By the way, I mean, it's funny, I mean about, you know, Dave and Dave, Dave and David reminded me of Thompson and Thompson, guess which comic book they're from? >> Thompson and Thompson- >> Thompson and Thompson. I don't know. >> Don't know. >> Tin Tin. >> Oh (laughs). >> (laughs) So you got to go read up. You guys don't look anything like that, but Dave and Dave, was an absolute pleasure. My first theCUBE and look forward to many more to come. >> Love to have you back- >> Absolutely. >> All right. Thank you for watching. >> Thank you. >> Keep it right there. TheCUBE's coverage of Veeamon 2022, 2 days of wall to wall coverage here at the ARIA in Las Vegas, we'll be right back. (upbeat music)

>>live from San Francisco. It's the queue covering our essay conference 2020 San Francisco Brought to you by Silicon Angle Media >>Hey, welcome back here. Ready? Jeff Frick here with the Cube. We're in our 2020 the biggest security conference in the country, if not the world. I guess there's got to be 50,000 people. We'll get the official word tomorrow. It's our sixth year here and we're excited to be back. I'm not sure why. It's 2020. We're supposed to know everything at this point in time with the benefit on inside. We got two people that do. You know a lot. We're excited to have him. My left is Chris Bets is the SVP and chief security officer for Centurylink. Chris, Great to see you. And to his left is Chris Smith, VP Global security Services for Centurylink. Welcome. >>Thank you for having me. >>Absolutely. You guys just flew into town >>just for the conference's great To be here is always a really exciting space with just a ton of new technology coming out. >>So let's just jump into it. What I think is the most interesting and challenging part of this particular show we go to a lot of shows you 100 shows a year. I don't know that there's one that's got kind of the breadth and depth of vendors from the really, really big the really, really small that you have here. And, you know, with the expansion of Moscone, either even packing more women underneath Howard Street, what advice do you give to people who are coming here for the first time? Especially on more than the buyer side as to how do you navigate this place >>when I when I come here and see So I'm always looking at what the new technologies are. But honestly, having a new technology is not good enough. Attackers are coming up with new attacks all the time. The big trick for me is understanding how they integrate into my other solutions. So I'm not so I'm not just focused on the technology. I'm focused on how they all fit together. And so the vendors that have solutions that fit together that really makes a difference in my book. So I'm looking for for products that are designed to work with each other, not just separate >>from a practice standpoint. The theme of IRA say this year is the human element, and for us, if you look at this floor, it's overwhelming. And if you're a CSO of an average enterprise, it's hard to figure out what you need to buy and how to build a practice with all of the emerging tools. So for us core to our practice, I think any mature, 30 security practices having a pro services capability and consulting capability that can be solved this all together, that helps you understand what to buy, what things to piece together and how to make it all work >>right. And it's funny, the human element that is the kind of the global theme. And what's funny is for all the technology it sounds like. Still, the easiest way in is through the person, whether it's a phishing attack or there's a myriad of ways that people are getting him to the human. So that's kind of a special challenge or trying to use technology to help people do a better job. At the end of the day, sometimes you're squishy ISS or easier access point is not a piece of technology, but it's actually a person. It's >>often because We asked people to do the wrong things. We're having them. Focus on security steps. Use email. Security is an easy to grasp example way all go through training every year to teach folks how to make sure that they avoid clicking on the wrong emails for us more often than a year. So the downside of that is arresting people to take a step away from their job and try to figure out how to protect themselves. And is this a bad emails that are really focusing on the job? So that's why it's so important to me to make sure that we've got solutions that help make the human better and frankly, even worse in security. We don't have the staff that we need. And so how do we help Make sure that the right tools are there, that they work together. They automate because asking everybody to take those steps, it's just it's a recipe for disaster because people are going to make mistakes >>right? Let's go a little deeper into the email thing. A friend of mines and commercial real estate, and he was describing an email that he got from his banker describing a wire transfer from one of his suppliers that he has a regular, ongoing making relationship with. You know, it's not the bad pronunciation and bad grammar and kind of the things that used to jump out is an obvious. But he said it was super good to the point where thankfully, you know, it was just this time. But, you know, he called the banker like, did you just send me this thing? So you know where this as the sophistication of the bad guys goes up specifically targeting people, how do you try to keep up with how do you give them the tools to know Woe versus being efficient? I'm trying to get my job done. >>Yeah, for me, it starts with technology. That takes a look. We've only got so many security practitioners in the company. Actually. Defend your email example. We've got to defend every user from those kinds of problems. And so how do I find technology solutions that help take the load off security practitioners so they can focus on the niche examples that really, really well crafted emails and help take that load off user? Because users just not gonna be able to handle that right? It's not fair to ask them. And like you said, it was just poorly time that helped attack. So how do we help? Make sure that we're taking that technology load off, identify the threats in advance and protect them. And so I think one of the biggest things that Chris and I talk a lot about is how to our solutions help make it easier for people to secure themselves instead of just providing only technology technology advantage, >>our strategy for the portfolio and it sort of tied to the complexity. CN This floor is simplicity. So from our perspective, our goal is a network service provider is to deliver threat free traffic to our customers even before it gets to the human being. And we've got an announcement that we launched just a week ago in advance of the show called Rapid Threat Defense. And the idea is to take our mature threat Intel practice that Chris has a team of folks focused on that. We branded black Lotus labs and Way built a machine learning practice that takes all the bad things that we see out in the network and protects customers before it gets to their people. >>So that's an interesting take. You have the benefit of seeing a lot of network traffic from a lot of customers and not just the stuff that's coming into my building. So you get a much more aggregated approach, so tell us a little bit more about that. And what is the Black Lotus Labs doing? And I'm also curious from an industry point of view, you know, it's just a collaboration with the industry cause you guys are doing a lot of traffic. There's other big network providers carrying a lot of traffic. How well do you kind of work together when you identify some nasty new things that you're doing the horizon? And where do you draw the line between better together versus still independent environment? >>When we're talking about making the Internet safer, it's not really to me a lot about competitive environment. It's really about better together. That's one of things I love about the security community. I'm sure you see it every year when you're here. You're talking security practitioners how across every industry security folks work together to accomplish something that's meaningful. So as the largest world's largest global I P we get to see a ton of traffic, and it's really, really interesting we'll be able to put together, you know, at any given point in time. We're watching many tens of thousands of probable malware networks. We're protecting our customers from that. But we're also able to ourselves take down nearly 65 now where networks every month just knock them off the Internet. So identify the command and control, and we take it off the Internet. We work with our partners. We go talk to hosting providers, maybe competitors of ours. And we say, Hey, here's a bad, bad actors bad server that's being used to control now where? Going shut it down. And so the result of that is not only protecting our customers, but more importantly, protecting tens of thousands of customers every month. By removing now where networks that were attacking, that really makes a difference. To me, that's the biggest impact we bring. And so it really is a better together. It's a collaboration story and, of course, for said, we get the benefit of that information as we're developing it as we're building it, we can protect our customers right away while we're building the confidence necessary to take something as dramatic and action as shutting down on our network. Right. Unilaterally, >>Citrix. I was gonna ask you kind of the impact of I o t. Right in this in this crazy expansion of the tax services, when you hear about all the time with my favorite example, somebody told the story of attacking a casino through the connected thermometer in the fish tank in the lobby, which may or may not be true, is still a great story. Great story. But I'm curious, you know, looking at the network, feeding versus the devices connecting that's really in an interesting way to attack this proliferation of attack services. You're getting it before it necessarily gets to all these new points of presence doing it based on the source. For >>us, that's the only way to make it scalable. It is true that automation blocking it before it gets to the azure to a device. It is what will create simplicity and value for our customers. >>Right on the other piece of the automation. Of course, that we hear about all the time is there just aren't enough security professionals, period. So if you don't have the automation. You don't have the machine learning, as you said, to filter low hanging fruit and the focus your resource. If they need to be, you're not going to do it. The bad news is the bad guys, similar tools. So as you look at kind of the increase in speed of automation, the increase in automated connectivity between these devices making decisions amongst each other, how do you see that kind of evolving? But you're kind of role and making sure you stay a step ahead of the bad guys. For >>me, it's not about just automation. It's about allowing smart people to put their brains against hard problems, hard impactful problems and so on. So simply automating is not enough. It's making sure that automation is reducing the the load on people so that they're able to focus on those hard, unique problems really solve all those solutions and, yes, Attackers, Attackers build automation as well. And so if we're not building faster and better than we're falling behind, so like every other part of this race, it's about getting better, faster and why it's so important that technology work together because we're constantly throwing out more tools and if they don't work better together, even if we got incremental automation, these place way still miss overall because it's end to end that we need to defend ourselves and our customers >>layered on what he said. For the foreseeable future, you're gonna need smart security people that help protect your practice. Our goal in automation is take the road tasks out of out of the gate. They live so they can focus on the things that provide the most value protecting their enterprise. >>Right when you're looking, you talked about making sure things work together, for you talked about making sure things work together. How do you decide what's kind of on the top of the top of the stack, where everybody wants to own the single pane of glass? Everybody wants to be the control plane. Everybody wants to be that thing that's on your computer all the time, which is how you work your day to day. How do you kind of dictate what are the top level tools while still going out? And, he said, exploring some of these really cutting edge things out around the fringe, which don't necessarily have a full stack solution that you're going to rely on but might have some cool kind of point solutions if you will, or point products to help you plug some new and emerging holes. Yeah, >>yeah. So for us, yeah, we take security capabilities and we build them into the other things that we sell. So it's not a bolt on. So when you buy things from us, whether whether it's bandwidth or whether its SD wan and security comes baked in, so it's not something you have to worry about integrating later. It's an ingredient of the things that we sell in all of the automation that we build is built into our practice, So it's simple for our customers to understand, like, simple and then layered. On top of that, we've got a couple different ways that we bring pro services and consulting to our practice. So we've got a smart group of folks that could lean into staff, augment and sit on site, do just about anything to help customers build a practice from day zero to something more mature. But now we're toying with taking those folks in building them into products and services that we sell for 10 or 20 hours a month as an ingredient. So you get that consulting wrapper on top of the portfolio that we sell as a service provider. >>Get your take on kind of budgets and how people should think about their budgets. And when I think of security, I can't help but think of like insurance because you can't spend all your money on security. But you want to spend the right amount on security. But at the end of the day, you can't be 100% secure, right? So it's kind of kind of working the margins game, and you have to make trade offs in marketing, wants their money and product development, wants their money and sales, wants their money. So what people are trying to assess kind of the risk in their investment trade offs. What are some of the things they should be thinking about to determine what is the proper investment on security? Because it can't just be, you know, locker being 100% it's not realistic, and then all the money they help people frame that. >>Usually when companies come to us in, Centurylink plays in every different segment, all the way down to, you know, five people company all the way to the biggest multinationals on the planet. So that question is, in the budget is a little bit different, depending on the type of customer, the maturity and the lens are looking at it. So, typically, way have a group of folks that we call security account managers those our consultants and we bring them in either in a dedicated or a shared way. Help companies that's us, wear their practices today in what tool sets for use again things that they need to purchase and integrate to get to where they need to be >>really kind of a needs analysis based on gaps as much as anything else. >>That's part of the reason why we try to build prisons earlier, so many of the technologies into our solution so that so that you buy, you know, SD wan from us, and you get a security story is part of it is that that allows you to use the customer to save money and really have one seamless solution that provides that secure experience. We've been building firewalls and doing network based security for going on two decades now, in different places. So at this point, that is a good place that way, understand? Well, we can apply automation against it. We can dump, tail it into existing services and then allow focused on other areas of security. So it helps. From a financial standpoint, it also helps customers understand from where they put their talent. Because, as you talked about, it's all about talents even more so than money. Yes, we need to watch our budgets. But if you buy these tools, how do you know about the talent to deploy them? And easier You could make it to do that simpler. I think the better off right >>typical way had the most success selling security practices when somebody is either under attacker compromised right, then the budget opens right up, and it's not a problem anymore. So we thought about how to solve that commercially, and I'll just use Vitas is an example. We have a big D dos global DDOS practice that's designed to protect customers that have applications out on the Internet that are business critical, and if they go down, whether it's an e commerce or a trading site losing millions of dollars a day, and some companies have the money to buy that up front and just have it as a service. And some companies don't purchase it from us until they're under attack. And the legacy telco way of deploying that service was an order and a quote. You know, some days later, we turned it up. So we've invested with Christine the whole orchestration layer to turn it up in minutes and that months so you can go to our portal. You can enter a few simple commercial terms and turn it on when you need it. >>That's interesting. I was gonna ask you kind of how has cloud kind of changed the whole go to market and the way people think about it. And even then you hear people have stuff that's secure in the cloud, but they mis configured a switch left something open. But you're saying, too it enables you to deploy in a very, very different matter based on you know, kind of business conditions and not have that old, you know, get a requisite get a p o requisition order, install config. Take on another kind of crazy stuff. Okay, so before I let you go, last question. What are your kind of priorities for this show for Centurylink when it's top of mind, Obviously, you have the report and the Black Lotus. What do you guys really prioritizing for this next week? Here for Cisco. >>We're here to help customers. We have a number of customers, a lot of learning about our solutions, and that's always my priority. And I mentioned earlier we just put out a press release for rapid threat defense. So we're here to talk about that, and I think the industry and what we're doing this little bit differently. >>I get to work with Chris Motions Week with customers, which is kind of fun. The other part that I'm really excited about, things we spent a bunch of time with partners and potential partners. We're always looking at how we bring more, better together. So one of the things that we're both focused on is making sure that we're able to provide more solutions. So the trick is finding the right partners who are ready to do a P I level integration. The other things that Chris was talking about that really make this a seamless and experience, and I think we've got a set of them that are really, really interested in that. And so those conversations this week will be exceptionally well, I think that's gonna help build better technology for our customers even six months. >>Alright, great. Well, thanks for kicking off your week with the Cube and have a terrific week. Alright. He's Chris. He's Chris. I'm Jeff. You're watching the Cube. Where? The RSA Conference in downtown San Francisco. Thanks for watching. See you next time. >>Yeah, yeah.

(lively music) >> Narrator: Live, from San Francisco, celebrating 10 years of high tech coverage, it's theCUBE, covering VMworld 2019! Brought to you by VMware and its ecosystem partners. >> Okay, welcome back to theCUBE's live coverage in VMworld 2019. We're in San Francisco. We're in Moscone North Lobby. I'm John Frer, my co Stu Miniman, here covering all the action of VMworld, two sets for theCUBE, our tenth year, Stu. Keeping it going. Two great guests, John Fanelli, CUBE Alumni, Vice President of Product, Virtual GPUs at NVIDIA Kevin Gray, Director of Product Marketing, Dell EMC. Thanks for coming back on. Good to see you. >> Awesome. >> Good to see you guys, too. >> NVIDIA, big news, we saw your CEO up on the keynote videoing in. Two big announcements. You got some stats on some Windows stats to talk about. Let's talk about the news first, get the news out of the way. >> Sure, at this show, NVIDIA announced our new product called NVIDIA Virtual Compute Server. So for the very first time anywhere, we're able to virtualize artificial intelligence, deep learning, machine learning, and data analytics. Of course, we did that in conjunction with our partner, VMware. This runs on top of vSphere and also in conjunction with our partner at Dell. All of this Virtual Compute Server runs on Dell VxRail, as well. >> What's the impact going to be for that? What does that mean for the customers? >> For customers, it's really going to be the on-ramp for Enterprise AI. A lot of customers, let's say they have a team of maybe eight data scientists are doing data analytics, if they want to move through GPU today, they have to buy eight GPUs. However, with our new solution, maybe they start with two GPUs and put four users on a GPU. Then as their models get bigger and their data gets bigger, they move to one user per GPU. Then ultimately, because we support multiple GPUs now as part of this, they move to a VM that has maybe four GPUs in it. We allow the enterprise to start to move on to AI and deep learning, in particular, machine learning for data analytics very easily. >> GPUs are in high demand. My son always wants the next NVIDIA, in part told me to get some GPUs from you when you came on. Ask the NVIDIA guy to get some for his gaming rig. Kidding aside, now in the enterprise, really important around some of the data crunching, this has really been a great use case. Talk about how that's changed, how people think about it, and how it's impacted traditional enterprise. >> From a data analytics perspective, the data scientists will ingest data, they'll run some machine learning on it, they'll create an inference model that they run to drive predictive business decisions. What we've done is we've GPU-accelerated the key libraries, the technologies, like PyTorch, XGBoost to use a GPU. The first announcement is about how they can now use Virtual Compute Server to do that. The second announcement is that workflow is, as I mentioned, they'll start small, and then they'll do bigger models, and eventually they want to train that scale. So what they want to do is they want to move to the cloud so they can have hundreds or thousands of GPUs. The second announcement is that NVIDIA and VMware are bringing Virtual Compute Server to VMware Cloud running on AWS with our T4 GPUs. So now I can scale virtually starting with fractional GPU to single GPU to multi GPU, and push a button with HCX and move it directly into AWS T4 accelerated cloud. >> That's the roadmap so you can get in, get the work done, scale up, that's the benefit of that. Availability, timing, when all of this is going to hit in-- >> So Virtual Compute Server is available on Friday, the 29th. We're looking at mid next year for the full suite of VMware Cloud on top of Aws T4. >> Kevin, you guys are supplier here at Dell EMC. What's the positioning there with you guys? >> We're working very closely with NVIDIA in general on all of their efforts around both AI as well as VDI too. We'll work quite a bit, most recently on the VDI front as well. We look to drive things like qualifying the devices. There's both VDI or analytics applications. >> Kevin, bring us up-to-date 'cause it's funny we were talking about this is our 10th year here at the show. I remember sitting across Howard Street here in 2010 and Dell, and HP, and IBM all claiming who had the lowest dollar per desktop as to what they were doing in VDI. It's a way different discussion here in 2019. >> Absolutely. Go ahead. >> One of the things that we've learned with NVIDIA is that it's really about the user experience. It's funny we're at a transition point now from Windows 7 to Windows 10. The last transition was Windows XP to Windows 7. What we did then is we took Windows 7, we tore everything out of it we possibly could, we made it look like XP, and we shoved it out. 10 years later, that doesn't work. Everyone's got their iPhones, their iOS devices, their Android devices. Microsoft's done a great job on Windows 10 being immersive. Now we're focused on user experience. When the VDI environment, as you move to Windows 10, you may not be aware of this, but from Windows 7 to Windows 10, it uses 50% more CPU, and you don't even get that great of a user experience. You pop a GPU in there, and you're good. Most of our customers together are working on a five-year life cycle. That means over the next five years, they're going to get 10 updates of Windows 10, and they're going to get like 60 updates of their Office applications. That means that they want to be future-proof now by putting the GPUs in to guarantee a great user experience. >> On the performance side too, obviously. In auto updates, this is the push notification world we live in. This has to built in from day one. >> Absolutely, and if you look at what Dell's doing, we really built this into both our VxRails and our VxBlocks. GPUs are just now part of it. We do these fully qualified. It stacks specifically for VDI environments as well. We're working a lot with the n-vector tools from VM which makes sure we're-- >> VDI finally made it! >> qualifying user experience. >> All these years. >> Yes, yes. In fact, we have this user experience tool called n-vector, which actually, without getting super technical for the audience, it allows you to look at the user experience based on frame-rate, latency, and image quality. We put this tool together, but Dell has really been taking a lead on testing it and promoting it to the users to really drive the cost-effectiveness. It still is about the dollar per desktop, but it's the dollar per dazzling desktop. (laughing) >> Kevin, I hear the frame-rate in there, and I've got all the remote workers, and you're saying how do I make sure that's not the gaming platform they're using because I know how important that is. >> Absolutely. There's a ton of customers that are out there that we're using. We look at folks like Guillevin as like the example of a company that's worked with us and NVIDIA to truly drive types of applications that are essential to VDI. These types of power workers doing applications like Autodesk, that user experience and that ability to support multiple users. If you look at Pat, he talked a little bit about any cloud, any application, any device. In VDI, that's really what it's about, allowing those workers to come together. >> I think the thing that the two of you mentioned, and Stu you pointed out brilliantly was that VDI is not just an IT thing anymore. It really is the expectation now that my rig, if I'm a gamer, or a young person, the younger kids, if you're under 25, if you don't have a kick-ass rig, (laughs) that's what they call it. Multiple monitors, that's the expectation, again, mobility. Work experience, workspace. >> Exactly, along those same lines, by the way. >> This is the whole category. It's not just like a VDI, this thing over here that used to be talked about as an IT thing. >> It's about the workflow. So it's how do I get my job done. We used to use words like "business worker" and "knowledge worker." It's just I'm a worker. Everybody today uses their phone that's mobile. They use their computer at home, they use their computer at work. They're all running with dual monitors. Dual monitors, sometimes dual 4K monitors. That really benefits as well from having a GPU. I know we're on TV so hopefully some of you guys are watching VDI on your GPU-accelerated. It's things like Skype, WebEX, Zoom, all the collaboration to 'em, Microsoft Teams, they all benefit from our joint solution, like the GPU. >> These new subsystems like GPUs become so critical. They're not just subsystem, they are the main part because the offload is now part of the new operating environment. >> We optimized together jointly using the n-vector tool. We optimized the server and operating environment, so that if you run into GPU, you can right-size your CPU in terms of cores, speed, etc., so that you get the best user experience at a most cost effective way. >> Also, the gaming world helps bring in the new kind of cool visualization. That's going to move into just the workflow of workers. You start to see this immersive experience, VR, ARs obviously around the corner. It's only going to get more complex, more needs for GPUs. >> Yes, in fact, we're seeing more, I think, requirements for AR and VR from business than we are actually for gaming. Don't you want to go into your auto showroom at your house and feel the fine Corinthian leather? >> We got to upgrade our CUBE game, get more GPU focused and get some tracing in there. >> Kevin, I know I've seen things from the Dell family on levering VR in the enterprise space. >> Oh, absolutely. If you look at a lot of the things that we're doing with some of the telcos around 5G. They're very interested in VR and AR. Those are areas that'll continue to use things like GPUs to help accelerate those types of applications. It really does come down to having that scalable infrastructure that's easy to manage and easy to operate. That's where I think the partnership with NVIDIA really comes together. >> Deep learning and all this stuff around data. Michael Dell always comes on theCUBE, talks about it. He sees data as the biggest opportunity and challenge. In whatever applications coming in, you got to be able to pound into that data. That's where AI's really shown... Machine learning has kind of shown that that's helping heavy lifting a lot of things that were either manual. >> Exactly. The one thing that's really great about data analytics that are GPU-accelerated is we can take a job that used to take days and bring it down to hours. Obviously, doing something faster is great, but if I take a job that used to take a week and I can do it in one day, that means I have four more days to do other things. It's almost like I'm hiring people for free because I get four more extra work days. The other thing that's really interesting as our joint solution is you can leverage that same virtual GPU technology. You can do VDI by day and at night, you run Compute. So when your users aren't at work, you migrate them off, you spin up your VMs that are doing your data analytics using our RAPIDS technology, and then you're able to get that platform running 24 by seven. >> Productivity gains just from an infrastructure. Even the user too, up and down, the productivity gains are significant. So I'll get three monitors now. I'm going to get one of those Alienware curved monitors. >> Just the difference we had, we have a suite here at the show, and just the difference, you can see such a difference when you insert the GPUs into the platform. It's just makes all the difference. >> John, I got to ask you a personal question. How many times have people asked you for a GPU? You must get that all the time? >> We do. I have a NVIDIA backpack. When I walk around, there's a lot of people that only know NVIDIA for games. So random people will always ask for that. >> I've got two sons and two daughters and they just nerd out on the GPUs. >> I think he's trying to get me to commit on camera on giving him a GPU. (laughing) I think I'm in trouble here. >> Yeah, they get the latest and greatest. Any new stuff, they're going to be happy to be the first on the block to get the GPU. It's certainly impacted on the infrastructure side, the components, the operating environment, Windows 10. Any other data you guys have to share that you think is notable around how all this is coming together working from user experience around Windows and VDI? >> I think one piece of data, again, going back to your first comment about cost per desktop. We're seeing a lot of migration to Windows 10. Customers are buying our joint solution from Dell which includes our hardware and software. They're buying that five-year life cycle, so we actually put a program in place to really drive down the cost. It's literally like $3 per month to have a GPU-accelerated virtual desktop. It's really great Value for the customers besides the great productivity. >> If you look at doing some of these workloads on premises, some of the costs can come down. We had a recent study around the VxBlock as an example. We showed that running GPUs and VDI can be up as much as 45% less on a VxBlock at scale. When you talk about the whole hybrid cloud, multi-cloud strategy, there's pluses and minuses to both. Certainly, if we look at some of the ability to start small and scale out, whether you're going HCI or you're going CI, I think there's a VDI solution there that can really drive the economics. >> The intense workloads. Is there any industries that are key for you guys in terms of verticals? >> Absolutely. So we're definitely looking at a lot of the CAD/CAM industries. We just did a certification on our platforms with Dassault's CATIA system. That's an area that we'll continue to explore as we move forward. >> I think in the workstation side of things, it's all the standard, it's automotive, it's manufacturing. Architecture is interesting. Architecture is one of those companies that has kind of an S and B profile. They have lots of offices, but they have enterprise requirements for all the hard work that they do. Then with VDI, we're very strong in financial services as well as healthcare. In fact, if you haven't seen, you should come by. We have a Bloomberg demo for financial services about the impact for traders. I have a virtualized GPU desktop. >> The speed is critical for them. Final question. Take-aways from the show this year, 2019 VMworld, Stu, we got 10 years to look back, but guys, take-aways from the show that you're going to take back from this week. >> I think there's still a lot of interest and enthusiasm. Surprisingly, there's still a lot of customers that haven't finished there migration to Windows 10 and they're coming to us saying, Oh my gosh, I only have until January, what can you do to help me? (laughing) >> Get some GPUs. Thoughts from the show. >> The multi-cloud world continues to evolve, the continued partnerships that emerge as part of this is just pretty amazing in how that's changing in things like virtual GPUs and accelerators. That experience that people have come to expect from the cloud is something, for me is a take-away. >> John Fanelli, NVIDIA, thanks for coming on. Congratulations on all the success. Kevin, Dell EMC, thanks for coming on. >> Thank you. >> Thanks for the insights. Here on theCUBE, Vmworld 2019. John Furrier, Stu Miniman, stay with us for more live coverage after this short break. (lively music)

>> Live from San Francisco, it's theCUBE! Covering IBM Think 2019. Brought to you by IBM. >> Welcome back, live here in San Francisco, it's theCUBE's coverage of IBM Think 2019. I'm John Furrier--Stu Miniman. Stu, four days, we're on our fourth day, the sun's shining, they've shut down Howard Street here at IBM. Big event for IBM, in San Francisco, not Las Vegas. Lot of great cloud action, lot of great AI data developers. Great story, good to see you again. Our next two guests, Julie Lockner, Director, Offering Management, Portfolio Operations at IBM, Data+AI, great to see you. >> Thank you, it's great to see you too, thank you. >> And Jay Limburn, Director of Offering Management, IBM Data+AI, thanks for coming on. >> Hey guys, great to be here. >> So, we've chatted many times at events, the role of data. So, we're religious about data, data flows through our blood, but IBM has put it all together now. All the reorgs are over, everyone's kind of, the table is set for IBM. The data path is clear, it's part of applications. It's feeding the apps. AI's the key workload inside the application. This is now a fully set-up group, give us the update, what's the focus? >> Yeah, it's really exciting because, if you think about it, before, we were called IBM Analytics, and that really is only a part of what we do. Now that we're Data+AI, that means that not only are we responsible for delivering data assets, and technology that supports those data assets to our customers, but infusing AI, not only in the technologies that we have, but also helping them build applications so they can fuse AI into their business processes. >> It's pretty broad, I mean, data's very much a broad swath of things. Analytics, you know, wrangling data, setting things up, cataloging them. Take me through how you guys set this up. How do you present it to the marketplace? How are clients engaged with it? Because it's pretty broad. But it could be, it needs to be specific. Take us through the methodology. >> So, you probably heard a lot of people today talk about the ladder to AI, right? This is IBM's view of how we explain our client's journey towards AI. It really starts at the bottom rung of the ladder, where we've got the collection of information. Collect your data. Once you've collected your data, you move up to the next rung, which is the Organize. And this is really where all the governance stuff comes in. This is how we can provide a view across that data, understand that data, provide trust to that data, and then serve that up to the consumers of that information, so they can actually use that in AI. That's where all the data science capabilities come in, allowing people to actually be able to consume that information. >> So, the bottom set is just really all the hard and heavy lifting that data scientists actually don't want to do. >> And writing algorithms, the collecting, the ingesting of data from any source, that's the bottom? And then, tell me about that next layer up, from the collection-- >> So, Collect is the physical assets or the collection of the data that you're going to be using for AI. If you don't get that foundation right, it doesn't really make sense. You have to have the data first. The piece in the middle that Jay was referring to, that's called Organize, our whole divisions are actually organized around these ladders to AI, so, Collect, Organize, Analyze, Infuse. On the Organize side, as Jay was mentioning, it's all about inventorying the data assets, knowing what data you have, then providing data quality rules, governance, compliance-type offerings, that allow organizations to not just know your data, trust your data, but then make it available so you can use your data, and the users are those data scientists, they're the analytics teams, they're the operation organizations that need to be able to build their solutions on top of trusted data. >> So, where does the Catalog fit in? Which level does that come into? >> Yeah, so, think of the Data Catalog as the DNS for data, all right? It's the way in which you can provide a full view of all of your information. Whether it's structured information, unstructured information, data you've got on PRAM and data you've got in a cloud somewhere. >> That's in the Organize layer, right? >> That's all in the Organize layer. So, if you can collect that information, you can then provide capabilities that allow you to understand the quality of that data, know where that data's come from, and then, finally, if you serve that up inside a compelling, business-friendly experience, so that a data scientist can go to one place, quickly make a decision on if that's the right data for them, and allow them to go and be productive by building a data science model, then we're really able to move the needle on making those data science organizations efficient, allowing us to build better models to transform their business. >> Yeah, and a big part of that is, if you think about what makes Amazon successful, it's because they know where all their products are, from the vendor, to when it shows up on the doorstep. What the Catalog provides is really the similar capability of, I would call it inventory management of your data assets, where we know where the data came from, its source--in that Collect layer-- who's transformed it, who's accessed it, if they're even allowed to see it, so, data privacy policies are part of that, and then being able to just serve up that data to those users. Being able to see that whole end-to-end lineage is a key point, critical point of the ladder to AI. Especially when you start to think about things like bias detection, which is a big part of the Analyze layer. >> But one of the things we've been digging into on theCUBE is, is data the next flywheel of innovation? You know, it used to be I just had my information, many years ago we started talking about, "Okay, I need to be able to access all that other information." We hear things like 80% of the data out there isn't really searchable today. So, how do you see data, data gravity, all those pieces, as the next flywheel of innovation? >> Yeah, I think it's key. I mean, we've talked a lot about how, you can't do AI without information architecture. And it's absolutely true. And getting that view of that data in a single location, so it is like the DNS of the internet. So you know exactly where to search, you can get hold of that data, and then you've got tools that give you self-service access to actually get hold of the data without any need of support from IT to get access to it. It's really a key-- >> Yeah, but to the point you were just asking about, data gravity? I mean, being able to do this where the data resides. So, for example, we have a lot of our customers that are mergers and acquisitions. Some teams have a lot of data assets that are on-premises, others have large data lakes in AWS or Azure. How do you inventory those assets and really have a view of what you have available across that landscape? Part of what we've been focusing on this year is making our technology work across all of those clouds. And having a single view of your assets but knowing where it resides. >> So, Julie, this environment is a bit more complicated than the old data warehousing, or even what we were looking at with big data and Hadoop and all those pieces. >> Isn't that the truth? >> Help explain why we're actually going to be able to get the information, leverage and drive new business value out of data today, when we've struggled so many times in the past. >> Well, I think the biggest thing that's changed is the adoption of DevOps, and when I say adoption of DevOps and things like containerization and Docker containers, Kubernetes, the ability to provision data assets very quickly, no matter where they are, build these very quick value-producing applications based on AI, Artificial Intelligence APIs, is what's allowing us to take advantage of this multi-cloud landscape. If you didn't have that DevOps foundation, you'd still be building ETL jobs in data warehouses, and that was 20 years ago. Today, it's much more about these microservices-based architecture, building up these AI-- >> Well, that's the key point, and the "Fuse" part of the stack, I think, or ladder. Stack? Ladder? >> Ladder. (laughs) >> Ladder to success! Is key, because you're seeing the applications that have data native into the app, where it has to have certain characteristics, whether it's a realtime healthcare app, or retail app, and we had the retail folks on earlier, it's like, oh my god, this now has to be addressable very fast, so, the old fenced-off data warehouse-- "Hey, give me that data!"--pull it over. You need a sub-second latency, or milliseconds. So, this is now a requirement. >> That's right. >> So, how are people getting there? What are some use cases? >> Sure. I'll start with the healthcare 'cause you brought that up. One of the big use cases for technology that we provide is really around taking information that might be realtime, or batch data, and providing the ability to analyze that data very quickly in realtime to the point where you can predict when someone might potentially have a cardiac arrest. And yesterday's keynote that Rob Thomas presented, a demonstration that showed the ability to take data from a wearable device, combine it with data that's sitting in an Amazon... MySQL database, be able to predict who is the most at-risk of having a potential cardiac arrest! >> That's me! >> And then present that to a call center of cardiologists. So, this company that we work with, iCure, really took that entire stack, Organize, Collect, Organize, Analyze, Infuse, and built an application in a matter of six weeks. Now, that's the most compelling part. We were able to build the solution, inventory their data assets, tie it to the industry model, healthcare industry model, and predict when someone might potentially-- >> Do you have that demo on you? The device? >> Of course I do. I know, I know. So, here is, this is called a BraveHeart Life Sensor. And essentially, it's a Bluetooth device. I know! If you put it on! (laughs) >> If I put it on, it'll track... Biometric? It'll start capturing information about your heart, ECG, and on Valentine's Day, right? My heart to yours, happy Valentine's Day to my husband, of course. The ability to be able to capture all this data here on the device, stream it to an AI engine that can then immediately classify whether or not someone has an anomaly in their ECG signal. You couldn't do that without having a complete ladder to AI capability. >> So, realtime telemetry from the heart. So, I see timing's important if you're about to have a heart attack. >> Yeah. >> Pretty important. >> And that's a great example of, you mentioned the speed. It's all about being able to capture that data in whatever form it's coming in, understand what that data is, know if you can trust that data, and then put it in the hands of the individuals that can do something valuable with the analysis from that data. >> Yeah, you have to able to trust it. Especially-- >> So, you brought up earlier bias in data. So, I want to bring that up in context of this. This is just one example of wearables, Fitbits, all kinds of things happening. >> New sources of tech, yeah. >> In healthcare, retail, all kinds of edge, realtime, is bias of data. And the other one's privacy because now you have a new kind of data source going into the cloud. And then, so, this fits into what part of the ladder? So, the ladder needs a secure piece. >> Tell me about that. >> Yeah, it does. So, that really falls into that Organize piece of that ladder, the governance aspects around it. If you're going to make data available for self-service, you've got to still make sure that that data's protected, and that you're not going to go and break any kind of regulatory law around that data. So, we actually can use technology now to understand what that data is, whether it contains sensitive information, credit card numbers, and expose that information out to those consumers, yet still masking the key elements that should be protected. And that's really important, because data science is a hugely inefficient business. Data scientists are spending too much time looking for information. And worse than that, they actually don't have all the information available that they need, because certain information needs to be protected. But what we can do now is expose information that wasn't previously available, but protect just the key parts of that information, so we're still ensuring it's safe. >> That's a really key point. It's the classic iceberg, right? What you see: "Oh, data science is going to "change the game of our business!" And then when they realize what's underneath the water, it's like, all this set-up, incompatible data, dirty data, data cleaning, and then all of a sudden it just doesn't work, right? This is the reality. Are you guys seeing this? Do you see that? >> Yeah, absolutely. I think we're only just really at the beginning of a crest of a wave, here. I think organizations know they want to get to AI, the ladder to AI really helps explain and it helps to understand how they can get there. And we're able then to solve that through our technology, and help them get there and drive those efficiencies that they need. >> And just to add to that, I mean, now that there's more data assets available, you can't manually classify, tag and inventory all that data, determine whether or not it contains sensitive data. And that's where infusing machine learning into our products has really allowed our customers to automate the process. I mentioned, the only way that we were able to deploy this application in six weeks, is because we used a lot of the embedded machine learning to identify the patient data that was considered sensitive, tag it as patient data, and then, when the data scientists were actually building the models in that same environment, it was masked. So, they knew that they had access to the data, but they weren't allowed to see it. It's perfectly--especially with HIMSS' conference this week as well! You were talking about this there. >> Great use case with healthcare. >> Love to hear you speak about the ecosystem being built around this. Everything, open APIs, I'm guessing? >> Oh, yeah. What kind of partners are-- >> Jay, talk a little bit-- >> Yeah, so, one of the key things we're doing is ensuring that we're able to keep this stuff open. We don't want to curate a proprietary system. We're already big supporters of open source, as you know, in IBM. One of the things that we're heavily-invested in is our open metadata strategy. Open metadata is part of the open source ODPi Foundation. Project Egeria defines a standard for common metadata interchange. And what that means is that, any of these metadata systems that adopt this standard can freely share and exchange metadata across that landscape, so that wherever your data is, whichever systems it's stored in, wherever that metadata is harvested, it can play part of that network and share that metadata across those systems. >> I'd like to get your thoughts on something, Julie. You've been on the analyst side, you're now at IBM. Jay, if you can weigh in on this too, that'd be great. We, here, we see all the trends and go to all the events and one of the things that's popping up that's clear within the IBM ecosystem because you guys have a lot of business customers, is that a new kind of business app developer's coming in. And we've seen data science highlight the citizen data scientist, so if data is code, part of the application, and all the ladder stuff kind of falls into place, that means we're going to see new kinds of applications. So, how are you guys looking at, this is kind of a, not like the cloud-native, hardcore DevOps developer. It's the person that says, "Hey, I can innovate "a business model." I see a business model innovation that's not so much about building technology, it's about using insight and a unique... Formula or algorithm, to tweak something. That's not a lot of programming involved. 'Cause with Cloud and Cloud Private, all these back end systems, that's an ecosystem partner opportunity for you guys, but it's not your classic ISV. So, there's a new breed of business apps that we see coming, your thoughts on this? >> Yeah, it's almost like taking business process optimization as a discipline, and turning it into micro-applications. You want to be able to leverage data that's available and accessible, be able to insert that particular Artificial Intelligence machine learning algorithm to optimize that business process, and then get out of the way. Because if you try to reinvent your entire business process, culture typically gets in the way of some of these things. >> I thought, as an application value, 'cause there's value creation here, right? >> Absolutely. >> You were talking about, so, is this a new kind of genre of developer, or-- >> It really is, I mean... If you take the citizen data scientist, an example that you mentioned earlier. It's really about lowering the entry point to that technology. How can you allow individuals with lower levels of skills to actually get in and be productive and create something valuable? It shouldn't be just a practice that's held away for the hardcore developer anymore. It's about lowering the entry point with the set of tools. One of the things we have in Watson Studio, for example, our data science platform, is just that. It's about providing wizards and walkthroughs to allow people to develop productive use models very easily, without needing hardcore coding skills. >> Yeah, I also think, though, that, in order for these value-added applications to be built, the data has to be business-ready. That's how you accelerate these application development life cycles. That's how you get the new class of application developers productive, is making sure that they start with a business-ready foundation. >> So, how are you guys going to go after this new market? What's the marketing strategy? Again, this is like, forward-pioneering kind of things happening. What's the strategy, how are you going to enable this, what's the plan? >> Well, there's two parts of it. One is, when Jay was mentioning the Open Metadata Repository Services, our key strategy is embedding Catalog everywhere and anywhere we can. We believe that having that open metadata exchange allows us to open up access to metadata across these applications. So, really, that's first and foremost, is making sure that we can catalog and inventory data assets that might not necessarily be in the IBM Cloud, or in IBM products. That's really the first step. >> Absolutely. The second step, I would say, is really taking all of our capabilities, making them, from the ground up, microservices-enabled, delivering them through Docker containers and making sure that they can port across whatever cloud deployment model our customers want to be able to execute on. And being able to optimize the runtime engines, whether it's data integration, data movement, data virtualization, based on data gravity, that you had mentioned-- >> So, something like a whole new developer program opportunity to bring to the market. >> Absolutely. I mean, there is, I think there is a huge opportunity for, from an education perspective, to help our customers build these applications. But it starts with understanding the data assets, understanding what they can do with it, and using self-service-type tools that Jay was referring to. >> And all of that underpinned with the trust. If you don't trust your data, the data scientist is not going to know whether or not they're using the right thing. >> So, the ladder's great. Great way for people to figure out where they are, it's like looking in the mirror, on the organization. How early is this? What inning are we in? How do you guys see the progression? How far along are we? Obviously, you have some data, examples, some people are doing it end-to-end. What's the maturity look like? What's the uptake? >> Go ahead, Jay. >> So, I think we're at the beginning of a crest of a wave. As I say, there's been a lot of discussion so far, even if you compare this year's conference to last year's. A lot of the discussion last year was, "What's possible with AI?" This year's conference is much more about, "What are we doing with AI?" And I think we're now getting to the point where people can actually start to be productive and really start to change their business through that. >> Yeah and, just to add to that, I mean, the ladder to AI was introduced last year, and it has gained so much adoption in the marketplace and our customers, they're actually organizing their business that way. So, the Collect divisions are the database teams, are now expanding to Hadoop and Cloudera, and Hortonworks and Mongo. They're organizing their data governance teams around the Organize pillar, where they're doing things like data integration, data replication. So, I feel like the maturity of this ladder to AI is really enabling our customers to achieve it much faster than-- >> I was talking to Dave Vellante about this, and we're seeing that, you know, we've been covering IBM since, it's the 10th year of theCUBE, all ten years. It's been, watching the progression. The past couple of years has been setting the table, everyone seems to be pumping, it makes sense, everything's hanging together, it's in one group. Data's not one, "This group, that group," it's all, Data, AI, all Analytics, all Watson. Smart, and the ladder just allows you to understand where a customer is, and then-- >> Well, and also, we mentioned the emphasis on open source. It allows our customers to take an inventory of, what do they have, internally, with IBM assets, externally, open source, so that they can actually start to architect their information architecture, using the same kind of analogy. >> And an opportunity for developers too, great. Julie, thanks for coming on. Jay, appreciate it. >> Thank you so much for the opportunity, happy Valentine's Day! Happy Valentine's Day, we're theCUBE. I'm John Furrier, Stu Miniman here, live in San Francisco at the Moscone Center, and the whole street's shut down, Howard Street. Huge event, 30,000 people, we'll be back with more Day Four coverage after this short break.

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Run. Welcome back to the Cubes live coverage here in San Francisco. Mosconi North while you're here as part of our exclusive covers. The Cube for IBM think twenty nineteen, their annual conference of customers and employees coming together to set the agenda for the next year. For IBM and its ecosystem. I'm John for a student. Um, in day. Volonte and Lisa Martin co hosting all week This week. Four days of wall to wall coverage. Day two of our kind Really Day one of the show Kickoff. We're here ending out that day and just had the CEO's keynote, and we're going to a review and analysis. David's do. We had a lot of interviews. Coming up to this theme is pretty clear. It's a I cloud and everything else going underneath that classic development application. Developers, developers in general, making applications That's classic, but eyes the big story. And, like like Always Cloud and the promise of Where That's Going, which is hybrid and multi cloud Dave, You set on the keynote. Any surprises from Ginny Rometty? >> I wouldn't say there were any surprises. First of all, I like Jenny. I think she she's a great presenter. I'd like to hang out with their like we were kids. That was what I wanted to hang out with us. He's a time person. I think I would feel comfortable talking to, you know, sports or business. She looked good. She had a really nice, sharp white suit on. She's self deprecating. She was drinking Starbucks. You know, they're obviously a client of IBM. I got the best moment was when Jim White hearse came on stage. He said, It's great to be here So he was like, Yeah, given thirty four billion reasons why it's great to be here kind of thing, So that was pretty funny. And she had. She made the comment. We've been dating Red Hat for twenty years before we decided to get married. She was trying to make a case You normally in Jenny's presentation, she she makes a really solid, puts forth the solid premise and then sort of backs it up with her guests. Today, I thought her premise, which was we're entering Chapter two. It's all about scaling and embedding a I everywhere. It's about hybrid. It's about bringing mission critical APS, you know, move those forward. And she had a number of other lessons learned. I thought she laid it out, but I think it sort of missed the back end. I don't think they punctuated the tail end of Jenny's talk. The guests were great and they had guys on from Kaiser Permanente E. T. And they were very solid. Well, think they made the case as strong as the premises that she put forward. And you know, we could talk more about that. >> And Stewart see red hat on stage. We've been commenting. We've been analyzing the acquisition of Red Hat, big number, thirty four billion dollars critical point you guys talk about in your opening on day one, the leverage they need to get out of that. This is the Alamo for them with the cloud. In my opinion, IBM is a lot to bring to the bear in the cloud. They I anywhere telegraphs that they wanna have their stuff with containers and multiple clouds. They want to be positioned as a multi cloud company but still have their cloud, providing the power for the workload. That makes sense, right? Bm. This is their last stand. This is like, you know, the Alamo for them. They They need to make cloud work right now. Watson, move from a product or brand ballistically open step. Is it tied together? Stew your thoughts on open stack and how this fits into their narrative. >> So I think you mean open shift, right, John s o from red hat standpoint. Absolutely what they're doing. They are involved in open stack, but open stack. You got a small, >> but they're one of the few that are sanguine on Open, Zachary read. >> I mean, read had open shift. My bad >> way it absolutely. And it is complicated in the multi cloud world and lots of different pieces. We've had a number of conversations with the IBM people that have worked with side by side, red hat in the open source communities, IBM, no stranger to open source and a CZ we talked about in our open on yesterday. It's the developers is really what where IBM needs to go and where Red Hat has a bevy of them on DH John. What you said about Multi Cloud? Absolutely. It's if IBM thinks that buying Red hat will make them the Goebel Global player in Cloud. I think that's wrong, and I don't think that's what they're doing. When I wrote a block post when it came, and I said, Is this move going to radically change the cloud landscape? No. Can this acquisition radically change IBM and change the trajectory of where they fit into Multi cloud? Absolutely. So there's cultural differences. We had Ah, Stephanie sheriffs on who's a longtime IBM er who now runs the biggest business inside of Red Hat. And she talked about the passion of open source. This is not lip service. I've many friends that have worked for it. Had I've, you know, worked with them, partner with them and cover them for most of those twenty years on DH? Absolutely. You've got over ten thousand people that are passionate involved in communities on DH. When you talk about the developer world, you talk about the cloud native world. This is what you know. Really. Red Hat moment has been waiting. >> It was interesting. John and I would like one if you could comment on this is you hearing IBM? Jenny talked about Chapter two. She took a digital reinvention. Here's yet another company using the reinvent terminology. I think that's what sort of pointed she talked. About forty percent of the world is going to be private. Sixty percent is going to be public Cloud. The sort of that's the first time I've heard those that she said It's flipped if you're ah, regulated industry. But what do your thoughts on people essentially using and Amazons narrative on reinvention? >> Everyone's using Amazons narrative. Here's the bottom line. Amazon is winning impact large margins. I think the numbers airway skewed in the favor of the people trying to catch up. I think that's more of a game. If vacation by the analyst firms, Amazon is absolutely blowing away the competition when it comes to public loud. The only game at the table right now for the Oracle's, IBM, Sze and Microsoft and Google is the slow down the adoption of Amazon. And you see the cloud adoption of Amazon, whether it's in the government sector, which I think is more acute. And Mohr illustrative, the Jet I contract a ten billion dollar contract. That is a quote sole source deal. But it was bid as a multi source deal means anyone could bid on it. Well, guess what? That is a going to be an award and probably to Amazon as the sole winner because IBM doesn't have the certification. Nor does Microsoft notice Oracle. Nobody's got Amazons winning that, and that begs the argument. Can you use one cloud? And the answer is Yes, you can. If the APP worked, Load works best for it, and procurement does not decide output for the cloud. For example, if it's a Jet I contract, it's a military application. So, like a video game, would you want to play a video game and be lagging? Would you want our military to be lagging? Certainly, the D O d. Says no. So one cloud makes sense. If you're running office three sixty five, you want to use azure. So Microsoft has taken that, and their earnings have been phenomenal by specialising around their workloads. That makes sense for Azure, and they're catching up. IBM has an opportunity to do the same for their workload. The business workload. So aye, aye, anywhere is interesting to me. So I think this is a good bet. If they can pull it off, that's the strategy, and the world will go multi cloud, where certain clouds will be sold for the apple sole source for the workloads. That makes sense for those workload. So this is where the market's going, right? So this whole notion of there won't be multi class. It's going to be multi cloud and it's gonna winner, winner take most. And the game right now is to stop ama's. That is clearly the case, and you're seeing it in the bids you see in the customer base. And IBM is catching Oppa's fast as they can. They got the people and the technology. The question is, how much do they catch up and level up? Tamas on? >> Well, stew despite Jenny, you know, invoking the reinvent terminology, they're her. Kino was starkly different than what you would expect from an Amazon Kino. They may. She mentioned a couple of the announcements, Watson anywhere, which, by the way, is about time. It's about time that Watson ran on other people's clouds of it, which should have been a while ago and in hyper protect is the world's most secure cloud. But we don't have any really details on that. And then I'd be in business automation with Watson, and that was really it. I think it was by design not to give a big product pitch, you know, very non Steve jobs. Like very done, Andy Jazzy like which is all product product product. I mean, kind of surprising in a big show with all these customers. You think they'd be pitching, but I think their intent was to really be more content. Orient >> Well, So Dave, you know, goes back at the core. What is IBM's biggest business? IBM biggest businesses. So services. So I've done a number of interviews this week already talking about how IBM is helping with digital transformation, how they're helping people move to more agile and development for environments. You know, the multi cloud world. How do they know IBM has a long history with C. S, P s and M s peace? So they have large constituencies And sure, they have products. You know, great stuff talking about, You know, how do they have the best infrastructure to run your workloads and the strength that they haven't supercomputing in HPC. And how they can leverage that? Because IBM knows a thing or two about scale. But, you know, Dave, one of the questions I have for you is we've seen the big services organizations go through radical downsizing. You know, HP spun off their business. Del got rid of the Perot business. You know, IBM still is, you know, services. At its core, it is IBM built for the multi cloud cloud native. You know, Ai ai world, Or do they still need to go through some massive changes? >> Well, multi Cloud is complicated and complex. IBM does complicated services, you know, deal with complexity, but I still can't help but feel like, >> Well, I well, I thought, wouldn't comment on them. I think the services. If the Manual Services Professional Services dropped down, IBM has a great opportunity to move them to cloud based services, meaning I can write software. And this is where I think they have an advantage. They could really nail the business applications, which will become services, whether its domain expertise in a vertical. And I think this is their cloud opportunity. IBM could capture that they could take entirely new category of applications. Business applications and services, automate them with machine learning, automate them with cloud scale their cloud scale while making them portable on multiple clouds. So the notion of services will be the professional services classic your grandfather's services, too. Cloud based services at scale. >> Yeah, well, I think you're right. Look, that's one. IBM is biggest strengths, and Jenny did that acquisition. By the way. The PwC acquisition is one hundred thousand. People instantly brought IBM into that deep vertical industry expertise, and they're not going to give that up any time soon. And this so many opportunities to code. If I those services or that song you know, through software and make them repeatable services, I mean, they're at as a service. Business is one of the fastest growing parts of IBM, you know, revenue stream. So I don't see that going. Wait. All I do think there was a missed opportunity and maybe they can't talk about it for was some regulatory reason. They're just paranoid. But you had white hearse up on the stage. You just spent thirty four billion dollars. I would have liked to hurt Mohr about the rationale, even though we've heard it before. They did. You know, Jim and Jeannie did a tour there on all the big TV shows You're on Kramer. But I would have liked to heard sort of six months on what that rationale is and how they're going to help transform with this in this new chapter and what that role that red hat was going play, I thought it was a missed opportunity. >> Well, speculate on that. I think of things. Probably. They probably don't have their answer yet. IBM is very good on messaging. You know, they're pretty tight, but I think Arvin Krishna talked to assert this morning. On our first interview. He brought up the container ization and Coburn Eddie's trend. I think that's where red hat fits and melons and give them cloud Native developers in Enterprise Fortune one thousand. They also got the cloud native ecosystem behind that the C in C F etcetera. But Containers does for Legacy Container ization, and Cooper daddies really preserves legacy. It allows developers to essentially keep the old while bringing in the new and managing the life cycle of those applications, not a ribbon replace. This is an opportunity for IBM, and if I think the messaging folks and the product dies or probably figure out okay, how do we take the red hat and open shift and be cloud native and take all the goodness that comes in with cloud Native the new developers, the Devil Infrastructures code, make under the covers infrastructure programmable and is Rob Thomas pointed out, having horizontal data layer that enables new kinds of business services. So to me, container ization, it's kind of nerdy Cooper netease. But this is really a new linchpin to what could be a sea change for IBM in terms of revenue. Keeping the Legacy customs happy because then the pressure to move to Amazon goes away because I can say, Whoa, wait. If the question is, why adopt if customs have an answer for that that gives IBM time, This is what they want otherwise, cloud native worlds could move very, very fast. We've seen the velocity of the momentum, and I think that's a key move. >> I think your point about slowing down the Amazon momentum is a good one, and I want to talk about five things that Ginny said that lessons learned, she said. One. You can approach the world from outside in and focus on customer experience. Or you could do inside out, identify new ways to work and new work flows, you know, kind of driving change. The third lesson learned was You need a business platform fueled by data with invented A I. The fourth is you need an ai ai platform. And in the fifth is Rob Thomas is you can't have a eye without a word that you needed information, architecture, which, by the way, I believe it to be true. So those are business oriented discussions. It's not something that you necessarily here from Amazon there kind of chewy. There's the services component to all that. The big question I have is Well, Watson, be that ai ai platform. >> Yeah, I mean something, You know, I look at is why Doe I choose a platform and a partner. So we understand Amazon, you know, they want to be the leader and everything. They have a lot more services in anyone. But, you know, if I want data services, first cloud that comes to mind to me is Google. You know, Google has a real strength there, You know. Where does IBM have a leadership compared to Google business productivity? IBM has a lot of strength there, but Microsoft also has a place so you know, customers. If they're going to live, Multi cloud, they're going Teo in many ways go backto best of breed on DH. Therefore, where will IBM differentiate themselves from some of those? >> We have visibility down. It's clear now that the industry the fog is lifting, starting to see Cem clear lines of sight and a few major trends. And it's pretty clear on where the industry's going for the next ten years. Application developers at the top of the stack gonna build APS The infrastructures cloud cloud something multi cloud cloud, native infrastructures, code and data. And a I see that Amazon reinvent sage maker. You're seeing all the major innovations happening around APS using data power advice, cloud scale, that's it. Everything else to me is glue or some sort of fabric component. Or a piece of that distributed architecture and its cloud. Aye, aye, and an apple. >> A CZ. Dave is often said, it's the innovation sandwich of today. >> Yeah, well, so I guess the things I want to mention it because of me. There's been some high profile failed failures with Watson, But watching was trying to do some things that were not, you know, voice response to Alexa, you know, solve cancer, you know, world problems and so I think IBM is actually earned the right to be in the discussion, and the Red had acquisition gives IBM instant credibility in this game, especially in this a multi cloud game. >> Well, they got me. They have the right to be the zillions of customers. They have a lot of a lot of business model innovations with that that their customers are innovating on. And if they keep the cloud innovate, they gotta match the specs. Specs of the cloud. They gotta be there with Cloud. If they don't make the cloud work, they're going to be subservient to the other clouds. They have to make it in the top three. This is clear. Hey, I think I think we're working a lot of experience and data. I think Watson kind of finding his home is a brand's natural fit. Got a portfolio of data? I think IBM will do very well in the data front. It's the cloud game that they got a really sure up. They got to make sure that IBM cloud conserved. They're custom, >> but the good news is there is there. In the game we saw HPD tried to get into HPD, tried to get the cloud it failed. Cisco, for a while, was trying to get with Sawyer. AMC make of numerous attempts. VM were made, made numerous attempts. IBM spent two billion dollars in software. They they they've got a cloud. You know, they've transformed what was essentially a bare metal hosting platform, you know, into a cloud. They've jammed all there as a service products in there. They're SAS portfolio. So there, at least in the game and, you know, again, I've said often, I think they're very Oracle like it's not the biggest cloud. It's not going to scale to the Amazon levels, but they've got a cloud, and it's a key part of the strategy. >> Innovation Sandwich applications Cloud What data? In the middle of a I. That's the formula, David said on the Q beer. All right day to coverage for the Cuba. Four days were here in the lobby of Mosconi North, part of the new refurbished Mosconi Center in San Francisco. Howard Street's closed. It feels like Salesforce. Dreamforce event. Big event in San Francisco. I'm John First Amendment Dave along. They were here for four days Day, two of four days of coverage for IBM think back tomorrow. Thanks for watching.

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Hello and welcome back to the Cubes. Live coverage here and savor still were alive for IBM. Think twenty nineteen. The Cubes Exclusive contract. Jon for a stimulant in our next two guests of the Cloud gurus and IBM and VM Where A. J. Patel senior vice president general manager Cloud Providers Software Business Unit. Good to see you again. Baron. Scram A general manager. IBM Cloud Guys. Thanks for Spend the time. Get to the cloud gurus. Get it? They're having What's going on? Having privilege. Osti Cloud's been around. We've seen the public Cloud Momentum hybrid Certainly been around for a while. Multi clouds of big conversation. People are having role of data that is super important. Aye, aye, anywhere you guys, an IBM have announced because I've been on this. I'm on >> a journey or a >> library for awhile. On premise. It was on VM, where all the good stuff's happening. This the customers customers want this talk about the relationship you guys have with IBM. >> You know, the broad of'em were IBM relationship over nine, ten years old. I had the privilege of being part of the cloud the last couple years. The momentum is amazing. Over seventeen hundred plus customers and the Enterprise customers, not your you know, one node trial customer. These are really mission critical enterprise customers using this at that scale, and the number one thing we hear from customers is make it easy for me to leverage Plowed right, operate in the world when I'm using my own prim and my public cloud assets make it seamless, and this is really what we've talked about a lot, right? How do we provide that ubiquitous digital platform for them to operate in this hybrid world? And we're privileged to have IBM Of the great partner in this journey >> are some of the IBM cloud, Ginny Rometty said on CNBC this morning. We saw the interview with my friend John Ford over there. Aye, aye. Anywhere means going run on any cloud. Watson with containers. That's cloud DNA. Sitting the cloud with good Burnett ease and containers is changing the game. Now you can run a lot of things everywhere. This's what customers want. End to end from on. Premise to wherever. How has that changed the IBM cloud posture? Its products? You share a little bit of that. >> You absolutely so look I mean, people have their data in different places, and as you know, it's a really expensive to move stuff around. You gotta make sure it's safe, etcetera, So we want to take our applications and run them against the data wherever they are right? And when you think about today's landscape in the cloud industry, I think it's a perfect storm, a good, perfect storm and that containers and Kubernetes, you know, everyone's rallying around at the ecosystem that consumers, the providers. And it just makes us easy for us to take that capability and really make it available on multicloud. And that's what we're doing. >> to talk about your joint customers. Because the BM where has a lot of operators running, running virtually change? For a long time, you guys have been big supporters of that and open source that really grew that whole generation that was seeing with cloud talk about your customers, your mo mentum, Howyou, guys air, just ballpark. How many customers you guys have together? And what if some of the things that they're doing >> all right? So I know this is a really interesting story. I was actually away from IBM for just over two years. But one of the last things I did when I was an IBM the first time around was actually start this Veum where partnership and seated the team that did it. So coming back, it's really interesting to see the uptake it's had, You know, we've got, like, seven hundred customers together over seventeen hundred customers. Together, we've moved tens of thousands of'em workloads, and as I just said, we've done it in a mission. Critical fashion across multiple zones across multiple regions. On now, you know, we want to take it to the next level. We want to make sure that these people that have moved their basic infrastructure and the mission critical infrastructure across the public cloud can extend those applications by leveraging the cloud near application that we have on our cloud. Plus, we want to make it possible for them to move their workloads to other parts of the IBM ecosystem in terms of our capabilities. >> Any one of the things we found was the notion of modernizer infrastructure, first lift and then transform. He's starting to materialize, and we used to talk about this has really the way the best way to use, cowed or use hybrid cloud was start by just uplifting your infrastructure and whether it's west back, you ask for some customers. I respect a great example. I think that we're talking about it in the Parisian. I joined presentation tomorrow or you look at, you know, Kaiser, who's going to be on stage tomorrow? We're seeing industries across the board are saying, You know, I have a lot of complexity sitting on aging hardware, older versions of infrastructure software. How do I modernize A platform first lifted, shifted to leverage a cloud. And then I could transform my application using more and more portable service that'S covering decides to provide a kind of infrastructure portability. But what about my data, Right. What about if I could run my application with the data? So I think we're starting to see the securing of the use of cloud based on workloads and averaging that's that's >> Yeah, a J. What wonder if we could dig a little love level deeper on that? Because, you know, I think backto, you know, fifteen years or so ago, it was bm where allowed me to not have to worry about my infrastructure. My, you know OS in my you know, server that I was running on might be going end of life. Well, let me shove it in a V M. And then I couldn't stand the life, and then I can manage how that happens. Course. The critique I would have is maybe it's time to update that that application anyway, so I like the message that you're saying about Okay, let me get a to a process where I'm a little bit freer of where, and then I can do the hard work of updating that data. Updating that application, you know, help us understand. >> It's no longer about just unlocking the compute right, which was worth trying the server. It's What about my network we talked about earlier? Do I need a suffered If our network well, the reality is, everything is going programmable. If you want a program of infrastructure, it's compute network storage all software defined. So the building block for us is a suffer to find data center running on the infrastructure that IBM pride sixty plus data centers bare metal at Scholastic and then leering that with IBM cloud private, whether it's hosted or on premise, fear gives you that full stack that nirvana, the people talk about supportable stack going, talk about >> right and adding to what he said, right? You said, You know, it's not about just moving your old stuff to the to the cloud. Absolutely. So as I said in one of the earlier conversations that we have, we had is we have a whole wealth of new services, whether it's Blockchain R. I o. T or the that used. You spoke about leveraging those capabilities to further extend your app and give it a new lease of life to provide new insights is what it's all about. >> What? Well, that that that's great, because it's one thing to just say, Okay, I get it there. Can I get better utilization? Is that change my pricing? But it's the services, and that's kind of the promise of the cloud is, you know, if I built something in my environment, that's great and I can update and I can get updates. But if I put it in your environment, you can help manage some of those things as well as I should have access to all of these services. IBM's got a broad ecosystem can you give us? You know what are some of the low hanging fruit is to people when they get there, that they're unlocking data that they're using things like a I What? What What are some of the most prevalent services that people are adding when they go to the IBM clouds? >> So when you look at people who first moved their work list of the cloud, typically they tend to dip their toe in the water. They take what's running on Prem. They used the IRS capabilities in the cloud and start to move it there. But the real innovation really starts to happen further up the stock, so to speak. The platform is a service, things like a II OT blocked and all the things that I mentioned, eso es very natural. Next movement is to start to modernize those applications and add to it. Capability is that it could never have before because, you know it was built in a monolith and it was on prim, and it was kind of stuck there. So now the composition that the cloud gives you with all of these rich services where innovation happens first, that is the real benefit to our customers. >> Every she said, you took a little hiatus from IBM and went out outside IBM. Where did you go and what did you learn? What was that? Goldman Jack. JP Morgan, Where were you? >> So it was a large bank. You know, I'm not not allowed to say the name of the bank. >> One of those two. It >> was a large bank on, and it wasn't the U S. So that narrows down the field. Some >> What is it like to go outside? They'll come inside. U C Davis for cutting edge bank. Now you got IBM Cloud. You feel good about where things are. >> Yeah. You know, if you look at what a lot of these banks are trying to do, they start to attack the cloud journey saying we're going to take everything that ran in the bank for years and years and years. And we're going to, you know, make them micro services and put them all on public cloud. And that's when you really hit the eighty twenty percent problem because you've got a large monolith that don't lend themselves to be re factored and moved out. Tio, eh, Public cloud. So you know again, Enter communities and containers, etcetera. These allow you a way to modernize your applications where you can either deploy those containerized You know, piers you go type models on prim or on public. And if you have a rich enough set of services both on Prem in on the public loud, you can pretty much decide how much of it runs on Trevor's is becoming much more clouds >> moment choice. So really, it's finding deployment. So basically, what you're saying is that we get this right. I want to get your reaction. This You don't have to kill the old to bring in the new containers and Cooper netease and now service measures around the corner. You can bring in new work clothes, take advantage of the cutting edge technology and manage your life cycle of the work loads on the old side or it just can play along. I >> think what we're finding is, you know, we moved from hybrid being a destination to an operating model, and it's no longer about doing this at scale like my multi clark. Any given applications tied to a cloud or destination? It's a late binding decision, but as an aggregate. I may be amusing multiple close, right. So that more model we're moving to is really about a loving developer. Super your workload centric and services centric to see Where do I want to run in Africa? >> Okay, what one of the challenges with multi cloud is their skill sets. I need to worry about it. It can be complex. I want to touch on three points and love to get both your viewpoints, networking, security and management. How do we help tackle that? Make that simple >> right off customers? >> Yeah, sure. So you know, I think when you think about clouds, public clouds especially it's beyond your data center and the mindset out there as if it's beyond my data center. It can be safe. But when you start to build those constructs in the modern era, you really do take care of a lot of things that perhaps you're on Prem pieces that not take into consideration when they were built like many decades ago. Right? So with the IBM public Cloud, for example, you know, security's at the heart of it. We have a leadership position. There was one of the things that we've announced is people keep protect for not only Veum, where workload visa and we sphere etcetera, but also for other applications making use off our public cloud services. Then, when you talk about our Z, you know we have a hardware as security model, which is fifty one forty, level two or dash to level four, which nobody else in the industry has. So when you put your key in there on ly, the customer can take it out, not him. Azaz clouds of his providers can touch it. It will basically disintegrate, you know, sort of speak >> H ey. Talk about VM wears customer base inside the IBM ecosystem. What's new? What should they pay attention to? As you guys continue the momentum. >> So I think if you look at the last two years, it's been around what we call these larger enterprise. Dedicated clouds. Exciting thing in the horizon is we're adding a multi tenant IRS on top of this BM, we're dedicated. So being able to provide that Brett off access thing with dedicated multi tenant public out I, as fully programmable, allows us to go downmarket. So expect the customer kind of go up being able to consume it on a pay as you go basis leveraging kind of multi tenant with dedicated, but it's highly secure or for depth test. So are the use cases kind of joke. We're going to see a much larger sort of use cases that I'm most excited about >> is the bottom line. Bottom line me. I'm the customer. Bottom line me. What's in it for me? What I got >> for the customers with a safest choice, right? It's the mission critical secure cloud. You can now run the same application on Prem in a dedicated environment in public, Claude on IBM or in a multi tenant >> world. And on the Klaxon match on the cloud sign. I could take advantage of all the things you have and take advantage of that. Watson A. I think that Rob Thomas has been talking about Oh yeah, >> absolutely. And again. You know the way that we built I c P forty, which is IBM plowed private for data. You know, it's all containerized. It's orchestrated by Coop, so you can not only build it. You can either run it on crime. You can run it on our public loud or you can run it on other people's public clouds as well >> nourished for customers and for people. They're looking at IBM Cloud and re evaluating you guys now again saying Or for the first time, what should they look at? Cloud private? What key thing would you point someone to look at, IBM? They were going to inspect your cloud offering >> so again, and it's back to my story in the bank. Right? It's, uh you can't do everything in the public cloud, right? There are just certain things that need to remain on creme On. We'll be so for the foreseeable future. So when you take a look at our hybrid story, the fact that it is has a consistent based on which it is built on. It is a industry standard open source base. You know, you build your application to suit the needs of an application, right? Is it low lately? See, Put it on. Crim. You need some cloud Native services. Put it on the public cloud. Do you need to be near your data that lives on somebody else's cloud? Go put it on their cloud. Right. So it really is not a one. Size fits all its whatever your business >> customer where he is, right? That's often >> the way flexibility, choice, flexibility. Enjoy the store for all things cloud. >> Yeah, last thing I want to ask is where to developers fit in tow this joint Solucion >> es O. So I think the biggest thing is that's trying to change for us is making these services available in a portable manner. When do I couldn't lock into the public cloud service with particular data and unlocking that from the infrastructures will be a key trend. So for us, it's about staying true to Coburn eddies and upstream with the distribution. So it's portable for wanting more and more services and making it easy for them to access a catalogue of services on a bagel manner but then making operation a viable. So then you're deployed. You can support the day two operations that are needed. So it's a full life cycle with developers not having to worry about the heavy burden of running an operating. What >> exactly? You know, it's all about the developers. As you well know in the cloud world, the developer is the operator. So as long as you can give him or her, the right set of tools to do C. I C. Dev ops on DH get things out there in a consistent fashion, whether it is on a tram or a public cloud. I think it's a win for all. >> That's exactly the trend We're seeing operations moving to more developers and more big time operational scale questions where your programming, the infrastructure. Absolutely. Developers. You don't want to deal with it >> and making it work. Listen tricks. So you know when to deploy. What workload? Having full control. That's part of the deployment >> exam. Alright, final question. I know we got a break. We're in tight on time. Final point share perspective of what's what's important here happening. And IBM. Think twenty nineteen people who didn't make it here in San Francisco are watching. You have to top cloud executives on VM wear and IBM here as biased towards cloud, of course. But you know, if you're watching, what's the most important story happening this week? What's what's going on with IBM? Think Why is this conference this week important? >> I think for us, it's basically saying We're here to meet you where you are, regardless, where you on your customer journey. It's all about choice. It's no longer only about public Cloud, and you now have a lot of capably of your finger trips to take your legacy workloads or your neck, new workplace or any app anywhere we can help you on that journey. That would be the case with >> you, and I wouldn't go that right, said it slightly differently. You know, a lot of the public service of public cloud service providers kind of bring you over to their public loud, and then you're kind of stuck over there and customers don't like that. I mean, you look at the statistics for everybody has at least two or more public clouds. They're worried about the connective ity, the interoperability, the security costs, the cost, the skills to manage all of it. And I think we have the perfect solution of solutions that really start Teo. Speak to that problem. >> So the world's getting more complex as more functionalities here, Software's gonna distract it away. Developers need clean environment to work in programmable infrastructure. >> And you know where an IBM Safe Choice, choice, choice. >> We have to go on top to cloud executives here. Inside the cue from IBM of'em were bringing all the coverage. Was the Cube here in the lobby of Mosconi North on Howard Street in San Francisco for IBM? Think twenty. Stay with us for more coverage after this short break. Thank you. Thank you.

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Okay. Welcome back, everyone. He live in San Francisco. Here on Mosconi St for the cubes. Exclusive coverage of IBM. Think twenty nineteen. I'm Jeffrey David Long. Four days of coverage bringing on all the action talking. The top executives, entrepreneurs, ecosystem partners and everyone who can bring the signal from the noise here on the Q and excuses. Rob Thomas, general manager, IBM Data and a I with an IBM Cube Alumni. Great to see you again. >> Great. There you go. >> You read a >> book yet? This year we've written ten books on a data. Your general manager. There's >> too much work. Not enough time >> for that's. Good sign. It means you're working hard. Okay. Give us give us the data here because a I anywhere in the center of the announcements we have a story up on. Slick earnings have been reported on CNBC. John Ford was here earlier talking to Ginny. This is a course centerpiece of it. Aye, aye. On any cloud. This highlights the data conversation you've been part of. Now, I think what seven years seems like more. But this is now happening. Give us your thoughts. >> Go back to basics. I've shared this with you before. There's no AI without IA, meaning you need an information architecture to support what you want to do in AI. We started looking into that. Our thesis became so clients are buying into that idea. The problem is their data is everywhere onpremise, private cloud, multiple public clouds. So our thesis became very simple. If we can bring AI to the data, it will make Watson the leading AI platform. So what we announced wtih Watson Anywhere is you could now have it wherever your data is public, private, any public cloud, build the models, run them where you want. I think it's gonna be amazing >> data everywhere and anywhere. So containers are big role in This is a little bit of a deb ops. The world you've been living in convergence of data cloud. How does that set for clients up? What are they need to know about this announcement? Was the impact of them if any >> way that we enable Multi Cloud and Watson anywhere is through IBM cloud private for data? That's our data Micro services architectural writing on Cooper Netease that gives you the portability so that it can run anywhere because, in addition Teo, I'd say, Aye, aye, ambitions. The other big client ambition is around how we modernize to cloud native architectures. Mohr compose herbal services, so the combination gets delivered. Is part of this. >> So this notion of you can't have a eye without a it's It's obviously a great tagline. You use it a lot, but it's super important because there's a gap between those who sort of have a I chops and those who don't. And if I understand what you're doing is you're closing that gap by allowing you to bring you call that a eye to the data is it's sort of a silo buster in regard. Er yeah, >> the model we use. I called the eye ladder. So they give it as all the levels of sophistication an organization needs to think about. From how you collect data, how you organize data, analyze data and then infused data with a I. That's kind of the model that we used to talk about. Talk to clients about that. What we're able to do here is same. You don't have to move your data. The biggest problem Modi projects is the first task is OK move a bunch of data that takes a lot of time. That takes a lot of money. We say you don't need to do that. Leave your data wherever it is. With Cloud private for data, we can virtualized data from any source. That's kind of the ah ha moment people have when they see that. So we're making that piece really >> easy. What's the impact this year and IBM? Think to the part product portfolio. You You had data products in the past. Now you got a eye products. Any changes? How should people live in the latter schism? A kind of a rubric or a view of where they fit into it? But what's up with the products and he changes? People should know about? >> Well, we've brought together the analytics and I units and IBM into this new organization we call Dayton ay, ay, that's a reflection of us. Seen that as two sides of the same coin. I really couldn't really keep them separate. We've really simplified how we're going to market with the Watson products. It's about how you build run Manager II watching studio Watson Machine Learning Watson Open scale. That's for clients that want to build their own. Aye, aye. For clients that wants something out of the box. They want an application. We've got Watson assistant for customer service. Watson Discovery, Watson Health Outset. So we've made it really easy to consume Watson. Whether you want to build your own or you want an application designed for the line of business and then up and down the data, stack a bunch of different announcements. We're bringing out big sequel on Cloudera as part of our evolving partnership with the new Cloudera Horn Works entity. Virtual Data Pipeline is a partnership that we've built with active fio, so we're doing things at all layers of the last. >> You're simplifying the consumption from a client, your customer perspective. It's all data. It's all Watson's, the umbrella for brand for everything underneath that from a tizzy, right? >> Yeah, Watson is the Aye, aye, brand. It is a technology that's having an impact. We have amazing clients on stage with this this week talking about, Hey, Eyes No longer. I'd like to say I was not magic. It's no longer this mystical thing. We have clients that are getting real outcomes. Who they II today we've got Rollback of Scotland talking about how they've automated and augmented forty percent of their customer service with watching the system. So we've got great clients talking about other using >> I today. You seen any patterns, rob in terms of those customers you mentioned, some customers want to do their own. Aye, aye. Some customers wanted out of the box. What? The patterns that you're seeing in terms of who wants to do their own. Aye. Aye. Why do they want to do their own, eh? I do. They get some kind of competitive advantage. So they have additional skill sets that they need. >> It's a >> It's a maker's mark. It is how I would describe it. There's a lot of people that want to make their own and try their own. Ugh. I think most organizations, they're gonna end up with hundreds of different tools for building for running. This is why we introduced Watson Open Scale at the end of last year. That's How would you manage all of your A II environments? What did they come from? IBM or not? Because you got the and the organization has to have this manageable. Understandable, regardless of which tool they're using. I would say the biggest impact that we see is when we pick a customer problem. That is widespread, and the number one right now is customer service. Every organization, regardless of industry, wants to do a better job of serving clients. That's why Watson assistant is taking off >> this's. Where? Data The value of real time data. Historical data kind of horizontally. Scaleable data, not silo data. We've talked us in the past. How important is to date a quality piece of this? Because you have real time and you have a historical date and everything in between that you had to bring to bear at low ladened psi applications. Now we're gonna have data embedded in them as a feature. Right. How does this change? The workloads? The makeup of you? Major customer services? One piece, the low hanging fruit. I get that. But this is a key thing. The data architecture more than anything, isn't it? >> It is. Now remember, there's there's two rungs at the bottom of the ladder on data collection. We have to build a collect data in any form in any type. That's why you've seen us do relationships with Mongo. D B. Were they ship? Obviously with Claude Era? We've got her own data warehouse, so we integrate all of that through our sequel engine. That thing gets to your point around. Are you gonna organize the data? How are you going to curate it? We've got data catalogue. Every client will have a data catalogue for many dollar data across. Clouds were now doing automated metadata creation using a I and machine learning So the organization peace. Once you've collected it than the organization, peace become most important. Certainly, if you want to get to self service analytics, you want to make data available to data scientists around the organization. You have to have those governance pieces. >> Talk about the ecosystem. One of the things that's been impressive IBM of the years is your partnerships. You've done good partners. Partnership of relationships now in an ecosystem is a lot of building blocks. There's more complexity requires software to distract him away. We get that. What's opportunities for you to create new relationships? Where are the upper opportunities for someone a developer or accompanied to engage with you guys? Where's the white spaces? Where is someone? Take advantage of your momentum and you're you're a vision. >> I am dying for partners that air doing domain specific industry specific applications to come have them run on IBM cloud private for data, which unleashes all the data they need to be a valuable application. We've already got a few of those data mirrors. One sensing is another one that air running now as industry applications on top of IBM Club private for data. I'd like to have a thousand of these. So all comers there. We announced a partnership with Red Hat back in May. Eventually, that became more than just a partnership. But that was about enabling Cloud Private, for data on red had open shift, So we're partnered at all layers of the stack. But the greatest customer need is give me an industry solution, leveraging the best of my data. That's why I'm really looking for Eyes V. Partners to run on Ivan clubs. >> What's your pitch to those guys? Why, why I should be going. >> There is no other data platform that will connect to all your data sources, whether they're on eight of us as your Google Cloud on premise. So if you believe data is important to your application. There's simply no better place to run than IBM. Claude Private for data >> in terms of functionality, breath o r. Everything >> well, integrating with all your data. Normally they have to have the application in five different places. We integrate with all the data we build the data catalogue. So the data's organized. So the ingestion of the data becomes very easy for the Iast V. And by the way, thirdly, IBM has got a pretty good reach. Globally, one hundred seventy countries, business partners, resellers all over the world, sales people all over the world. We will help you get your product to market. That's a pretty good value >> today. We talk about this in the Cube all the time. When the cloud came, one of the best things about the cloud wasn't allowed. People to put applications go there really quickly. Stand them up. Startups did that. But now, in this domain world of of data with the clouds scale, I think you're right. I think domain X expertise is the top of the stack where you need specially special ism expertise and you don't build the bottom half out. What you're getting at is of Europe. If you know how to create innovation in the business model, you could come in and innovate quickly >> and vertical APS don't scale enough for me. So that's why focus on horizontal things like customer service. But if you go talk to a bank, sometimes customer service is not in office. I want to do something in loan origination or you're in insurance company. I want to use their own underwriting those air, the solutions that will get a lot of value out of running on an integrated data start >> a thousand flowers. Bloom is kind of ecosystem opportunity. Looking forward to checking in on that. Thoughts on on gaps. For that you guys want to make you want to do em in a on or areas that you think you want to double down on. That might need some help, either organic innovation or emanate what areas you looking at. Can you share a little bit of direction on that? >> We have, >> ah, a unique benefit. And IBM because we have IBM research. One of their big announcement this week is what we call Auto Way I, which is basically automating the process of feature engineering algorithm selection, bringing that into Watson Studio and Watson Machine learning. I am spending most of my time figure out howto I continue to bring great technology out of IBM research and put in the hand of clients through our products. You guys solve the debaters stuff yesterday. We're just getting started with that. We've got some pretty exciting organic innovation happen in IBM. >> It's awesome. Great news for startups. Final question for you. For the folks watching who aren't here in San Francisco, what's the big story here? And IBM think here in San Francisco. Big event closing down the streets here in Howard Street. It's huge. What's the big story? What's the most important things happening? >> The most important thing to me and the customer stories >> here >> are unbelievable. I think we've gotten past this point of a eyes, some idea for the future we have. Hundreds of clients were talking about how they did an A I project, and here's the outcome they got. It's really encouraging to see what I encourage. All clients, though, is so build your strategy off of one big guy. Project company should be doing hundreds of Aye, aye projects. So in twenty nineteen do one hundred projects. Half of them will probably fail. That's okay. The one's that work will more than make up for the ones that don't work. So we're really encouraging mass experimentation. And I think the clients that air here are, you know, creating an aspirational thing for things >> just anecdotally you mentioned earlier. Customer service is a low hanging fruit. Other use cases that are great low hanging fruit opportunities for a >> data discovery data curation these air really hard manual task. Today you can start to automate some of that. That has a really big impact. >> Rob Thomas, general manager of the data and a I groupie with an IBM now part of a bigger portfolio. Watson Rob. Great to see you conventionally on all your success. But following you from the beginning. Great momentum on the right way. Thanks. Gradually. More cute coverage here. Live in San Francisco from Mosconi North. I'm John for Dave A lot. They stay with us for more coverage after this short break

>> Live from San Francisco, it's theCUBE. Covering IBM Think 2019. Brought to you by IBM. >> Welcome back to San Francisco, everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante and I'm with my cohost, Stu Minman, Lisa Martin is also here. John Furrier'll be up tomorrow. This is day one of IBM Think. Kind of the pregame, Stu. The festivities kick off tomorrow, they're building out the Solutions Center, they got Howard Street takeover. We're in Moscone North, stop by and see us. Daniel Berg is here. He's a distinguished engineer with IBM Cloud Kubernetes service IBM, of course. Dan, great to see you again. >> Thank you. Thank you very much. >> Thanks for coming on. So everybody's got a Kubernetes story these days. What's IBM's Kubernetes story? >> So, IBM has taken a big bet on Kubernetes, two, two and a half years ago. Never really looked back, it's our primary foundation for our platform services. And we have two key distributions for the Kubernetes service, we have IBM Cloud Private, which is a software distribution for on premises, set up your own private cloud based on Kubernetes, behind your firewall. And then we have a manage service in the public cloud. So you're moving to public cloud, doing cloud native, grab an API, CLI, you get a cluster. >> So a lot of people think Kubernetes, oh, I can be able to move it anywhere, private cloud, public cloud. But there are other benefits of just, say, for instance, a private cloud. Maybe explain those. >> Yeah, I mean the biggest benefit for us is that we're able to give you the IBM cloud experience and IBM cloud content, so IBM content, middleware, things that you've been using for a decade. We've modernized it, put it in containers, install it and manage it on Kubernetes. The nice thing is that content, you can bring on premises where it's needed the most, and run it in ICP, IBM Cloud Private, and also take that and run it in our public cloud, as you migrate and move those workloads into the public sector. >> Dan, one of the things we've been watching is, you talk about a hybrid cloud or a multi-cloud world. There's a lot of pieces and it can be complicated. >> Yes. >> Now, Kubernetes itself, not exactly the simplest solution out there, but when you can deliver it as a service, but you can take a certain piece of your environment and IBM helps to simplify that. Maybe explain what it simplifies and, you know, what still are some of the hard places that we have to play at in these environments? >> Yeah, definitely. So, I mean, the IBM cloud Kubernetes service, we, anyone that has dealt with Kubernetes knows it's easy to install , pretty easy to set up, and basically easy to get started. It's the day two, it's the operations, it's the long pull. It's doing all the updates, the maintenance, the security patches, the securing it. Making it highly available, that's hard. And that's hard over time, and it takes a lot of resources. So IKS is a service that, we do that. Let the experts do it, is basically what we tell people. We are experts at managing Kubernetes. We do this as our day job, 24/7, right? Literally, because we manage a 24/7 service. So we operate it 24/7 and we keep it updated. That allows our customers to focus on their business problem. Focus on their app, not building the platform. But there are still some complexities, because you have, you don't have just one cluster. If you only had one cluster, it'd be no big deal. I probably wouldn't have a job. But you have many clusters. You've got development clusters, you've got test clusters. But if you're doing a global service, you've got many clusters throughout the world. Highly available clusters. You put clusters in various data centers for keeping your data in one location, right? So you've got many clusters, so it gets complicated to manage all of those clusters. So, with Kubernetes service we provide all the capabilities to manage and set up and secure your cluster, but then the content, like, moving and configuring things across all those clusters, becomes complicated. And that's where we released recently a new product called Multicloud Manager. >> Tell us, you know, tell us more. (laughter) >> I thought you were going to ask a question. (laughs) So, Multicloud Manager, what it basically does is it provides a control plane that allows you to manage, and today it manages resources, Kubernetes resources, across many different clouds, across many different cloud platforms. So it works with our Cloud Private, which runs on premises, but it also works with our public cloud, IKS. And it can work with other cloud providers, it can work with Amazon, it can work with Google, it can work with Azure. And it works with OpenShift, as well, obviously. So those, having that one tool, then, gives you the mechanism to drive consistency of the resources across all of those distribution of Kubernetes clusters that you have. And another big thing that it does, and it helps with, is security compliance. So it has ability to define security postures that you need to have across your clusters, and then apply it and run it in both a check mode, to see is that policy, or, provided across all your clusters, and where do you have gaps? And then it also has a setting to do enforcement. So, if it's not there, it'll make it there, it'll make it so. >> So, IBM hides all that complexity from the customer. >> Yes. >> But I'm curious as to what the conversations are like, Dan, with the customer. In other words, you're basically figuring out how to do it. Customer knows what it's doing. Do you ever get into a situation, no, of course, at scale you wan consistency and standards. So, do you ever get into a situation where a customer says, well, I'd like you to do it this way, and what's that conversation like? >> Yeah, so that's where, and that's where it's nice having multiple distributions, right? So having, so in our public cloud with IKS, having variations and unique configurations for each and every customer, I don't, we don't do that, right? It's a service. And services scale and provide value by doing consistency, right? So we consistently set up and manage clusters, thousands of, tens of thousands of clusters that way. But if you need something that's highly, highly specific to a given use case or you have differences in your infrastructure that you need to have more flexibility, that's where IBM Cloud Private comes in. And we do have customers like, especially on premises, right? On premises, those ae unique beasts, right? The infrastructure, the hardware, the network. You got to have a custom configuration. So coupling our ICP production with global services team, they can come in and they can customize it to suit any customer's needs. >> So, Dan, you talked about living in multiple environments, whether that be public cloud, your private cloud, you also mentioned Red Hat, I think, in there. Tell us where customers are today with OpenShift, where that fits, and give as a little bit compare contrast as to what IBM's doing today. >> Yeah, definitely. So, and it's interesting, watching what's hapepening in the industry, because there's the whole push to cloud, and everybody knows they want to get there, but trying to get there all in one fell swoop with all the workloads that you have on premises is quite complicated and difficult and almost impossible to do on day one. So, the story is all about how do I modernize what I have today, on premises? And how does IBM help with that in my journey to move into public cloud? And that's where, I know it's a buzzword, but hybrid cloud comes in. But for me, the hybrid cloud, and what our customers are saying, is that I want to modernize what I have, so give me a platform there. And ICP, IBM Cloud Private, and OpenShift are the two best products in the market, bar none, that provide that experience there. And our ICP runs on top of OpenShift, so for those customers that have already been invested in the OpenShift space, you still get the value of IBM's content and integrated monitoring, integrated logging, right there in that product space, on the platform for which they're already standardized. >> How do you define best? What are the attributes of high quality and best? >> So, I guess best is (laughs) kind of difficult to really define. But for us it's all about ensuring that we have a solid platform, a solid strategy and technology set that we're building our offerings from. And we gain a lot of experience from our public cloud. Because we built and standardized on Kubernetes, we provide Kubernetes service, and we do that at scale and secure as well as highly available. We take a lot of those same lessons, because we have hundreds of customers running on it at scale. We take those lessons and we help evolve our private cloud offering as well. So we bring those down, we provide a very tuned somewhat customizable, but, highly tuned supporting IBM content in that environment. So when I say best, it is definitely the best platform for running IBM content, right? It's tuned for running IBM content, bare none. >> Okay, and my other question is, you know, you'd mentioned hybrid, said it was a buzzword, okay, fine. But at least we know what hybrid is. You got resources on pram, you've got resources in the public cloud, multi cloud is the other buzzword. Sometimes we worry that companies that are, vendors like yourselves going after this multi cloud opportunity, which is, you know, clearly a large opportunity and one that's needed, because I want a consistent way of managing at scale. But there seems to be a lot of different initiatives within organizations. There might be different lines of business, there might be, you know, international people. Are you seeing any hope or sense that the customer constituents are getting together? The different constituents saying, hey, this is the strategy that we want to use to manage all of our clouds. Or is sort of, you know, fiefdoms that are popping up? What do you see there? >> Yeah, so it's funny, when you do go into a large organization, a large enterprise. You're having a conversation, they've made a choice down one path using, let's say, IKS as an example. But then you realize you're having another conversation with another group that hasn't made any choices. I don't think that within an organization, within a large enterprise, coming together and saying we're all going to go down one path with one tool to rule them all. I just don't, I just don't see it, right? And also, even just going down the path of saying, I'm only going to stick and use one cloud vendor. That's also somewhat a thing of the past, you don't see that anymore, at least where customers are moving, so within an organization, yes, you still have the lines of businesses, and they might have different tools and they might decide on different tools and how they manage their environments. But the thing that customers do need to look at, and what they do need to standardize across an enterprise, is just some of the core tenets and the core technologies. So, for example, if they're moving the cloud, whether it's one premises or off premises, what's the platform that you're going to build to so you have portability? It's got to be Kubernetes, right? That is a decision that as an organization, as an enterprise, you've got to agree on as you move forward. Because, whether you use the same provider or the same set of tools doesn't matter as much. It'd be nice. But you got to have some agreement on the core technologies and platforms. >> Because ultimately you can get there. It might be a little harder, but still, if you're core Kubernetes, it's not, it's going to be easier than different flavors of UNIOS, for example. (laughs) >> There's path, >> there's at least a path that as they mature and as they simplify and they converge, they can do that seamlessly. >> Dan, back to the cloud monitoring tool that IBM has. Who's the constituency, who uses that? And give us a little bit of color inside, you know, kind of the administrator, developer, you know cloud architect, you know, what do you see? >> Well, yeah, so that's a great one. The cloud monitoring, IBM cloud monitoring provides visibility into your workloads within your environment. And that's not specific to just Kubernetes, either, right? There's Kubernetes, but then there's VMs and bare metal workloads, more traditional workloads that the monitoring service works just fine. The, our developers, have to have a monitoring solution. You can't build a cloud native solution without monitoring, right? Monitoring and log, they, it's like peanut butter and jelly. You got to have 'em. And if you're building a cloud native solution, you're building Kubernetes, you're dealing with multiple clusters, like I said earlier. Hundreds, if not thousands, of workloads. You can't log into each one of 'em. You need, you need a system where you can monitor and log. So the monitoring service is necessary here for simple developers to understand what's happening in their environment. And our partnership STEG provides us with a very rich monitoring solution, which we've done extensive integration in IBM cloud to make it simple for even developers. They don't have to go and install and set up STEG themselves. All they do is a simple I want a new instance. Directly in the IBM cloud catalog they get a new instance of STEG and it gets installed into their cluster and they're off and running. Simple as that. >> And we're talking, we're talking visibility on things like performance management, security? >> Network. >> Problem, change management. >> Yes, yes, absolutely. So you get, and obviously that's all configurable, but what's nice with STEG and one of the reasons I like it, especially as a developer, as soon as you turn it on for one of your clusters, there's so much rich data that's available there, just out of the box. And they support other projects too and provide integration, deep integration, like the Istio project, for example. Great little project for service mesh. STEG supports that out of the box as well. Built in polling metrics, dashboards built specifically for Istio, and I don't have to do anything as a developer. I just turn it on, and then I start watching. (laughs) Seeing all the metrics coming. >> So it's kind of day zero here at IBM Think. Dan, what are some of the things that you're hoping to accomplish this week? I know you've got a bunch of customer meetings. Some of the things you're excited about. >> Yeah, definitely, lots of sessions, great sessions. But it is the customer meetings I'm most excited about. I have a large number of 'em. I want to hear what they're doing, right? I want to understand a little bit better what they would like us to do, and moving forward, how can we help them? How can we help accelerate their adoption of cloud? Get on the cloud native, and obviously, I'm here to talk Kubernetes and containers, so the more I get to talk about that, the happier I'm going to be. >> Well, it's a hot space. We're bringing you theCUBE inside of our little container here. Dan Berg, thanks very much for coming on today. >> Thank you. >> All right, Dave Vellante for Stu Miniman. You're watching theCUBE from IBM Think, day one. We'll be right back right after this short break. (light music)

(techy music) >> Announcer: Live from Las Vegas, it's theCUBE, covering Dell Technologies World 2018. Brought to you by Dell EMC and its ecosystem partners. >> We're back in not-so-sunny Las Vegas. You're watching theCUBE, the leader in live tech coverage. We're here at day three, wall-to-wall coverage of Dell Technologies World, the Inaugural Dell Tech World. I'm here with Tom Sweet, who's the CFO of the 80 billion dollar Dell Technologies empire. Thanks for coming to theCUBE. >> Happy to be here. >> So, really thrilled to have you on. I think it's the first time you've been on theCUBE. >> You guys usually don't let me on, so you know, they're letting me out a little bit, I guess. >> Well, I say, we're happy to have you. So, a lot going on, obviously, in your business. I mean, let's start with, you know, we're a couple of years into the integration, you guys, obviously, you dug in. You've got a pretty good handle on this, like I said, 80 billion. When it started, you guys were in the low 70's, I believe, so you've seen some growth. Not a lot of growth in this business, but you guys are growing. So, give us the rundown of your business. How should we think about the Dell empire, as I called it? >> Look, I think that we're very happy with the progress that we've made since the integration, which was back in September of 16, so over the last 20 months, we've been focused on building velocity within the business, and particularly, as you think about our major tranches of product, if you will. So, you know, our client business is growing quite nicely, as we evidenced by last year, 21 consecutive quarters of share gain. Pleased with our server velocity. Last year, we were number one in servers. Storage has been a bit of a work in process, as you know, but I think we're beginning to see a little bit better velocity in that business. Clearly, we have VMware, and we have Pivotal. So, what's been really interesting is how the companies have come together, and the offerings have come together in a much more integrative fashion, which has been fun to watch and fun to sort of help put this thing together. The customer buy-in and the customer acceptance of the vision and the story has been pretty remarkable, from my perspective. >> And, the client's side of the business surprised me anyway. It's like the gift that keeps on giving. >> Well, you know, what was it, 10 years ago, they said the PC was dead, you know, and today it's roughly half of our revenue and growing nicely. I think the secret, as always, as you know, is work gets done on a keyboard. The tablet and the phone become an and device, a notebook and a tablet, a notebook and a phone. We keep innovating form factors or innovating the interfaces with the device, so we're pretty excited about it. It's just a really good, really great business for us. >> I think what Michael said in his keynote, when IBM announced the end of the PC era, since then there's been four, I think he said four billion PCs shipped. >> Yes, exactly. >> It's astounding. >> Clearly, the overall market for PCs is flat to slightly down, it's going to be in that range, but in that type of market, our point of view, as you well know, is you have to take share, you have to grow. The team's done a nice job. Jeff Clark and his product team have done a really nice job around form factor innovation, 87 CES awards this year for PCs, so really good business. >> And, from a CFO's perspective, it's throwing off cash, you're comfortable with, what is it, a 5% to 6% operating margin, basically? >> We typically think of that as about a 5% op inc business, but it provides huge amount of scale for us, if you think about our supply chain, our ability. It's a nice, predictable, really strong cash flow business for us, so it's a good business. >> And, the higher end, the server business and the storage business is what now, around 7% op inc, and there's a lot of upside there, potentially? >> Yeah, it's a little bit higher than that, but there is upside there as we continue to drive the business and drive efficiency in that business and, as you know, we're doing a lot of work right now in our storage area in terms of how, over time, do we evolve that road map around the solution set, and working more in an integrative fashion with VMware around the convergence of hardware and software, into more thoughtful and more smarter designs or in the storage platforms. So, you know, that business is, that's going to be a really interesting business for us over the next year or so. >> Well, really, VMware, people look at Dell as a hardware company, but VMware is not a hardware company. It's software, marginal economics. It throws off 50% roughly of your operating cash, I mean, it's a gem. >> We're actually huge fans of VMware. It's a great company, growing very nicely, and extraordinarily well-positioned, as you think about the world of Multi-Cloud. And, what we're doing and how they're thinking about any device to any device, any Cloud to any Cloud, that whole story is resonating, and from a CFO perspective, you got to like software margins. It's a good business. >> So, let's talk about the debt a little bit, because I think there are a lot of misconceptions out there. You paid down $10 billion in debt, I think it's roughly around 40 billion now. Is that about right? >> A little bit higher than that, because we've added some debt related to our GFS business, but I think the way you ought to think about our debt load is that very manageable, we're right on the schedule we thought we were going to be on, in terms of debt paydown, and we'll continue to pay down debt, from a capital allocation focus. You know, 60-70% of our capital is focused on debt paydown, doesn't mean we're not investing in the business properly, 'cause I think we are, and we're continuing to fuel those investments, and then we're going to add some debt, because our DFS, or financing business, we use debt to fund that business, but that's a little bit different sort of perspective. We think about that debt separately and different than the core debt of the business, and our analyst community and the credit rating agencies think about that debt differently. And the GFS business is growing very nicely in terms of originations, and it's a great tool for our sales force to help in terms of the financing capacity and credit capacity for our customers. So, it's a good business. >> And, let's talk taxes for a second. I know it's kind of off the normal CUBE interviews, but a lot of people talk about that. All the legislation tax, legislation, that's bad for Dell, you can't write off that debt, but essentially, from what I've read, it's a net neutral to you guys. >> It's generally neutral to maybe slightly negative, as we understand the debt regulatory environment today, with the US tax reform. They did put some limits on how much interest, and there's transition rules around how much you can deduct, but you know, you got to lower corporate tax rate in the US, you also have the immediate expensing of CapX, and then you've got the repatriation toll charge, but when you throw it all together, slightly negative, but it's not a big cash dynamic for us, it's not a driver of, geez, we've got to go do something with our capital structure as a result of that. So, that's just a misconception that's out there right now. >> And then, you've told me earlier that the Pivotal move was not about delevering, it was a move that you guys have been planning for a while. I mean, that was in the works before the merger. Talk about that. >> Look, I mean, Pivotal's done, their growth at Pivotal and the acceptance of Pivotal's been remarkable. So, that conversation around should we IPO, when should we IPO, has been in the works for over a year, and Pivotal needed to continue to grow and mature a little bit in some of its processes and making sure that when you decide to go public that you're ready to go public. For that last year, that's what they've been working on. But in terms of the actual, to go public and the proceeds from that, that's all about giving Pivotal their own capital to fund their business growth and dynamic. We could have done it at the Dell level, Dell technology level, but I thought it was more appropriate, the size of company they are, that they have their own capital. They're doing business with over half of the Fortune 500, so they need some substance, and it's a great retention to 'em, in terms of having currency for their employee base, for both their attracting talent and retaining talent. >> A Silicon Valley company with its own, I've visited those offices. It's not the normal corporate office down on Howard Street, right? >> No, you know, they're doing the huddles in the morning, but that's what's interesting about Dell technology, the family of businesses, the different cultures, the different capabilities, it's a pretty remarkable set of companies with it. >> The market's booming right now, hope it continues, knock wood here, but what are the assumptions you're making in your business, maybe the economy, you could touch on that. >> We look across the top 45 economies right now, where we do business. They're all growing, GDP's growing, so we feel pretty good about the overall economic environment. Interest rates are slightly rising, but not a big issue for us, even with our debt load. We're about, roughly 70% fixed, 30% floating, so the fact that LiveBoard's up a little bit isn't a big deal. Currency's relatively stable, so we're positive, and companies and institutions are spending on IT, the round of innovation that's being driven, the round of investments and the changes in business models. Typically, one of the first things they go do is they invest in IT to help with that digital transformation, that IT transformation. We're bullish on the economics, so it's a good platform for us. >> One of the things I've said for quite some time now is that the merger between Dell and EMC was inevitable. You had these pressures of Cloud, you needed a company who was comfortable, with a lower margin business and had a profitability model that could thrive, and it made a lot of sense. But, you don't have a public cloud, and you're comfortable with that, but you've done a lot of work with, I'll call, utility pricing. Can you talk about that a little bit? >> Well, one of the feedback things we got from our customers is, hey, look, I like the economics of the Cloud. I like this pay-as-you-consume, pay-as-you-grow, that flexibility to scale up, scale down, so through our Dell Financial Services and using our own balance sheet, we have put together flexible consumption models, so I can offer you a pay-as-you-grow, pay-as-you-consume, or we can do a straight out utility where the assets are on my balance sheet and you're paying a monthly fee, if you will. So, all we're trying to do there is to normalize the economics for our customers, say, hey, I want you to take economics out of your decision about whether you want to go to the Cloud or not, because we can offer that capacity and capability. And, let's really talk why, and what's the purpose, and what's the work load, what's the problem that you're trying to solve? >> And, you obviously recognize that as radical revenue. >> Yeah, absolutely. >> I'm guessing it's not meaningful, like a software company shifting from a perpetual model, or is it? >> Well, I think over time you're going to see the rise in these types of models. Customers are interested, as a service models. So, there is interest in that, and I think you'll see that piece of the business grow over time, but I don't think it's going to be a step function change. But, again, it's just another example, I think, of Dell Technologies offering customers what they want and in different and innovative ways to do business with us. >> One of the things that EMC did, was they did a lot of M&A. That's kind of how EMC innovated, no offense to my friends from EMC, but they fill gaps. And, a lot of times, those gaps created huge overlaps. You guys are addressing that carefully, I understand that. How has the merger, the debt, affected your ability to do M&A? How critical is that to you guys, because you are very acquisitive, obviously, as well? >> We are still very active, as we look at the technology trends and what type of capabilities and new technologies are on the horizon, so we haven't done a lot of M&A since the acquisition of EMC. We've principally focused on the integration, but if you look at VMware, they've done acquisition, we've done a couple of really small tuck-ins within the family, but we'll continue to look at that. And, one of the other tools in our tool chest, as you know, is Dell Technologies Capital. I think we've got roughly over 81 investments in technology startups, principally on the West Coast, but some overseas, and very focused on security, AI, machine learning, next-generation storage capabilities, and so we get exposed to that type of technology, and we put our R&D teams together with them, so I feel like we're in a reasonable position, and as the business tells me they need something, we'll go evaluate it. >> I want to ask you a question about your peers, the CFOs. I'm getting to know you a little bit. I think you're a rock star CFO. One of our analysts said to us the other day, Tom Sweet is a stud, I said, yeah, it's the make-up on theCUBE. >> I don't know about that. >> So, what's going on in the, well, you've got a big job, and you've got a really good handle on what's going on here. What's going on in the world of CFOs these days? I mean, obviously, you've got stuff like GDPR that gets in there, but digital transformation is obviously a huge theme among the C-Suite. Security is a board level issue. What kind of discussions are you having with your peers these days? >> Look, I mean, most of the conversations tend to be around two or three different areas. One is how do you think about how does the finance function and our capabilities change over the coming three, five years, right? How do you think about the use of AI, machine learning, and in the processes of the company? And, what is everybody doing to innovate around that? That's a pretty common conversation we're having. You know, security cyber is a huge conversation point in terms of how is your board looking at it, how are you thinking about it. Since we're CFOs, we're always talking about how much money, what's that investment profile you need to have there, in terms of what's the right amount? As you well know, you can spend a lot of money there. Are you guaranteed of a perfect defense? Absolutely not, so that tends to be a common area, but more importantly, there's this whole comment, this whole big data conversation that's also happening around how do you help the business make better decisions? How do you add and drive value back to the business? How are you using advanced analytics to drive insight back into the business, the various businesses? So, pretty much the same sort of conversations we're having with our customers, we're having internally, or amongst the CFO community. >> A lot of risk management, obviously, >> Yeah, absolutely, absolutely. >> goes into that equation. >> I mean, inside of tech or outside of tech, are there companies or CFOs that you sort of follow, admire, kind of models that you look at? >> Look, there's some great CFOs that I've had the opportunity to have interactions with. You know, Mark Hawkins at Salesforce is a great CFO, also a good friend, Amy up at Microsoft, really doing a really nice job up there, and then Bob Swan at Intel. So, we tend to sort of be industry-organized, just because that's how we interact, but they're all doing nice jobs and really interesting innovative things within the context of their companies' business models. >> Have you changed the sources of where you guys get information? Obviously, your peers is probably number one, but as the digital world comes forward, have you sort of changed the sources, or still sort of the Wall Street Journal every day? >> Well, it's guys like you, right? We're all watching the blogs and, look, the amount of data and information that's flowing these days can be overwhelming, so I tend to be, I'm looking at industry publications, I'm looking at some of the online blogs in terms of trying to understand where are our competitors headed, where is the industry headed, what are the themes out there? You know, Michael's got a perspective with his leadership team that, hey, he wants us out in front of customers, so I spend roughly 30% of my time with customers and partners. You have to be aware of, obviously, what's going around in the industry, not only to be thoughtful and intelligent, but to also help think about where do you position the company, three and five years down the road? And, helping Michael in that thought process, and helping the leadership team in that thought process. >> Well, Tom, it's been a real pleasure getting to know you a little bit, and watching you guys in action. Wish you best of luck. >> I appreciate it. >> Thank you so much for being on theCUBE. >> It was a lot of fun. >> All right. Keep it right there, buddy. We'll be right back with our next guest, right after this short break. You're watching Dell Technologies World, live on theCUBE. (techy music)

(clicking) >> Hey, welcome back everybody. Jeff Frick here with theCUBE. It looks like they're letting the general session out. We're here at the Professional Business Women of California Conference; 6,000 women, about 5% men really talking about, it's amazing, the 28th year. I've never been to this show about how women can get more inclusive and diversity and taking, executing on steps to actually make it happen as somebody said in the key note. It's not a strategy problem, it's an execution problem. So, we've got a great story here and we're really excited to have CUBE alumni, Andrea Ward. She's now the CMO of Magento Commerce. Welcome back, Andrea. >> Thank you so much, it's great to be here and great to be at this conference. The buzz is amazing and I was here two years ago and it's grown so much, just in the two years. >> How many people were there, they say it's 6,000, now. >> I mean, it looks like it's about doubled. I don't know what the numbers were two years ago but the participation is amazing and it's such a great opportunity for local businesses to bring employees from their companies, have them have a chance just to talk and learn from such powerful women. So, it's been a really great conference. >> And, it's also a cross of so many kind of verticals if you will, because you know we go to a lot of tech conferences. This is more kind of a cross industry with banking and insurance and, you know, United Airlines we talked to earlier. And so, it's a much more diverse kind of set. >> Absolutely, I mean the women on the panels this morning spanned legal professions, government, entertainment, business, really diverse issue and it's fantastic that women are coming together to support each other to help make a difference. >> So last we saw you, I think we were on the street on Howard Street a couple years back which was pretty exciting as well, but now your new company, Magento Commerce. So, for people who aren't familiar with the company, give them kind of the four-one-one. >> Yeah great, well Magento Commerce is a leading commerce technology platform for mid-size businesses. We have recently separated from Ebay about 15 months ago and are now a privately held company and we power about a third of the world's commerce, believe it or not. >> That is amazing. Yeah. >> A third of the world's eCommerce. >> That's right. So, it's a fantastic company. We're growing and a part of that growth is absolutely growing a more diverse workforce and we've been putting into place some initiatives since last year. >> Yeah, part of the key note conversations were, obviously, that you need to put goals down on paper and you need to measure them and I think it was Bev Crair from Intel talked about, you know, doing it across all the pay grades. It's not just in engineering or just on the board or just the executive ranks, but really all the way across and it sounds like you guys are executing that to really help you just grow the company generically. >> Well, we're in a very lucky position in that we're experiencing growth and so that gives us room to really go out and look for amazing talent across the board. And so, we put a focus on diversity and inclusion and by doing that, we've increased the percentage of women in all roles across the company by 50% and that's since last June. So I think, you know, really just what you said earlier about execution and putting some numbers and goals against that can really make a difference. >> Right, and if you hadn't had those, that execution detail you probably couldn't have grown that fast because let's face it, it's hard to get good talent. If you're not including a broader base of talent, you're not going to be able to achieve your goals. >> Well, that's right and I think that some of that is, I don't know if you want to call it unconscious bias or unintentional, we're used to hiring people that look like us, have experience like us. And so, by encouraging that diversity, it really has made us expand the pool of applicants, make sure that we're not going for the easiest choice or the simplest choice but really considering a wide range of candidates to fill those positions. >> You know, I don't the birds of a feather conversation comes up enough, it's just easy to go with what you're familiar with. So whether it's unconscious or not, it's just easy, people are busy, you want to check the box and get off to your next task. So, you have to take a step back and consciously do the extra work, take the extra effort. >> Well, in the industry we support, the industries we support are going through digital transformation, I mean, commerce is key and central to digital transformation. And, transformation and change means that you have to consider other perspectives. You need to learn from new ideas and I think, you know, diversity plays a big part in that as well. So, I think bringing that into our own company because we're supporting that broader industry has been very important. >> Right. So, I want to take that opportunity to pivot on what you just said about in terms of the changing role of commerce. You know, I often think of like banks because in a bank, you know, your relationship was with your local branch; maybe you knew the banker, maybe you knew a couple of the tellers whatever, but you had a personal connection. Now, most people's engagement with the brands they interact with is electronic and via their phone and it's interesting that you say that. And, it's the commerce around those engagements, that the commerce is becoming the central point of gravity if you will and the relationship is spawning all from that. >> Well, I mean, personal connections are still very important and commerce I feel is like the moment where a conversation really turns into a relationship. So, it's important that those digital experiences, the customer experiences really make up the right connection with the brand. And so, that seamless interaction between what happens at the branch, for example in the financial example, on what you can do at home, that needs to be very cohesive. It needs to be trustworthy, it needs to be authentic and that means businesses need to create individual experiences that really reflect their brand. And, our company specifically has really helped businesses create those experiences, seamless experiences and translated them from digital to in-store or in the branch. I think the biggest change now is how that's starting to impact business-to-business relationships, I think. >> In what way? In the consumer world, we're used to that now right? We're all doing that in our everyday experiences. Now, we're starting to see that also come into a business-to-business relationship. So, just like the seamless conveniences that you have online in your day to day life, people want to see that in the workplace, too. And so, we're seeing the biggest change now in those types of business models. >> They're rocking in the background, if you can't hear them. >> Yeah! We are here. >> Yeah! You know, it's funny, I just saw, something come across the feed talking about that annoying business-to-business add in Instagram, but then aren't you glad you saw it? >> Yeah. >> So, it's interesting how, you know, the B to C norms, you know, continue to help define what's going on in the B to B space and we've seen it in Enterprise Software Applications and Cloud and the flexibility and speed of innovation. It just continues to really drive the business-to-business relationship. >> Yeah, and I think just like in the business-to-consumer world, it has started with content in business-to-business. But, now people want to move from just learning and knowledge to actually transacting which means that companies need to enable specialized price list, account management, things like that and that's starting to surface in the commerce world as well. So, we're really excited about that and we're going to be sharing some of that at our conference next week; Imagine, in Las Vegas. >> Okay yeah, it's amazing how fast. It was not that long ago, we were just trying to get the 360 view. Right? We were just trying to pull from all the various desperate systems to know who that customer was for a given system. Now, it's a segmentation to want, a very different challenge. >> Right, I mean it's that change from thinking about trying to attract your customer to come to your business to really bringing the business to the customer. I mean, I think that's what some of this digital technology is allowing us to do. We're going to them rather than trying to draw them in to come to us, if that makes sense. This idea of commerce coming to you, right? >> And, it's got to come to you with something that's relevant, that's topical, that's timely. >> That's easy to execute, that can mirror a real experience. I mean, you hear a lot of things about, things like virtual reality, artificial intelligence. I mean, all of that's just gimmicks unless you can actually think about how you make that real for your brand. So, for example, we have a customer in Mexico City who is selling eyewear, right. And so, everybody when they buy glasses, they want to try them on, so we need to help them give their customers that virtual experience. If they can't come into the store and try them on, we want to be able to let them try them on at home. So, that's a natural extension of the brand and a way to use virtual reality and I think businesses are still trying to figure that out. But, if those customers didn't have that experience, it'd be less likely that they actually would buy or, you know, make a commerce transaction. >> But, if I'm hearing you, instead of it really kind of being in a marketing effort that then it's completed with a transaction, you're kind of coming at that which you just described from the transaction first and this is really a supporting or an enabling activity. >> That's right, it all starts with the customer understanding what is going to help them make their decisions. Giving them experiences that feel seamless, giving them options. So, if they want to come in-store but see what's maybe available at another store for pick-up or if they want to come in-store and order online or if they want to order from home and then go into the store and pick it up. It's really about giving the customer the right options for them. >> Right. >> Another great story we had is, I mean, how many of us travel, I know you travel a lot. >> Right. >> I travel a ton. >> Especially, to Vegas. (chuckling) >> Especially, to Vegas! And, you know, my kids are always expecting something when I come home but who has time? So, you know, one of our partners worked with the Frankfurt Airport and created an application where on the way to the airport, you can go shopping at all of their stores in the airport and have your package waiting for you at the gate on the way to the plane. So now, you know, they've figured out what their customers want to do first by creating this great shopping experience at the airport. Now, they know people are running through the airport, how can we extend that shopping experience for them while they're sitting in the taxi (chuckling) on the way, have it waiting for them at the gate? And so, for me personally, working for a company that's helping customers to do those kinds of things has really been fun. >> Right, because they always have the liquor for ya ready to go at the gate but never the kids', you know, t-shirts or a little tchotchke or, I can remember running through Heathrow time and time again trying to find something quickly. >> Yeah, and now with two kids and a husband that all want something different, (laughing) you know, it makes it much easier for me. >> Alright, Andrea, well you've been doing this marketing thing for a long time. I'll give you the last word both on the conference and kind of, you know, as a marketer to see where we're going with A.I. and really the ability to actually segment to one. You know, how exciting is that for you? >> Yeah, I mean, it's fantastic. I think, you know, marketers want to create relationships with their brand and all of these tools are giving us better access, better chance to create that fantastic experience. So, it's a great time to be a marketer. (chuckling) And, it's a great time to be at this conference, too so. >> Alright. Thanks very much. >> Thanks for stopping by, Andrea Ward. I'm Jeff Frick, you're watching theCUBE from the Professional Business Women's Conference in San Francisco. Thanks for watching. (upbeat electronic music)

>> Narrator: Live from San Jose, California it's the Cube, covering Big Data Silicon Valley 2017. (upbeat music) >> Big Data SV 2016, day two of our wall to wall coverage of Strata Hadoob Conference, Big Data SV, really what we call Big Data Week because this is where all the action is going on down in San Jose. We're at the historic Pagoda Lounge in the back of the Faramount, come on by and say hello, we've got a really cool space and we're excited and never been in this space before, so we're excited to be here. So we got George Gilbert here from Wiki, we're really excited to have our next guest, he's Fred Rice, he's the chief architect at IBM Spark Technology Center in San Francisco. Fred, great to see you. >> Thank you, Jeff. >> So I remember when Rob Thomas, we went up and met with him in San Francisco when you guys first opened the Spark Technology Center a couple of years now. Give us an update on what's going on there, I know IBM's putting a lot of investment in this Spark Technology Center in the San Francisco office specifically. Give us kind of an update of what's going on. >> That's right, Jeff. Now we're in the new Watson West building in San Francisco on 505 Howard Street, colocated, we have about a 50 person development organization. Right next to us we have about 25 designers and on the same floor a lot of developers from Watson doing a lot of data science, from the weather underground, doing weather and data analysis, so it's a really exciting place to be, lots of interesting work in data science going on there. >> And it's really great to see how IBM is taking the core Watson, obviously enabled by Spark and other core open source technology and now applying it, we're seeing Watson for Health, Watson for Thomas Vehicles, Watson for Marketing, Watson for this, and really bringing that type of machine learning power to all the various verticals in which you guys play. >> Absolutely, that's been what Watson has been about from the very beginning, bringing the power of machine learning, the power of artificial intelligence to real world applications. >> Jeff: Excellent. >> So let's tie it back to the Spark community. Most folks understand how data bricks builds out the core or does most of the core work for, like, the sequel workload the streaming and machine learning and I guess graph is still immature. We were talking earlier about IBM's contributions in helping to build up the machine learning side. Help us understand what the data bricks core technology for machine learning is and how IBM is building beyond that. >> So the core technology for machine learning in Apache Spark comes out, actually, of the machine learning department at UC Berkeley as well as a lot of different memories from the community. Some of those community members also work for data bricks. We actually at the IBM Spark Technology Center have made a number of contributions to the core Apache Spark and the libraries, for example recent contributions in neural nets. In addition to that, we also work on a project called Apache System ML, which used to be proprietary IBM technology, but the IBM Spark Technology Center has turned System ML into Apache System ML, it's now an open Apache incubating project that's been moving forward out in the open. You can now download the latest release online and that provides a piece that we saw was missing from Spark and a lot of other similar environments and optimizer for machine learning algorithms. So in Spark, you have the catalyst optimizer for data analysis, data frames, sequel, you write your queries in terms of those high level APIs and catalyst figures out how to make them go fast. In System ML, we have an optimizer for high level languages like Spark and Python where you can write algorithms in terms of linear algebra, in terms of high level operations on matrices and vectors and have the optimizer take care of making those algorithms run in parallel, run in scale, taking account of the data characteristics. Does the data fit in memory, and if so, keep it in memory. Does the data not fit in memory? Stream it from desk. >> Okay, so there was a ton of stuff in there. >> Fred: Yep. >> And if I were to refer to that as so densely packed as to be a black hole, that might come across wrong, so I won't refer to that as a black hole. But let's unpack that, so the, and I meant that in a good way, like high bandwidth, you know. >> Fred: Thanks, George. >> Um, so the traditional Spark, the machine learning that comes with Spark's ML lib, one of it's distinguishing characteristics is that the models, the algorithms that are in there, have been built to run on a cluster. >> Fred: That's right. >> And very few have, very few others have built machine learning algorithms to run on a cluster, but as you were saying, you don't really have an optimizer for finding something where a couple of the algorithms would be fit optimally to solve a problem. Help us understand, then, how System ML solves a more general problem for, say, ensemble models and for scale out, I guess I'm, help us understand how System ML fits relative to Sparks ML lib and the more general problems it can solve. >> So, ML Live and a lot of other packages such as Sparking Water from H20, for example, provide you with a toolbox of algorithms and each of those algorithms has been hand tuned for a particular range of problem sizes and problem characteristics. This works great as long as the particular problem you're facing as a data scientist is a good match to that implementation that you have in your toolbox. What System ML provides is less like having a toolbox and more like having a machine shop. You can, you have a lot more flexibility, you have a lot more power, you can write down an algorithm as you would write it down if you were implementing it just to run on your laptop and then let the System ML optimizer take care of producing a parallel version of that algorithm that is customized to the characteristics of your cluster, customized to the characteristics of your data. >> So let me stop you right there, because I want to use an analogy that others might find easy to relate to for all the people who understand sequel and scale out sequel. So, the way you were describing it, it sounds like oh, if I were a sequel developer and I wanted to get at some data on my laptop, I would find it pretty easy to write the sequel to do that. Now, let's say I had a bunch of servers, each with it's own database, and I wanted to get data from each database. If I didn't have a scale out database, I would have to figure out physically how to go to each server in the cluster to get it. What I'm hearing for System ML is it will take that query that I might have written on my one server and it will transparently figure out how to scale that out, although in this case not queries, machine learning algorithms. >> The database analogy is very apt. Just like sequel and query optimization by allowing you to separate that logical description of what you're looking for from the physical description of how to get at it. Lets you have a parallel database with the exact same language as a single machine database. In System ML, because we have an optimizer that separates that logical description of the machine learning algorithm from the physical implementation, we can target a lot of parallel systems, we can also target a large server and the code, the code that implements the algorithm stays the same. >> Okay, now let's take that a step further. You refer to matrix math and I think linear algebra and a whole lot of other things that I never quite made it to since I was a humanities major but when we're talking about those things, my understanding is that those are primitives that Spark doesn't really implement so that if you wanted to do neural nets, which relies on some of those constructs for high performance, >> Fred: Yes. >> Then, um, that's not built into Spark. Can you get to that capability using System ML? >> Yes. System ML edits core, provides you with a library, provides you as a user with a library of machine, rather, linear algebra primitives, just like a language like r or a library like Mumpai gives you matrices and vectors and all of the operations you can do on top of those primitives. And just to be clear, linear algebra really is the language of machine learning. If you pick up a paper about an advanced machine learning algorithm, chances are the specification for what that algorithm does and how that algorithm works is going to be written in the paper literally in linear algebra and the implementation that was used in that paper is probably written in the language where linear algebra is built in, like r, like Mumpai. >> So it sounds to me like Spark has done the work of sort of the blocking and tackling of machine learning to run in parallel. And that's I mean, to be clear, since we haven't really talked about it, that's important when you're handling data at scale and you want to train, you know, models on very, very large data sets. But it sounds like when we want to go to some of the more advanced machine learning capabilities, the ones that today are making all the noise with, you know, speech to text, text to speech, natural language, understanding those neural network based capabilities are not built into the core Spark ML lib, that, would it be fair to say you could start getting at them through System ML? >> Yes, System ML is a much better way to do scalable linear algebra on top of Spark than the very limited linear algebra that's built into Spark. >> So alright, let's take the next step. Can System ML be grafted onto Spark in some way or would it have to be in an entirely new API that doesn't take, integrate with all the other Spark APIs? In a way, that has differentiated Spark, where each API is sort of accessible from every other. Can you tie System ML in or do the Spark guys have to build more primitives into their own sort of engine first? >> A lot of the work that we've done with the Spark Technology Center as part of bringing System ML into the Apache ecosystem has been to build a nice, tight integration with Apache Spark so you can pass Spark data frames directly into System ML you can get data frames back. Your System ML algorithm, once you've written it, in terms of one of System ML's main systematic languages it just plugs into Spark like all the algorithms that are built into Spark. >> Okay, so that's, that would keep Spark competitive with more advanced machine learning frameworks for a longer period of time, in other words, it wouldn't hit the wall the way if would if it encountered tensor flow from Google for Google's way of doing deep learning, Spark wouldn't hit the wall once it needed, like, a tensor flow as long as it had System ML so deeply integrated the way you're doing it. >> Right, with a system like System ML, you can quickly move into new domains of machine learning. So for example, this afternoon I'm going to give a talk with one of our machine learning developers, Mike Dusenberry, about our recent efforts to implement deep learning in System ML, like full scale, convolutional neural nets running on a cluster in parallel processing many gigabytes of images, and we implemented that with very little effort because we have this optimizer underneath that takes care of a lot of the details of how you get that data into the processing, how you get the data spread across the cluster, how you get the processing moved to the data or vice versa. All those decisions are taken care of in the optimizer, you just write down the linear algebra parts and let the system take care of it. That let us implement deep learning much more quickly than we would have if we had done it from scratch. >> So it's just this ongoing cadence of basically removing the infrastructure gut management from the data scientists and enabling them to concentrate really where their value is is on the algorithms themselves, so they don't have to worry about how many clusters it's running on, and that configuration kind of typical dev ops that we see on the regular development side, but now you're really bringing that into the machine learning space. >> That's right, Jeff. Personally, I find all the minutia of making a parallel algorithm worked really fascinating but a lot of people working in data science really see parallelism as a tool. They want to solve the data science problem and System ML lets you focus on solving the data science problem because the system takes care of the parallelism. >> You guys could go on in the weeds for probably three hours but we don't have enough coffee and we're going to set up a follow up time because you're both in San Francisco. But before we let you go, Fred, as you look forward into 2017, kind of the advances that you guys have done there at the IBM Spark Center in the city, what's kind of the next couple great hurdles that you're looking to cross, new challenges that are getting you up every morning that you're excited to come back a year from now and be able to say wow, these are the one or two things that we were able to take down in 2017? >> We're moving forward on several different fronts this year. On one front, we're helping to get the notebook experience with Spark notebooks consistent across the entire IBM product portfolio. We helped a lot with the rollout of notebooks on data science experience on z, for example, and we're working actively with the data science experience and with the Watson data platform. On the other hand, we're contributing to Spark 2.2. There are some exciting features, particularly in sequel that we're hoping to get into that release as well as some new improvements to ML Live. We're moving forward with Apache System ML, we just cut Version 0.13 of that. We're talking right now on the mailing list about getting System ML out of incubation, making it a full, top level project. And we're also continuing to help with the adoption of Apache Spark technology in the enterprise. Our latest focus has been on deep learning on Spark. >> Well, I think we found him! Smartest guy in the room. (laughter) Thanks for stopping by and good luck on your talk this afternoon. >> Thank you, Jeff. >> Absolutely. Alright, he's Fred Rice, he's George Gilbert, and I'm Jeff Rick, you're watching the Cube from Big Data SV, part of Big Data Week in San Jose, California. (upbeat music) (mellow music) >> Hi, I'm John Furrier, the cofounder of SiliconANGLE Media cohost of the Cube. I've been in the tech business since I was 19, first programming on mini computers.

>> Announcer: Live from Boston, Massachusetts, it's theCUBE, covering Spark Summit East 2017. Brought to you by Databricks. Now, here are your hosts Dave Vellante and George Gilbert. >> Welcome back to snowy Boston, everybody. This is theCUBE, the leader in live tech coverage. We're here at Spark Summit East, hashtag SparkSummit. Manish Gupta is here, he's the CMO at Redis Labs. Manish, welcome to theCUBE. >> Thank you, good to be here. >> So, you know, 10 years ago you say you're in the database business and everybody would yawn. Now you're the life of the party. >> Yeah, the world has changed. I think the party has lots and lots of players. We are happy to be on the top of that heap. >> It is a crowded space, so how does Redis Labs differentiate? >> Redis Labs is the company behind the massively popular open source Redis, and Redis became popular because of its performance primarily, and then simplicity. Developers could very easily run up an instance of Redis, solve some very hairy problems, and time to market was a big issue for them. Redis Enterprise took that forward and enabled it to be mission critical, ready for the largest workloads, ready for things that the enterprises need in a highly distributed clustered environment. So they have resilience and they benefit from the performance of Redis. >> And your claim to fame, as you say, is that top-gun performance, you guys will talk about some of the benchmarks later. We're talking about use cases like fraud detection, as example. Obviously ad serving would be another one. But add some color to that if you would. >> Redis is whatever you need to make real time real, Redis plays a very important role. It is able to deliver millions of operations per second with sub-millisecond latency, and that's the hallmark. With data structures that comprise Redis, you can solve the problems in a way, and the reason you can get that performance is because the data structures take some very complex issues and simplify the operation. Depending on the use case, you could use one of the data structures, you can mix and match the data structures, so that's the power of a Redis. We're used for ITO, for machine learning, for metering of billing and telecommunications environment, for personalization, for ad serving with companies like Groupon and others, and the list goes on and on. >> Yeah, you've got a big list on your website of all your customers, so you can check that out. Let's get the business model piece out of the way. Everybody's always fascinated. Okay, you got open source, how do you make money? How does Redis make money? >> Yeah, you know, we believe strategically fostering the growth of open source is foundational in our business model, and we invest heavily both R&D and marketing to do that. On top of that, to enable enterprise success and deployment of Redis, we have the mission critical, highly available Redis Enterprise offerings. Our monetization is entirely based on the Redis Enterprise platform, which takes advantage of the data structures and performance of core Redis, but layers on top management and the capabilities that make things like auto-recovery, auto-sorting, management much, much easier for the enterprise. We make that available in four deployment models. The enterprise can select us as Redis cloud, which runs on a public infrastructure on any of the four major platforms. We also allow for the enterprise to select a VPC environment in their own private clouds. They can also get software and self-manage that, or get our software and we can manage it for them. Four deployment options are the modalities in other ways where the enterprise customers help us monetize. >> When you said four major platforms, you meant cloud platforms? >> That's right. AWS, >> So, AWS, Azure >> Azure, Google, and IBM. >> Is IBM software, got there in the fourth, alright. >> That's right, all four. >> Go to the whip IBM. Go ahead, George. >> Along the lines of the business model, and we were sort of starting to talk about this earlier offline, you're just one component in building an application, and there's always this challenge of, well, I can manage my component better than anyone else, but it's got to fit with a bunch of other vendors' components. How do you make that seamless to the customer so that it's not defaulting over to a cloud vendor who has to build all the components themselves to make it work together? >> Certainly, you know, database is an integral part of your stack, of your application stack, but it is a stack, so there are other components. Redis and Redis Labs has a very, very large ecosystem within which we operate. We work closely with others for interfaces, for connectors, for interoperability, and that's a sustained environment that we invest in on a continuous basis. >> How do handle application consistency? A lot of in the no-SQL world, even in the AWS world, you hear about eventual consistency, but in the real-time world, there's a need for more rigorous, what's your philosophy there, how do you approach that? >> I think that's an issue that many no-SQL vendors have not been able to crack. Redis Labs has been at the forefront of that. We are taking an approach, and we are offering what we call tuneable consistency. Depending on the economics and the business model and the use case, the needs of consistency vary. In some cases, you do need immediate consistency. In other cases, you don't ever need consistency. And to give that flexibility to the customer is very important, so we've taken the approach where you can go from loose consistency to what we call strong eventual consistency. That approach is based on a fairly well trusted architecture and approach called CRDT, Conflict-free Replication Data Type. That approach allows us to, regardless of what the cluster magnitude or the distribution looks like geographically, we can deliver strong eventual consistency which meets the needs of majority of the customers. >> What are you seeing in terms of, you know, also in that a discussion about acid properties, and how many workloads really need acid properties. What are seeing now as you get more cloud native workloads and more no-SQL oriented workloads in terms of the requirement for those acid properties? >> First of all, we truly believe and agree that not all environments required acid support. Having said that, to be a truly credible database, you must support acid, and we do. Redis is acid-compli, supports acid, and Redis Labs certainly supports that. >> I remember on a stage once with Curt Monash, I'm sure you know Curt, right? Very famous database person. And he basically had a similar answer. But you would say that increasingly there are workloads that, the growth workloads don't necessarily require that, is that fair statement? >> That's a fair statement I would say. >> Dave: Great, good. >> There's a trade-off, though, when you talked about strong eventual consistency, potentially you have to wait for, presumably, a quorum of the partitions, I'm getting really technical here, but in other words, you've got a copy of the data here-- >> Dave: Good CMO question. (laughing) >> But your value proposition to the customers, we get this stuff done fast, but if you have to wait for a couple other servers to make sure that they've got the update, that can slow things way down. How does that trade-off work? >> I think that's part of the power of our architecture. We have a nothing shared, single proxy architecture where all of the replication, the disaster recovery, and the consistency management of the back end is handled by the proxy, and we ensure that the performance is not degraded when you are working through the consistency challenges, and that's where significant amount of IP is in the development of that proxy. >> I'll take that as a, let's go into it even more offline. >> Manish: Sounds good. >> And I have some other CMO questions, if I may. A lot of young companies like yours, especially in open source world, when they go to get the word out, they rely on their community, their open source community, and that's the core, and that makes a lot of sense, it's their peeps. As you become, grow more into enterprise grade apps and workloads, how do you extend beyond that? What is Redis Labs doing to sort of reach that C-Suite, are you even trying to reach that C-Suite up level to messaging? How do you as a CMO deal with those challenges? >> Maybe I'll begin by talking about our personas that matter to us in the ecosystem. The enterprise level, the architects, the developers, are the primary target, which we try to influence in early part of the decision cycle, it's at the architectural level. The ultimate teams that manage, run, and operate the infrastructure is certainly the DevOps, or the operations teams, and we spend time there. All along for some of the enterprise engagements, CIOs, chief data officers, and CTOs tend to play a very important role in the decisions and the selection process, and so, we do influence and interact with the C-Suite quite heavily. What the power of the open source gives us is that groundswell of love for Redis. Literally you can walk around a developer environment, such as the Spark Summit here, and you'll find people wearing Redis Geek shirts. And we get emails from Kazakhstan and strange, places from all over the world where we don't necessarily have salesforce, and requesting t-shirts, "send us stickers." Because people love Redis, and the word of mouth, that ground level love for the technology enables the decisions to be so much easier and smoother. We're not convincing, it's not a philosophical battle anymore. It's simply about the use case and the solution where Redis Enterprise fits or doesn't fit. >> Okay, so it really is that core developer community that are your advocates, and they're able to internally sell to the C-Suite. A lot of times the C-Suite, not the CTO so much, but certainly the CIO, CDO are like, "Yeah, yeah, they're geekin' out on some new hot thing. "What's the business impact?" Do you get that question a lot, and how do address it? >> I think then you get to some of the very basic tools, ROI calculators and the value proposition. For the C-level, the message is very simple. We are the least risky bet. We are the best long-term proposition, and we are the best cost answer for their implementation. Particularly as the needs are increasingly becoming more real-time in nature, they are not batch processed. Yes, there will always be some of that, but as the workloads are becoming, there is a need for faster processing, there is a need for quick insights, and real-time is not a moniker anymore, right. Real-time truly needs to be delivered today. And so, I think those three propositions for the C-Suite are resonating very well. >> Let's talk about ROI calculators for a second. I love talking about it because it underscores what a company feels as though its core value proposition is. I would think with Redis Labs part of the value proposition is you are enabling new types of workloads and new types of, whether it's sources of revenue or productivity. And these are generally telephone numbers as compared to some of the cost savings head to head to your competition, which of course you want to stress as well because the CFO cares about the cap-backs. What do you emphasize in that, and we don't have to get into the calculator itself, but in the conceptual model, what's the emphasis? Is it on those sort of business value attributes, is it on the sort of cost-savings? How do you translate performance into that business value? A lot of questions there, but if you could summarize, that'd be great. >> Well, I think you can think of it in three dimensions. The very first one is, does the performance support the use case or the solution that is required? That's the very first one. The second piece that fits in it, and that's in our books, that's operations per second and the latency. The second piece is the cost side, and that has two components to it. The first component is, what are the compute requirements? So, what is the infrastructure underneath that has to support it? And the efficiency that Redis and Redis Enterprise has is dramatically superior to the alternatives. And so, the economics show up. To run a million operations per second, we can do that on two nodes as opposed to alternative, which might need 50 nodes or 300 nodes. >> You can utilize your assets on the floor much better than maybe the competition can. >> This is where the data structures come into play quite a bit. That's one part of-- >> Dave: That's one part of the cost. >> Yeah. The other part of the cost is the human cost. >> Dave: People, yeah. >> And because, and this goes back to the open source, because the people available with the talent and the competency and appreciation for Redis, it's easy to procure those people, and your cost of acquisition and deploying goes down quite a bit. So, there's a human cost to it. The third dimension to this whole equation is time to market. And time to market is measured in many ways. Is it lost revenue if it takes you longer to get there? And Redis consistently from multiple analysts' reports gets top ranking for fastest way to get to market because of how simple it is. Beyond performance, simplicity is a second hallmark. >> That's a benefit acceleration, and you can quantify that. >> Absolutely, absolutely. And that's a revenue parameter, right. >> For years, people have been saying this Cambrian explosion of databases is unsustainable, and sort of in response we've gotten a squaring of the Cambrian explosion. The question is, with your sort of very flexible, I don't want to get too geeky, 'cause Dave'll cut me off, but the idea that you can accommodate time series and all these different ways of, all these different types of data, are we approaching a situation where customers can start consolidating their database choices and have fewer vendors, fewer products in their landscape? >> I think not only are we getting there, but we must get there. You've got over 300 databases in the marketplace, and imagine a CIO or an architect trying to have to sort through that to make a decision, it's difficult, and you certainly cannot support it from a trading standpoint or from an investment, cap-backs, and all that standpoint. What we have done with Redis is introduce something called Redis Modules. We released that at the last RedisConf in May in San Francisco. And the Redis Module is a very simple concept but a very powerful concept. It's an API which can be utilized to take an existing development effort, written as CC++, that can be ported onto the Redis data structures. This gives you the flexibility without having to reinvent the wheel every single time to take that investment, port it on top of Redis, and you get the performance, and you can make now Redis becomes a multi-model database. And I'm going to get to your answer of how do you address the multiple needs so you don't need multiple databases. To give you some examples, since the introduction of Redis Modules, we have now over 50 modules that have been published by a variety of places, not just Redis Labs. To indicate how simple and how powerful this model is. We took Lucene and developed the world's fastest full-text search engine as a module. We have very recently introduced Redis machine learning as a module that works with Spark ML and serves as a great serving layer in the machine learning domain. Just two very simple examples, but work that's being done ported over onto Redis data structures and now you have ability to do some very powerful things because of what Redis is. And this is the way future's going to be. I think every database is trying to offer multi-functionality to be multi-model in nature, but instead of doing it one step at a time, this approach gives us the ability to leverage the entire ecosystem. >> Your point being consolidation's inevitable in this business as well. >> Manish: Architectural consolidation. >> Yes, but also you would think, company consolidation, isn't that going to follow? What do you make of the market, and tell me, if you look back on the database market and what Oracle was able to achieve in the face of, maybe not as many players, but you had Sybase and Informix, and certainly DB2's still around, and SQL Server's still around, but Oracle won, and maybe it was SQL standards that. It's great to be lucky and good. Can we learn from that, or is this a whole different world? Are there similarities, and how do you, how do you see that consolidation potentially shaking out, if you agree that there will be consolidation? >> Yeah, there has to be, first and foremost, an architectural approach that solves the OPEX, CAPEX challenge for the enterprise. But beyond that, no industry can sustain the diversity and the fragmentation that exists in database world. I think there will always be new things coming out, of universities particularly. There's great innovation and research happening, and that is required to augment. But at the end of the day, the commercial enterprises cannot be of the fragmented volume that we have today in the database world, so there is going to be some consolidation, and it's not unnatural. I think it's natural, it's expected, time will tell what that looks like. We've seen some of our competitors acquire smaller companies to add graph functionality, to add search functionality. We just don't think that's the level of consolidation that really moves the needle for the industry. It's got to be at a higher level of consolidation. >> I don't want to, don't take this the wrong way, don't hate me for saying it, but is Oracle sort of the enemy, if I can say that. I mean, it's like, no, okay. >> Depends how you define enemy. >> I'm not going to go do many of the workloads that you're talking about on Oracle, despite what Larry tells me at Oracle OpenWorld. And I'm not going to make Oracle my choice for any of the workloads that you guys are working on. I guess in terms, I mean, everybody who's in the database business looks at that and say, "Hey, we can do it cheaper, better, "more productively," but, could you respond to that, and what do you make of Amazon's moves in the database world? Does that concern you? >> We think of Amazon and Oracle as two very different philosophies, if you can use that word. The approach we have taken is really a forward-looking approach and philosophy. We believe that the needs of the market need to be solved in new ways, and new ways should not be encumbered by old approaches. We're not trying to go and replicate what was done in the SQL world or in a relational database world. Our approach is how do you deliver a multi-model database that has the real-time attribute attached to it in a way that requires very limited computer force power and very few resources to manage? You take all of those things as kind of the core philosophy, which is a forward-looking philosophy. We are definitely not trying to replicate what an Oracle used to be. AWS I think is a very different animal. >> Dave: Interesting, though. >> They have defined the cloud, and I think play a very important role. We are a strong partner of theirs, much of our traffic runs on AWS infrastructure, certainly also on other clouds. I think AWS is one to watch in how they evolve. They have database offerings, including Redis offerings. However, we fully recognize, and the industry recognizes that that's not to the same capability as Redis Enterprise. It's open sourced Redis managed by AWS, and that's fine as a cache, but you cannot persist, and you really cannot have a multi-model capability that's a full database in that approach. >> And you're in the marketplace. >> Manish: We are in the marketplace. >> Obviously. >> And actually, we announced earlier, a few weeks ago, that you can buy and get Redis cloud access, which is Redis Enterprise cloud, on AWS through the integrated billing approach on their marketplace. You can have an AWS account and get our service, the true Redis Enterprise service. >> And as a software company, you'd figure, okay, the cloud infrastructures are service, we don't care what infrastructure it runs on. Whatever the customer wants, but you see AWS making these moves up-market, you got to obviously be paying attention to that. >> Manish: Certainly, certainly. >> Go ahead, last question. >> Interesting that you were saying that to solve this problem of proliferation of choice it has to be multi-model with speed and low resource requirement. If I were to interpret that from an old-style database perspective, it would be you're going to get, the multi-model is something you are addressing now, with the extensibility, but the speed means taking out that abstraction layer that was the query optimizer sort of and working almost at the storage layer, or having an option to do that. Would that be a fair way to say? >> No, I don't think that necessarily needs to be the case. For us, speed translates from the simplicity and the power of the data structures. Instead of having to serialize, deserialize before you process data in a Spark context, or instead of having to look for data that is perhaps not put in sorted sets for a use case that you might be doing, running a query on, if the data is already handled through one of the data structures, you now have a much faster query time, you now have the ability to reach the data in the right approach. And again, this is no-SQL, right, so it's a schema lesson write and it sets your scheme as you want it be on read. We marry that with the data structures, and that gives you the ultimate speed. >> We have to leave it there, but Manish, I'll give you the last word. Things we should be paying attention to for Redis Labs this year, events, announcements? >> I think the big thing I would leave the audience with is RedisConf 2017. It's May 31 to June 2 in San Francisco. We are expecting over 1,000 people. The brightest minds around Redis of the database world will be there, and anybody who is considering deploying the next generation database should attend. >> Dave: Where are you doing that? >> It's the Marriott Marquis in San Franciso. >> Great, is that on Howard Street, across from the--? >> It is right across from Moscone. >> Great, awesome location. People know it, easy to get to. Well, congratulations on the success. We'll be lookin' for outputs from that event, and hope to see you again on theCUBE. >> Thank you, enjoyed the conversation. >> Alright, good. Keep it right there, everybody, we'll be back with our next guest. This is theCUBE, we're live from Spark Summit East. Be right back. (upbeat electronic rock music)

>> Narrator: Live from Boston, Massachusetts, this is The Cube, covering Spark Summit East 2017. Brought to you by Data Bricks. Now, here are your hosts, Dave Valente and George Gilbert. >> Boston, everybody. Nick Pentry this year, he's a principal engineer a the IBM Spark Technology Center in South Africa. Welcome to The Cube. >> Thank you. >> Great to see you. >> Great to see you. >> So let's see, it's a different time of year, here that you're used to. >> I've flown from, I don't know the Fahrenheit's equivalent, but 30 degrees Celsius heat and sunshine to snow and sleet, so. >> Yeah, yeah. So it's a lot chillier there. Wait until tomorrow. But, so we were joking. You probably get the T-shirt for the longest flight here, so welcome. >> Yeah, I actually need the parka, or like a beanie. (all laugh) >> Little better. Long sleeve. So Nick, tell us about the Spark Technology Center, STC is its acronym and your role, there. >> Sure, yeah, thank you. So Spark Technology Center was formed by IBM a little over a year ago, and its mission is to focus on the Open Source world, particularly Apache Spark and the ecosystem around that, and to really drive forward the community and to make contributions to both the core project and the ecosystem. The overarching goal is to help drive adoption, yeah, and particularly enterprise customers, the kind of customers that IBM typically serves. And to harden Spark and to make it really enterprise ready. >> So why Spark? I mean, we've watched IBM do this now for several years. The famous example that I like to use is Linux. When IBM put $1 billion into Linux, it really went all in on Open Source, and it drove a lot of IBM value, both internally and externally for customers. So what was it about Spark? I mean, you could have made a similar bet on Hadoop. You decided not to, you sort of waited to see that market evolve. What was the catalyst for having you guys all go in on Spark? >> Yeah, good question. I don't know all the details, certainly, of what was the internal drivers because I joined HTC a little under a year ago, so I'm fairly new. >> Translate the hallway talk, maybe. (Nick laughs) >> Essentially, I think you raise very good parallels to Linux and also Java. >> Absolutely. >> So Spark, sorry, IBM, made these investments and Open Source technologies that had ceased to be transformational and kind of game-changing. And I think, you know, most people will probably admit within IBM that they maybe missed the boat, actually, on Hadoop and saw Spark as the successor and actually saw a chance to really dive into that and kind of almost leap frog and say, "We're going to "back this as the next generation analytics platform "and operating system for analytics "and big debt in the enterprise." >> Well, I don't know if you happened to watch the Super Bowl, but there's a saying that it's sometimes better to be lucky than good. (Nick laughs) And that sort of applies, and so, in some respects, maybe missing the window on Hadoop was not a bad thing for IBM >> Yeah, exactly because not a lot of people made a ton of dough on Hadoop and they're still sort of struggling to figure it out. And now along comes Spark, and you've got this more real time nature. IBM talks a lot about bringing analytics and transactions together. They've made some announcements about that and affecting business outcomes in near real time. I mean, that's really what it's all about and one of your areas of expertise is machine learning. And so, talk about that relationship and what it means for organizations, your mission. >> Yeah, machine learning is a key part of the mission. And you've seen the kind of big debt in enterprise story, starting with the kind of Hadoop and data lakes. And that's evolved into, now we've, before we just dumped all of this data into these data lakes and these silos and maybe we had some Hadoop jobs and so on. But now we've got all this data we can store, what are we actually going to do with it? So part of that is the traditional data warehousing and business intelligence and analytics, but more and more, we're seeing there's a rich value in this data, and to unlock it, you really need intelligent systems. You need machine learning, you need AI, you need real time decision making that starts transcending the boundaries of all the rule-based systems and human-based systems. So we see machine learning as one of the key tools and one of the key unlockers of value in these enterprise data stores. >> So Nick, perhaps paint us a picture of someone who's advanced enough to be working with machine learning with BMI and we know that the tool chain's kind of immature. Although, IBM with Data Works or Data First has a fairly broad end-to-end sort of suit of tools, but what are the early-use cases? And what needs to mature to go into higher volume production apps or higher-value production apps? >> I think the early-use cases for machine learning in general and certainly at scale are numerous and they're growing, but classic examples are, let's say, recommendation engines. That's an area that's close to my heart. In my previous life before IBM, I bought the startup that had a recommendation engine service targeting online stores and new commerce players and social networks and so on. So this is a great kind of example use case. We've got all this data about, let's say, customer behavior in your retail store or your video-sharing site, and in order to serve those customers better and make more money, if you can make good recommendations about what they should buy, what they should watch, or what they should listen to, that's a classic use case for machine learning and unlocking the data that is there, so that is one of the drivers of some of these systems, players like Amazon, they're sort of good examples of the recommendation use case. Another is fraud detection, and that is a classic example in financial services, enterprise, which is a kind of staple of IBM's customer base. So these are a couple of examples of the use cases, but the tool sets, traditionally, have been kind of cumbersome. So Amazon bought everything from scratch themselves using customized systems, and they've got teams and teams of people. Nowadays, you've got this bold into Apache Spark, you've got it in Spark, a machine learning library, you've got good models to do that kind of thing. So I think from an algorithmic perspective, there's been a lot of advancement and there's a lot of standardization and almost commoditization of the model side. So what is missing? >> George: Yeah, what else? >> And what are the shortfalls currently? So there's a big difference between the current view, I guess the hype of the machine learning as you've got data, you apply some machine learning, and then you get profit, right? But really, there's a hugely complex workflow that involves this end-to-end story. You've got data coming from various data sources, you have to feed it into one centralized system, transform and process it, extract your features and do your sort of hardcore data signs, which is the core piece that everyone sort of thinks about as the only piece, but that's kind of in the middle and it makes up a relatively small proportion of the overall chain. And once you've got that, you do model training and selection testing, and you now have to take that model, that machine-learning algorithm and you need to deploy it into a real system to make real decisions. And that's not even the end of it because once you've got that, you need to close the loop, what we call the feedback loop, and you need to monitor the performance of that model in the real world. You need to make sure that it's not deteriorating, that it's adding business value. All of these ind of things. So I think that is the real, the piece of the puzzle that's missing at the moment is this end-to-end, delivering this end-to-end story and doing it at scale, securely, enterprise-grade. >> And the business impact of that presumably will be a better-quality experience. I mean, recommendation engines and fraud detection have been around for a while, they're just not that good. Retargeting systems are too little too late, and kind of cumbersome fraud detection. Still a lot of false positives. Getting much better, certainly compressing the time. It used to be six months, >> Yes, yes. Now it's minutes or second, but a lot of false positives still, so, but are you suggesting that by closing that gap, that we'll start to see from a consumer standpoint much better experiences? >> Well, I think that's imperative because if you don't see that from a consumer standpoint, then the mission is failing because ultimately, it's not magic that you just simply throw machine learning at something and you unlock business value and everyone's happy. You have to, you know, there's a human in the loop, there. You have to fulfill the customer's need, you have to fulfill consumer needs, and the better you do that, the more successful your business is. You mentioned the time scale, and I think that's a key piece, here. >> Yeah. >> What makes better decisions? What makes a machine-learning system better? Well, it's better data and more data, and faster decisions. So I think all of those three are coming into play with Apache Spark, end-to-end's story streaming systems, and the models are getting better and better because they're getting more data and better data. >> So I think we've, the industry, has pretty much attacked the time problem. Certainly for fraud detection and recommendation systems the quality issue. Are we close? I mean, are we're talking about 6-12 months before we really sort of start to see a major impact to the consumer and ultimately, to the company who's providing those services? >> Nick: Well, >> Or is it further away than that, you think? >> You know, it's always difficult to make predictions about timeframes, but I think there's a long way to go to go from, yeah, as you mentioned where we are, the algorithms and the models are quite commoditized. The time gap to make predictions is kind of down to this real-time nature. >> Yeah. >> So what is missing? I think it's actually less about the traditional machine-learning algorithms and more about making the systems better and getting better feedback, better monitoring, so improving the end user's experience of these systems. >> Yeah. >> And that's actually, I don't think it's, I think there's a lot of work to be done. I don't think it's a 6-12 month thing, necessarily. I don't think that in 12 months, certainly, you know, everything's going to be perfectly recommended. I think there's areas of active research in the kind of academic fields of how to improve these things, but I think there's a big engineering challenge to bring in more disparate data sources, to better, to improve data quality, to improve these feedback loops, to try and get systems that are serving customer needs better. So improving recommendations, improving the quality of fraud detection systems. Everything from that to medical imaging and counter detection. I think we've got a long way to go. >> Would it be fair to say that we've done a pretty good job with traditional application lifecycle in terms of DevOps, but we now need the DevOps for the data scientists and their collaborators? >> Nick: Yeah, I think that's >> And where is BMI along that? >> Yeah, that's a good question, and I think you kind of hit the nail on the head, that the enterprise applied machine learning problem has moved from the kind of academic to the software engineering and actually, DevOps. Internally, someone mentioned the word train ops, so it's almost like, you know, the machine learning workflow and actually professionalizing and operationalizing that. So recently, IBM, for one, has announced what's in data platform and now, what's in machine learning. And that really tries to address that problem. So really, the aim is to simplify and productionize these end-to-end machine-learning workflows. So that is the product push that IBM has at the moment. >> George: Okay, that's helpful. >> Yeah, and right. I was at the Watson data platform announcement you call the Data Works. I think they changed the branding. >> Nick: Yeah. >> It looked like there were numerous components that IBM had in its portfolio that's now strung together. And to create that end-to-end system that you're describing. Is that a fair characterization, or is it underplaying? I'm sure it is. The work that went into it, but help us maybe understand that better. >> Yeah, I should caveat it by saying we're fairly focused, very focused at HTC on the Open Source side of things, So my work is predominately within the Apache Spark project and I'm less involved in the data bank. >> Dave: So you didn't contribute specifically to Watson data platform? >> Not to the product line, so, you know, >> Yeah, so its really not an appropriate question for you? >> I wouldn't want to kind of, >> Yeah. >> To talk too deeply about it >> Yeah, yeah, so that, >> Simply because I haven't been involved. >> Yeah, that's, I don't want to push you on that because it's not your wheelhouse, but then, help me understand how you will commercialize the activities that you do, or is that not necessarily the intent? >> So the intent with HTC particularly is that we focus on Open Source and a core part of that is that we, being within IBM, we have the opportunity to interface with other product groups and customer groups. >> George: Right. >> So while we're not directly focused on, let's say, the commercial aspect, we want to effectively leverage the ability to talk to real-world customers and find the use cases, talk to other product groups that are building this Watson data platform and all the product lines and the features, data sans experience, it's all built on top of Apache Apache Spark and platform. >> Dave: So your role is really to innovate? >> Exactly, yeah. >> Leverage and Open Source and innovate. >> Both innovate and kind of improve, so improve performance improve efficiency. When you are operating at the scale of a company such as IBM and other large players, your customers and you as product teams and builders of products will come into contact with all the kind of little issues and bugs >> Right. >> And performance >> Make it better. Problems, yeah. And that is the feedback that we take on board and we try and make it better, not just for IBM and their customers. Because it's an Apache product and everyone benefits. So that's really the idea. Take all the feedback and learnings from enterprise customers and product groups and centralize that in the Open Source contributions that we make. >> Great. Would it be, so would it be fair to say you're focusing on making the core Spark, Spark ML and Spark ML Lib capabilities sort of machine learning libraries and in the pipeline, more robust? >> Yes. >> And if that's the case, we know there needs to be improvements in its ability to serve predictions in real time, like high speed. We know there's a need to take the pipeline and sort of share it with other tools, perhaps. Or collaborate with other tool chains. >> Nick: Yeah. >> What are some of the things that the Enterprise customers are looking for along the lines? >> Yeah, that's a great question and very topical at the moment. So both from an Open Source community perspective and Enterprise customer perspective, this is one of the, if not the key, I think, kind of missing pieces within the Spark machine-learning kind of community at the moment, and it's one of the things that comes up most often. So it is a missing piece, and we as a community need to work together and decide, is this something that we built within Spark and provide that functionality? Is is something where we try and adopt open standards that will benefit everybody and that provides a kind of one standardized format, or way or serving models? Or is it something where there's a few Open Source projects out there that might serve for this purpose, and do we get behind those? So I don't have the answer because this is ongoing work, but it's definitely one of the most critical kind of blockers, or, let's say, areas that needs work at the moment. >> One quick question, then, along those lines. IBM, the first thing IBM contributed to the Spark community was Spark ML, which is, as I understand it, it was an ability to, I think, create an ensemble sort of set of models to do a better job or create a more, >> So are you referring to system ML, I think it is? >> System ML. >> System ML, yeah, yeah. >> What are they, I forgot. >> Yeah, so, so. >> Yeah, where does that fit? >> System ML started out as a IBM research project and perhaps the simplest way to describe it is, as a kind of sequel optimizer is to take sequel queries and decide how to execute them in the most efficient way, system ML takes a kind of high-level mathematical language and compiles it down to a execution plan that runs in a distributed system. So in much the same way as your sequel operators allow this very flexible and high-level language, you don't have to worry about how things are done, you just tell the system what you want done. System ML aims to do that for mathematical and machine learning problems, so it's now an Apache project. It's been donated to Open Source and it's an incubating project under very active development. And that is really, there's a couple of different aspects to it, but that's the high-level goal. The underlying execution engine is Spark. It can run on Hadoop and it can run locally, but really, the main focus is to execute on Spark and then expose these kind of higher level APRs that are familiar to users of languages like R and Python, for example, to be able to write their algorithms and not necessarily worry about how do I do large scale matrix operations on a cluster? System ML will compile that down and execute that for them. >> So really quickly, follow up, what that means is if it's a higher level way for people who sort of cluster aware to write machine-learning algorithms that are cluster aware? >> Nick: Precisely, yeah. >> That's very, very valuable. When it works. >> When it works, yeah. So it does, again, with the caveat that I'm mostly focused on Spark and not so much the System ML side of things, so I'm definitely not an expert. I don't claim to be an expert in it. But it does, you know, it works at the moment. It works for a large class of machine-learning problems. It's very powerful, but again, it's a young project and there's always work to be done, so exactly the areas that I know that they're focusing on are these areas of usability, hardening up the APRs and making them easier to use and easier to access for users coming from the R and Python communities who, again are, as you said, they're not necessarily experts on distributed systems and cluster awareness, but they know how to write a very complex machine-learning model in R, for example. And it's really trying to enable them with a set of APR tools. So in terms of the underlying engine, they are, I don't know how many hundreds of thousands, millions of lines of code and years and years of research that's gone into that, so it's an extremely powerful set of tools. But yes, a lot of work still to be done there and ongoing to make it, in a way to make it user ready and Enterprise ready in a sense of making it easier for people to use it and adopt it and to put it into their systems and production. >> So I wonder if we can close, Nick, just a few questions on STC, so the Spark Technology Centers in Cape Town, is that a global expertise center? Is is STC a virtual sort of IBM community, or? >> I'm the only member visiting Cape Town, >> David: Okay. >> So I'm kind of fairly lucky from that perspective, to be able to kind of live at home. The rest of the team is mostly in San Francisco, so there's an office there that's co-located with the Watson west office >> Yeah. >> And Watson teams >> Sure. >> That are based there in Howard Street, I think it is. >> Dave: How often do you get there? >> I'll be there next week. >> Okay. >> So I typically, sort of two or three times a year, I try and get across there >> Right. And interface with the team, >> So, >> But we are a fairly, I mean, IBM is obviously a global company, and I've been surprised actually, pleasantly surprised there are team members pretty much everywhere. Our team has a few scattered around including me, but in general, when we interface with various teams, they pop up in all kinds of geographical locations, and I think it's great, you know, a huge diversity of people and locations, so. >> Anything, I mean, these early days here, early day one, but anything you saw in the morning keynotes or things you hope to learn here? Anything that's excited you so far? >> A couple of the morning keynotes, but had to dash out to kind of prepare for, I'm doing a talk later, actually on feature hashing for scalable machine learning, so that's at 12:20, please come and see it. >> Dave: A breakout session, it's at what, 12:20? >> 20 past 12:00, yeah. >> Okay. >> So in room 302, I think, >> Okay. >> I'll be talking about that, so I needed to prepare, but I think some of the key exciting things that I have seen that I would like to go and take a look at are kind of related to the deep learning on Spark. I think that's been a hot topic recently in one of the areas, again, Spark is, perhaps, hasn't been the strongest contender, let's say, but there's some really interesting work coming out of Intel, it looks like. >> They're talking here on The Cube in a couple hours. >> Yeah. >> Yeah. >> I'd really like to see their work. >> Yeah. >> And that sounds very exciting, so yeah. I think every time I come to a Spark summit, they always need projects from the community, various companies, some of them big, some of them startups that are pushing the envelope, whether it's research projects in machine learning, whether it's adding deep learning libraries, whether it's improving performance for kind of commodity clusters or for single, very powerful single modes, there's always people pushing the envelope, and that's what's great about being involved in an Open Source community project and being part of those communities, so yeah. That's one of the talks that I would like to go and see. And I think I, unfortunately, had to miss some of the Netflix talks on their recommendation pipeline. That's always interesting to see. >> Dave: Right. >> But I'll have to check them on the video (laughs). >> Well, there's always another project in Open Source land. Nick, thanks very much for coming on The Cube and good luck. Cool, thanks very much. Thanks for having me. >> Have a good trip, stay warm, hang in there. (Nick laughs) Alright, keep it right there. My buddy George and I will be back with our next guest. We're live. This is The Cube from Sparks Summit East, #sparksummit. We'll be right back. (upbeat music) (gentle music)

theCUBE presents an exclusive on the ground conversation with Oracle CEO Mark Hurd.  Mark sat down with John Fourier at Oracle's redwood city campus. >> Hello everyone welcome to a special presentation of theCUBE. I'm John Furrier   the founder of SiliconANGLE and we're here with Mark Hurd the Co-CEO for a one-on-one exclusive conversation , Mark welcome to theCUBE on the ground welcome.    >> Thanks John >> OpenWorld we were there with theCUBE >> So at Oracle and we were on Howard Street , we talked to 48 folks from Oracle executives and we learned a lot and we've been there covering it for six years and one of the striking things was Oracle's cloud message wasn't really well received by the press in the sense of they consider you kind of not in the top two. It's Amazon , Amazon it's this, that & the other thing. You guys had been doing cloud for awhile and I want to explore that conversation with you about Oracle's cloud your business startup landscape competition but one of the things that struck me was your interview on CNBC with John Ford he said are you determined to be in the cloud and you kind of had a shock back response and said determined we're in the cloud we're winning and quoted some stats give us the update you guys are in the cloud we watched that we learned that it's end to end what's the current status of Oracle's cloud play right now.    >> Thanks John,  well I think the way I would describe it numerically is not only in the cloud were a multi-billion dollar player in the cloud and so we started really several years ago in the application part of the cloud or SAS we've had tremendous success across the pillars of our SAS products or the pillars of applications in the industry we've added a platform capability or paths to that portfolio and now we've added infrastructure as a service so we're actually the only player in the cloud now today in infrastructure in pass and platform and in application so a complete portfolio differentiated by its by its scope and also differentiated by each of the pieces we believe to be Best of Breed and it's resulted in bookings I think that's out in the marketplace but I'll reiterated today. We'll book more business in the cloud  than this year than anybody else in the industry.  >> One of the things about the cloud that people love is the fact that it's fast it's got great economics but it has a scale component that customers are attracted too,  yet a lot of the folks who provide cloud technologies have different approaches.  Larry Ellison was on stage at Oracle OpenWorld saying he's long in the cloud game and you've reiterated that. What does that mean you know and the business folks out there they love this but they don't want to have different technologies that become outdated they want to have just solutions so every vendor's got different approaches why is Oracle well-positioned for this long win or the long players Larry's and you talked about.  >> Well first John we've been in this business a long time and so the fact is I think nobody's provided solutions at the depth and breadth that Oracle has over the past 20-some years so we've got a lot of experience in this business and that experience really as at the enterprise level so experience is is deep. That said to your point most of our customers spend a lot of money on IT and most of them have to go do this themselves. One of the promises of cloud is all of the things you said plus the fact it's it's simpler it's easier and you're actually not you're actually moving your innovation from your IT budget to Oracle's R&D budget and that's very attractive not just economically, it is ,attractive economically to your point but it's very attractive now to get in an area like HR. We have almost 2,000 programmers coming to work every day feature stringing that application would you rather be doing that on your IT staff or have that done by 2,000 people coming every work today who's on our payroll not yours to drive your innovation. >> global. Cloud is a global phenomenon  >>  The other impact is Obviously the geographic regions is hear now that as a key table stakes but you know it also brings in some economics on the economy side. What's your take on the global economy outlook right now in the world right now and and how does that affect customers decisions and buying patterns you know right now >> If you look over and when you say right now I'll look at it over the past couple of years. Revenue growth across the global economy the S&P 500 is fairly flat so you've had about one percent revenue growth of the S&P 500 over the past five years or so. Earnings growth though is about 5% and you've seen that reflected a bit to a degree in the stock market and the run-up of the stock market over the past several years so with revenue flat and earnings up that tells you that people are cutting expenses people are being very careful what they spend in what they invest and that gets reflected in IT and you see this in the IT industry and some of the results of the companies in it so companies are very much being very careful what they spend. I think companies overall are comfortable with their cost structures. They wish they could grow faster and it becomes the reason why cloud not just as a technology but as a business approach in a business model is extremely attractive to our customers into the broader market >> So they were there see expenses they don't only have to spend aggressively but they need to perform as well so it's also top-line >> John, it's a bigger problem than that it's a bigger problem than that because I'm worried about cost but at the same time many of our customers face competition. They face competition from startups new entrants into their industries and so they have to be innovative so it can't be just cut cost for cutting costs sake because if they do they can easily get disintermediated from their customer from their market and therefore they wind up not being competitive so the attractiveness back to the point about innovation and cloud is yes it's it's lower cost it's better economically yes it's simpler but it also drives more innovation at the same time and it's really the combination of all these factors that do the trick >> I put a question on my Twitter feed and Facebook I was interviewing you and I got a question I want to read to you as it says 'Marks on the road constant of customers then coming back to the ranch to meet Larry and Safra and the teams,  what is he hearing what is the consistent need from his customers and CEOs he's talking to who position themselves'  what's the common thread what's the holy grail for the customer that you're hearing from from consistently in the pattern that you're seeing your customer visits?  >> Help us get from here to there and and I think when you know you're in our industry you get a lot of people talking about cloud you know let's go to the cloud well if you're if you're not in the tech industry and you hear that you're like what does that mean and and then more importantly how do I get there so it's easy for us to talk about you know where we are. Most of our customers are stuck in where they are today and most of that is an on-premise many of those are older applications their homegrown applications so the process of not just telling us telling them where they could go but how do I help you get there.  At Oracle again we feel uniquely positioned and we're not just big in the cloud multibillion-dollar cloud player but we have a heritage on-premise and I see that as a very very strong asset and the ability now to bring those two worlds together and help our customers operate some of their IT on-premise, some of their IT in the cloud and be able to work those move those workloads back and forth seamlessly. >> you know you understand the athletes world >>  Timing is everything you  play tennis, being at the right spot the right time is really the business focus with customers and so when they hear cloud or hey this is a new technology from Silicon Valley think how well is that real so this isn't not so much as scared of the Silicon Valley innovation you're seeing you know for Tesla innovating things like GM and Ford but a lot of mainstream businesses want to have an answer to their problems not so much the shiny new technology. How do you balance the timing of delivering new cloud technologies with that next big thing in R&D or what not I mean what's the secret and what do customers look for is the timing issue of having the right solution at the right time what's your philosophy on that what's your take on that >> Well of course you're right I mean the fact is you know as we sit here in the Silicon Valley we tend to invent words every couple of years they're gonna solve all of the customers problems cloud big data whatever it may be whatever your problem is we're gonna we have a solution for it and the reality is most customers want to solve their business problem they're concerned about growing their revenue they're just they're concerned about becoming more efficient with their processes and so therefore we have to help them get that done so to your point we have to come in with real solutions, our solutions are baked around things as simple as running your HR system. You know running running your core accounting your core ERP and your core sales organization and being able to be able to automate those applications. I think you'll see  a tremendous workload coming around dev test. You know 30% of all of IT for example today is really done in developing and testing applications, it's all done on premise, it's all done with very little governance around it,  that whole process. Think of that, if Enterprise IT is a billion dollars,  Dev-Test at 30% is let's see I think 300 million dollars. How efficient do you think that spend is? Let's pretend it was 50 percent efficient,  which I believe is very high. A hundred and fifty billion dollars of opportunity for our customers to no longer have data centers,  computers, operating systems, databases,  people and be able to move all that to the cloud be able to access all of that capability from the cloud build and test their applications directly from the cloud and if they even want they can move those workloads to their on-premise production for their on premise production applications. So these are tremendous opportunities to change the way we think of IT and your point the timing has to be right there has to be an openness and an excitement about embracing these opportunities and I think that time is now. >> on that because it can be scariest shit >> What are you hearing from customers into the cloud and and and they might hey Oracle you know all you know you have your stuff and I hear the shiny new toy in Silicon Valley new technologies but what's in it for me that's the customer I've but I think mentality what's in it for me my problems as you said what it what is that issue for that for customers for your standpoint how do you how do they get over that fear to take that leap will the parachute open when they go to the cloud that that's the kind of mindset the customer I hear and I thought to what >>   >> various different people that have >> Well I mean they're different opinions I think many of those initial perceptions are beginning to change so I think you're getting more customers more openness and we're sitting here in the United States I think if you went back to to Europe and Western Europe there was always concerns about various issues security etc data sovereignty many of those issues I believe we're beginning to tackle and to resolve. But at the end of the day that the the real excitement is about the core things we started with,  this just costs less, this is simply driving more innovation,  and it's easier at the end of the day, and those are three fantastic benefits for customers.  >> So now there's a new class of buyers entering the market your customers and some of them are younger and you know we see some of them don't have voicemail setup, they don't really use email. Is Oracle's success generational and how are you guys bridging the gap or if no how are you bridging the gap to reach these new demographic of buyers who understand mobile and cloud have some that love that some are kind of you know as I mentioned earlier crossing the chasm on their own but this new generation of buyers what are you seeing >> there are you seeing a new demographic >> are you seeing a new class of buyers?  >> So it's a complex issue you bring up because the new generation in people sometimes generalize about these generations called Millennials,  etc.   They are both employees and customers and to a large degree they interrupt much of the status quo they work differently they also buy differently. Now at the same time remember that our customers have multiple generations of workers and multiple generations of customers so this actually gets quite quite interesting.  So if you take workers somebody my generation I like to might think of self myself as young and I'm in the technology etc but that the actual data says I'm not and I still work I still work in a workflow basis I use pieces of paper like you have today and and I look at those pieces of paper.   Not my kids. They work differently. They also work more collaboratively they work in groups but now I'm still in the company and so are a whole lot of Millennials that work at Oracle so we have to put processes and tools together that not only deal with what I do but what they do and make sure that we can all then work together that's a lot of work that's a lot of technology and it's actually made the business problem that we're talking about harder. Same thing from a customer perspective those same employees that work differently, they buy differently and you better be prepared to engage them where they want to be engaged,  how they want to be engaged, and that gives an opportunity for Oracle to help our customers innovate to give them better applications, better tools to go >> meet those customers and employees. >> Brings up a great point I mean it gets getting more complex on the business logic and business model and also the consumption and technology but isn't IT supposed to get easier?  I mean it once was easy compared to what it seems to be now what's your take on that it's got to get simpler what's your strategy. >> part of the issue is the data set >>   First of all the part of the continues to grow so the data set continues to grow and that drives tremendous desire for more information this while in some degree more data creates complexity it also creates tremendous amount of insight. The things we can do today we would never have thought of 10 years ago I mean there are things think about, can you imagine the  world 15 years ago where we couldn't search for anything.   We didn't have,  think of all the tools we have today that we use every day that we didn't have think about it this way applications the average age of an application in this country is about 21 22 years old meaning they were built in 1993 1994 1995 pre-search pre-mobile pre- social pre everything,  that  we're used too, so as a result you have this really old infrastructure trying to support this this new world and that's part of the promise I think of these new applications. They're engineered with mobile integrated into the applications themselves,  they're integrated with collaboration tools from the ground up,  and this world will get continue to get easier.  >> One of the questions we're asking our on our wikibon analyst team to our surveys and our customers is which vendor will provide the value fastest for getting the most out of the data. This seems to be a question that's kind of buried a little bit in some of the conversations out in the marketplace but it seems to be consistent. The value of the data is seems to be really really important. Who's gonna build the tooling and the automation and the integration capabilities to maximize the data whether it comes from some integration on an iPhone or collaborative document or an ERP system it could cover them anywhere and or mixing and matching data that seems to be the focus what's your thoughts on that and getting the most out of the data and what is Oracle doing >> with that in that regard? >> Yeah well listen historically in our industry you basically had applications that produced data, you then taken that data extracted it from the transaction application and warehoused it or  marted or used whatever term you wanted to use, and then create a bunch of analytics through some very very experienced scientific users who then would distribute reports out to the rest of the company that's the history of sort of data analytics. I did that for a good part of the earlier part of my career and I would say things are changing now that those analytics have to have to move right next to the application itself, they have to become real-time,  they have to be integrated into the core applications.  So we see happening today in Oracle applications is no longer do you have to take data out of the application you have to integrate it directly into the application so you can now get real-time insights. The ability now to integrate structured data and unstructured data and do it in near real-time so that you can now make a decision on something based on early indicators and then merge it and integrate it with the core way that you run a company and that's how you'll see analytics evolve,  the ability to take massive amounts of unstructured data but it's not gonna be good enough just to analyze that unstructured data that's social data,  you're gonna have to be able to merge that data where the system that can now do something with it.  >> And customers telling you that there and you're hearing that from customers as well? >> to, I want data that allows me to make >> Listen the fundamentals come back the right decision at the right time with the right customer the right employee to optimize my business. How do I get through all of this massive amount of data that you've been talking about so that I can make the optimal decision at the right time to benefit my business. That's the key.   >> the trends in the industry that you're >> Let's talk about trends, competing in the technology landscape has been very robust over the past few years and specifically past three years. What's your take on the landscape now I mean obviously the table stakes that the bar that the bar to get into the game that they're at entry what is the technology landscape like today from your perspective as a CEO co-ceo of Oracle with your competitors and your customers >> Well I think the shift is significant to your point I think this forget the overused term of cloud but that method of computing at the application layer the platform layer and the infrastructure layer is clearly where this industry is  Oheaded I made a presentation at OpenWorld that I felt by 2025, I predicted that 80% of that workload will be in the cloud. And I think I associated I made this statement then that I may be slow,  it may go faster and and that shift has a seismic impact on on our industry and it will happen and the reason it will happen is because of the reasons I've keep coming back to it when the customer can get better economics,  the customer can get more innovation, and they can get something done more simply, they're gonna they're gonna go do it . That's gonna cause losers and that's going to cause winners and that's why we've made the investments we have,  that's why we've built out all the data centers around the world that we have,  it's why Oracle has rewritten all of its applications from the ground up hundred percent >> all of our products now have basically >> 100 percent all of our been cloudified, they've been rewritten from the ground up to be cloud ready. And it's critical for us John because we believe this is and Larry started on this a decade ago so this isn't something we we thought about like 18 months ago and said hey why don't we go do this this this this came back a long time ago even before the term cloud was popular so it's this is this whole method and approach to computing which which which is key and frankly we started out getting into the SAS business the applications business and it was clear when you're in the applications business to really do that right you had to be in the platform business and then really to be in the platform business you had to be in the infrastructure business and that's why when you look at the barrier to entry John the ability to build out all three layers of the cloud the ability  R&D wise to do that or from a financial capital perspective to acquire all that good luck trying to do that then to build the infrastructure the data center infrastructure and the capital and remember John you have to do all this in advance think of it as to get into the cloud business from a IT perspective it's like building a hotel and you have to build a hotel before you can rent a room nobody can stay in the hotel til it's built think of that on a much bigger scale as being what it takes to get into the global cloud business >> So it's not winner-take-all it's winner take most or >> listen I was public in my view that I >> They'll be a couple of winners I think think that they'll be probably a couple of application providers I predict Oracle will be one I don't know right now today there is no other company in the industry who has got a complete suite of SAS applications Oracle's the only one somebody eventually will get will get that done I believe and I believe you'll have a couple of providers in that part of the industry I think probably likely at the platform level you have a couple of platforms that survive you'll also find the ability for those platforms to work together and I think like anything you'll see a couple of providers two three providers at the infrastructure layer >> Is Oracle a one big cloud or is it a company of many clouds I mean saw an  acquisitions this week, AddThis, and  I saw the word datacloud  sounds good great good marketing data cloud but it makes sense it's social data you see marketing cloud and social cloud you get in your are they a collection of clouds or does it matter is it labeling as the long tail distribution?  >> are clearly a set of capabilities in the >>  Well it's branding I mean they Oracle public cloud. Those capabilities are a marketing cloud a sales cloud they are not if you will architected as separate clouds they are built on as I said earlier they are architected on the same platform everything is built on Fusion Middleware common platform common base common infrastructure that can work together. >> You talked about in your prediction here that you know all data >>   You talked about in your prediction here that all  enterprise data we stored in the cloud faster and cheaper you also announced that pricing was or might have been earlier that cheaper than glacier and Amazon is that consistent the trend that you see pushing the price down lower and lower for the data storage.  >> think at the infrastructure layer we've >>   Yes I mean I looked at that world as more of a commoditized world that you know basically the infrastructure is a service there you're selling compute and you're selling storage and we think that market will continue to decline in in price and we expect to be very aggressive with our pricing in that market >> the cycle cycle styves kenzan flow as >> I want to get a take on startups we've seen in the 90s when I did my first startup it was really hard to get into the business you're the provision of data center buy router,  buy a Sun box at that time was very expensive it was also hard to get customers if you were starting up an enterprise customer in this case and then the world shifted easy to get customers with open source what seemed to be shifting back around where it's hard for startups to get enterprise customers because of the scale and integration challenges and the SLA is and the global requirements compliance and the list goes on and on do you agree with that statement or do you see it differently that it's gonna be harder and harder for startups it might be easy to start building stuff but they actually come in and compete and win enterprise customers what's your take of the the appetite of >> and John you're talking about tech startups  >> or tech startups that sell say you know how cells store take and I've just invented an all flash array and it's kick-ass and it's gonna you know eat into Oracle Exadata and EMC and all these those guys and I'm gonna go sell it to GM or I have a software product that I want to sell to company so again getting into the enterprises used to be hard and then it got easy it seems to be getting hard again what's your take of the state of that >> a long a subject that's got that's got >> So again quite a bit to it I think first I don't think companies are gonna buy all stick on the application layer for a second and talk about application startups I don't think customers are gonna buy from a hundred different companies for their cloud applications I I think when you're looking at applications specifically you think about automating a vertical process but companies also have to work together horizontally not just vertically so I think in the end they will they will have fewer cloud providers I mentioned sort of to could a company have three or a four a couple best to breeds maybe but they're not going to have they're not gonna make the on-premise complexity and just move that complexity to the cloud this is an opportunity to make things simpler to your to your earlier point I think that's what will happen now we happen to be we acquire quite a bit as I know you know and so we actually get to look at a lot of startups and I would say you're right that that we see with many startups is they start off trying to as inexpensively as possible which is I don't think I try to do it as expensively as I could try to try to build a capability and then many run into problems with eventually scaling and being eventually being able to build out we see this as we as we are I think for startups one of the real attractiveness of the cloud is that no longer any of those costs you described a few minutes ago exist I can now go do the remember that dev test I talked about that dev test I talked about for the big company is the same thing you could do on the cloud you can go get Java you can get the Oracle database you can only use or pay for what you use no longer you have to buy a Sun server that you describe or get a license and you can build on the most industrial strength commercial capability in the world Oracle and you can do that now as a start-up and be enterprise-grade from the first piece of code you write. >> So being a world-class leader might be harder for start to crack that nut versus becoming part of an ecosystem >> think that's right I think what you said >> I is right and I was trying to address both I think as a start-up you have an opportunity to to build on on commercial-grade tools from from the beginning and I do think you're right that being part of an ecosystem almost assuredly will be necessary as this market matures.  >> week at CES before GM announcing >>  A lot of commentary this Lyft could deal with Lyft and big investments try to be like Uber and Tesla electronic cars to in-car entertainment so I'm going to say that the car is one big gadget smartphone Internet of Things device which is true that big data problem that brings up the question GM and Ford or incumbent leaders in Detroit and the automotive industry are shifting radically this digital transformation is that something that you see similar in other verticals that >>  Well I'll stick with that vertical for a second I mean that vertical has shifted dramatically over the years I mean it used to be those companies made money selling cars they no longer made money selling cars years ago they then made money on service now they don't make much money on service now it's going to become the services that sit in the car with those are entertainment services or whatever they may be and so it's gonna be very interesting in that industry how they innovate do they outsource those services to another technology company in the Silicon Valley or do those become the core differentiators of those companies and and it's it's going that disintermediation occurs industry by industry by industry we've now talked about tech and what the implications are for the cloud on tech same things occurring in virtually every vertical.  >>  So you said early it's you know they're an enabler or it's gonna freak people out it's it >> Well this is what happens with innovation when time comes this is why we've done Oracle what we've done.  We've moved as quickly to the cloud as we possibly could.  It doesn't mean our on-premise business isn't strategic and important to us of course it is and I think the combination of the two capabilities gives us a huge differentiator. But that said for us to move quickly was critical we think to our long-term success and that's why we've been as fast moving as we can and I believe that true in every industry.  If you spend doing words like balance protect all of those sort of verbs they don't lend themselves to long-term success.  >> Let's talk about the company now that you're leading with the team. The number one question I get to ask I was told to ask you was ask them how the Co-CEO job is going and I'd like to know what it's like in the day in the life of Mark Hurd with Safra Catz, Larry Ellison take us through some color around what goes on behind the curtain >>  No.  I think well first of all we've been together awhile so so this is not like a new new phenomena so we we think we have sort of a capability that we can do a lot of things at the same time I don't know that that there is a broader team in terms of experiences I'm not trying to say we're great or try to be arrogant about it at all but it gives us the capability to touch a lot of things at the same time.  I've been a CEO multiple times and I can tell you it's a lonely job it's a hard job and it has a lot of responsibilities associated with it the fact that you can get a team that brings with it different skills different capabilities and you get the right personalities that that blend together that's that's a blessing and if you can get it take it . >> That's not just at the top tier of the management team also it's a >> company's pretty strong you know it's a >> I'm glad you brought that up John because I get questions like that a lot about Larry or Safra or they get questions about about all that but the reality is we're 140 thousand people in this company so we're a we're a large company with an enormous number of talented people I mean Thomas Kurian who runs our software development organization John Fowler runs our hardware development organization Dave Donatelli are people running regions we have we have a lot of very very skilled people come our Chief Architect Edward Screven I mean we just have a lot of depth at >> oracle and so it's a lot bigger than >> And the newly hired Dave Donatelli who is a shark when it comes to infrastructure he is strong and how's he working out I mean how's the that's a big >> listen and Dave is really leading the >> I think Dave's done great I mean product management go-to-market efforts around all of our all of our systems team which is going through its own transformation because we see the way infrastructure is now being used today and it's going through a lot of changing and Dave's just a great addition to Oracle >> He should me he knows it he knows the EMC playbook and certainly they have their challenges so I ought to ask you a question another one is that the hardware middleware market is about integration you mentioned that horizontal integration how how challenging is that for you guys and is this part of the transformation message that you guys have done internally because you're asking customers to transform and so can you give an example where you've transformed yourself >> Well when you talk about the middleware market I actually you mentioned the middleware market at least in some of the transformation I actually think with all of the data that we described earlier the opportunity to integrate that data and to integrate that data in the cloud is a huge opportunity for us we introduced an Oracle OpenWorld integration cloud services Oracle integration cloud services and the opportunity now for us to bring that to market and bring that capability to customers you know fantastic opportunity >> Let's talk about competition my favorite subject HP split up EMC sold to Dell , IBM is trying to make a run at it what does all this mean for the marketplace and specifically customers because you know those are big those are big companies that are transitioning or struggling as I'm saying what should what does all that mean connect the dots for the industry dynamics for those >> Well I think the industry our industry is no different than any other industry it's looking for revenue growth it's got leaders that that are are being driven to to grow revenue to grow or means to grow cashflow and in many times when you realize you you can't do that or they they find that they they're not in a position to do that they change and and change is inevitable and that's all you're seeing here is the change of what we described earlier you've got a certain market that behaved a certain way for a long time that market is now interrupted it's going to cause certain people to fail it's going to cause certain people to combine and as a result that change is going to occur and if you're not able to do the things I described the things that Oracle's done so if you will cross the chasm then change is coming and I don't think >> you've seen the end of it John. >> And a lot of these folks made big bets years ago going back a decade what bets do you see not paying off and what bets should people be making to be competitive in this new era >> believe what I said about our strategy I >> Well I think if you're not first in the cloud to begin with you're not gonna be long for this industry point one point two if you don't have enough breath in the cloud and you're just a single player with a point solution you're probably not long for this world so in the end companies want more from fewer people they want help with innovation they want better economics and that's going to prove in the end to come from a few companies in my opinion I think you'll see the same cycle that we've seen before that you'll see companies that frankly remember if you went back to the 80s think about how many great companies were in this industry in the 80s when I started in the industry I'm shame to have to admit that a shame but I hate to have to admit I'm old enough so I started yeah and therefore you look good well they're all gone yeah I mean Wang is gone the Digital's gone Data General is gone this Prime Computer is gone I mean this happens a lot and and this is just us going back to the future where we've got an interruption in the industry it's gonna cause winners and losers and it's the reason John that we've made the investments we've we have we could have easily done none of this invested none of this capital and harvested our existing business and it would look great for a while yeah not long run.    >> Yeah and you and you guys invested in the future at the right time seems it's working great for you guys the numbers are good how do you invest in R&D of some of the numbers in the cloud in terms of revenue book asking . l >> don't we don't give out you know all of >> Welll we our data forward-looking projections but what we did in our last quarter was we talked about our growth in the cloud virtually double our bookings year-over-year we've now got a chance to be in the ball well I won't give numbers out right now because I was already gonna make a forward projection but think of us now as multiple billions of dollars in revenue in  PAS platform and SAS growing and as our revenue has grown John our growth rate has actually gone up we say one more time the revenues grown and the growth rate has increased and so I think this comes down to the fact that we've just gotten better and better at this we've added more people from a salesperson perspective more of our products have become available in the market to the point of the percent of our portfolio that's now available in the cloud and we've now got lots of references and so it's an exciting time for us >> I've got to ask about Amazon Web Services obviously they've been going to have to work with our database and saying they can suck all that in and it'll come up in a second but I interviewed the former CTO of EMC who's now doing a storage startup on his own and he had a comment and I said well  Amazon's winning he says well we always debate what inning are we in in the industry and  Dave Vellante and I'm my cohost argued that he thinks were in the seventh inning I think we're in the first inning and so the guests said no you guys were both wrong,   Amazon won Game one of the doubleheader Game two is about the enterprise and it's not even started so I wanna get your thoughts Amazon certainly did well and doing well and numbers are pretty clear with public cloud now they're aggressively moving into the enterprise and it's just different ballgame talk about the dynamics their vis-a-vis Oracle you're targeting much more business approach understanding the IT side of the business Amazon is kind of do-it-yourself you know launching new stuff every day what's the distinction between the two some love Amazon people love the success you know good job Amazon people you know we cover them we like them they have a good product but it's not the end game to your message what's the difference in the two >> All right I'm gonna stay away from all the baseball analogies I think that they nstarted out as a retailer they had an IT infrastructure to support a retailer I think very clever they needed a lot of IT capacity when retail season was at its height during the holidays they said we've got a bunch of used capacity during other parts of the  un year we'll go rent it to people so they can leverage it makes sense now as you start to move into other workloads as you start working into enterprise workloads and dealing with all of the issues that come up there are more complexities to come up I think that we are in the I'll just say early stages and and by the way remember one thing I mentioned to you I think earlier just before we started and started this interview it doesn't take much of a change in it to have a dramatic effect on the revenue of the industry so I mentioned earlier about this dev test thing 30% of the industry three hundred billion dollars if only 5% of that moves its 15 billion dollars 15 billion goes from somewhere some companies that are supplying that today to somebody else and that's the very beginning of this see I actually don't think very little of this workload today has moved compared to what it will be five to six to seven years from that so - from that just a sheer numerical dimension we're in the very beginnings the very early phases of this the ability to get the bulk of this market is the ability to move massive amounts of workloads from some of the most complicated jobs >> so we're just scratching the surface of what it means >> just beginning >> ok so talk about the customers that you have because you have a lot of customers you guys have a zillion customers Oracle is a dominant player for many many generations of IT and computing we've seen that but I'm sure some of them have Amazon presence or they're kicking the tires doing some shadow IT through some things how are you guys do that because you kind of partner with Amazon on one hand but you also have cuffs cuz you have customers there how is how is that conversation going with Oracle and Amazon you say hey whatever or is there >> no I think that customers can chose to take their Oracle licenses and run them on Amazon they can also get those same capabilities directly out of the Oracle cloud we can take jobs between Amazon and Oracle and have them work together so it's it's really the customer's choice as to what's best for the customer my general view would be that if a customer is doing a platform job writing an application in Java I'll probably get infrastructure from the same person I'm getting Java from so I'm more likely to buy that infrastructure from Oracle if I'm buying that application from Oracle or using that platform from Oracle but if a customer says I'd really like to do my platform job on Oracle and store some of that up on Amazon that's customer's choice >> Okay Amazon is on the list of competitors Larry said one of the things is seeing new competitors he's SAP and IBM now new names yes Amazon, Microsoft Azure seems to be doing well we don't see vmware on that list yet but i mean as you're speaking in a little bit of some of the other players market share and cloud people have different cloud visions Amazon certainly has their in incumbent business Microsoft's what's your take on them visa vie Oracle which one Microsoft Microsoft Microsoft for that >> I'd say Microsoft done a good job I think Microsoft has moved its it's estate to the cloud not very dissimilar from from Oracle their applications is Microsoft the competitor of Oracle I think the answer to that would be sort of but but in many cases not directly their applications are really different from our applications my guess is many of the people using infrastructure from Microsoft are using infrastructure because they use their IP and their platform and/or their applications so I think therefore they they're doing the job that strategically that you see Oracle's multiple billion dollar cloud business doing as well which is moving many of its core capabilities from on Prem to to to the cloud they also have the capability now to merge and on Prem business and a cloud business which again I think it's a really key differentiator as we move forward >> differentiation seem to be dependent >> It seems to be the upon what people had or have going on either past or present so with that there's different approaches so I got to answer the question I'm a customer pretend I'm a customer hey Mark how do I evaluate all this stuff in the day is this like I need a matrix of like who's got one no wonder one's got checkboxes what criteria should I use to decide who >> I think John it comes back to the core stuff of you know who's got the best stuff you know whose stuff really in the end does does the best job for you starting at the application layer through through the platform layer through through the infrastructure layer and then the fact that you can now get this stuff in the cloud is a huge advantage for all the reasons we've been talking about for the past past several minutes but it's still gonna be about who's got the best IP but whoever's got the best IP in the end probably matters - I mean you know performance security I can go through a lot of other issues John but let's start with who's got the best IP I promise you promise you we will perform from a performance perspective I promise you we will have the best security now that said so a customer has done a license on Amazon Web Services are certainly probably doesn't run as good as an Oracle listen I mean obviously I believe the IP you have I believe that we're pretty good at running Oracle workloads I actually believe we're the best in the world at running Oracle workloads and and and and and I think you're gonna see that get yet even better as we >> I can attest theCUBE  interviews on the 48 interviews we did it was pretty clear that Oracle is very well optimized for Oracle on Oracle no doubt and clearly the performances order of magnitude significant >> and our cloud will also be capable of >> But John let me add handling non Oracle workloads so you know we think in the end while we'd love the whole world to run on Oracle we believe there'll be a portion of the world that doesn't and the fact that you can run those capabilities on the Oracle cloud along with your Oracle workload becomes critical as well >> Yeah I want to drill down on that because one of the things that I've observed over the past decade and past five years in particular there's been kind of a Oracle huge community because you have huge customer base but it's always been like you know redstack its proprietary and it's kind of like some whether it's truthful not that's been kind of a narrative but now it's with my sequel you got a lot of open technologies this Oracle OpenWorld it became very clear that integration it's not about redstack anymore referring to Oracle's you know their boxes and brand it's Oracle runs great on Oracle but if you don't have Oracle  you can still be an Oracle customer so talk about that dynamic this is a significant opportunity for Oracle news business >> You know maybe the narrative is the way you describe the narrative and you lowered your voice you know I got a certain impression and from the words you said now that said Oracle's always run hybrid workloads multiple applications around the Oracle database SAP runs in the Oracle database lots of applications run on the Oracle database so I think Oracle's always been if you will open from that perspective while continuing to build a complete stack now I'd make the argument that the cloud in many ways is of any cloud provider is a proprietary stack I mean insert name here is what is by the way that you know what the middleware is that Salesforce uses or the database or the middleware that Workday uses or day you can go down company by company and and at the end of the day you really though don't know what's behind that it is really totally provided to you by that provider and that is what you see being shifted in the cloud you can make the argument and this gets very into another interesting debate much of IT has been the do-it-yourself sort of approach I'm gonna if I will as an IT staff become an R&D organization and if you're a CEO and not a tech CEO but as CEO of a company with an IT organization you have to ask yourself is that really what I want to do do I really want to glue an operating system to a server build anything from scratch sure support it and do all this work and and or would I rather have somebody do it for me now as long as the economics are right and as long as I have trust in that in that in that partner and I'm secure and all the things we've talked about but at the end of the day transferring a lot of work that doesn't give me a lot of economic value add and moving that as I've mentioned earlier to Oracle's R&D budget I think becomes really attractive for a whole suite of >> I think it's great I'll rephrase the question so Oracle has a business as great business and you have customers they have Oracle software and contract value increases they renew they buy a new license new technology you grow your customer base but with cloud native what we with the web skills you pointed out a lot of companies were successful building their own stuff because they didn't have the cash but they had expertise so they would build their own caching and myself and they support it and pick up that cost but now as IT moves to cloud native that's a huge deal they don't want the build there also I agree with you you're looking at me >> I will say this and I don't mean to interupt you but there still is quite a debate in big companies and this is one of these transitions we've talked about the transition really from a tech industry perspective but inside the customer inside IT organizations the cloud is a threat so when you when you look at it as like the mainframe guys many computers were threatened exactly yeah so I'm now in an IT organization you know this do-it-yourself thing this is quite a bit of job security I wrote this application I've got to glue this to this and this is all really complicated and if you talk to a CEO and not get a non tech CEO and you say listen you really don't want to mess with all this because this is really complex and I'm the only one that really knows how to do this this whole thing work we're gonna transfer that complexity to somebody else has its own degree of threat to IT organizations so that debate you described that debate today John is still not over >> I think the Holy Grail whoever can provide a cloud native scalable turnkey infrastructure will probably of course you're right win that business of course right >> this is why these these these moves to your point about what in inor we in or what phase are we in these things have have multiple episodes so >>  are we in that cloud native phase right now are we for the for the new customer comes to Oracle hey you know what I'm I'm growing I've been doing stuff in the cloud with Amazon I've been doing this over here got my bootstrap data center I really want to go to cloud in a big way and we're growing leaps and bounds >> I'll stick with what I said we're in the very beginning of this and and we're in the beauty of this that the amount of IT John the suite of applications you go to any of these big banks in the United States around the world they have just sores of applications most of which were homegrown many of which sit on those mainframes you say we're threatened 25 or 30 years ago this whole move is a big set of moves that will take you know several years and you know use my discussion of 10 years out where I think I'll had it it'll take time like that to move now what customers are gonna want again one more time is I'm not going to be able to take that whole on-prem capability and just say thank you move it over here it's not gonna work so therefore the ability to move this thing job by job and then to be able to coexist these hybrid environments over a period of time become a become a key issue for our customers >> move at their own pace basically not >> so have them happy for examples and I think devtest is a as as >> I think customers I give you much work as has to get done to do that is is a sort of an intellectual layup I I think you're gonna see a lot of devtest move quickly I think you're gonna see applications particularly those applications that don't differentiate the enterprise customer facing application that you think is your unique sacred sauce you may keep that as homegrown on-prem but those commercial applications that don't differentiate me I mean me being the company I will move to the cloud as as quickly as I can >> Great excitement at Oracle OpenWorld this year the theme of integration and we talked to some customers and they were excited by that it's a big problem so that's that's one thing I'd like to talk about the second thing is what confidence can you share with the customers around new growth stretch I was the organic M&A and  organic growth versus M&A your a big buyer you're not afraid to go out and pay a premium for world-class IP but also you're doing IP internally tie those two together integrations the big themes continue to advance the product side as well as the growth strategy around organic growth and buying companies that might fit into >> Sure we spend a fair amount of R&D starting with your second question when I came I think we started spending 3.8 billion and in R&D we'll probably spend 5.2 billion this year in R&D so we we are we invest but not all of it is date we have a few hundred million dollars of our as well so we spent R&D and in in addition to the D the way I like to think about the innovation of Oracle is it's the D it's the art and it's what we acquire and so we have not built everything we've had very much a buy and build strategy we bought in some capabilities that we weren't building and we've merged those to create the portfolio that we have today and yeah we're not gonna stop that's continuing that's the cadence of Oracle right just continue yeah I won't put anything but I will so stop and I will say that we're very focused and and and not at all hesitant when we see something that we think is strategic to us to bring it in and add it to the portfolio you mentioned something early I want to drill down and horizontal integration and growth and vertical integration sometimes people think that mutually exclusive horizontal industry standard commodity hardware was a rage with open-source that helped grow a lot of the market and the web-scale days now vertical integration where hey it works it's kick-ass high-performance you are I don't really care what's in there it works Oracle support set is also working Oracle was kind of people were kind of poopoo in this whole appliance thing go back up you know five years ago good call working so by the way that is the same strategy that's called the class hey so when you really look at vertical integration the cloud is the ultimate in vertical integration because somebody's done now all the work for you when you buy a I try to explain this to customers all the time that when when somebody buys an application in the cloud they have actually procured a hardware database middleware services a data center floor space security they've bought all of that at the same time and so this this shift to the cloud really is the ultimate testimony to to vertical integration and horizontal they're not mutually exclusive you don't see them that's why I mentioned earlier what I said about why I think there will not be a hundred cloud providers supplying to our customer because integration we just talked about it in the vertical sense we want an HR implication that's completely integrated or in the ERP application that's completely integrated but those applications have to work horizontally as well as vertically so I would actually like my ERP application to talk to my HR application it might be nice if my marketing service applications talk to my ERP applications so I really can't I don't want to spend a munch of money on my IT staff horizontally integrating a hundred clouds I'd like somebody to do that for me and that's why having you know Oracle having the suite that we have in terms of applications platform and infrastructure is so important and that's really the trick balancing both really making that happen it seems to be you've got to do both I mean I'm a firm believer that you really have to have that full suite of capability ok so David lanthum IKOS and she'd want to get a question and so I told him I'd read a question for him he says and this is around the on-prem thing your strategy to create seamless experience between on Prem off principle is obviously your customers can't get there overnight how far along on the completion bar are you and your customers to achieving that vision of integration of allogram and off Prem and off prep seamless experience between seamless experience between off Prem and on-premise solutions today you can have an Oracle job running in the cloud you can have an Oracle job running on-premise with Oracle Enterprise Manager you can manage both jobs seamlessly and move workloads back and forth between on Prem in the cloud and you can do that today if we talk a lot about you know mainframes minis going back and looking at history total cost of ownership is a word that's been used in the computer industry going back to technology is a great way to justify things so let's talk about total cost of ownership but also want to get your take on what does patchwork IT mean to you that notion of patchwork IT in context well you've got a lot of terms you'd like to use I I would stick strategically what I said earlier I I think of much of what happened over the last seven eight years as a lot of do-it-yourself work whether you want to call that whatever term you want to use it the whole view of it for example in this valley if you drove up and down one you would see a slew of companies who individually are trying to sell you an IT organization of a company a piece part be sort of like driving up and down and buying a muffler and then buying a bumper and buying all kinds of stuff and putting it together in your driveway this is really now a shift in the industry away from you know patching together all these systems that are extremely complex and moving to a simpler more fully integrated tested optimized environment and it completely increases the complexity of tossa cost of ownership you said increases the complexity decreases the complexity and decreases total cost of ownership even in the industry through many cycles of innovation does that mean I'm old here at the peak of your career thank you very much people are freaking out some people are winning and happy because they're on one side of the disruption era or the other what does this innovation cycle mean to you right now compare and share your color a personal opinion around what's going on right now in the industry compared to other ones and then and how big seismic differences are there or there is it a big shift little shift compare contrast this much I think it's so exciting I think the most exciting things have in our industry in a long time I think the fact is this industry isn't now in a position and evolving into a position where we can really help customers we can get them out of this very complex world that we the industry have created and and like many industries simplify the way our customers get access to a fabulous intellectual property and make it easier and I think this is an opportunity that if you're if you're in this game if you're not listen let's face it out of colleges we haven't there we haven't had the excitement in the tech industry in years the fact is now with a new game to play this is a tremendous change with tremendous set of winners and and you know frankly there's gonna be the losers involved at the same time that's what makes it exciting and cloud is the better mark security was huge an Oracle OpenWorld I gotta ask you this question this came from a source on our wiki bond team top killer tech announcement Oracle OpenWorld was was security but with the Isis Massacre and the France thing the encryption has become a bad word was debated about four years encryption was a top topic in in the conversation that was a key message at Oracle overall everything could be encrypted beyond on encryption all the time as Larry said you guys are talking about what is the state of security right now with encryption and Oracle does that change your security angle with the products or what's what's going on with security right now so we're talking very much now about enterprise applications and and you know I think there's the cloud of all you know we we talked about this little earlier about the perception that I'm now going to take my data that is is very safe in my data center and on prime which we could debate and I'm now gonna move it to a cloud and therefore I feel vulnerable I feel vulnerable that my data is now in the hands of some other entity and and for us I think one big advantage Oracle has is the fact that that we're very good at data we've managed data since the beginning of the company I mean our first customer was yeah well in the CIA was our first customer they remain a customer today and so security has always been at the core of Oracle's DNA now the one of the reasons we have an encrypted database is four years is because when you encrypt them it the performance of the database actually slows so it's been years of evolution years in terms of Exadata development in terms of all the memory that's now I won't go into all the details of the technology but now we can fully encrypt the database and get incredible performance so what you have no hidden performance no I'm not you ready in great job none none incredible performance and the same theme you have an encrypted database now let me tell you what that means that means that when when a customer's HR data is in our cloud our people that are moving around the customers data don't see the customers data they see frankly gibberish they have files the key to that encrypted data can sit with the customer so when that those files come back across the network the customer can decide when where to use the key to open to open that encrypted file so therefore when you're in the Oracle cloud and I listen I encourage everybody ask our competitors how they deal with this ask ask them what their options are how do they deal with that data is is somebody whose nature or provider are there are there people looking at the customers data as they move files around well we've decided that we think the most important thing we can do is secure that data so let's pretend and by the way I don't think this would ever happen but if somebody actually got access to those there's nothing to have access to it's all encrypted talk about the implications for cloud on a global basis data sovereignty is a huge issue with cloud yeah does this impact at all there's a help it does no it does and so that's it's the reason we've had to one of one of the reasons that we've put data centers in many locations as we have so we do have customers that by law have operate in Germany and in the UK and employee data can't be of a UK employee cannot be in Germany and vice versa well we have we now have the ability because of our data center capability in Germany and our data center in the UK to actually make that capability work and so this this issue of data sovereignty like security is a big issue and you're helping the data sovereignty problem with this Robert yes we've had to address it we've had to address it we've had to embrace it and we've had to help it and it's the same thing with security so now you can have a fully secure capable capability in you know 19 20 different countries to help deal with that with that with that data sovereignty and security issue Barker thanks taking the time here for the cube 101 conversation thank you very much thanks John appreciate it you're watching special one-on-one exclusive conversation with Mark Hurd CEO of Oracle here on the cube on the ground here at Oracle's headquarters you

>>live from San Francisco, extracting the signal from the noise. It's the cues covering Oracle OpenWorld 2015. Brought to you by Oracle. How your hosts, John Courier and Jeff Rick Wait, >>We are here. Live in Howard's treated oracle. OpenWorld for Silicon Angles, The Cube Exclusive coverage Star flagship program. We go out to the events extract the cinnamon noise. I'm John Kerry, the founder of Silicon, and Brian gracefully lead analyst on all the cloud and all the infrastructure stuff going on here. Next guess is Jeffrey Davis, Principal Gore, Oracle, global leader for Deloitte and Touche. Legend in the industry. I've been covering Oracle for a long time. Good to see you, John Bryan allegedly knew she had to get that in there. Love that. You know you guys are. The service's angle has been something that the service's business is. It's been changing radically. Now more than ever with clouds. I really want to get your take because you are an executive looking at this transformation of cloud. But the Lloyd across all the Oracle customer base, your party with customers. So you're the front lines. I gotta ask you straight up. What is the number one thing customers are looking at right now that you partner with four Cloud to figure it out. Is it a migration? All the above, And what do you think about that? So when customers are evaluating the cloud or our clients are looking at the club, you really focus on three things. One is agility. Thea other one is time and the other one is valued. So how quickly can we adopt to the changing environment? How quickly can we leverage technologies like clouds in order to be able to respond to our customers, to adapt to the changing needs of our employees, to embrace our business strategy in a new and innovative way? So I said legend, you know, talk about the eighties for women on camera. That's important point I want to bring up. Is that Is that the old way? Big growth of client server was around software middleware right year BC around you name it that created huge consultancies like Lloyd, you participated in that create a lot of wealth creation for the customers, create value, right, but their cycles were long in the deal. That'll be about 12 13 years now, months and almost a year or two, there were all these big deployments. Now the cloud is accelerating when you compare and contrast time of then share. And now with the cloud Just how much the deployments change the software, the organizations, How you guys operate a new way to do that job well, and we're all responding to the market, right? While responding to customers needs Cloud didn't come about because of technology in it of itself. But we're really all in this ecosystem responding to our customers must customers a really demanding from us is there demanding agility and speed. As I said before, if you take a look at the way we used to do things, basically you had a a large capital investment on the part of the customers. They went, they bought the software, they bought the hardware, they had to hire the expertise of an advantage, mail the eggs, and you're looking at a transformation for them that could take anywhere from 12 to 24 months or longer before they would get time to value. And, you know, these projects didn't go as planned. No, that's this is Yeah, I know the change orders came in paid more cash on DSO. We all got a really bad reputation because of the high costs in a long time to value and even if value was ever realized in some cases, now we take a look at the environment and what the cloud enables us to do is move in a much faster pace. Way used to have what we call a waterfall approach to design and implementation went into a big room and you talked about the world and I never ran that way. And then you put it into the system and then people never really embraced it, because when it came out, it didn't look like anything they thought they were gonna get. This is completely different with cloud. Now you can take an agile approach. Now you can sit and listen to the customer demands very quickly respond to what they think they need, where they really generate value. And then you can focus on those things and very quickly there, in a design session with you And at the end of the day, >>changed management is much easier because they've been a part of the process and also, you know, looking at 90 days sprints. You're looking at things that are done. You know, in >>six months, six months, time to value that can give you compress a competitive advantage. You know, that could help you retain Maur employees or customers. So it's really some timetable. Met Lavery s V p of the Cloud Gru. Gru Integration was saying they were doing provisioning on in 24 minutes. Multiple deployments like like nobody's business. What has them in the timetable that you're seeing for some of these times of value, horizons means hurdles. These milestones said days, weeks, months, hours, minutes. I mean, when you go to a customer base where their expectations of what you guys deliver, there's some insight there. Some of it depends on the environment. So remember they're still clients. We have local customers that are in a highly regulated industry or have a very complex prisons process. Those are gonna take a longer there is they're gonna take in. Technology is not necessarily on the critical path. But when you look at those other areas that frankly, you don't differentiate yourself very much or speed with a solution concave you a competitive advantage. You know, you're looking at a client expectations of anywhere from 90 days, you know, to six months, you know, manager here, very manager, but aggressive. Visa VI the old way. Well, certainly, And the other piece that we're not really talking about is, you know, it's not enough for us to put the technology out there. It's also got to be used and adopted. You know, when you had those large transformations. It's very hard for an organization to absorb all of that change. Now we're looking at the fine entry point that you could get with clouds with that fine entry point. Now we can sub select areas with greatest impact, but we're not changing the entire organization. >>Mark Hurd has the C I. O. G. On this morning and one of the comments that he made. I've heard this a number of times over the last 12 18 months. He essentially said, I have a ton of undifferentiated applications now. They're things that that Oracle thinks are fantastic. HCM and C. R. M and Air P. But in essence, everybody has those. Every business has those very undifferentiated, but they're complicated. What? You Seymour, you see more people saying you know what take those. Help me migrate those into SAS applications, you know, save costs. Where do you see more saying, You know what? Give me the other 20%. The ones that drive business differentiation, ones that are new cloud native applications. What do you see in your mix? What's pushing your customers >>to push you? You know, it depends on the geography, and it depends on the industry and some other things. If you want to talk about North America, which tends to be one of the largest markets in the world, if not the largest market in the world, when you're looking in North America, really people have gone through a lot of the major ear piece. Remember the earlier conversation? You know, they have suffered through tens of millions, hundreds of millions of dollars, and their boards were not satisfied that they got the results of the expected. Now, when you take a look at what's happening, you know, people are now being much more strategic in their investments, much more prescriptive there. Look how they spent exactly, because now the boards have different expectations. They've already gone and spent all that money on technology. They can't go back to the board. Can't say we need to redo this. What they do are willing to fund is you want to get into a new business. If you want to spin something off, you need to stand it up right away. If a customer you know, provide you a new opportunity, you want to shift to that new opportunity. Really? Well, technology is the basis of a lot of this transformation. So Cloud provides that opportunity and it's modest investment with really quick, high value. It's a great point >>you look at I t In the past decades prior to this evolution, we're seeing the cloud consolidate, consolidate, consolidate, right? I don't know the well again. I just went to the well, apparently running, you know, whatever the model was there. But now they're under a lot of pressure to drive top line revenue. Absolute. Now, the top line revenue equations, a completely different mindset. You have to go out and oh, cut the market. You gotta use a shadow I t or your authorized go out. Do legitimate stand up new platforms are Can you give me an example of that? We're seeing more of that now. A clear Mandate. Cee Io's Go take a New Hill or let's consolidate these apt and reposition for this new use case, which is not. That's experiment, but it's certainly a new market opportunity, and they gotta do their due diligence, so it's almost unparalleled. Due diligence kills your waterfall. That's one doesn't talk about that dynamic. Where examples you give go. Take that new top line revenue driver. So you know that there are customers that are looking at new partnerships in the marketplace, and those new partnerships have dynamic new business models. You know, it's not like opening up another hamburger stand. You know, they're not necessarily expanding into our core business. They're really looking at ways to amplify growth. If you're gonna take that as a strategic position, then you know customer or client of ours would focus on, you know, let's take this innovation the market. We don't want to invest a lot in it, waste a lot of time and lose the competitive advantage. Let's >>get to market first. Let's provide a new product or service to the market where we can move very quickly, and then the >>net result is we can see the benefits right away. And if it isn't way, haven't sunk a lot of time and money and something that's not necessarily gonna have the same values. We just had Shawn Price on. And I'm gonna ask this because it's a lemon that you're in because you're part of the customer right here, the strategic partner of the customer. So that idea top line revenue growth could come from a partner. When I see How do you work in that? Quick, You're cool to work with my Aunt VI's. Bring that into the table. You're absolutely so this market is changing. You know, Cloud clearly changes everything and much more so than some of the things we've seen in the past. And so now we need to position ourselves differently now for the Deloitte Business Model way. We're really in a specialized business of focusing highly on value and value creation. We weren't necessarily in other areas and we have different partnerships now. Those partnerships are shifting. Oracle provides us a complete platform. You know, we don't >>have to really get involved in a lot of the aspects of the platform that, frankly, we're in our core competency and frankly, weren't our clients what >>you talked about that customer interaction? What do you have to do to change what we've seen? Different size, trying different approaches? We've seen some that are partnering with cloud Provider, but they want to be their own flat for acquiring them. What changes in terms of the skills you have to hire the way you expect that interaction toe happen between you and customer. Because to a certain extent, like for developers, developers love self service. They do. You know, they they are shadow I because they're driving What changes in your world for that? >>So this is really kind of an interesting question. Very early on, when Oracle made cloud product available >>in HCM, we saw an opportunity. Our clients had the demand because they wanted to create a more sticky environment from customers. What better >>way than providing them better products in the HCM space? We made major investments there. Now we're a leader in HCM, and if I look back over that experience, what do we do differently? First of all, we had to change our mindset. You know, it's not enough just to say the cloud, but you gotta live the cloud because it truly is more agile. It truly is faster. You can take your old methods and tools and approaches all the things that worked for you before. A lot of them don't work anymore. There's some but some really good winds here, especially in the change management side. Also, you know, we'd have clients that had to kind of do it yourself brain surgery that have to order their own hardware that have provisional themselves. You know, that became a real mess. Now we're looking at something that's a lot different. We're not in that business anymore. You know, we do support on Prem where our clients think it's important and strategic course. But now we've got a new, agile methodology. Now we've trained our workforce. We've got 14,500 professionals around the world. We've had to move that group, and Oracle really helped us do that. They've been very collaborative in sharing I p and sharing methods and tools with us so we can make that adjustment. Not only have we had to change that when you think about our other methodologies, all of our other methodology to create value to change management, they were all thoroughly integrated. We've had to rethink those, but it's been a great story because we could go to the client. We can say we can get you there faster because where technology was a barrier world, >>it was on the critical path. We're now changing that. And by the way, this technology is not your old technology. It's much better. It's much more robust. How >>do you you know, obviously we're here It at an oracle OpenWorld. It could be called Oracle Cloud >>World if we really wanted to. I mean, >>it's a lot of it is the red stack. A lot of it is one cloud. How do you manage that against customers saying, Well, look, there's other options as well. I wanna have the ability to leverage this cloud for something. Oracles cloud for certain things. How do you do? You find your customers want multiple clouds or one cloud is good enough? >>Well, we're all teaching right? We're all teaching the world about God because you know there's still people that look at it in a variety of different ways. I think it's an excellent question, so let's think about this. >>Do you want to be your own systems integrator for your smartphone. You want to go by an operating system? Do you want to go buy a separate peace of heart? Where do you >>want to decide what APS fit? What don't. And do you want to actually try to get those abs together? I don't think we want to do that anymore. And I try to use that as an example for my clients. Tell them. Look, let's not be your own systems integrator. You is a iittie executive. You could be an officer toe, help the organization get to their business goals. You know, you're not in another yourself a business objective, but you could be an agent for change. I try to educate them so they can help their colleagues explain cloud, take the fear out and then show the art of the possible. What about the security model? I mean, I wouldn't get your take on you little bit biased because your manager Oracle really? But what would be global, critical or complementary events? How you feel about it? But the intense security message is really a game changer in my mind. Follows on incredible theory. Incredible application. Certainly the product's gonna be ready soon. If it works, it's like a car that does the key turnover. It's like it's all good on paper. Certainly a game changer. Security outside number One thing you're hearing Get some color to that because, you know, if that plays out, if you believe that end N security on the chips and software Silicon plays out the way they say it would, that's gonna change the game. For sure. It is. So none of us and you can go through a week without hearing about a major security breach. When you think about this, you step back and think about the potential here. Our stuff is starting to talkto our stuff. But our stuff isn't unless it's based on. Oracle isn't all thoroughly integrated, so somebody can break into our stuff and they can get access to our lives and they can change our lives. That's hugely powerful. So we are very concerned about security, and Lloyd is one of the largest organizations. In fact, we have a cyber practice that looks at both Proactiv reactive aspects of security. Here's the big concern we have as all this stuff starts, get interconnected. The Internet of things, security becomes a major issue. We need more breakthroughs and security. And I think oracles on the vanguard certainly as we get into what we call a hyper hybrid cloud on Prem on Cloud. Some of that's gonna be a great emotion is no. Perimeter is nothing either. Protect is the Wild West total while and, you know, despite what you believe, boards and people are not reacting fast enough to security threats. And that's why you're seeing these breaches into my knowledge. I don't think anybody has been breached with Orgel security in place. But that said, you have to be really, But still, they probably would get out. There's not that they're hiding it, but the point is, you need to be united engine system. It's hard to do that in a open source world, right? So you have a horizontally scaled open source phenomenon, and it's growing our market and a vertically integrated product requirement. You believe I want Indian security, then you gonna go vertically integrated. You do purpose built. But if you want scale a 1,000,000,000 large scale a k a cloud, you want horizontally scalable. How do you reconcile that with your customers? Well, you know so again. It's difficult for them because unless you've had a security threat, it's very difficult to really get them to take the initiative. You know, the more that we can build security in, the more that it's covered in the Red Sea. More that we get a comprehensive end to end product. I think it allows us to help the client realize you know the risk and help them. The old Fowler said. In The Cube they had they had this done in 2005. Finally took a bunch of security breaches to get people's attention to your point. It's on everyone's agenda. Number one right it is. And yet you know how much is enough? Well, we find the people are too reactive and not not proactive enough. >>What's the What's the temperature of your customers right now? I mean, you know, Tesla's out, they're disrupting Uber's out. Their Airbnb are they? Are they sort of defensive and paranoid? You know that Andy Grove, always trying to be aggressive with a saying No, no, no, no. I'm not letting these little guys into my market. I'm gonna go be aggressive and try and push back what a general feeling. There's a lot of interesting startup disruption going on really changing industry. >>There is, and you know, there's so many sort of partnerships and alliances, mergers and new innovations. You know, right now, clients are very uncomfortable. Just the transition from on Prem to Cloud is a major change in our clients have been the expert for technology for decades for their organization. They are having trouble keeping up with all of it. It can be disruptive. They're looking at what's unique in their industry. You know what is regulation driving? You know what is innovation driving in their industry? But, you know, they're always on the learning curve. They're always trying to figure out if we want to get your final thought wrapping up here to get your take for the folks that are watching here on camera that couldn't make it here were beloved world. What is this show about it? We've been here six years. You've seen that transformation. About four years ago, Larry looked like a deer in the headlights, almost stuck in his tracks and smoke coming out of his ears like he felt that the scene felt like a pivotal moment couple years ago. And then since then, just been every year. Oracle just gets more and more energy, just like dominated that march of the crowd. Almost like four years ago. Like we're gonna win that. What's your vibe? You see that same thing here and shared some color on the take is over the years, and we've been doing this a lot in various forms Over the years. There's been the promise of riel innovation. There's been the promise, real change in the industry. We saw sort of incremental change. We really see increments. Exponential change now and now. The promises fulfilled. We have real product. We're taking the market. We're doing interesting product, right? Israel product. It's very riel, and we have work to be done. But yeah, really studies and customers? Well, it's an evolution. But this is really sort of an epiphany at the moment, because we've never had, >>you know, full sweets of product in the marketplace. Not right now. I don't know that there are any other large you know. Air Pia options in the clouds away there is for Oracle and look at the host of service is that have been announced over the last year. >>This this particular show for us, you know, really isn't accelerating. All these products and service is in the cloud that are now available. They give us a lot of different options that we never had. A great quote. Put that on a cube. Jim. Thanks for joining Us. Way are here live in San Francisco's Howard Street for the Cube Special. Exclusive coverage of Oracle OpenWorld Q. Be right back with more of this short break. Thanks for watching.