>> From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. (smooth music) >> Hi, I'm Stu Miniman, and welcome to this special exclusive presentation from theCUBE. We're digging into Pensando and their Future Proof Your Enterprise event. To help kick things off, welcoming in a friend of the program, Scott Raynovich. He is the principal analyst at Futuriom coming to us from Montana. I believe first time we've had a guest on the program in the state of Montana, so Scott, thanks so much for joining us. >> Thanks, Stu, happy to be here. >> All right, so we're going to dig a lot into Pensando. They've got their announcement with Hewlett Packard Enterprise. Might help if we give a little bit of background, and definitely I want Scott and I to talk a little bit about where things are in the industry, especially what's happening in networking, and how some of the startups are helping to impact what's happening on the market. So for those that aren't familiar with Pensando, if you followed networking I'm sure you are familiar with the team that started them, so they are known, for those of us that watch the industry, as MPLS, which are four people, not to be confused with the protocol MPLS, but they had very successfully done multiple spin-ins for Cisco, Andiamo, Nuova and Insieme, which created Fibre Channel switches, the Cisco UCS, and the ACI product line, so multiple generations to the Nexus, and Pensando is their company. They talk about Future Proof Your Enterprise is the proof point that they have today talking about the new edge. John Chambers, the former CEO of Cisco, is the chairman of Pensando. Hewlett Packard Enterprise is not only an investor, but also a customer in OEM piece of this solution, and so very interesting piece, and Scott, I want to pull you into the discussion. The waves of technology, I think, the last 10, 15 years in networking, a lot it has been can Cisco be disrupted? So software-defined networking was let's get away from hardware and drive towards more software. Lots of things happening. So I'd love your commentary. Just some of the macro trends you're seeing, Cisco's position in the marketplace, how the startups are impacting them. >> Sure, Stu. I think it's very exciting times right now in networking, because we're just at the point where we kind of have this long battle of software-defined networking, like you said, really pushed by the startups, and there's been a lot of skepticism along the way, but you're starting to see some success, and the way I describe it is we're really on the third generation of software-defined networking. You have the first generation, which was really one company, Nicira, which VMware bought and turned into their successful NSX product, which is a virtualized networking solution, if you will, and then you had another round of startups, people like Big Switch and Cumulus Networks, all of which were acquired in the last year. Big Switch went to Arista, and Cumulus just got purchased by... Who were they purchased by, Stu? >> Purchased by Nvidia, who interestingly enough, they just picked up Mellanox, so watching Nvidia build out their stack. >> Sorry, I was having a senior moment. It happens to us analysts. (chuckling) But yeah, so Nvidia's kind of rolling up these data center and networking plays, which is interesting because Nvidia is not a traditional networking hardware vendor. It's a chip company. So what you're seeing is kind of this vision of what they call in the industry disaggregation. Having the different components sold separately, and then of course Cisco announced the plan to roll out their own chip, and so that disaggregated from the network as well. When Cisco did that, they acknowledged that this is successful, basically. They acknowledged that disaggregation is happening. It was originally driven by the large public cloud providers like Microsoft Azure and Amazon, which started the whole disaggregation trend by acquiring different components and then melding it all together with software. So it's definitely the future, and so there's a lot of startups in this area to watch. I'm watching many of them. They include ArcOS, which is a exciting new routing vendor. DriveNets, which is another virtualized routing vendor. This company Alkira, which is going to do routing fully in the cloud, multi-cloud networking. Aviatrix, which is doing multi-cloud networking. All these are basically software companies. They're not pitching hardware as part of their value add, or their integrated package, if you will. So it's a different business model, and it's going to be super interesting to watch, because I think the third generation is the one that's really going to break this all apart. >> Yeah, you brought up a lot of really interesting points there, Scott. That disaggregation, and some of the changing landscape. Of course that more than $1 billion acquisition of Nicira by VMware caused a lot of tension between VMware and Cisco. Interesting. I think back when to Cisco created the UCS platform it created a ripple effect in the networking world also. HP was a huge partner of Cisco's before UCS launched, and not long after UCS launched HP stopped selling Cisco gear. They got heavier into the networking component, and then here many years later we see who does the MPLS team partner with when they're no longer part of Cisco, and Chambers is no longer the CEO? Well, it's HPE front and center there. You're going to see John Chambers at HPE Discover, so it was a long relationship and change. And from the chip companies, Intel, of course, has built a sizeable networking business. We talked a bit about Mellanox and the acquisitions they've done. One you didn't mention but caused a huge impact in the industry, and something that Pensando's responding to is Amazon, but Annapurna Labs, and Annapurna Labs, a small Israeli company, and really driving a lot of the innovation when it comes to compute and networking at Amazon. The Graviton, Compute, and Nitro is what powers their Outposts solutions, so if you look at Amazon, they buy lots of pieces. It's that mixture of hardware and software. In early days people thought that they just bought kind of off-the-shelf white boxes and did it cheap, but really we see Amazon really hyper optimizes what they're doing. So Scott, let's talk a little bit about Pensando if we can. Amazon with the Nitro solutions built to Outposts, which is their hybrid solution, so the same stack that they put in Amazon they can now put in customers' data center. What Pensando's positioning is well, other cloud providers and enterprise, rather than having to buy something from Amazon, we're going to enable that. So what do you think about what you've seen and heard from Pensando, and what's that need in the market for these type of solutions? >> Yes, okay. So I'm glad you brought up Outposts, because I should've mentioned this next trend. We have, if you will, the disaggregated open software-based networking which is going on. It started in the public cloud, but then you have another trend taking hold, which is the so-called edge of the network, which is going to be driven by the emergence of 5G, and the technology called CBRS, and different wireless technologies that are emerging at the so-called edge of the network, and the purpose of the edge, remember, is to get closer to the customer, get larger bandwidth, and compute, and storage closer to the customer, and there's a lot of people excited about this, including the public cloud providers, Amazon's building out their Outposts, Microsoft has an Edge stack, the Azure Edge Stack that they've built. They've acquired a couple companies for $1 billion. They acquired Metaswitch, they acquired Affirmed Networks, and so all these public cloud providers are pushing their cloud out to the edge with this infrastructure, a combination of software and hardware, and that's the opportunity that Pensando is going after with this Outposts theme, and it's very interesting, Stu, because the coopetition is very tenuous. A lot of players are trying to occupy this edge. If you think about what Amazon did with public cloud, they sucked up all of this IT compute power and services applications, and everything moved from these enterprise private clouds to the public cloud, and Amazon's market cap exploded, right, because they were basically sucking up all the money for IT spending. So now if this moves to the edge, we have this arms race of people that want to be on the edge. The way to visualize it is a mini cloud. Whether this mini cloud is at the edge of Costco, so that when Stu's shopping at Costco there's AI that follows you in the store, knows everything you're going to do, and predicts you're going to buy this cereal and "We're going to give you a deal today. "Here's a coupon." This kind of big brother-ish AI tracking thing, which is happening whether you like it or not. Or autonomous vehicles that need to connect to the edge, and have self-driving, and have very low latency services very close to them, whether that's on the edge of the highway or wherever you're going in the car. You might not have time to go back to the public cloud to get the data, so it's about pushing these compute and data services closer to the customers at the edge, and having very low latency, and having lots of resources there, compute, storage, and networking. And that's the opportunity that Pensando's going after, and of course HPE is going after that, too, and HPE, as we know, is competing with its other big mega competitors, primarily Dell, the Dell/VMware combo, and the Cisco... The Cisco machine. At the same time, the service providers are interested as well. By the way, they have infrastructure. They have central offices all over the world, so they are thinking that can be an edge. Then you have the data center people, the Equinixes of the world, who also own real estate and data centers that are closer to the customers in the metro areas, so you really have this very interesting dynamic of all these big players going after this opportunity, putting in money, resources, and trying to acquire the right technology. Pensando is right in the middle of this. They're going after this opportunity using the P4 networking language, and a specialized ASIC, and a NIC that they think is going to accelerate processing and networking of the edge. >> Yeah, you've laid out a lot of really good pieces there, Scott. As you said, the first incarnation of this, it's a NIC, and boy, I think back to years ago. It's like, well, we tried to make the NIC really simple, or do we build intelligence in it? How much? The hardware versus software discussion. What I found interesting is if you look at this team, they were really good, they made a chip. It's a switch, it's an ASIC, it became compute, and if you look at the technology available now, they're building a lot of your networking just in a really small form factor. You talked about P4. It's highly programmable, so the theme of Future Proof Your Enterprise. With anything you say, "Ah, what is it?" It's a piece of hardware. Well, it's highly programmable, so today they position it for security, telemetry, observability, but if there's other services that I need to get to edge, so you laid out really well a couple of those edge use cases and if something comes up and I need that in the future, well, just like we've been talking about for years with software-defined networking, and network function virtualization, I don't want a dedicated appliance. It's going to be in software, and a form factor like Pensando does, I can put that in lots of places. They're positioning they have a cloud business, which they sell direct, and expect to have a couple of the cloud providers using this solution here in 2020, and then the enterprise business, and obviously a huge opportunity with HPE's position in the marketplace to take that to a broad customer base. So interesting opportunity, so many different pieces. Flexibility of software, as you relayed, Scott. It's a complicated coopetition out there, so I guess what would you want to see from the market, and what is success from Pensando and HPE, if they make this generally available this month, it's available on ProLiant, it's available on GreenLake. What would you want to be hearing from customers or from the market for you to say further down the road that this has been highly successful? >> Well, I want to see that it works, and I want to see that people are buying it. So it's not that complicated. I mean I'm being a little superficial there. It's hard sometimes to look in these technologies. They're very sophisticated, and sometimes it comes down to whether they perform, they deliver on the expectation, but I think there are also questions about the edge, the pace of investment. We're obviously in a recession, and we're in a very strange environment with the pandemic, which has accelerated spending in some areas, but also throttled back spending in other areas, and 5G is one of the areas that it appears to have been throttled back a little bit, this big explosion of technology at the edge. Nobody's quite sure how it's going to play out, when it's going to play out. Also who's going to buy this stuff? Personally, I think it's going to be big enterprises. It's going to start with the big box retailers, the Walmarts, the Costcos of the world. By the way, Walmart's in a big competition with Amazon, and I think one of the news items you've seen in the pandemic is all these online digital ecommerce sales have skyrocketed, obviously, because people are staying at home more. They need that intelligence at the edge. They need that infrastructure. And one of the things that I've heard is the thing that's held it back so far is the price. They don't know how much it's going to cost. We actually ran a survey recently targeting enterprises buying 5G, and that was one of the number one concerns. How much does this infrastructure cost? So I don't actually know how much Pensando costs, but they're going to have to deliver the right ROI. If it's a very expensive proprietary NIC, who pays for that, and does it deliver the ROI that they need? So we're going to have to see that in the marketplace, and by the way, Cisco's going to have the same challenge, and Dell's going to have the same challenge. They're all racing to supply this edge stack, if you will, packaged with hardware, but it's going to come down to how is it priced, what's the ROI, and are these customers going to justify the investment is the trick. >> Absolutely, Scott. Really good points there, too. Of course the HPE announcement, big move for Pensando. Doesn't mean that they can't work with the other server vendors. They absolutely are talking to all of them, and we will see if there are alternatives to Pensando that come up, or if they end up singing with them. All right, so what we have here is I've actually got quite a few interviews with the Pensando team, starting with I talked about MPLS. We have Prem, Jane, and Sony Giandoni, who are the P and the S in MPLS as part of it. Both co-founders, Prem is the CEO. We have Silvano Guy who, anybody that followed this group, you know writes the book on it. If you watched all the way this far and want to learn even more about it, I actually have a few copies of Silvano's book, so if you reach out to me, easiest way is on Twitter. Just hit me up at @Stu. I've got a few copies of the book about Pensando, which you can go through all those details about how it works, the programmability, what changes and everything like that. We've also, of course, got Hewlett Packard Enterprise, and while we don't have any customers for this segment, Scott mentioned many of the retail ones. Goldman Sachs is kind of the marquee early customer, so did talk with them. I have Randy Pond, who's the CFO, talking about they've actually seen an increase beyond what they expected at this point of being out of stealth, only a little over six months, even more, which is important considering that it's tough times for many startups coming out in the middle of a pandemic. So watch those interviews. Please hit us up with any other questions. Scott Raynovich, thank you so much for joining us to help talk about the industry, and this Pensando partnership extending with HPE. >> Thanks, Stu. Always a pleasure to join theCUBE team. >> All right, check out thecube.net for all the upcoming, as well as if you just search "Pensando" on there, you can see everything we had on there. I'm Stu Miniman, and thank you for watching theCUBE. 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>> Narrator: From around the globe, it's theCUBE with coverage of SUSECON Digital, brought to you by SUSE. >> Welcome back, I'm Stu Miniman. And this is theCUBE's coverage of SUSECON Digital '20. Really excited we get to talk to the SUSE executives, their partners and their customers. In this segment, we have one of the customers, he's in the keynote and really excited to talk to him, Günther Tschabushnig and he is the CIO of ZAMG. If you're not familiar with them, they are the Central Institute for meteorology and geodynamics, the oldest weather service in the world, based out of Austria. Günther, thank you so much for joining us. Great to see you. >> Thank you for being here, thank you. >> All right, so obviously weather something we are very interested on theCUBE. We talk how important data is. And data, is it for central to what your service is doing, providing data, the organizations, they can do lots with it. Give us a little bit, we probably don't have time to go through the 150 plus, years history of the organization, but tell us a little bit about what your organization does, and especially your role as CIO. What's involved with that? >> Oh, let me hook you in. One thing you said, we have the oldest, weather service in the world. I always tell people, we are doing big data analytics between until 1851. And actually that's true. We have actually two big data centers based in Austria. We are operating about 20 petabytes of data, 100,000 data sets per minute. What is very, very interesting for tech guys. We have one small data center additional on over 3000 meters above sea level on the observatory. It's in the middle of the glacier. Can't imagine how cool that is. When you go up, into the glacier and yeah, you have a lot of sensors, a lot of measurements and a lot of data collecting, configurations. Actually, we are also using a lot of super-computers. We do simulating, we do a lot of AI. We did big data analytics and the most important thing, we do a lot of cooperation with the people that are out there. >> Yeah, in 1851, wasn't exactly super-computers. You're gathering data from a lot of sources. Help us understand a little bit. What are some of the, asks that the business have for you? What are the kind of challenges? In 2020, that might be a little bit different than they were years ago. >> Weather comes from, but different source, actually in 1851, it was more for the King, for their wars. Nowadays it's much more peaceful, thank, God. It's more for sporting, it's more for producing things. It's a lot for logistics, but it's actually for all the human people are out there, and therefore we have to use a lot of data, a lot of processes and a lot of different customer journeys. Our most important thing is customer first. So we try to produce, our full costs, our, integrated processes, especially for the customers. Justin, quick example is, the Olympic winter games. The ZMAG is doing the forecast for the last two, winter games, because we are doing now casting and we're very good at now casting that means the forecast between the next five minutes to 15 minutes, with, what's it call a breath of 100, 150 meters, which is very, very important for, some kind of events. But we do other forecast as well. The only thing we cannot forecast but we also to, earthquakes, that means naturally earthquakes on the one side, on the other side, artificial earthquakes, which are produced through, normally bombs or nuclear bombs. And, we are working with the CTBTO, the UN organization together to analyze and to measure is illegally, nuclear tests. To make the world a little bit a better place. >> Yeah, so Günther it's interesting you mentioned in the early days it was, weather for the king. One of the things we look about in data, especially in the public sector is what data, where do you collected from? How much hearing is there? Can you talk a little bit about, how it goes kind of beyond your borders and is there, I guess, how do you work with other organizations there any of data that shared any of the models? How does that work together in your organization? >> The most important thing is the link data to link our data to other organizations and to collect other data from other organizations. It's not forecast anymore. It's forecast, integrating into processes, especially in the business processes. Weather doesn't stop at the borders. That's a good thing. So we had a lot of collaboration with our neighbors. We found a weather services from our neighbors. That's one thing. I have them, the big picture. For, our models for our simulations. But what we also do is a lot of crowd data. Because the more data we get, the more data we can assimilate into our model. The better, the higher is the resolution of our forecast, so we do a lot of integration of this crowd source weather, that could be on the one hand, a simple app that could be a weather station, in our, in your home. But that could also be a photograph. What did you do with your smartphone? Well, we do artificial intelligence algorithms. To get out the information about clouds, about damages, what we integrate again in our models, in our simulations. And give you the better forecast as a response. We have a big, cooperation, for example, with, the Austrian fire department. They get the best forecasts we can ever do. A specialist forecast for the emergencies. When does, a fire in the woods, for example, they need a special soil moisture for example, then wind directions. Do we need wind strengths? They can use this on their smartphone. They can, use the smart watch. They do pictures after emergency, send it back to us. We analyze it and do a live modeling through our super-computers. To have a better forecast on this place. >> Excellent, now you talked about a bit about communities, leveraging, a lot of different technologies, I guess that's a good way for us to help connect the dots to us talking here to at SUSECON. Obviously, open-source, the communities, the piece of what we or hearing at the show. Talk to us a little bit about SUSE , what technologies are using them, what's the role of open-source, is that, the piece of how you look at technology. >> Nothing is more boring than they get weather from yesterday. So what we need is a really fast development of our forecasts, to our customers. And SUSE helps us, there. We have special services, especially on our ship of computers. Well, we use the special SUSE ranking system. We use SUSE, on our storage systems on our software defined storage system. To have a, we can develop man, to our customers, to our cooperation partners. And, the last big thing is we use SUSE containering, that forms, and on AI platforms. So the new SUSE AI platform, we tried to do forecasts for avalanches, for snow avalanches and that's a really, really big effort at the moment, because there are people dying every year in Austria and in the Alps, because of avalanches. And maybe we can save some of them, because we do have good forecast together with SUSE. >> Excellent, you talk about moving to containerization, gives a little insight. You are a government agency. How easy it is for you to take advantage of new technologies? Any guidance you can give as to things that you've through that might be able to help? >> Innovation and new technologies, but kind of moving on the edge, because on the one hand we have 24/7, the whole year long, we have to be high availability. We have a very stable, on the other hand, we want to have new technologies, new innovations. So it's really, really working on the edge. We use two groups, two separate data centers. On one hand, we do the all the stable thing. The high availability things on the other things. On the other data center, on other group, they are doing the true new things. They do containerization, they do blockchain and they do artificial intelligent moves. And the thing is they are working together. They are connected, that means tell it this way. We have a very, very experienced, head of our one group, our stable 24/7 group, and very, very young high potential or not innovation group. To be honest, first two weeks they hated each other, because one guy wanted to have the innovation and going forward and forward and forward, and the other one said, "No stop, we have to be stable. "That's the most important thing." After four weeks with a lot of maintenance for sure, and with a lot of guidance, they started to love each other because they can learn from each other. And that's the main point. We learned about all of these things. Now we can combine, stable with technology, with new technology, with cool, new things, which can be proved in the one side and integrate that in the stable side, a little later. >> That's an excellent story to learn from, learning so important, great to hear that the more traditional, reliable group and the new innovation group work together. Of course we can't let you go talking about weather without touching on climate. So, anybody that's watched the space with his global pandemic has some interesting, I guess you'd say, positive side effects, there are parts of the world where pollution's cleaned up, major impacts, on climate that, I'd expect you have some interesting data on. What can you share, when it comes to climate change? Any advice, you'd give for business leaders, that are looking to help contribute in a positive way. >> Okay, sure actually, a data center, we are also data hub for the ESA, the European Space Agency for their sentinel data. This data is very interesting, because it hasn't direct shows and direct impact how the climate is changing. The most important thing I can tell you as a CIO, it is changing. That's the most important thing. What we are looking for is how can we combine data, to stop this climate change. How can we show other leaders, politicians, etc. How to stop it, how can we work against it, and how they can be cooperate, work against. The thing is if we only show us the weather service, our climate data, that's nice to have. You see what a curve that's going to be warmer and warmer and the parameters are changing, but that's not the goal. The goal is, how can we work together? How can we link data together? To stop pollution, to stop several kind of attributes. To stop climate change. We started to do some collaborations with big companies. One of these is SUSE. One of these is Hewlett Packard, to work together. To combine resources, to combine a compute power, to combine storage, to combine knowledge, especially data to stop climate change. >> Excellent, so Günther final question is, anything you've been seeing strange, being a CIO, a question we always have, something we heard in the keynote is the changing role of the CIO. You talked a bit about AI, talked about, you live with actual cloud, and super-computers. So what in 2020 is kind of different about the role of CIO? >> What I really learned is IT, it's the supporting accompany or the supporting department anymore. IT is, the strategic partner of each domain we have, we had all our scientists and they always told us, "We had a scientist and we need IT." From several years now, they started to work together with the IT, with Artificial Intelligence, with big data analytics, with several platforms, both integrations, how to, solve problems. So the CIO especially, is not the IT leader anymore, it's more the management part of the management board. So that means, the integration of the CIO in the whole company is much, much more then it was several years ago. Meg Whitman, I met years ago and we had a good talk, told me there is no company anymore without IT. That's not correct. There's no company anymore that is IT. Even every culture is IT, everything is IT. It's no support anymore, it's linking anymore. >> Excellent, yeah Günther, such an important point to talk about if a company, is going to thrive in the modern era. Data is such a critical piece of that gives you as a CIO, a seat at the table to work closely with them, because if the business needs to be driven by data, the CIO's role of connecting IT in the business, so important. Thank you so much for sharing your stories. Pleasure to talk with you. >> Thank you, it was a pleasure. >> All right, and we'll be back with more coverage from SUSECON Digital '20. I'm Stu Miniman and thank you for watching theCUBE. (upbeat music)

>>Fly from San Francisco. It's the cube covering RSA conference, 2020 San Francisco brought to you by Silicon angle media. >>Hi everyone. Welcome back to the cubes coverage here at in San Francisco, the Moscone center for RSA conference 2020 I'm job for your host. We are the very special guests, the COO of VMware, Sanjay Poonen, cube alumni. When you talk about security, talk about the modern enterprise as it transforms new use cases, new problems emerge. New opportunities exist here to break it down. Sanjay, welcome back. Thank you John. Always a pleasure to be on your show and I think it's my first time at RSA. We've talked a number of times, but nice to see you here. Well, it's a security guard. Well, this is really why I wanted you to talk, talk to you because operations is become now the big conversation around security. So you know, security was once part of it. It comes out and part of the board conversation, but when you look at security, all the conversations that we're seeing that are the most important conversations are almost a business model conversation. >>Almost like if you're the CEO of the company, you've got HR people, HR, organizational behavior, collaboration, technology, stack compliance and risk management. So the threat of cyber has to cut across now multiple operational functions of the business. It's no longer one thing, it's everything. So this is really kind of makes it the pressure of the business owners to be mindful of a bigger picture. And the attack velocity is happening so much faster, more volume of attacks, milliseconds and nanosecond attacks. So this is a huge, huge problem. I need you to break it down for me. >> Good. But then wonderful intro. No, I would say you're absolutely right. First off, security is a boardroom topic. Uh, audit committees are asking, you know, the CIO so often, you know, reports a report directly, sometimes, often not even to the CIO, to the head of legal or finance and often to the audit. >>So it's a boardroom topic then. You're right, every department right now cares about security because they've got both threat and security of nation state, all malicious, organized crime trying to come at them. But they've also got physical security mind. I mean, listen, growing a virus is a serious threat to our physical security. And we're really concerned about employees and the idea of a cyber security and physical security. We've put at VMware, cybersecurity and, and um, um, physical security. One guy, the CIO. So he actually runs vote. So I think you're absolutely right and if you're a head of HR, you care about your employees. If you're care ahead of communications, you care about your reputation and marketing the same way. If you're a finance, you care about your accounting systems and having all of the it systems that are. So we certainly think that holistic approach does, deserves a different approach to security, which is it can't be silo, silo, silo. >>It has to be intrinsic. And I've talked on your show about why intrinsic and how differentiated that intrinsic security, what I talked about this morning in my keynote. >> Well, and then again, the connect the dots there. It's not just security, it's the applications that are being built on mobile. For instance, I've got a mobile app. I have milliseconds, serious bond to whether something's yes or no. That's the app on mobile. But still the security threat is still over here and I've got the app over here. This is now the reality. And again, AirWatch was a big acquisition that you did. I also had some security. Carbon black was a $2 billion acquisition that VMware made. That's a security practice. How's it all coming together? Can you think of any questions? Blame the VMware because it's not just security, it's what's around it. >> Yeah. I think we began to see over the course of the last several years that there were certain control points and security that could help, you know, bring order to this chaos of 5,000 security vendors. >>They're all legitimate. They're all here at the show. They're good vendors. But you cannot, if you are trying to say healthy, go to a doctor and expect the doctor to tell you, eat 5,000 tablets and sailed. He just is not sustainable. It has to be baked into your diet. You eat your proteins, your vegetables, your fruit, your drink, your water. The same way we believe security needs to become intrinsically deeper parts, the platform. So what were the key platforms and control points? We decided to focus on the network, the endpoint, and you could think of endpoint as to both client and workload identity, cloud analytics. You take a few of those and network. We've been laboring the last seven years to build a definitive networking company and now a networking security company where we can do everything from data center networking, Dell firewalls to load balancing to SDN in this NSX platform. >>You remember where you bought an nice syrup. The industry woke up like what's VM ever doing in networking? We've now built on that 13,000 customers really good growing revenue business in networking and and now doing that working security. That space is fragmented across Cisco, Palo Alto, FIU, NetScaler, checkpoint Riverbed, VMware cleans that up. You get to the end point side. We saw the same thing. You know you had an endpoint management now workspace one the sequel of what AirWatch was, but endpoint security again, fragmented. You had Symantec McAfee, now CrowdStrike, tenable Qualis, you know, I mean just so many fragmented IOM. We felt like we could come in now and clean that up too, so I have to worry about to do >> well basically explaining that, but I want to get now to the next conversation point that I'm interested in operational impact because when you have all these things to operationalize, you saw that with dev ops and cloud now hybrid, you got to operationalize this stuff. >>You guys have been in the operations side of the business for our VMware. That's what you're known for and the developers and now on the horizon I gotta operationalize all the security. What do I do? I'm the CSO. I think it's really important that in understanding operations of the infrastructure, we have that control point called vSphere and we're now going to take carbon black and make it agentless on the silverside workloads, which has never been done before. That's operationalizing it at the infrastructure level. At the end point we're going to unify carbon black and workspace one into a unified agent, never been done before. That's operationalizing it on the client side. And then on the container and the dev ops site, you're going to start bringing security into the container world. We actually happened in our grade point of view in containers. You've seen us do stuff with Tansu and Kubernetes and pivotal. >>Bringing that together and data security is a very logical thing that we will add there. So we have a very good view of where the infrastructure and operations parts that we know well, a vSphere, NSX workspace one containers with 10 Xu, we're going to bring security to all of them and then bake it more and more in so it's not feeling like it's a point tool. The same platform, carbon black will be able to handle the security of all of those use cases. One platform, several use cases. Are you happy with the carbon black acquisition? Listen, you know, you stay humble and hungry. Uh, John for a fundamental reason, I've been involved with number of acquisitions from my SAP VMware days, billion dollar plus. We've done talking to us. The Harvard business review had an article several years ago, which Carney called acquisitions and majority of them fail and they feel not because of process of product they feel because good people leave. >>One of the things that we have as a recipe does acquisition. We applied that to AirWatch, we apply the deny Sera. There is usually some brain trust. You remember in the days of nice area, it was my team Cosato and the case of AirWatch. It was John Marshall and that team. We want to preserve that team to help incubate this and then what breve EV brings a scale, so I'm delighted about Patrick earlier. I want to have him on your show next time because he's now the head of our security business unit. He's culturally a fit for the mr. humble, hungry. He wants to see just, we were billion dollar business now with security across networking endpoint and then he wants to take just he's piece of it, right? The common black piece of it, make it a billion dollar business while the overall security business goes from three to five. >>And I think we're going to count them for many years to come to really be a key part of VMware's fabric, a great leader. So we're successful. If he's successful, what's my job then? He reports to me is to get all the obstacles out of the way. Get every one of my core reps to sell carbon black. Every one of the partners like Dell to sell carbon black. So one of the deals we did within a month is Dell has now announced that their preferred solution on at Dell laptops, this carbon bike, they will work in the past with silence and crowd CrowdStrike. Now it's common black every day laptop now as a default option. That's called blank. So as we do these, John, the way we roll is one on here to basically come in and occupy that acquisition, get the obstacles out of the way, and that let Patrick scaled us the same way. >>Martine Casado or jumbo. So we have a playbook. We're gonna apply that playbook. Stay humble and hungry. And you ask me that question every year. How are we doing a carbon black? I will be saying, I love you putting a check on you. It will be checking in when we've done an AirWatch. What do you think? Pretty good. Very good. I think good. Stayed line to the radar. Kept growing. It's top right. Known every magic quadrant. That business is significant. Bigger than the 100 million while nice here. How do we do a nice hero? NSX? It's evolved quite a bit. It's evolved. So this is back to the point. VMware makes bets. So unlike other acquisitions where they're big numbers, still big numbers, billions or billions, but they're bets. AirWatch was a good bet. Turned out okay. That the betting, you're being conservative today anyway. That's it. You're making now. >>How would you classify those bets? What are the big bets that you're making right now? Listen, >> I think there's, um, a handful of them. I like to think of things as no more than three to five. We're making a big bet. A multi-cloud. Okay. The world is going to be private, public edge. You and us have talked a lot about VMware. AWS expanded now to Azure and others. We've a big future that private cloud, public cloud edge number two, we're making a big bet on AB motorization with the container level 10 zoos. I think number three, we're making a big bet in virtual cloud networking cause we think longterm there's going to be only two networking companies in matter, VMware and Cisco. Number four, we're making a big bet in the digital workspace and build on what we've done with AirWatch and other technologies. Number five, and make it a big bet security. >>So these five we think of what can take the company from 10 to 20 billion. So we, you know, uh, we, we've talked about the $10 billion Mark. Um, and the next big milestone for the company is a 20 billion ball Mark. And you have to ask yourself, can you see this company with these five bets going from where they are about a 10 billion revenue company to 20. Boom. We hope again, >> Dave, a lot that's doing a braking and now he might've already shipped the piece this morning on multi-cloud. Um, he and I were commenting that, well, I said it's the third wave of cloud computing, public cloud, hybrid multi-cloud and hybrids, the first step towards multi-cloud. Everyone kind of knows that. Um, but I want to ask you, because I told Dave and we kind of talked about this is a multi-decade growth opportunity, wealth creation, innovation, growth, new opportunity multicloud for the generation. >>Take the, this industry the next level. How do you see that multicloud wave? Do you agree on the multigenerational and if so, what specifically do you see that unfolding into this? And I'm deeply inspired by what Andy Jassy, Satya Nadella, you know, the past leading up to Thomas Korea and these folks are creating big cloud businesses. Amazon's the biggest, uh, in the iOS pass world. Azure is second, Google is third, and just market shares. These folks collectively are growing, growing really well. In some senses, VM-ware gets to feed off that ecosystem in the public cloud. So we are firm believers in what you're described. Hybrid cloud is the pot to the multicloud. We coined that term hybrid thought. In fact, the first incantation of eco there was called via cloud hybrid service. So we coined the term hybrid cloud, but the world is not multi-cloud. The the, the key though is that I don't think you're gonna walk away from those three clouds I mentioned have deep pockets. >>Then none of them are going away and they're going to compete hard with each other. The market shares may stay the same. Our odd goal is to be a Switzerland player that can help our customers take VM or workloads, optimize them in the private cloud first. Okay? When a bank of America says on their earnings caller, Brian Warren and said, I can run a private cloud better than a public cloud and I can save 2 billion doing that, okay? It turns off any of the banks are actually running on VMware. That's their goal. But there are other companies like Freddie Mac, we're going all in with Amazon. We want to ride the best of both worlds. If you're a private cloud, we're going to make you the most efficient private cloud, VMware software, well public cloud, and going to Amazon like a Freddie Mac will help you ride your apps into that through VMware. >>So sometimes history can be a predictor of future behavior. And just to kind of rewind the computer industry clock, if you looked at mainframe mini-computers, inter networking, internet proprietary network operating systems dominated it, but you saw the shift and it was driven by choice for customers, multiple vendors, interoperability. So to me, I think cloud multicloud is going to come down to the best choice for the workload and then the environment of the business. And that's going to be a spectrum. But the key in that is multi-vendor, multi, a friend choice, multi-vendor, interoperability. This is going to be the next equation in the modern error. It's not gonna look the same as mainframe mini's networking, but it'll create the next Cisco, the create the next new brand that may or may not be out there yet that might be competing with you or you might be that next brand. >>So interoperability, multi-vendor choice has been a theme in open systems for a long time. Your reactions, I think it's absolutely right, John, you're onto something there. Listen, the multicloud world is almost a replay of the multi hardware system world. 20 years ago, if you asked who was a multi hardware player before, it was Dell, HP at the time, IBM, now, Lenovo, EMC, NetApp, so and so forth and Silva storage, networking. The multicloud world today is Amazon, Azure, Google. If you go to China, Alibaba, so on and so forth. A Motiva somebody has to be a Switzerland player that can serve the old hardware economy and the new hardware economy, which is the, which is the cloud and then of course, don't forget the device economy of Apple, Google, Microsoft, there too. I think that if you have some fundamental first principles, you expressed one of them. >>Listen where open source exists, embrace it. That's why we're going big on Kubernetes. If there are multiple clouds, embrace it. Do what's right for the customer, abstract away. That's what virtualization is. Managed common infrastructure across Ahmed, which is what our management principles are, secure things. At the point of every device and every workload. So those are the principles. Now the engineering of it changes. The way in which we're doing virtualization today in 2020 is slightly different from when Diane started the company and around the year 2020 years ago. But the principals are saying, we're just not working just with the hardware vendors working toward the cloud vendors. So using choices where it's at, the choice is what they want. Absolutely, absolutely. And you're right. It's choice because it was the big workloads. We see, for example, Amazon having a headstart in the public cloud markets, but there's some use cases where Azure is applicable. >>Some use his word, Google's applicable, and to us, if the entire world was only one hardware player or only one cloud player, only one device player, you don't need VMware. We thrive in heterogeneity. It's awesome. I love that word. No heterogeneity provides not 3000 vendors. There's almost three, three of every kind, three silver vendors, three storage vendors, three networking vendors, three cloud vendors, three device vendors. We was the middle of all of it. And yeah, there may be other companies who tried to do that too. If they are, we should learn from them, do it better than them. And competition even to us is a good thing. All right. My final question for you is in the, yeah, the Dell technologies family of which VMware is a part of, although big part of it, the crown jewel as we've been calling them the cube, they announced RSA is being sold to a private equity company. >>What's the general reaction amongst VMware folks and the, and the Dell technology family? Good move, no impact. What we support Dell and you know, all the moves that they've made. Um, and from our perspective, you know, if we're not owning it, we're going to partner it. So I see no overlap with RSA. We partner with them. They've got three core pillars, secure ID, net witness and Archer. We partnered with them very well. We have no aspirations to get into those aspects of governance. Risk and compliance or security has been, so it's a partner. So whoever's running it, Rohit runs on very well. He also owns the events conference. We have a great relationship and then we'll keep doing that. Well, we are focused in the areas I described, network, endpoint security. And I think what Michael has done brilliantly through the course of the last few years is set up a hardware and systems company in Dell and allow the software company called Vima to continue to operate. >>And I think, you know, the movement of some of these assets between the companies like pivotal to us and so on and so forth, cleans it up so that now you've got both these companies doing well. Dell has gone public, we Hammer's gone public and he has said on the record, what's good for Dell is good, what's good for VMware and vice versa and good for the customer. And I think the key is there's no visibility on what cloud native looks like. Hybrid, public, multi, multi, not so much. But you get almost, it's an easy bridge to get across and get there. AI, cyber are all big clear trends. They're waves. Sasha. Great. Thank you. Thanks for coming on. Um, your thoughts on the security show here. Uh, what's your, what's your take to, uh, definitive security shows? I hope it stays that way. Even with the change of where RSA is. >>Ownership goes is this conference in black hat and we play in both, uh, Amazon's conference. I was totally starting to, uh, reinforce, reinforce cloud security will show up there too. Uh, but we, we think, listen, there's what, 30,000 people here. So it's a force. It's a little bit like VMworld. We will play here. We'll play a big, we've got, you know, it just so happens because the acquisition happened before we told them, but we have two big presences here. We were at carbon black, um, and it's an important business for us. And I said, like I said, we have $1 billion business and security today by 30,000 customers using us in a security network, endpoints cloud. I want to take that to be a multi, multiple times that size. And I think there's a pot to do that because it's an adjacent us and security. So we have our own kind of selfish motives here in terms of getting more Mindshare and security. >>We did a keynote this morning, which was well received with Southwest airlines. She did a great job. Carrie Miller, she was a fantastic speaker and it was our way of showing in 20 minutes, not just to our point of view, because you don't want to be self serving a practitioner's point of view. And that's what's really important. Well finally on a personal note, um, you know, I always use the term tech athlete, which I think you are one, you really work hard and smart, but I got to get your thoughts. But then I saw you're not on Twitter. I'm on. When IBM announced a new CEO, Arvin, um, fishnet Indian American, another CEO, this is a pattern. We're starting to see Indian American CEOs running cup American companies because this is the leadership and it's really a great thing in my mind, I think is one of the most successful stories of meritocracy of all time. >>You're quick. I'm a big fan of oven, big fan of Shantanu, Sundar Pichai, something that Ellen, many of them are close friends of mine. Uh, many of them have grown up in Southern India. We're a different ages. Some of them are older than me and in many cases, you know, we were falling behind other great players like Vino Cosla who came even 10 to 15 years prior. And you know, it's hard for an immigrant in this country. You know, um, when I first got here and I came as an immigrant to Dartmouth college, there may have been five or 10 Brown skin people in the town of Hanover, New Hampshire. I don't know if you've been to New Hampshire. I've been there, there's not many at that time. And then the late 1980s, now of course, there's much more, uh, so, you know, uh, we stay humble and hungry. >>There's a part of our culture in India that's really valued education and hard work and people like Arvin and some of these other people are products. I look up to them, the things I learned from them. And um, you know, it's true of India. It's a really good thing to see these people be successful at name brand American companies, whether it's IBM or Microsoft or Google or Adobe or MasterCard. So we're, we're, I'm in that fan club and there's a lot I learned from that. I just love being around people who love entrepreneurship, love innovation, love technology, and work hard. So congratulations. Thank you so much for your success. Great to see you again soon as you put in the COO of VM-ware here on the ground floor here at RSA conference at Moscone, sharing his insight into the security practice that is now carbon black and VMware. All the good things that are going on there. Thanks for watching.

>> Narrator: Live from Las Vegas, it's theCUBE. Covering UiPath Forward Americas, 2019. Brought to you by UiPath. >> Welcome back everyone to theCUBE's live coverage of UiPath Forward here at the Bellagio in Las Vegas, Nevada. I'm your host, Rebecca Knight, co-hosting alongside of Dave Vellante. We're joined by Cathy Tornbohm, she is the distinguished VP Analyst at Gartner. Thank you so much for coming on theCUBE. >> Very welcome, nice to be here. >> And Guy Kirkwood, he is the Chief Evangelist at UiPath. Thank you so much. >> Thanks Rebecca. >> So, we're hearing so much of these mantras, these catchphrases of UiPath. "automation first", "a robot for every person", "we're re-booting work", these are the theme's that Guy was touting up on the main stage, Cathy. Beyond that, I'd like to hear from you a little bit about what you're seeing in the RPA space at the moment. What are the trends and the themes that you think are most salient? >> I think the most fascinating thing about RPA right now is that it's really highlighting the problems the organizations have. All their accidents of history are really being brought up by RPA. And then you've got these digital darlings that they're trying to compete with, the Greenfield site kind of people. And some of those don't have beautiful back offices, but let's not go there for a minute. So, it, RPA is an opportunity for companies to link their digital dreams with their existing legacy nightmares. >> And those legacy nightmares include all of the things that Guy was talking about today: the drudgery, the dreariness, those mundane tasks that take up so much of our time. >> Absolutely, and really, if you think about it, in organizations, typically less than 15% of the applications that they're using have got some sort of application programming interface. So if you don't have a way of linking them, you end up with this long turn of applications that aren't linked together, with people literally being swivel-chair integration between the applications. >> Well, why can't you just string a bunch of API's together and automate that way? >> Well, in fact, there's a guy called Ian Barkin who works for Symphony, one of their organizations, it was set up to create automations for organizations. So one of the services businesses since been acquired by Sykes. And he describes it as process sediment, and it builds up in businesses in the same way that sedimentary rock builds up over millions of years. And digging through that, so that you can actually become more efficient is very difficult to do. So doing it on API level means you got to join up all those things individually. Whereas, using RPA, if system 'A' has a user interface, and system 'B' has a user interface, you can just use RPA. >> So, Cathy, you've been following process automation as a category for a number of years. Why RPA, why is it so hot, and why now? We've heard that it's the number one software category... >> Cathy: Fastest growing, yeah. Fastest growing, from Gartner. We've seen spending data that confirms that. Why now? (sighing) >> It's the digital competition that companies are facing, and the recognition that they cannot continue to be quite as bad at some of the things that they are bad at. So it's really that business transformation story back again, business process re-engineering, the same story that we had with BPO like ten years ago, but now, with robots instead. >> Yeah, it's interesting, I was at a, we had a show last weekend, it was the CEO of Suze, Suze... How do ya say it? Anyway, Suze, she said to me, "Well, you know, digital transformation's really about business transformation." And you kind of said the same thing. I mean, thoughts on that? >> I mean, you look at the start of the outsourcing market, the BPA market, twenty years ago. The very first deals were actually IT outsourcing deals that then transformed the business using IT as the enabler. So the first deal that I got involved with ever, in the outsourcing market, was Perot Systems with a British and Asian company. And we were putting in business process re-engineering consultants who actually transformed the business using IT as the enabler for that. There is no difference now, in fact one of the, one of the partners here, one of our original customers, actually put together a plan where we did the implementation, you know, soup to nuts, so that we could find out how we fit in to that whole transformation piece. And our team put together a whole package on all the learnings that we got out of that. And I had to laugh, because they're exactly the same things that every transformation program has had for the last thirty years. >> You know, if you look at kind of the history of certain segments, and I wonder if, Cathy, if you see RPA as one of them, like if you could've figured out who was implementing ERP the best, you didn't know SAP was going to become the leader, but if you could've figured out who was adopting ERP, you could've made a lot of money in the stock market, 'cause those companies had a huge productivity boost. Kind of same thing with Big Data, nobody really made any money in Big Data, so-called 'Big Data', a dupe. But the guys who applied it probably did pretty well. Do you see RPA as similar where the practitioners are going to actually be the ones that add more value to the industry than the new, the newly minted billionaires? >> It's almost the opposite. So the more RPA a company needs, it means the worse they did at managing their ERP in the first place. >> So they're kind of a mess? >> Yeah, yes. That need to be cleaned up, yeah. >> Yes, if you've got a hundred and twenty four ERP's that don't talk to each other, and you want to close your books in any kind of reasonable time frame, you're going to be a massive adopter of RPA, which basically means the more rubbish you are and activity, the more opportunity there is to automate more of it. >> So, what are the metrics that matter when you talk to your clients? >> Well, what I try and encourage clients to do is to really focus on business outcomes. So, much as Guy probably doesn't want me to say this, I don't really care how many 'scripts', aka robots, you've built, or how many run times you've deployed. What I care about is the business impact that you've managed to achieve. So, whatever KPI's are important to you, so are you managing to collect more revenue? Are you managing to make your customers happier because you're managing to decrease average handle times? or increase right first time activities. So anything that you're doing that actually improves the good old business metrics, is just going to be fantastic. So those are the sort of metrics that, really, companies should be focusing on. Not how many scripts they've built, that's absolutely pointless. >> I mean, are they focusing on that? I mean, when you... >> Yeah, lots of people are. >> Yeah? >> Yeah. >> In terms of ROI, we hear from customers that it has had them more accurate, they're more efficient, they're cost saving on human hours of the mundane tasks. But, when you were up on the main stage talking about how we're rebooting work, we're changing this moment, is it sparking the creativity, the imagination, the time spent on strategy in the more higher-level things? Is that, I mean that seems like that's the goal of return on investment. >> It is, within those organizations that are the most mature. So, what we're seeing, is the bifurcation, really, of the market between those organizations that are just starting and scaling up what they can, internal senses of excellence. Those organizations that are using the partners behind us. Those organizations that are using external parties to help them develop that. So Delight, for instance, they are sort of a managed service business. And instead of using people, they're using automation. So, Delight, by accident, has a BPA business in Spain, but then they'll turn that into an automation-heavy business and then providing that managed service. And then, the smartest customers, including SNBC, who we heard from yesterday, are actually turning their back office cost operations into a front office of revenue generator. Now, that is radically different from what we've seen prior. >> So Cathy, I got to ask you, when I was on a plane out here, somebody texted me a picture of the latest hype cycle. And they said, they knew I was going to UiPath, they said, "RPA has entered the trough of disillusionment." I said, "Oh, awesome, Gartner's, Cathy's coming on, and I can ask her about that." Well, what's your take on that? >> I think as Guy says, some people have already sailed through the trough, they've already gone through the challenges, or some of the challenges, and they've already found these fantastic productive things. I mean, we're estimating that people will save close to a million dollars for a large company, and just not having to do re-work of getting it wrong first time with re-keying that data. So, where there's some fantastic savings available, that you know, some of the ones have gone through the trough and done that, a lot of the other ones, they kind of, they don't understand the limitations of RPA and all those other partner tools that they need to put with it. So, don't understand it, can't handle unstructured data by itself. It needs a sister tool, so, what Gartner's talking about right now is this concept of hyper automation where you look across all the different activities that you would need to, sort of replace a person. So the people that are heading into the trough as sort of this second wave of adopters that Guy talked about, that will really struggle because they didn't understand the limitations in the first place. >> Well then, you know the, sometimes, things like the Magic Quadrant, and the trough of disillusionment, they're somewhat misunderstood sometimes, people, you know they see 'em, Gartner's very clever with the way it works things, but, so how should we think about that hype cycle? It's actually, in a way it's progress, isn't it? For an industry where they start... Entering that trough. >> Its, what Gartner says, is all industries have to go through that type of growing pains. And I think that we're seeing that, UiPath's expanded massively, and that's always a challenge for companies as they grow very rapidly. And as companies try and, as they say, take these wrong metrics. So I think things like UiPath buying ProcessGold is fantastic, it's a really, really good move for them. And I expect to see a lot of other process mining companies acquired, brought in to the RPA fold, because, there's four reasons why companies are going to go into this disillusionment, right? These are the main challenges with companies trying to use RPA properly. One is, they don't know what the processes are. So ProcessGold will give you a really good indication, they don't know about the microscopic level, and they don't know about the macro level. So things like digital twins will be something else that we would expect to see very closely partnered with companies like UiPath. And they don't know how to orchestrate their resources. So, other companies, like Innate, that can help you figure out how to do that will become... So its kind of like we're sort of breaking down a lot of what happened in other software categories and re-building them all up, in the way that the business can actually adopt them, hence, the AI Fabric sort of idea. So they don't know the processes, politics, people will lie to you about what they do all day, so they can sabotage your process, and there's a lot of silos within organizations that hate each other and throw things over the wall. So that all needs streamlining, and the more you can do across silos, the more successful any automation project would be. Then you've got, when you take a person out of a process, you take their eyes, their ears, the mouth, the nose. How are you going to replace that when you're trying to take them out, because you've got the keyboard fingers thing with the RPA tool? You need all these other activities replaced, replicated, supported. And then you've got the economics of production, so actually making sure that the scripts that you've built are actually worthwhile and are going to be cost-effective. It's something that we're studying at the moment. So you've got all these, all these different barriers, from all these different angles that are really going to push this thing into the trough for a little bit. And that's why it's great that RPA companies are looking at ways to mitigate that for their customers. >> Now, remember we said, as the understandings. So RPA is really good at dealing with structured data. Rule-spaced activities, deterministic things. That's why in regulatory, highly regulated environments, it's very effective, and the regulators love this sort of stuff. Because it's deterministic. When you look at AI, then we look at it in four ways. So you've got process understanding, which is the ProcessGold acquisition, you look at conversational understanding, 'cause ultimately robots are going to be controlled by voice. So you have to understand, the system has to understand that, let's say you're sitting in a bank, and the robot doesn't understand something, you say, "Okay, robot, stick that in the Well's account." It has to understand that Well's, in this case, means Well's Fargo. It does not mean a hole in the ground, water at the bottom, or a town in Somerset, in the UK, 'cause they're well's. So getting those ontologies correct is so important. So, that's conversational understanding. Document understanding. Because, as Cathy said, companies are still wading around in paper. So, understanding what those different documents are and how to action them is going to be really important. And finally, you're looking at visual understanding. So understanding and viewing things on the screen exactly the same way that humans do. So it's getting that combination right. >> So for RPA to live up to the hype, and there's a lot of hype, and it's a good thing, it's fun to track. It's got to go presumably beyond cleaning up the crime scene, if you will, to this new vision that you and Guy just laid out. What is the distance between, I dunno, sometimes I say 'paving the cow path', which gives you a nice hit, but as you say, it's 'cause companies... Ya know, they're messed up, to this vision of this, actually the guy from Pepsi today talked about it, this fabric of automation across the organization. How big of a gap is that? >> It's very different by every different company on the planet, really, in terms of their accidents of history, what their IT application landscape looks like, and what their business landscape looks like. And when you try and put the two things together, that's where you find the opportunities for any type of automation. >> Well come on, that's such an 'it depends' answer. (laughing) At the macro, will... In your expert opinion, will RPA live up to the hype? So many trends haven't, enterprise data warehousing, Big Data, Doob, all that stuff. You think RPA has the potential to crack through that. >> You mentioned a very good point. I think the most successful companies are the ones that actually will take the person that's managing the data and analytics of how their process is performing, and doing that with their automation strategy. And there are very few companies that've actually worked that out. They've still got totally two walls and they just meet up here at the CEO. So, unless companies actually take a more active business outcomes approach, and look at their end-to-end processes of order to cash and source to pay, these problems will carry on for some time. >> Well that's a great point, I mean, so it's data, it's machine intelligence, I guess Cloud for scale, you guys made a SAS announcement today, it's "automation first", to use your buzz word. >> Cathy: You need it all to come together. >> And it's really developing those best practices in your role as Chief Evangelist in helping understand what the most successful companies do, and then making sure that's implemented. >> Well that's why I spend more of my time listening than I do talking. Because the very nature of being a Chief Evangelist is the best job and the worst job title in the world. It's the best job because I spend my entire time talking to people like Cathy who know about what's happening within the market, and then feeding it back into our organization so we can make the right bets, so we can make the right acquisitions, but develop the right things. The bad thing about the job, is that I keep getting an inordinate number of people on LinkedIn saying, "So pleased that Jesus has entered your life." And I'm not that type of evangelist. (laughing) >> It's in the title. >> You know there's always this age-old debate in the industry of best of breed versus kind of a sweet approach. You see in SAP, for instance, acquired an RPA company, In Four talks about it. And then you get the specialist, UiPath. How do you see that shaking out, as the industry gets kind of more consolidated, how do you see a company like UiPath thriving, continuing to thrive? >> Gartner's going to predict coming in our new prediction series, but... Roughly 20 to 30% of enterprise adoption of AI, machine learning activities for process-based activities, will go through the RPA market. So, and with the IBPMS market, sort of combined together, that process management, because RPA has managed, cleverly, to capture the imagination of the business person. So, actually, there's a lot of IT departments that are talking to us about, how do we, how do we enshrine this activity, foreshadow IT, that's happening in the business, and make it successful, put governance plans in place so it will actually be successful in the way that it's actually now dealing with its own crime scene... (laughing) (mumbling) Its own rubbish, in a much better way. And I think that responsibility of business to understand how it can automate things and how it can manage things will really help a lot. So, I think the RPA players are well-placed to either be acquired into that bigger set of the established, large... Software providers, all to kind of keep blazing a trail for independence of the business. I'm not so sure about this idea that everybody should be programming their own scripts, I think that's a challenge. And I think the new interfaces will help mitigate some of the problems that we've seen with that approach, that hasn't been, haven't been very well done historically, so that's another area that will probably be a bit trough of disillusionment, but, actually, well-managed RPA projects have actually got a really good chance of delivering back very interesting benefits for businesses. >> Yeah, as a discreet innovation category, it does kind of feel that way, and often times, those markets are winner take most, the winner makes a ton of dough, number two makes a little bit of money, number three kind of breaks even, and everybody else gets consolidated or goes out of business, so, you guys go big or go home. That's kind of... Your posture. >> Tomorrow morning I'm doing, I'm doing my predictions for next year, and one of them is that the challenger RPA vendors, and indeed the service organizations that are small, are going to continue to consolidate and get acquired next year. So that's the 2020 prediction for us. >> Great. Well, Guy and Cathy, thank you both so much for coming on theCUBE. It was a great conversation. >> Oh, good, thank you. >> Thank you very much, indeed. Thanks Rebecca. >> Dave: Thanks you guys. >> I'm Rebecca Knight for Dave Vellante, stay tuned for more of theCUBES live coverage of UiPath. (techno music)

(upbeat music) [Narrator] Live from Boston, Massachusetts, it's theCUBE, covering AWS re:Inforce 2019. Brought to you by Amazon Web Services and its ecosystem partners. >> Everyone, welcome back to the CUBE'S live coverage here in Boston for AWS re:Inforce, Amazon Web Service's inaugural event. I'm John Furrier, my co-host Dave Vellante, two days of wall to wall coverin'. Christian Beedgen is the CTO and co-founder of Sumo Logic. A couple we've covered on theCUBE many times as well as on our siliconANGLE.com. Great to see you thanks for coming out. >> Thanks for having me. >> Being the co-founder you've seen it, you guys are celebrating your tenth year. >> That's right. >> Congratulations. >> Thank you very much. >> theCUBE is now 10 years old this year too, >> Oh right on. >> So we're kind of in school together growing up. (laughing) >> Started right here. >> We're going to graduate together, right on. >> We'll go have a cocktail later maybe talk about some tech. I love talkin' tech. >> Yeah of course. >> Lets get into it. As the co-founder and CTO you've seen your journey. You guys have been doing great. You've seen the waves of big data. >> Yep. >> You've seen the evolution of cloud coming in. >> Yep. >> The infrastructures standing up more and more efficient, more effective. Game is changing, stakes are higher, what's your view of this industry right now? >> I think its on fire really, right? So, you know, on one level we have this, I think its fairly well known at this point that the data now today follows Moore's law right? So we have basically data grows you know, roughly two x year over year. That's exponential growth and that's pretty incredible, right? I think every business now knows or, you know, they either know or they act on it or they sort of know it at least, you know, subconsciously right? That they are essentially in a race to sort of optimize, their own business mostly based on data. >> In your opinion, Christian, what was the inflection point of the past few years? When did the data market really change for the highly accelerated we're seeing now because back in 2010 when you guys started when we started, we saw Hadoop just getting out of the blocks. >> Yep. >> People were standing up Hadoop clusters and being proud of it but then cloud came. Was there a point in time when you say, you know that was really the flash point where things started tipping over, or was cloud adoption or was it AI machines, was the machine learning? Where do you see that kick up on the growth of emphasis? >> So you know the Hadoop stuff basically came out of the ad optimization being you know businesses and that was like a small set of companies that really had to do that in order to basically compete with each other. And then we sort of got open source versions of that and then we'd got behind them after we'd do a small model and teaching people how to do that. I think in my mind I have sort of two things. One was you know, the whole of management space that I came out of and you know where I still am today coming out of, the security information of in management and you know a lot of management underneath. Semi-structure data, you know nasty data that doesn't fit into our relational data base. You know they are sort of-- and then lots and lots of that data as you put all the firewall data in there, we saw that back at dark side, where I spent a considerable amount of time. You know that becoming a problem that, like enterprise software that was kind of delivered, you know on a CD and then oh now go scale Oracle behind it, as in even data warehouses. That's kind of how I experience it. It just didn't really work very well, and we were kind of doing big data or trying to do big data. There were like various levels of success, right. We've already knowing about the term and then, you know, obviously, picked up on a new Windows type, so things and then, you know, but if you want to do big data or something like Hadoop, then you're suddenly running into having to run, you know, I don't know, a hundred instances. I'm already saying instances. A hundred boxes, 80 you know back then, or like maybe 500 boxes, and now you're running into all of the management, you know, challenges that distributed infrastructure brings. And in my mind, you know since you're like asking for an inflection point, I think Amazon EMR, you know, and my friends at Cloudera, they're not going to like me saying that because that's a long story but I think having something like Hadoop, put on an infrastructure as a service platform like Amazon and I think they did that fairly early on, right. I think it's still a great product. >> Cloud-scale's a lot faster, it emphasizes, it more, you can do more with it. >> Exactly. >> IoT comes around now you're connected, devices are coming in, natural place to just put that data lake as they now called it, and work with it. >> Exactly, exactly. So I think that's one inflection point and then the second one I think clearly was sort of the advancements especially around deep learning and so forth, right, where, you know, I think a lot of that, you know the deep mind stuff and so forth, where now along with the sort of exponential growth of data where there's also now much more sophisticated analysis that people want to run. I think that's another inflection point. >> Yeah, so 2010 you saw cloud and data coming together and obviously you guys saw the need to secure that. What are the challenges of securing these massively distributed systems? >> Oh, there's a number of challenges, but, you know, it starts with sort of this basic law that says that, you know, that, you know processing data creates more data. Right, and if you look what business systems do, they're basically, you know, just like really fancy pocket calculators at life scale, right, but it's all about processing data. That's what computing means, right. And then as you do that it actually turns out that you create more data, which is all the logs, all the telemetry, the metrics tracing all of this type of stuff. And so these data sets become their own kind of, you know, big data nightmares potentially, right, but at the same time, they're full of, you know, really useful information to maintain availability performance, you know, to secure your systems and so forth. And I think the main challenge that we are seeing today with systems like ours and what's out there in the market is, you know, actually being able to scale. And it becomes almost an aggressive thing, it's kind of funny. >> You know, I got to ask you about the digital transformation equation that's out there. People, process, technology. I think people generally would agree that, hey, cloud's great, love deep learning, I mean how could you not, you know, get intoxicated on large-scale resources that's almost free and AI around the corner. It's good stuff, I mean pretty cool, right? And then the reality sits in, like you can't just hand wave it in, You got to hire people, you got to have the tech to do it, and then the process. And you made a profound comment before we came on camera, process is a reflection of culture. This is a really a big deal in the digital transformation. So, there are people out there, people are getting trained, there's a course you can take, you can buy technology that's getting better every day. Process seems to be where everyone's getting caught up on it and there's new ways to break through it and it's just a reality. What's your thoughts on process as a reflection of culture and how people can handle that and what people should think about? >> That's a good question. So I think what I'm seeing is that when we, we see a lot of companies at various stages of their sort of journey into the cloud. We come from the Bay Area so we have a lot of born in the cloud guys like ourselves and there's sort of a new culture that's kind of baked in from the beginning, but that's interesting. The even more interesting bits, in my mind, are when we are looking at companies that have been around for a long time. They basically, they're starting to realize that cloud transformation is almost more about basically picking up a culture of agile DevOps and then DevSecOps or whatever you want to call it. Apparently somebody at the keynote today made a nasty comment about it. Personally I didn't see it but again the whole Shift Left paradigm, but it's essentially a culture where you actually remove the silos that have been in place between departments, keeping people from working closely together, throwing stuff over the wall we all know how well that works, trying to keep your fiefdoms. And I find that all the successful cloud transformations stories that we've seen are really a decor, you know, cultural transformation stories, along the sort of plus minus DevOps route. >> So you're talking about the big challenge being scale, so two things you just said, well one is bringing together the mindset of infrastructure's code, we were talking about security as code. The other is automation, right. >> Absolutely. >> So that seems to be big focus of security practitioners. >> Yep. >> My question is, what's a good day look like to a security practitioner? >> Oh, I think, that's another really good question. I think there's an obvious answer, but I think the obvious answer would be I'm still in business, right, and I haven't leaked millions of Social Security numbers. >> Nothing happened, good day! >> And so I think that is definitely a good day but I think the sort of slightly more, I think, interesting answer is that I think a good day is day where you as a security practitioner have a bunch of good interactions with the rest of the folks in the company that are part of building products, on the operational side, on the development side, giving good feedback maybe to a bunch of developers maybe on secure coding practices, plugging in additional Veolia monitoring or code monitoring or scanning tools into the bill pipeline and so forth. And then also actually getting a bunch of alerts from all your monitoring systems and being able to very quickly figure out whether those are true positives or false positives and when they are true positives, being able to quickly react on them. >> So you guys, obviously cloud focused, that's a huge area for you, but I'm interested in how you say you differentiate. It's an extremely competitive market. What's your big differentiator? When you win, why do you win? >> So, it goes back to somewhat of a fundamental kind of things that led us to start the company. It's a little philosophy heavy, I guess, but it actually plays its way out in every single customer conversation, and every displacement and every time we end up expanding in the customer. And it's fundamentally that our philosophy is that this needs to be delivered as a service. That, you know, our philosophy is that enterprise software is just not a thing anymore. And our philosophy has always been that. >> It's very true. >> It's a good philosophy. >> It some days feels like, man, Christian, you've been saying the same thing for the last 10 years and here we are. Our philosophy is that you need monitoring, you need troubleshooting tools, you need security tools. Those tools themselves should not become behemoths in their selves where you're going to sink endless amount of resources and money into scaling and building them out and then who's going to monitor those? It's kind of you have a huge installation of vendor X and then how does that get monitored because if you don't monitor it then that thing will blow up and then you're blind again. So we just felt that this idea, what was really appealing to us from our experience was the idea that build the code but also run the code with ultimately get the customer back to actually using the tool rather than worrying about how the tool works underneath and having to worry about how to make it works. And we're all nerds and I love it and I wish I could understand all the stuff that happens in AWS underneath and every once in a while I meet some of these guys and it's very cool but that's where they deliver differentiation. And for us we can basically focus on delivering value to the customer. >> I think the cloud model, I think, shows everyone that you can deliver stuff as service, you have horizontal integration points that you need to keep aware of, certainly the data, you need horizontally scalability and freedom of access to the data and that brings up the goodness. I think that's a great philosophy, we subscribe certainly with you on that. You had mentioned earlier about alerts and one of the conversations that we're hearing around workforce and people is how many extra people are being deployed properly cause if everything's a service, then you can, if automation kicks in, and things are at service, you can eliminate things. So, one of the trends that we're hearing is the move from threat detection to alerts. >> Okay. >> Threat detections you can automate that and you can share data so the shared stuff kicks in. So that's a new kind of trend we're seeing alerts, quality alerts, having your people work on those kinds of problems, what to pay attention to on the monitoring side, becomes super important. Two years ago you couldn't walk down the street without threat detection, threat detection, threat detection. Although important, these mechanisms for that now. So what's your thoughts on the ongoing evolution from threat detection to alerts? >> I think it's about dehumaning the end. And all the machines are just sitting there, creating signals and we can have the discussion about AI and you know generally AI and all these sorts of things, I don't really believe that that's going to happen anytime soon. But I do like algorithmic approaches, I like the power of data analytics. Sometimes it's simple analytics that give good signals, sometimes it's complicated and very sort of sophisticated analytics, but in the end, none of these things can really capture any sort of objective truth and so it ends up in somebody's queue and then they got to burn through it. And that is fundamentally, again, a human problem in the best sense because I think that's we as humans, we have processing capabilities that have not been matched. >> And also humans want to hoard the data too. They're, "Aw I want to protect." And if you share the data, more transparency, better algorithms, better visibility, better alerts. >> Exactly. I do think, to a point, I think in the security space now, of course there's still a lot of hype around just add AiN you're going to be better but the reality is that this can only go so far. And it ends up in somebody's queue and analyst workflow, how do you treat ash incidents and so forth. How much time do you spend trying to figure out whether it's a true positive or a false positive, that all matters because no detection system will be perfect at only alerting you on true positives. >> I heard a comment the other night in the bar area, someone was commenting around security analytics and they said, "Yeah, if you don't really know what you're looking for, and you rely too heavily on these metrics, you end up with Chernobyl." Which, the Netflix series that's out about how they just following data >> AC-5 >> So they're you can just, if you're looking at the data too hard, not zooming out and taking a humanistic approach, why are you measuring something, why are you monitoring something, what is a quality signal? >> Look, I think it's fundamentally, this is all just tools. I'm a strong believer in, I don't know whether, I'm sort of a strong believer in the humans run the show. And I think that's what makes us human, right, I think outsourcing everything to an algorithm, especially when algorithms are making decisions about humans, that's like a wider topic, it gets very tricky and it usually backfires pretty quickly. >> So the security marketing narrative for decades has been fear. You're in trouble, you're in trouble, you got to be sure. Amazon put forth today in the keynote that the state of cloud security, the state of the union, is actually quite good and the focus should be on how to implement new tooling and we're actually really doing a great job. Do you buy that? >> To some degree. I do think that they're paying a lot of attention. I do like stuff that they've done from the beginning like security groups being deny all and all of those things. And they have a bunch of really smart guys over there that really care and worry about this type of stuff. I think they've also learned over the years in their own move towards selling from this side that's selling to a bunch of hipsters and then it started becoming a real enterprise play that all of these things are important, including having really good outage fail data and cloud trail and these types of things. The part that I like and we've argued this from the very beginning with our prospects when they basically kept saying you're putting the data in the cloud and how can I trust that? And we walk them through carefully in how we had designed our own security processes and a lot of what that was about automation and basically leveraging the APIs that we had. So basically at its core AWS has turned the data center into an API. And an API is something that I can automate and I can do a good job or I can do a bad job at that, that depends on the individual and so forth, but it's fundamentally a very powerful abstraction that allows one guy to do the work of potentially hundreds of people running around checking network connections. For me as a customer, that I can build a secure system on top of AWS. >> So they've turned the data center into an API, which is a very powerful metaphor, but they've turned it into a lot of APIs. How does that affect the complexity and the impact on security? >> Yeah, I know they are, look the reality is complex and I feel like their approach has been very carefully build from the bottom up, Lego by Lego, and then put other Legos on top of that. And I can very much appreciate that approach. I don't believe in one button security. I think it's just basically, everybody in the space knows that that's not a reality. >> Well we've asked Andy Jassy about this, John, and he said we want the fine grained access to primitives because when the market moves, we can move with it. If we don't have that, we put in all these abstraction layers that has implications on performance and, down the line, our agility. >> Power to the people, man, I think ultimately so many guys at Amazon, they're all very reasonable but you know they shouldn't make all the decisions. And everybody's use case is fundamentally a little bit different. And at the same time they're adding additional things because they realize that there's a lot of complexity even just looking at IM in these types of things is like, wow, okay, there's a lot of footguns built into this. The reality is that the entire industry is a giant footgun, on some level, so I like the fact that they ended up doing stuff like cloud trail and then pull all the cloud trail and repeat C logs that say flow logs into something like guard duty, for example, which they then try to do some correlation on there and they're trying to automate some of the detection as far as they can see it, as well. So I overall think they have a good approach to that. I think it's bottoms up. I think that works. I'm a builder type so for me that works. >> So Christian, final question, what're you looking at, CTO in the industry right now, what are some of the things you're looking at in the industry that's getting you excited and you guys are integrating into the vision? >> Well, it's really two things. I think one of the things we are seeing is as far as just general how people deploy software. We had containers and then nobody knew what to do with containers and it was orchestration and we now have Kubernetes basically having won all of the orchestration awards and I think that's going to be an industry standard that everybody has to deal with for the next couple of years. A lot of enterprise folks, is what I'm seeing, are now starting to kind of land on Kubernetes as part of sort of their cloud transformation, even if it's just pooling all the monoliths and then refactoring them afterwards. So I think that there's a lot of stuff going on there that Kubernetes adds its own layer of complexity. And there's opportunity for us there as a monitoring vendor. I'm extremely, I am probably more excited, almost irrationally excited about all the serverless stuff. I think I am a big proponent of not having to do undifferentiated heavy lifting. It feels to me that the sort of serverless track will get people to build better applications even faster in time to market everything that counts. And then on the security side I think that's an evergreen thing. You call it fear and then of course I've always said it's basically insurance. On some level, that's why the security market continues to be essentially evergreen and our customers are using us for their own security monitoring. We are building a lot of additional functionality there and I think that's going to continue to be a big and ongoing discussion because the underlying primitives, now you have Kubernetes, how do you secure that, how do you even build security in the serverless phase and whatever comes next after that. >> And I think also that point, I think you're seeing new brands are emerging as suppliers because they have that architectural, horizontal, the view. They're thinking holistically around the tech stacks and thinking about the role of data and just IoT is just a mind-blowing conversation around, where are you going to pour, where are you going to store that data? >> Yeah. >> Okay, so again, all this is kind of moving into a whole 'nother generational shift and you're either on the wrong side of the street or the right side of the street. This is like really binary at this point. >> And it's accelerating, right? Folks probably had one or two transformations in the last 30 years and now they're running through a transformation every three years, it's like getting whiplash, right? >> Buckle up. Christian, thanks for coming on theCUBE. Great insights. >> Thanks again for having me. >> Great insights here on theCUBE. Bringing you all the action Boston for AWS re:Inforce, Amazon Web Service's inaugural event around security's key developers, the new security pros and engineers out there. CUBE coverage continues after this short break. (upbeat music)

>> live from London, England. It's the queue covering a ws summat. London twenty nineteen Brought to you by Amazon Web services. >> Thiss really is huge, >> isn't it? David >> London is my co star today on the Cube. We're going to be extracting the signal from the noise and there is a lot of noise. Just trying to register. Here was an event in itself, and one guy in the queue with me earlier said, You know, this is like an army of young technologist backing one particular platform, and we've had the main keynote speeches already in the conference hall. There are breakout sessions going on as well as we speak. And in those keynote speeches, it really wants the focus again on Hey I and machine learning and a huge array of services that eight of us now provide. Because, of course, every tech company, every company is a tech company these days. Where do you work in transportation or defense or retail? Let's talk >> about Dave a little bit about a ws and the exponential growth that it's seen over the past two years because it just keeps on getting bigger and you could see testament really out there just so many people here. >> You know, Susannah, when a WS announced its first service in two thousand six, very quietly announced E C, too, which is a computer service. Nobody really paid much attention. But a devious has permanently changed the landscape of the of the technology business. And we're here in London twelve thousand people at a one day summit. I mean, that's his large as many or or larger than most U. S based three day conferences. >> And there are many thousands more watching the life streaming as well, >> right? And when you talk to the people here, they're a division. First of them has builders, and it was interesting to hear some of the key knows this morning talking about some of the innovations that occurred in the UK he obviously UK, very prideful country. The first lights in electric lights work the Savoy Theatre, the Colossus, you know, Code breaker and many, many others. Home computing originated in the UK It so a diverse are connecting that invention and that what they call reinvention. Eight of us talks about his differentiation. The number of regions that it has around the world believe they said twenty one regions, sixty for availability zones, which are little, many regions inside of the regions. In case there's a problem, you can fail over fourteen database services. You know what's happening is all the traditional tea, which is eighty percent of the market place, trying to sort of hang on to their legacy install basis. So they're trying to substantially mimic eight of us. The problem is, eight of us moves faster, has more services, and it's just growing at such a phenomenal rate. >> And it's really kind of bottom up. A CZ. Well, it's so got that head start. So it's learning from its current customers and those it's had in the past, really to find out what new services they want that has his wealth of data ofthe gods to build on it, doesn't it? So every it seems every month it's it's another step ahead. >> Well, the data is critical. Amazon. Is it a dogfight? I always say, for your data with Google and Microsoft and Oracle, they all want your data. Why? Because data is the most valuable resource today, right? People talk about data is the new oil. We think data is more valuable than oil. You could put oil in your car. You can put in your house, but you can't put it in. Both data is reusable in a way that we've never seen a natural resource before. So it's extremely powerful applying machine intelligence to data. So Amazon knows if it can get your data into the cloud and do so cost effectively and deliver services that make you happy and delight you that they have a perpetual business model that's really unbeatable. The company now is at a thirty billion dollars run rate, growing at a constant currency rate of forty two percent per year. No people will say, Well, well, Microsoft is going faster. Microsoft is growing at seventy two percent here, but it's a much, much smaller base we're talking about single digit, a few billion versus thirty billion. So Amazon each year is growing at a nine to ten billion dollars incremental rate. Even more importantly, the operating income is phenomenal. I mean, a WS is only twelve percent of Amazon's revenue, but it accounts for fifty percent of its operating income. Hey, Ws is operating income is is in the high twenties, twenty eight twenty nine percent higher than Cisco, higher than AMC when it when he had seen was a public company. And those air very profitable companies the only companies that are more profitable on a percentage basis that that Amazon a pure place, software companies like an oracle. So Amazon, who's an infrastructure company, is as profitable almost as a software company. It's astounding, >> really interesting to see some of the partners that were invited on. It's about the keynote speeches. For example, Saint spreads so real traditional retailer at a prompter state that they'd be in the business for one hundred fifty years and some would say in many ways a competitive toe. Amazon at marketplace because they sell a vast array of goods and services to the customers. But they talked about how they're using around eighty eight WS services. It's always like a kind of a pic, a mix sweet shop. Or, as you would say, a candy store isn't and I think that's that's some of the benefits that some customers view for A W. S. Some would say, actually, I would prefer all of my product be in one place or the car that access and services in one place. And so is this pick a mix idea that I think really is taking off, isn't it? >> I'm glad you brought up the state's very example because, essentially, in a way, they are in adjacent competitors Teo, eight, of us. And yet they've chosen to put their data. And there's in leverage Amazon services. It's like Netflix. Everybody uses Netflix as the example. I mean, they compete vigorously with with Amazon Prime Video, and yet they choose to run in the age of U. S code. Now this is one of the areas where you heard at the Google Cloud next show a lot of talk about retail companies, you know, considering using Google, because, of course, they're concerned about Amazon eating their lunch. And so it's a hard decision for retail companies to make. Sainsbury obviously has said OK, we can compete. We have a unique advantage with Amazon retail, you know, but it's something worth watching for sure, because, you know, Walmart obviously doesn't wantto run in the eight of us Cloud because it's it's fearful. Ah, at the same time, Amazon would tell you, Auntie Jessie offenses look. There's a brick wall between eight of us and the retail side. We don't share data, so it's just a matter of that. Trade off is the risk of running in a ws er and potentially running at a competitors sight worth the extra value that you get out of the services. And that's what the market has to decide, >> yet certainly does interesting as well. We had the Department of Justice on the UK Department of Justice because they're has beans real concerned about security, about putting all your eggs in one basket effectively put a your data into a club no operated by you. And it does, though seem is, though little by little, some of those security fears are being laid up. Play >> well, there was this. The seminal moment in a WS. His history was in two thousand thirteen, when it won the CIA CIA contract who was more security conscious than the CIA. And they beat Big Blue IBM for that contract way back in two thousand thirteen, and the analysis that came out of that because IBM contested that contract. What came out of that was information that suggested that eight of us said the far superior solution forced IBM to go spend two billion dollars on a company called Software to actually get into the public Cloud does. It couldn't really compete with its own sets of services, and since that, Amazon has only accelerated its lead. IBM, of course, has a public cloud, and it's competitive in its own right. But the point is that the CIA determined that security the cloud was better than it could do on Prem. Now you're seeing the big battle for the Jet I contract Joint Enterprise Defensive Initiative. It's the biggest story in DC Amazon is the front runner. It's down the Amazon and Microsoft. Not surprisingly, Oracle has contested that because the government uses these sources from multiple suppliers and there's contesting it, saying, Hey, that's not fair to use one cloud. When a vendor contests Abid, a lot of information comes out. The General Accountability Office and the D. O. D determined that a single cloud was more secure, more reliable, more cost effective and less complex to run. So this is big debate around multi cloud versus single cloud. And again, Amazon continues to lead in the marketplace and in many many instances, is winning >> on DH. There were a few comments made in certainly one of the key notes today, trying to kind of blow the competition out of the water again knows whether a few specific references, in fact, to Oracle and Microsoft >> were right. And so they called the database freedom they had hashtag database freedom again. As they say, Microsoft, IBM, Oracle, Amazon, they're in a fight for your data. That's why Oracle has launched fourteen database services. Now it's not trivial. So Sainsbury and the Ministry of Justice both talked about moving Oracle databases into the eight of us Cloud. It's not trivial. It's much easier for data warehouse and stateless applications for online transaction processing. Things like banking much, much more difficult to migrate into the clouds. So it's interesting. Sainsbury talked about racquets stands for a really application close. There's a very high end, complicated Oracle database that they migrated to Aurora. The Ministry of Justice talked about moving Oracle in tow. RGS, this is a battle I tweeted today earlier, Susana, you pick up the Wall Street Journal is a quarter page ad on the front page. Cut your Amazon bill in half now, of course, what? Oracle doesn't tell you is that they date to X the price when you're running on or on Amazon versus Oracle. So they're playing pricing games. Having said that organism very good database, the best database in the industry, the most reliable. So for mission critical applications, Oracle continues to be the leader. However, Oracle, strong arms people, they'LL, they'LL raise prices, they'LL get you in a headlock and do audits. And that's what Amazon was referring today about Microsoft and Oracle will do out. It's so they position. They tried a D position Oracle as an evil company. The Oracle, of course, so way add value. We have the best database, and they're trying to add value for the customers. Build their own cloud. So it's quite a battle that's going on, and you see the instance. Creation of that battle manifest itself in the general contract. >> Absolutely interesting is well, what we heard from really both states bruise on the Ministry of Justice, really talking about the end users and how they're so different. So for public sector organizations, this isn't about making more money making profit. It's about the experience for the user. But in fact, that came up from Sainsbury's as well, making sure that the right products are with the right part of the store. And that's how a I could help them do that and efficient, usable data they currently have. >> I think every enterprise really wants to have a consumer app like experience, and very few do. I mean, we all know used these enterprise APS from large, you know, brands, and they're often times not that great. So what, you're seeing a closing of the Gap? People see what's happening with Facebook and Instagram and Whatsapp and so forth and say we should be able to have apse that run that simply and so you're seeing that gap clothes. I don't see how you could do that without some kind of public cloud infrastructure because of the massive scale that's required. It's so companies like Saintsbury are moving in that direction. Mobile has been critical for the last decade, and so that's what the consumer wants. That's what the cloud can provide. >> Is that what every consumer wants? Because increasingly, we're hearing a lot more concerned about privacy, that people not wanting to give all of her data across to private companies and do you think this could be dist sticking point ready going forward and could actually hold back the growth all they ws and its competitors >> a great point because you have a problem. Wonder problems. You have this app creep. I can tell you have dozens and dozens and dozens of app on my phone. I don't know if I trust them with the data. So having said that, one way to simplify that is to eliminate the need to do heavy lifting and patching of your infrastructure. Let us take care of that and build value up the stack by focusing re shifting your resource is on on value added services. Could it be a problem? I think no question. When Snowden came out in the U. S. People in Europe for sure. As you know, we're concerned about putting their data in the cloud that seems to have attenuated. I don't hear much about that anymore, you know. But if the NSA can come in and demand access to my data, well, that could be problematic. That's why I ws is putting so much or one reason why they're putting so much emphasis on setting up regions. It not just eight of us, Amazon and Google and Microsoft as well for many reasons. Privacy. GPR compliance on of course, Leighton. See the laws of physics? >> Absolutely. Okay, Dave Melody, thank you very much for being with me here at the age of us. That summit here >> in London at the XL Center there is still so much going on here. Lots of breakout sessions, many more kind of individual keynotes taking place with the various different subsections. Although the A W s business and also its partners. So we will be keeping across all of those on the Cube. Thanks for watching.

>> Live from Barcelona, Spain, it's theCUBE, covering Cisco Live Europe, brought to you by Cisco and its ecosystem partners. >> Welcome back to theCUBE's live coverage here in Barcelona, Spain, for Cisco Live Europe 2019. I'm John Furrier, your host of theCUBE, with Dave Vellante as well, Stu Miniman, who's been doing interviews with us all week, our next guest is Roland Acra, Senior Vice President, General Manager of the Data Center Group. He's in charge of that core business of data center now, at the center of cloud and the edge. Roland, great to see you, thanks for coming on. >> Thank you, thank you for having me. >> So a lot of announcements, a lot of the big guns are out there for Cisco, you got the data center, you got the networking group, and you got IoT, and then cloud center suite was part of the big announcement, your team had a big piece of the keynote yesterday and continues to make waves. Give us a quick update on the news, the key points, what was the announcements? >> Yeah, the two big announcements for my group were ACI Anywhere and HyperFlex Anywhere, and we captured them under a common moniker of There's Nothing Centered About the Data Center Anymore, because both of these speak to things going outside the data center. ACI Anywhere is the integration of ACI, our software-defined networking solution, into two of the most prominent public cloud providers out there, Amazon and Azure, and for HyperFlex Anywhere, the exciting news is the expansion of HyperFlex, which is our hyper-converged solution, also outside the data center, to the edge of the enterprise, specifically branch offices and remote locations. >> And the other thing that came out of our conversation here on theCUBE and also on the keynote, is that the center of the value is the data center, as you guys pointed out with the slides, big circle in the middle, ACI Anywhere, HyperFlex Anywhere, but the network and the data and the security foundation has been a critical part of this new growth. >> Yes. >> Take a minute to explain the journey of ACI, how it started, where are we? It's been a progression for you guys, certainly inside the enterprise, but now it's extended. What's the journey, take us through that. >> When ACI came into the market five years ago now, we have a five year anniversary, ACI brought a software-defined networking solution into the market. It brought an automated network fabric capability, which said you can no longer screw yourself up by having incoherence between one part of the network and another, it's all managed coherently as one thing, and it brought, to your point about security, what's called segmentation of applications. Today, applications have data, they have databases, they have different sensitive pieces, and it's important to be able to tell the network not only get the traffic from one place to the other, but also selectively get the traffic that I tell you to get there, and not the one, and don't get the traffic that has no business getting there, and that's known as segmentation, which is a security concern, particularly when you have sensitive data like consumer data or things that have regulatory things around them. ACI has brought that to the market. That was the value proposition of ACI. We worked on then expanding ACI in the direction of scale. Customers have two or more data centers for disaster recovery, for resiliency, we made that possible. We got to bigger and bigger footprints. Then we took ACI to the edge of the enterprise. What if somebody wanted to put some computing capability in a store, or in a logistics center. ACI then was expanded with that. Step N minus one, was we took ACI to bare metal clouds. Customers now want to deploy also things in co-locations or bare metal clouds. We decoupled ACI software from the Cisco switches, which is the ACI hardware, and ACI became completely virtualized, and still able to be doing everything it does in hardware on premise, in software instead, in somebody's else's capability. And yesterday we announced the full combination of this, which is what if you don't want the ACI soft switching or hard switching, can you use the native switching of a public cloud, like Azure or AWS, and you tell the other APIs, please let those packets go from A to B because they're part of the whitelisted paths,, and don't let packets from C to D go because they're part of the blacklisted paths. And that was the full integration with these clouds-- >> Can you abstract that complexity? >> Completely, completely. One orchestrator, which is the multi-site orchestrator, the same one people have used on premise, that they've developed their policies around, so that we have invested a lot of sweat equity in that controller, it's where also they put their compliance, verification, and audit and assurance, and they use that thing even when something goes to Azure or it goes to AWS. >> So you mentioned the progression. So it's now your full progression, from core to the cloud, including edge-- >> Going through edge. >> What has been some of the results? You mentioned that segmentation's one of 'em, I get that. How has ACI been used, what are some highlights that show the value, because people start looking at ACI, saying, hmm, I like this, I like scale, I have a scale challenge with the new cloud world and edge, and complexity's abstracted away with software, okay, check, so far, so good. Where has been the success of ACI and how do you see that unfolding specifically in the cloud? >> Yeah, the biggest value our customers have gotten, cloud or no cloud, has been with ACI, they've been able to shorten the speed of change, shorten the time for change, therefore increase the speed of change of their network, because now the network needs to operate at the speed of the applications. Applications reconfigure themselves sometimes on hourly or daily basis, and it used to be that changing something in the network, you sent a ticket to somebody who took weeks to reconfigure things. Now that software-defined capability means the network reconfigures and people can change generations of compute on the fly, and the network is in lockstep with that. The agility and speed has been great. The other value has been the value of automation, which is people can run a bigger and bigger and bigger network with a small number of people. You don't have to scale your people the more switches you have. Again, because programming and automation comes to the rescue with that. >> Well I'll tell you, people who are watching right now can look behind Roland and see that it's a packed house. We're in the dev net zone, which has been the massively growing organization within Cisco. Community's been growing very fast, people are developing on top of the networks, and these are network folks, and as well there's new talent coming in. So skill gap is shortening, so you're getting a different makeup for a Cisco user, your customers are changing and changing, growing, existing base plus new people. Talk about that dynamic about how that impacts this intent-based networking, this notion of policy software is defined. >> Yes, you it's you know what many people have been calling infrastructure as code, which is you go from scripting to actually coding and composing very sophisticated automation capabilities and change management capabilities, for an automatable system, which is what ACI is. It's made for people drawing on the strengths that they were doing in the application domain or in the server domain, and bringing that into the network. And that's a new and exciting thing, it brought the network within the purview of coders, people who know how to do Python and know how to do Go language and things which are modern and exciting for the younger generation. It's made also for bringing the analytical capabilities, you know, a lot of what those young coders are used to is a lot of logs, a lot of visibility, a lot of analytics running on, because they've done that on web servers, they've done that on applications that run in the cloud, and we now offer the network, which is very rich in data. If you think about, we see every packet, we see every flow, we see every pattern of how the traffic is changing, and that becomes a data set that is subject to programming because then from there you can extract anomaly detection, you can extract security signatures of malware, you can extract prediction of where the traffic is going to be going in six months. There's a lot of exciting potential from the telemetry and the visibility that we bring into that framework. >> And as you point out, devs love that. I mean Cisco, we've talked about this, is one of the few large established companies that has, in our view, figured out developers, right? There's a lot of examples of those companies that haven't and continue to struggle, we've just witnessed here the dev crowd. I want to ask you about ACI and how it's different from, for example, VMware NSX. What's the differentiation there? >> The biggest differentiation is ACI is one system through which you manage the entire network, the overlay which is the virtual view of the network that the applications care about, as well as the underlay, which is the actual real delivery system that makes the packets get from A to B with quality of service and so forth. So that's first thing. It actually does a lot more, it has much more scope than NSX does. The other thing that's very unique about ACI is we have integrated it with every hypervisor on the planet and every container management framework on the planet, and ever bare metal system on the planet, which means that any workload, something sitting on a mainframe, something sitting on a Sun Oracle server, something on OpenStack on OpenShift, on VMware or on Hyper-V, and now on the EC2 APIs of AWS or on Azure, all of those are integrated with ACI. We're not wedded to one hypervisor, and our cloud implementation that we announced yesterday is a true integrated cloud capability, it's not a bring your own license and go put it on bare metal at AWS, which has been VMware's cloud strategy is to team up with AWS and let customers bring their software licenses into AWS bare metal. That's not EC2. And of course that's not Azure and that's not the other clouds we're going to be doing. So the openness to being multi-cloud on premise, which means every hypervisor and every container framework, and bare metal, with one system. We're extending that into the cloud to give customers choice and openness, that's really a very fundamental philosophy in networks. >> So much wider scope. That's kind of always been Cisco's philosophy in partnership. When you think about HyperFlex going back 10 years when you guys sort of created that with partners and then multiple partners now, maybe talk about that journey a little bit. >> HyperFlex? >> Yes. >> Yeah, 'cause hyperconvergence is another very exciting and fast growing trend in our industry. And really, HyperFlex started off with the hyperconverged infrastructure, started of being the notion of putting a mini-cloud in a box on-premise for application developers to rapidly deploy their applications, as if it was in the cloud. So speed and simplicity were really at a premium, and that's really what defines hyperconvergence. And we've done a tremendous amount of work at Cisco to make speed and simplicity there, because we've integrated network compute storage and a cloud management system called Intersight to give that whole capability to customers. We then hardened it. We took it from being able to do VDI kind of workloads and rather benign workloads, to mission-critical workloads. So databases are now running on HyperFlex. ERP systems are running on HyperFlex, the real crown jewels of the enterprise are now running on HyperFlex. Then we made it multi-cloud. We opened it to all hypervisors and to all container frameworks. We announced OpenShift yesterday, we have already done Hyper-V, we had done OpenStack and DSX, so again, same spirit of openness. And yesterday's announcement was, what if I want to take hyperconvergence outside of the data center in hundreds or thousands of remote locations? Think a retailer. In a retail environment, some of the most interesting data is born outside the data center, it's born in a store. The data is center that follows the customer who's interested in a plasma TV, and that data has a perishable lifetime. You act on it on location and on time or you lose the value. So sending it over, taking two hours to do a machine learning job on it and come back, the customer's already back home watching a movie. And so the window of opportunity for the data is often right there and then, and that's why our customers are taking their computing environment off into where the data is, to act on it fast and on location. >> It sounds easy but I want to just get your thoughts on this, because this is a critical data challenge. If data's stored in classic old ways, data warehouses and fenced off area, it's kind of in the internet, you're not going to have the latency to get that data in real time. Talking about real time data that's addressable for part of the application value. So this is a new notion that's emerged with dev ops and infrastructure as code. >> That's right. >> That's hard. How do you guys see that progressing, how should customers prepare to have that data centered properly for app addressability, discovery, whatever the uses of the data contextually is, time series data or whatever data it is, this is a critical thing. >> It's a critical thing, and there's no one answer, because depending on what the data is, sometimes you only see the value when you concentrate it and consolidate it, because the patterns emerge from rolling out a thousand stores worth of data and seeing that people who buy this toothbrush tend to buy that toothpaste. There may be that value where you want to concentrate the data, but there are also many things where acting on the data in the moment and on location quickly without referring to the other thousand stores extracts 90% of the value of that data. So that's why you want to do forward deploy computing on that data. >> So this highlights network programmability, this means the applications driving the queries or the network for that data, if it's available... So there's two things, network programmability from the app, and availability of the data. >> Yeah, and the ability for the entire infrastructure, network, compute, and storage, and hyperconvergence is the automation of all three to be able to deliver its value equally in remote locations or in a cloud, as it would have in a data center, because that's where, the application's going to want to go where the value is, and if the infrastructure can't follow it there, then you get a degraded ability to take advantage of the opportunity. >> Right, real time decisions happen at the edge, but then as you describe, you got to bring data back, certain data, back to the cloud, do the modeling there and then push the models back down. So you're going to have-- >> And you're going to have decision making distributed. >> And you've got to have low latency to be able to enable that. >> Yeah, and the same goes for other considerations. For example, why is it important to do, allow people to put data both on their premises and in the cloud? For disaster recovery, for data replication, for resiliency. Sometimes for governance reasons. GTPR in Europe says the data of European citizens that's personally identifying has to stay in Europe. Somebody may not have a data center in Europe. Could they take advantage of a co-location ability or somebody else's cloud? >> This is the theme we're seeing at this show this year, and certainly at the center of the news is, complexity is increasing 'cause it's just evolution, more devices are connected, diverse environments, scale for cloud and connectivity, but software driving that. So I got to ask you the question. Go back to the old days, you know, the 1990s, multi-vendor was a big word. Now multi-cloud feels the same way. This is the openness thing. How would you describe multi-cloud strategy for Cisco in context of this notion of being open? >> It is really the new dimension of openness, right? We've been open in the past to multiple forms of physical networks. Customers to use wireless or fiber or copper or what have you, we need to give them an IP network that operate equally well over all media. That was one dimension of openness. Another dimension of openness was, does a product from vendor A work with a product from vendor B? My router, your router, my switch, your firewall, those are other dimensions. Hardware and software coupling. Can I buy the hardware from Peter and the software from Mary, will it work well? The new dimension of openness is, can a customer avail themselves of any form of cloud, either because they like the tooling and how well their developers are more efficient on a given cloud, or because the pricing of the other guy, or the third guy has a point of presence in Tokyo, which this one doesn't. All of those are business choices that if we make our technology, let them take advantage of them with no technical restriction, they will, because now they can shop on the merit of what they want to do, and not on, oh well, sorry, if you want to go to Azure, I can't help you, but if you're willing to settle for your own premise or for Amazon, then I have a story for you. So that's-- >> Roland, you're leading the team on the core crown jewels for Cisco, as you guys, the rising tide's floating all boats here within the company. What's your plan for the year, what's your goals, you'll be out there pounding the pavement with customers, what's your objective, what do you hope to accomplish this year in 2019? >> Well 2019 is the year of many things for us, it's a very exciting year. It's the year of, on the physical infrastructure side, we're taking our switches to 400 gigabit per second. We have our new silicon capability, our new optics, so we're going to be able to scale for the cloud providers who are heading the next frontier of speed and density and scale. So performance will always, always be there, and when we're done with 400, we're already going to be asking about 800. So that's an exciting new generation of switches. ACI Anywhere getting deployed now and adopted across multiple clouds, is another exciting thing. HyperFlex Anywhere, we're really looking forward to the potential in financial services, in logistics, in retail, where's there's a lot of deployed data at the edge. And then, security is a never finished journey, right? Everything with give our customers in the way of security, because there, there's an active actor who's trying to make you fail, right? It's not that you're only fighting physics to get to 400 gigabit, then you win. There we have a guy who's trying to foil your schemes and trying to foil their schemes. Security is a great-- >> Constant attacks are on the network. You guys have seen this movie before, so you know how critical, Roland thanks so much for spending the time, congratulations on ACI Anywhere, HyperFlex Anywhere, intent-based networking at the core. It's theCUBE bringing you all the data, we have an intent here to bring you the best content from Cisco Live in Barcelona. I'm John, Dave Vellante, stay with us for live coverage, day two of three days of coverage here in the dev net zone, packed with developers learning new skills. We'll back with more after this short break.

>> Live from Barcelona, Spain. It's the cue covering Sisqo Live Europe, brought to you by Cisco and its ecosystem partners. Welcome back >> to Barcelona. Everybody would adapt. Wrapping up day one of Sisqo live Barcelona Cube coverage. I'm David. Long day. He's stupid men. You're watching the Cube. The leader in live tech coverage. Donnie Williams is it director at Scott Equipment out of Louisiana. And Eric hurts August back. He's the CMO of IBM storage. Gentlemen, good to see you. Welcome. >> Thank you for having us. >> You're very welcome. So tell us about Scott equipment. What do you guys do? Look, what's the company all about were >> a heavy equipment dealer, So we've been we've been in the business for eighty years, privately owned company. And so we're we're We started out and farm implement eighty years ago by the founder, Thomas Scott, which is where the name Scott equipment comes from. And so we transition over the years, Teo construction equipment, Andi were now back in two thousand fourteen, we sold all of our the farm stores that handled all of that equipment. And now we're We're strictly servicing the construction industry and petrochemical in >> history. So your dealer of exactly what equipment and your services as well? >> Yes. We service that we were primarily a rental company. First then then we We also sell what we rent. We service service it and and also parts as well. So we're talking massive? Yes, they got. If you if you think our one of our main lines is Volvo, which you have you have you seen the show? Gold rush that that Volvo equipment you see there, that's that's what we sell. So is incredible machine. Yeah, Yeah, they are. Hada chance tio to play with one. I went Teo Shippensburg, Pennsylvania. Where were their North America offices and had a chance to play with their largest excavator? That was That was >> fun. So is a lot of your Senate on sort of the maintenance business in the service business? >> Yes. So we were just mostly. Mirror is like a car dealership. If if you so we were like I said, we do sale service parts, all of that. >> So the business flow starts after the sale is made on >> exactly. Yes. We still like, Yeah, exactly. We get. We get equipment out there in the in the in the territory, and then the revenue continues tio to come in. >> So what are some of the challenges? The external challenges that are driving your business? You really >> are. The whole heavy equipment industry is It's kind of behind the times in my from a dealership perspective from from a manufacturer perspective there. They're somewhat up with technology, especially especially Volvo. But from a dealership there, there might mainly privately owned. So they're not there's not a whole lot of resource is in, and ah, in technology they don't. That's not a focus for them that they're they're focused on the business side of it. So what? We we're not When I first started the company ten, eleven years ago, now there was one guy servicing six hundred employees and and it was one eyed person, one i t person. So, as you can imagine, it was, it was a nightmare. Go. I mean, it's not the guy's fault. I don't blame him at all. Is this Is this the way that they had done business and not change bombed out, >> right? Exactly. Yeah. Guys >> find them. >> So their customer of ours for the versus stack, we have, ah, partner that they've been buying their IBM in their Cisco gear from. And then when they were doing a modernization effort, the reseller talk to Scott and said, Dani, what do you think? How about doing this? Converge infrastructure. Easier to play. It's after. So it all came through their existing channel. Part of that they were using for both IBM gear and Cisco Gear. >> So you wanted a solution. That one guy could run, right? We've now at least growing that company to house. We have six total in our in our department. So we've changed a lot since I started the eleven years ago. >> And why are they spending their time doing what? Premier >> Li? We do a lot of help desk on systems administration way do mostly, uh, are My focus is to make sure that our employees are satisfied that so they could take care of the customer, and that's that's the primary goal. And along with that comes comes systems administration. A cz. Well, so, But, >> you know, a full stack like this. I mean, the joke. You need more than one person, but it's going to be simplified. You know what you're buying, right? Predictable. And therefore, you shouldn't need to be seen on a basis. >> Yes, I like keeping things simple. Simple as possible. So that makes that makes my job easier. It makes my team's job easier. What >> kind of >> things you driving? Is it? You know, data protection, is it? You know what? What? What? What sort of, you know, use cases do you have on your stack >> on that Were from our were servicing on our with Francisco verse. Sorry versus stack. We are mostly it is all profit cloud were servicing applications. That's the supplement. Our court system. So we have reporting solutions. We were when we first bought it. The vs stack way were considering moving to another Air P system. Oh, and we would have that that infrastructure in place tio migrate to that. So we see what we still have that that actually on the table as a as an option >> for us, but the migration to a new Europe E system. Yes, we should talk afterwards. No, you >> were warning that it >> all about you. Of course, you don't want to convert if you don't have to write. But sometimes there's a business case. Sometimes it's hard to make you talk. Cloud in your in your future president were doing some that's ass stuff. >> Yeah, a little of that. I mean, anything. I mean things that that makes sense for us to to cloud I security services we're doing. Of course, probably most common is hosting email. Were doing a lot of that share point that that type of solution in the cloud >> How long you been with the company? Eleven years. Eleven years. Okay, So, thinking about the last decade, I mean, it's a lot of lot has changed. Yes. What's your What do you most proud of? What you like your biggest success that you can share with us. Oh, >> really? Building my the that dude the I T department and bringing our company into the twenty first system century from a from a technology perspective. I mean, like I said, we had one person that was that was handing. It was really impossible. I mean, you couldn't depend. Depends on one person. And and and, yeah, expect the company's or saw survive long term. Yeah, That one person had to say no a lot. Exactly. Right. Why would he? Just couldn't get everything >> done right? So that really that modernization? Yes, I know where you guys >> can. Ninety Mater, My team modernization play. The versus stack is heavily used for that. And, you know, as we said, on the earlier and every we had to see ESPN, we've also used it to do you know, to the next level from a night transformation to the future. Because in that case, as you know that was a CSP who uses it to service. You know, hundreds of customers all across the UK in a service model. And in this case, this is more of a mighty modernization. Take the old stuff, upgraded to what it was. They even have old IBM blade servers. That's how old the stuff wass old, actually, six played servers that must have been ten years old before they went to the Versus Stack. >> How many people in the company >> right now? We've actually sold off side since I've been with the company we sold off. Some of our non performing business units were probably roughly around five hundred fifty now. Okay, so I mean, we're Ah, we're actually more profitable now than we were eleven years ago from Ah, I mean, we have less employees, but our profitability is actually exceeded >> the name of simplification. Exactly. Right. So what's the biggest challenge you face Is the head of it today? The biggest, Probably >> the biggest challenge would be me wanting to implement technologies. They're not really not ready. I want it. I want tohave the competitive edge, that of the industry. I want to be able to be ahead of of the ahead of the curve. Uh, and that's probably the probably biggest challenge. And you're >> saying you can't Because the tech is ready or skills >> is just is just the industry just trying Teo. I work with vendors and getting getting them to be ready for I say, vendors, manufacturers, they're our vendors. Toe Get them Tio and other dealers as well. Teo Teo Albee. Acceptable to technology that's been there twenty years. >> What would you say is the but the top number one or the top things that IBM has done to make your life easier? And what's the one thing they could do that they're they're not doing that could make your life easier. What's the start with what they've done? You know whether successes, you know that >> really? Really. I mean, we've been a long time IBM customer. We have not, not just the versus Stack, but we also have the power system, which were actually runs are our core AARP. Um, okay. And so that we had long standing relationship with IBM, and the reliability is there. The trust is, >> there's well, a long term partnership. But what's the one thing they could do? One thing that you could If you could wave a wand and IBM will do x what would x B to make your life better? Uh, cut the price way. Go >> way. I should have prefaced that something that size >> on that topic. But you know, the power system thing brings up. You know, our friend Bob. Pity on who's running the cognitive systems group now You guys do with some stuff in a I talked about that a little bit. >> So what we've done is two things. First of all, we've been beauty inside of our system's ai ai all over the place. So, for example, we tear data which can weaken due not only to our own array, but literally two four hundred forty rays that have someone else's logo on them. It's all a eye dunce. When the data is hot, it's on the fastest here. So if you have fifteen thousand rpm drives in seventeen hundred rpm drives, it goes to fifteen thousand. When it cools off A. I automatically moves that the storage admin does nothing. You don't set policies, A takes care. We have flash and you have hard drive's same thing. It'll move around and you could have on IBM array talking to any AMC array. So all sorts of technology that we implement, that's a I in the box. Then, on top of that, what we've done is come up with a Siri's of a reference architectures for storage, as one of the critical elements in the platform. So we've done is create what we call a data pipeline. It involves not only our storage raise, but four pieces of our software spectrum scale, which is giant scale out file system, in fact, to fastest super computers in the world have almost half an exabyte of that software storage. With that software, our spectrum discover which we announced in queue for which is all about better management of metadata. So for a I workloads, big get anally work loves the data scientist doesn't prep the data. They can actually talk to what we do, and you could create all these meditate a template, then boom. They run a a ay workload on Thursday and then run a analytic workload on Friday. But all automated our archive and then our cloud objects towards. So all that is really think about it. Maura's an oval because when you're doing an A I system, you're constantly learning. So the thing you got to do is one you've got to have high performance and be ableto handle the analytics, which we do on flash. Okay, so the flashes connected, you've got to be able to move the date around. And part of thing with the spectrum Discover is that we can talk through an A P I to a piece of a AI software two piece of analytic software to piece of big data software, and they can literally go through that. AP I create templates for the metadata and then automatically suck what they need into their app and then munge it and then spirit back out and then obviously on the archives side, you want to be able to quickly recall the data, because if you think about a I system, it's like a human. So it's giving my Russian example. So I'm old enough. When I was a kid, there were bomb shelters in my neighborhood that people dug in the backyard. Then we have, you know, Nixon lightening up with the Chinese and we have Reagan and Gorbachev next, You know, the wall comes down right then. Next thing you know, there's no longer Soviet Union. All of a sudden, no, the Russians might get a little aggressive, even though they're no longer communist. And now, you see, depending on which political party. Either they're totally against us where they're totally helping us. But, you know, if they really were hacking systems whose whatever political party urine, they really were hacking our system, tried to manipulate the election pro or con. The point is, that's kind of like a cyber attack, and that's not a good thing. So we learn and it changes. So when a I system needs to understand and change constantly, learn. If all of a sudden you have flying cars, that's going to be different than a car with tires. Now, a lot of it, maybe the same, the interior, all the amenities. But the engine is going to be different. And there are companies, including the big Big three, four five who are actually working on flying cars, knows it will happen. But the A I system needs to understand and learn that and constantly learning. So the foundation has to be heavily resilient, heavily performance, heavily available, lasting one is an A I system going down on you, especially if you're in health care or big giant manufacturing. Like Volvo, his customer. When they're building those cranes and things, they must cost fifty sixty million dollars at that assembly line goes down its prey a big deal for them. So you need a I systems that always keep your other systems up and running. So you have to have that solid foundation storage underneath. >> Awesome. All right, we got to leave it there. Give the customer the last word. Donnie. First time in Barcelona, right? Yes. It ISS how you find in the show and the >> syphilis is awesome. This's my, actually my fifth, uh, Cisco lifers our first time in Europe, so yeah, enjoying it. >> Good. Good. Well, thank you, guys. For German of the >> correct. Thank you. Have you appreciate it? >> You're welcome. Alright. Keep right there, everybody. We'll be back to rap Day one. Sisqo live Barcelona watching you.

>> Live from Miami Beach, Florida, it's theCUBE. Covering UiPathForward Americas. Brought to you by UiPath. >> Welcome back to Miami everybody. You're watching theCUBE, the leader in live tech coverage. We go out to events, we extract the signal from the noise. A lot of noise here but the signal's all around automation and robotic process automation. I'm Dave Vellante, he's Stu Miniman, my co-host. Guy Kirkwood's here he's the UiPath chief evangelist otherwise known as the chief injector of Kool-Aid. Welcome. (guests chuckling) And Craig LeClair, the Vice President at Forrester. Covers this market, wrote the seminal document on this space. Knows it inside out. Craig, great to see you again. >> Yeah, nice to see you again. It's great to be back at theCUBE. >> So let's start with the analyst perspective. Take us back to when you first discovered RPA, why you got excited about it, and what Forrester Research is all about in that space. >> Yeah, it's been a very a interesting ride. Most of these companies, at least that are the higher value ones in the category they've been around for a long time. They've been around for over a decade, and no one ever heard of them three years ago. So I had covered at Forrester, business process management and some of the business rules engines, and I've always been in process. I just got this sense that there was a way that companies could make progress and digital transformation and overcome the technical debt that they had. A lot of the progress has been tepid in digital transformation because it takes tremendous amount of time and tons of consultants to modernize that core system that really runs the company. So along comes this RPA technology that allows you to build human equivalence that patch up the inefficiencies without touching. I came in on American Airlines and the system that cut my ticket was designed in 1960. It's the same Sabre reservation system. That's the big obstacle that a lot of companies have been struggling to really take advantage of AI in general. A lot of the more moonshot and more sophisticated promises haven't been realized. RPA is a very practical form of automation that companies can get a handle on right now, and move the dial for digital transformation. >> So Guy we heard a vision set forth by Daniel this morning. Basically a chicken in every pot, I call it, a robot for every person. Now what Craig was just saying about essentially cutting the line on technical debt, do you have clear evidence of that in your customer base? Maybe you could give some examples. >> What we're really seeing is that as organizations have to deal with the stresses, what Leslie Wilcox professor at LSE describes as the stresses within organizations and particularly in environments where the demographics are changing. What we're seeing is that organizations have to automate. So the best example of that is in Japan where the Japanese population peaked in 2010. It's now falling as a whole, plus all the baby boomers, people of Craig's and my age are now retiring. So we're now in a position where they measure levels of dangerous overwork as being more that 106 hours a week. That isn't 106 hour a week in total, that's 106 hours a week in addition to the 60 hours a week the Japanese people normally work. And there is a word in Japanese, which is (speaking in foreign language), which means to work oneself to death. So there really is no choice. So what we're seeing happening in Japan will be replicated in Western Europe and certainly in the US over the next few years. So what's driving that is the rise of the ecosystems of technologies of which RPA and AI are part, and that's really what we're seeing within the market. >> Craig, sometimes these big waves particularly in infrastructure, you kind of saw it with virtualization and some other wonky techs, like data reduction. They could be a one-time step function, and not an ongoing business value creator. Where does RPA fit in there? How can organizations make sure that this is a continuous business value generator as opposed to a one time hit? >> Good question. >> Well, I like the concept of RPA as a platform that can lead to more intelligence and more integration with AI components. It allows companies to build an automation center or a center of excellence focused on automation. But the next thing they're going to do after building some simple robots that are doing repetitive tasks, is they're going to say "Oh well wouldn't it be better "if my employee could have a textual chat with a chatbot "that then was interacting with the digital worker "that I built with the bot." Or they're going to say "You know what? I really want to use that machine learning algorithm "for my underwriting process, but I can use these bots "to go out and collect all the data from the core systems "and elsewhere and from the web and feed the algorithms "so that I could make a better decision." So again it goes back to that backing off the moonshot approach that we've been talking about that AI has been taking because of the tremendous amount of money spent by the major players to lay out the promise of AI has really been a little dysfunctional in getting organizations' eye off the ball in terms of what could be done with slightly more intelligent automation. So RPA will be a flash in the pan unless it starts to embed these more learning-capable AI modules. But I think it has a very good chance of doing that particularly now with so much investment coming into the category right. >> Craig, it's really interesting. When I heard you describe that it reminds me of the home automation. The Cortanas and Alexas and consumer side where you're seeing this. You've got the consumer side where you can build skills yourself, you know teenagers people can do that. One of the challenges always on the business side is how do you get the momentum when you don't have the consumer side. How do those interact? >> It's the technical debt issue and it's just like the mobile peak in 2011. Consumers in their hands had much better mobility right away than businesses. It took businesses five, they're still not there in building a great mobile environment. So these Alexa in our kitchen snooping on our conversation and to some extent Netflix that observes our behavior. That's a light form of AI. There is a learning from that behavior that's updating an algorithm autonomously in Netflix to understand what you want to watch. There's no one with a spreadsheet back there right. So this has given us in a sense a false sense of progress with all of AI. The reality is business is just getting started. Business is nowhere with AI. RPA is an initial foray on that path. We're in Miami so I'll call it a gateway drug. >> In fact there's also an element that the Siris, the Cortanas, the Alexas, are very poor at understanding specific ontologies that are required for industry, and that's where the limitation is right now. We're working with an organization called Humly, they're focused on those ontologies for specific industries. So if the robot doesn't understand something, then you could say to the robot Okay sit that in the Wells account, if you're in a bank, and it understands that Wells in that case means Wells Fargo it doesn't mean a hole in the ground with water at the bottom or a town in Somerset in the UK, 'cause they're all wells. So it's getting that understanding correct. >> I wonder if you guys could comment on this. Stu and I were at Splunk earlier this week and they were talking up NLP and we were saying one of the problems is that NLP is sometimes not that great. And they made a comment that I thought was very interesting. They said frankly a lot of the stuff that we're ingesting is text and it's actually pretty good. I would imagine the same is true for RPA. Is that what you see? >> You were talking about that on stage. With regards to the text analytics. >> Yes. So RPA doesn't handle unstructured content the way that NLP does. So NLP can handle voice, it can handle text. For the bots to work in RPA today you have to have a layer of analytics that understands those documents, understands those emails and creates a nice clean file that the bots can then work with. But what's happening is the text analytics layer is slowly merging with the RPA bots platforms so it's going to be viewed as one solution. But it's more about categories of use cases that deal with forms and documents and emails rather than natural language, which is where it's at. >> So known business processes really is the starting point. >> Known business-- >> One example we've got live is an insurance company in South Africa called Hollard, and they've used a combination of Microsoft Cognitive Toolkit, plus IBM Watson and it's orchestrated doing NLP and orchestrated by UiPath. So that's dealing with utterly unstructured data. That's the 1.5 million emails that that organization gets in a year. They've managed to automate 98% of that, so it never sees a human. And their reduction in cost is 91% cost in reduction per transaction. And that's done by one of our implementation partners, a company called LarcAI down there. It's superb. >> Yeah, so text analytics is hard. Last several years we have that sentiment out of it, but if I understand it correctly Craig, you're saying if you apply it to a known process it actually could have outcomes that can save money. >> Yes, absolutely yes. >> As Guy was just saying. >> I think it's moving from that rules-based activity to more experience-based activity as more of these technologies become merged. >> Will the technology in your view advance to the point, because the known processes. okay, there's probably a lot of work to be done there, but today there's so many unknown processes. It's like this messy, unpredictable thing. Will machine intelligence combined with robotic process automation get to the point, and if so when, that we can actually be more flexible and adapt to some of these unknown processes or is that just decades off? >> No, no, I think we talk at Forrester about the concept of convergence. Meaning the convergence of the physical world and the digital world. So essentially digital's getting embedded in everything physical that we have right. Think of IoT applications and so forth. But essentially that data coming from those physical devices is unstructured data that the machine learning algorithms are going to make sense of, and make decisions about. So we're very close to seeing that in factory environments. We're seeing that in self-driving cars. The fleet managers that are now understanding where things are based on the signals coming from them. So there's a lot of opportunity that's right here on the horizon. >> Craig, a lot of the technologies you mentioned, we may have had a lot of the technical issues sorted out, but it's the people interactions some things like autonomous vehicles, there's government policies going to be one of the biggest inhibitors out there. When you look at the RPA space, what should workers how do they prepare for this? How do companies, make sure that they can embrace this and be better for it? >> That's a really tough and thoughtful question. The RPA category really attacks what we call the cubicle population. And there are we're estimating four million cubicles will be emptied out in five years by RPA technology specifically. That's how we built the market forecast 'cause each one of the digital workers replacing a cubicle worker will cost $11,000 or what. That's how we built up the market forecast. They're going to be automation deficits. It's not all going to be relocating people. We think that there's going to be a lot of disruption in the outsource community first. So companies are going to look at contractors. They're going to look at the BPO contract. Then they're going to look at their internal staff. Our numbers are pretty clear. We think they're going to be four million automation deficits in five years due to RPA technology specifically. Now there will be better jobs for those that are remaining. But I think it's a big change management issue. When you first talk about robots to employees you can tell them that their jobs are going to get better, they're going to be more human. They're going to have a much more exhilarating experience. And their response to you is, What they're thinking is, "Damn robot's going to take my job." That's what they're thinking. So you have to walk them up the mountain and really understand what their career path is and move them into this motion of adaptive and continual learning and what we call constructive ambition. Which is another whole subject. But there are employees that have a higher level of curiosity and are more willing to adapt to get on the other side of the digital divide. Yep. >> You mentioned the market. You guys did a market forecast. I've seen, read stats, a little over a billion today. I don't know if that's consistent with your numbers? >> Yeah that's about right. >> Is this a 10X market? When does it get to 10 billion? Is it five, seven, 10 years? >> So we go out five years and have it be close to three billion. I think the numbers I presented on stage were 3.2 billion in five years. Now that's just software licenses and it's not the services community that surround that. >> You'd probably triple it if you add in services. >> I think two to three times service license ratio. There's always an issue at this point in emerging markets. Some of the valuations that are there, that market three billion has to be a bit bigger than that in eight or nine years to justify those valuations. That's always the fascinating capital structure questions we create with these sorts of things. >> So you describe this sort of one for one replacement. I'm presuming there's other potential use cases, or maybe not, that you forecast. Is that right? >> Oh no for the cubicles? >> Yes, it's not just cubicle replacement in that three billion right? It's other uplifts. >> No there are use cases that help in factory automation, in supply chain, in guys carrying around clipboards in warehouses. There are a tremendous number of use cases, but the primary focus are back office workers that tend to be in cubicles and contact center employees who are always in cubicles. >> And then we'll see if the non-obvious ones emerge. >> I think ultimately what's going to happen is the number of people doing back office corporate functions, so that's both finance and accounting procurement, HR type roles and indeed the industry specific roles. So claims processing insurance will diminish over time. But I think what we're going to see is an increase in the number of people doing customer experience, because it's the customer intimacy that is really going to differentiate organizations going forward. >> The market's moving very fast. Reading your report, it's like you were saying yesterday's features are now table steaks. Everybody's watching everybody else. You heard Daniel today saying, "Hey our competitors are watching. "We're open they're going to steal from us so be it." The rising tide lifts all boats. What do you advise clients in terms of where they should start, how they should get started? Obviously pick some quick wins. But what do you tell people? >> I always same pretty much the same advice you give almost on any emerging technology. Start with a good solution provider that you trust. Focus on a proof of concept, POC and a pilot. Start small and grow incrementally, and walk people up the mountain as you do that. That's the solution. I also have this report I call The Rule of Fives, that there are certain tasks that are perfect for RPA and they should meet these three rules of five. A relatively small number of decisions, relatively small number of applications involved, and a relatively small number of clicks in the click stream. 500 clicks, five apps, five decisions. Look for those in high volume that have high transaction volume and you'll hit RPA goal. You'll be able to offset 2 1/2 to four FTE's for one bot. And if you follow those rules, follow the proof of concept, good solution partner everyone's winning. >> You have practical advice to get started and actually get to an outcome. Anything you'd add to that? >> In most organizations what they're now doing, is picking one, two, or three different technologies to actually play with to start. And that's a really good way. So we recommend that organizations pick three, four, five processes and do a hackathon and very quickly they work out which organizations they want to work with. It's not necessarily just the technology and in a lot of cases UiPath isn't the right answer. But that is a very good way for them to realize what they want to do and the speed with which they'll want to do it. >> Great, well guys thanks for coming on theCUBE, sharing your knowledge. >> Thank you. >> Pleasure. >> Appreciate your time. >> Thanks very much indeed. >> Alright keep it right there everybody. Stu and I will be back from UiPathForward Americas. This is theCUBE. Be right back. (upbeat music)

(techno music) >> Announcer: From the Corinium Chief Analytics Officer Conference Spring San Francisco. It's theCUBE. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in downtown San Francisco at the Parc 55 Hotel at the Corinium Chief Analytics Officer Spring 2018 event, about 100 people, pretty intimate affair. A lot of practitioners here talking about the challenges of Big Data and the challenges of Analytics. We're really excited to have a very special Cube guest. I think he was the first guy to launch his company on theCUBE. It was Big Data New York City 2013. I remember it distinctly. It's Prakash Nanduri, the co-founder and CEO of Paxata. Great to see you. >> Great seeing you. Thank you for having me back. >> Absolutely. You know we got so much mileage out of that clip. We put it on all of our promotional materials. You going to launch your company? Launch your company on theCUBE. >> You know it seems just like yesterday but it's been a long ride and it's been a fantastic ride. >> So give us just a quick general update on the company, where you guys are now, how things are going. >> Things are going fantastic. We continue to grow. If you recall, when we launched, we launched the whole notion of democratization of information in the enterprise with self service data prep. We have gone onto now delivered real value to some of the largest brands in the world. We're very proud that 2017 was the year when massive amount of adoption of Paxata's adaptive information platform was taken across multiple industries, financial services, retail, CPG, high tech, in the OIT space. So, we just keep growing and it's the usual challenges of managing growth and managing, you know, the change in the company as you, as you grow from being a small start-up to know being a real company. >> Right, right. There's good problems and bad problems. Those are the good problems. >> Yes, yes. >> So, you know, we do so many shows and there's two big themes over and over and over like digital transformation which gets way over used and then innovation and how do you find a culture of innovation. In doing literally thousands of these interviews, to me it seems pretty simple. It is about democratization. If you give more people the data, more people the tools to work with the data, and more people the power to do something once they find something in the data, and open that up to a broader set of people, they're going to find innovations, simply the fact of doing it. But the reality is those three simple steps aren't necessarily very easy to execute. >> You're spot on, you're spot on. I like to say that when we talk about digital transformation the real focus should be on the deed . And it really centers around data and it centers around the whole notion of democratization, right? The challenge always in large enterprises is democratization without governance becomes chaos. And we always need to focus on democratization. We need to focus on data because as we all know data is the new oil, all of that, and governance becomes a critical piece too. But as you recall, when we launched Paxata, the entire vision from day one has been while the entire focus around digitization covers many things right? It covers people processes. It covers applications. It's a very large topic, the whole digital transformation of enterprise. But the core foundation to digital transformation, data democratization governance, but the key issue is the companies that are going to succeed are the companies that turn data into information that's relevant for every digital transformation effort. >> Right, right. >> Because if you do not turn raw data into information, you're just dealing with raw data which is not useful >> Jeff: Right >> And it will not be democratized. >> Jeff: Right >> Because the business will only consume the information that is contextual to their need, the information that's complete and the information that is clean. >> Right, right. >> So that's really what we're driving towards. >> And that's interesting 'cause the data, there's so many more sources of data, right? There's data that you control. There's structured data, unstructured data. You know, I used to joke, just the first question when you'd ask people "Where's your data?", half the time they couldn't even, they couldn't even get beyond that step. And that's before you start talking about cleaning it and making it ready and making it available. Before you even start to get into governance and rights and access so it's a really complicated puzzle to solve on the backend. >> I think it starts with first focusing on what are the business outcomes we are driving with digital transformation. When you double-click on digital transformation and then you start focusing on data and information, there's a few things that come to fore. First of all, how do I leverage information to improve productivity in my company? There's multiple areas, whether it is marketing or supply chain or whatever. The second notion is how do I ensure that I can actually transform the culture in my company and attract the brightest and the best by giving them the the environment where democratization of information is actually reality, where people feel like they're empowered to access data and turn it into information and then be able to do really interesting things. Because people are not interested on being subservient to somebody who gives them the data. They want to be saying "Give it to me. "I'm smart enough. "I know analytics. "I think analytically and I want to drive my career forward." So the second thing is the cultural aspect to it. And the last thing, which is really important is every company, regardless of whether you're making toothpicks or turbines, you are looking to monetize data. So it's about productivity. It's about cultural change and attracting of talent. And it's about monetization. And when it comes to monetization of data, you cannot be satisfied with only covering enterprise data which is sitting in my enterprise systems. You have to be able to focus on, oh, how can I leverage the IOT data that's being generated from my products or widgets. How can I generate social immobile? How can I consume that? How can I bring all of this together and get the most complete insight that I need for my decision-making process? >> Right. So, I'm just curious, how do you see it your customers? So this is the chief analytics officer, we go to chief data officer, I mean, there's all these chief something officers that want to get involved in data and marketing is much more involved with it. Forget about manufacturing. So when you see successful cultural change, what drives that? Who are the people that are successful and what is the secret to driving the cultural change that we are going to be data-driven, we are going to give you the tools, we are going to make the investment to turn data which historically was even arguably a liability 'cause it had to buy a bunch o' servers to stick it on, into that now being an asset that drives actionable outcomes? >> You know, recently I was having this exact discussion with the CEO of one of the largest financial institutions in the world. This gentleman is running a very large financial services firm, is dealing with all the potential disruption where they're seeing completely new type of PINTEC products coming in, the whole notion of blockchain et cetera coming in. Everything is changing. Everything looks very dramatic. And what we started talking about is the first thing as the CEO that we always focus on is do we have the right people? And do we have the people that are motivated and driven to basically go and disrupt and change? For those people, you need to be able to give them the right kind of tools, the right kind of environment to empower them. This doesn't start with lip service. It doesn't start about us saying "We're going to be on a digital transformation journey" but at the same time, your data is completely in silos. It's locked up. There is 15,000 checks and balances before I can even access a simple piece of data and third, even when I get access to it, it's too little, too late or it's garbage in, garbage out. And that's not the culture. So first, it needs to be CEO drive, top down. We are going to go through digital transformation which means we are going to go through a democratization effort which means we are going to look at data and information as an asset and that means we are not only going to be able to harness these assets, but we're also going to monetize these assets. How are we going to do it? It depends very much on the business you're in, the vertical industry you play in, and your strengths and weaknesses. So each company has to look at it from their perspective. There's no one size fits all for everyone. >> Jeff: Right. >> There are some companies that have fantastic cultures of empowerment and openness but they may not have the right innovation or the right kind of product innovation skills in place. So it's about looking at data across the board. First from your culture and your empowerment, second about democratization of information which is where a company like Paxata comes in, and third, along with democratization, you have to focus on governance because we are for-profit companies. We have a fiducial responsibility to our customers and our regulators and therefore we cannot have democratization without governance. >> Right, right >> And that's really what our biggest differentiation is. >> And then what about just in terms of the political play inside the company. You know, on one hand, used to be if you held the information, you had the power. And now that's changed really 'cause there's so much information. It's really, if you are the conduit of information to help people make better decisions, that's actually a better position to be. But I'm sure there's got to be some conflicts going through digital transformation where I, you know, I was the keeper of the kingdom and now you want to open that up. Conversely, it must just be transformational for the people on the front lines that finally get the data that they've been looking for to run the analysis that they want to rather than waiting for the weekly reports to come down from on high. >> You bet. You know what I like to say is that if you've been in a company for 10, 15 years and if you felt like a particular aspect, purely selfishly, you felt a particular aspect was job security, that is exactly what's going to likely make you lose your job today. What you thought 10 years ago was your job security, that's exactly what's going to make you lose your job today. So if you do not disrupt yourself, somebody else will. So it's either transform yourself or not. Now this whole notion of politics and you know, struggle within the company, it's been there for as long as, humans generally go towards entropy. So, if you have three humans, you have all sort of issues. >> Jeff: Right, right. >> The issue starts frankly with leadership. It starts with the CEO coming down and not only putting an edict down on how things will be done but actually walking the walk with talking the talk. If, as a CEO, you're not transparent, it you're not trusting your people, if you're not sharing information which could be confidential, but you mention that it's confidential but you have to keep this confidential. If you trust your people, you give them the ability to, I think it's a culture change thing. And the second thing is incentivisation. You have to be able to focus on giving people the ability to say "by sharing my data, "I actually become a hero." >> Right, right. >> By giving them the actual credit for actually delivering the data to achieve an outcome. And that takes a lot of work. But if you do not actually drive the cultural change, you will not drive the digital transformation and you will not drive the democratization of information. >> And have you seen people try to do it without making the commitment? Have you seen 'em pay the lip service, spend a few bucks, start a project but then ultimately they, they hamstring themselves 'cause they're not actually behind it? >> Look, I mean, there's many instances where companies start on digital transformation or they start jumping into cool terms like AI or machine-learning, and there's a small group of people who are kind of the elites that go in and do this. And they're given all the kind of attention et cetera. Two things happen. Because these people who are quote, unquote, the elite team, either they are smart but they're not able to scale across the organization or many times, they're so good, they leave. So that transformation doesn't really get democratized. So it is really important from day one to start a culture where you're not going to have a small group of exclusive data scientists. You can have those people but you need to have a broader democratization focus. So what I have seen is many of the siloed, small, tight, mini science projects end up failing. They fail because number one, either the business outcome is not clearly identified early on or two, it's not scalable across the enterprise. >> Jeff: Right. >> And a majority of these exercises fail because the whole information foundation that is taking raw data turning it into clean, complete, potential consumable information, to feed across the organization, not just for one siloed group, not just one data science team. But how do you do that across the company? That's what you need to think from day one. When you do these siloed things, these departmental things, a lot of times they can fail. Now, it's important to say "I will start with a couple of test cases" >> Jeff: Right, right. >> "But I'm going to expand it across "from the beginning to think through that." >> So I'm just curious, your perspective, is there some departments that are the ripest for being that leading edge of the digital transformation in terms of, they've got the data, they've got the right attitude, they're just a short step away. Where have you seen the great place to succeed when you're starting on kind of a smaller PLC, I don't know if you'd say PLC, project or department level? >> So, it's funny but you will hear this, it's not rocket science. Always they say, follow the money. So, in a business, there are three incentives, making more money, saving money, or staying out of jail. (laughs) >> Those are good. I don't know if I'd put them in that order but >> Exactly, and you know what? Depending on who are you are, you may have a different order but staying out of jail if pretty high on my list. >> Jeff: I'm with you on that one. >> So, what are the ambiants? Risk and compliance. Right? >> Jeff: Right, right. >> That's one of those things where you absolutely have to deliver. You absolutely have to do it. It's significantly high cost. It's very data and analytic centric and if you find a smart way to do it, you can dramatically reduce your cost. You can significantly increase your quality and you can significantly increase the volume of your insights and your reporting, thereby achieving all the risk and compliance requirements but doing it in a smarter way and a less expensive way. >> Right. >> That's where incentives have really been high. Second, in making money, it always comes down to sales and marketing and customer success. Those are the three things, sales, marketing, and customer success. So most of our customers who have been widely successful, are the ones who have basically been able to go and say "You know what? "It used to take us eight months "to be able to even figure out a customer list "for a particular region. "Now it takes us two days because of Paxata "and because of the data prep capabilities "and the governance aspects." That's the power that you can deliver today. And when you see one person who's a line of business person who says "Oh my God. "What used to take me eight months, "now it's done in half a day". Or "What use to take me 22 days to create a report, "is now done in 45 minutes." All of a sudden, you will not have a small kind of trickle down, you will have a tsunami of democratization with governance. That's what we've seen in our customers. >> Right, right. I love it. And this is just so classic too. I always like to joke, you know, back in the day, you would run your business based on reports from old data. Now we want to run your business with stuff you can actually take action on now. >> Exactly. I mean, this is public, Shameek Kundu, the chief data officer of Standard Chartered Bank and Michael Gorriz who's the global CIO of Standard Chartered Bank, they have embraced the notion that information democratization in the bank is a foundational element to the digital transformation of Standard Chartered. They are very forward thinking and they're looking at how do I democratize information for all our 87,500 employees while we maintain governance? And another major thing that they are looking at is they know that the data that they need to manipulate and turn into information is not sitting only on premise. >> Right, right. >> It's sitting across a multi-cloud world and that's why they've embraced the Paxata information platform to be their information fabric for a multi-cloud hybrid world. And this is where we see successes and we're seeing more and more of this, because it starts with the people. It starts with the line of business outcomes and then it starts with looking at it from scale. >> Alright, Prakash, well always great to catch up and enjoy really watching the success of the company grow since you launched it many moons ago in New York City >> yes Fantastic. Always a pleasure to come back here. Thank you so much. >> Alright. Thank you. He's Prakash, I'm Jeff Frick. You're watching theCUBE from downtown San Francisco. Thanks for watching. (techno music)

>> Announcer: Live from the Computer History Museum, in Mountain View, California, it's theCUBE! Covering DevNet Create 2018, brought to you by Cisco. >> Hello and welcome back to theCUBE's exclusive live coverage here in Mountain View, California, the heart of Silicon Valley at the Computer History Museum for Cisco's DevNet Create. I'm here with Lauren Cooney, the analyst, for the Wikibon team and our next guest is I'm proud to have Guy Kawasaki here on theCUBE. Guy is, goes without mentioning, a legend in the industry. Currently, the chief evangelist for Canva author of Art of the Start, a real pioneer in entrepreneurship, tech entrepreneurship, tech evangelism. Guy, great to see you, thanks for joining us. >> Thank you. >> Among other things, you've done a lot of amazing things. Thanks for joining us. >> What better place to be. >> The tech culture now is so mainstream. You're seeing Facebook CEO draw in more audience than a Supreme Court justice. >> More people watched the Senate hearings yesterday-- >> He probably has more impact than a Supreme Court justice. >> He's running the world. The tech culture has really grown to be a mainstream...in the early days the computer industry when it was really the beginning of the revolution, the PC revolution, Macintosh and the PC, you were there. So much has happened. I mean, as you look back, I mean looked out at the young guns coming up, what's your view, what's your reaction to all this? You have these (mumbles) moments. >> What's your take on all this? >> I suppose many people would say, we never thought it would get to this point. It's turned destructive and negative and all that. But it's a short snapshot of time and, first of all, can we put the genie back in the bottle? No, so it doesn't really matter. But, all things considered, the democratization of computing, everybody has a computer, whether it's a phone or a computer. The democratization of the transfer of information, obviously some information may be faint, may be not what you like. But would we go back to a time where we send things by fax machines? Not at all, I mean all things considered, >> it's a great time to be alive. >> Democratization goes through these waves, democratization with the PC, democratization with the internet, democratization of web 2.0 and social media. The beginning of social media, about 15 years, maybe 10, whatever way you might want to mark it. And now democratization with data and AI is interesting. So you're having these waves of democratization. It's going to take some time to sort out. I mean, as you look at the tech trends, how do you make sense of it, or what do you get excited about? How do you surf that wave? (chuckling) If you're going to surf the wave, the big wave coming, which some say is block chain and cryptocurrency and decentralization. What's the wave that you're on, that's the question? >> To use a surfing analogy, if we're going to go down that rat hole, a good, experienced surfer knows where to sit, can look out and say, I'll take the fourth wave. And I'll sit in the right place, turn around at the right time, paddle at the right time, you know, all that. And then there's people like me. We sit in the same place, and every 15 minutes, the right wave comes along and catches us. Those are the two theories. >> I think if only predicting tech trends were as easy as predicting surfing. >> Interviewer: Timing's everything. >> Timing is everything, luck is a lot to do with it. We only learn about the Apples and the Googles and the Ciscos and the Facebooks and the Pinterests and the Instagrams. I think you think, well, there are these really smart people and they can predict the trend or cause a trend. I think it's more the game of big numbers where if you have enough surfers in the water, somebody's going to catch a wave. (chuckling) And then you can say, yeah, I knew he was the best surfer. >> But really, right place, right time. >> And you got to know what a wave looks like. >> Guy: Well, yeah. >> You got to be, like, okay, am I in a tide pool >> or am I on a boogie board. >> And to your point, you've got to be in the water. [John] Yeah, yeah. >> You can't be standing on the shore, saying I'm going to catch a wave. You have to be in the water, and if you're in the water, >> nine times out of ten you're going to get crushed. (chuckling) >> If you're not out in front of that next wave, you're driftwood. In surfing, people will jump and try to take your wave, this sounds like the tactic of the whole industry. >> Guy: Exactly, right, right. >> What waves do you see that are coming, in your mind. You've seen a lot of waves in your day. I mean, right now, what wave is exciting you right now. >> If you look at the waves, what's out there? >> What I learn about that is, you can only declare your intelligence and victory after the fact, right. I can tell you the internet of things is big. I can tell you that social media is big. I can tell you that computing is big. Problem is I could tell you that because I know it's big now. Can I tell you what's in the future, no. If I could...first of all I wouldn't tell you. (chuckling) So I think in a rare moment of humility it's the law of big numbers. Infinite monkeys typing at keyboards, somebody's going to come up with Beethoven. >> I want to ask you a question because I get asked this question a lot, Hey, John, you've been around a while. I want to catch that next big wave, I want to be in the next Google, I want to be rich on stock options. (Guy chuckling) I said, a lot of times the best companies where you take the most advantage of is when no one else wants to work there or no one yet knows it. We really can't say, Oh, I'm going to get rich on that company because by that time it's either too late and people are chasing the wrong thing. >> Guy: Absolutely. >> How do you give that same advice to someone? >> Listen, you're talking to a guy who quit Apple twice and turned down Steve once. So how smart could I be? (John chuckling) Now we can say Apple is the most valuable company in the world, you should have stayed there. Well, thank you very much, thanks for tell me now. I think it's really... I don't want to be too dramatic, but I could almost build a case that you should invest in or work for the most dumb-ass idea you heard of. Because at any given point-- >> Airbnb, we're going to rent out mattresses >> and give out cereal. >> Very good example, Airbnb. Let's face it, if somebody told you Airbnb, before there was Airbnb, you would say, So you're telling me that I'm going to rent a room from somebody I met on the internet, and I'm going to sleep in that person's house, hoping he's not a murderer or pedophile. On the flip side, you're saying, I'm going to rent out my room to someone who I hope is not a pedophile or an ax murderer. Or ebay...I'm going to buy this printer from 3000 miles away and I'm going to assume it works. Or I'm going to sell my good printer to someone 3000 miles away and assume that he's not going to say he never got it or that it didn't work and he wants a refund. So if you go down the line of all these ideas, you'd have to say at the time, nobody. Even take an extreme: Zappos. If you told me that women would buy shoes without trying them on, seeing them, smelling them, and touching them, I would tell you you're crazy. You'd buy a book that way. You'd buy a CD that way, you'd buy a DVD. Would you buy shoes, would you buy shoes without trying them on. >> I totally would. (laughing) Now I can say that. >> To Zappos's credit, some of the way it made that work is it offered shipping back for free. So there was really no risk. But I would have been a skeptic about Zappos. >> Well, it was one of those things for me, Zappos, where they shipped in one day so I could get them immediately, try them on and if they didn't work, I could ship them back and get a different size. It was no big deal, it was very low overhead. So that's one of the reasons that that worked. But I think when you mention all of these great things like Ebay and Airbnb, it's really part of the sharing economy with people really wanting to share the goodness of their goods with other people that need them. >> It's just really connecting those folks. >> Places like Oakland and San Francisco, where there are certain streets where you line up and you just get in the next car with a stranger, and you go to San Francisco with them. >> Lauren: Yeah. >> And it's not computerized or anything. It's just trust. >> I did that once and it was frightening. (laughs) You never know who the driver is going to be or how they're going to drive. >> But you did it. >> I did it. >> People do it every day. >> I know. >> I'm amazed. >> I did it once, but... (laughing) >> Let's ask you a question. What's the craziest idea that you've seen that worked and the craziest idea that didn't work. >> Let's start with the easy one. I had a company called garage.com, and we were a venture capitalist investment bank, so we got pitched all the time. One day, a guy comes in and says, I'm going to build... A dirigible hotel over San Francisco. So you stay in the dirigible. Another person said, We're going to build a geodesic dome over Los Angeles. And I can't remember if it was to keep the air pollution in or out. I'll just tell you one really great one. These people were from Seagate so they had Cray, they worked for Seagate. And they say, We have this patent-pending, curb-jumping, patent-pending whatever technology so that if you drop your laptop with your hard disk, the head won't crash into the hard disk and ruin the hard disk. And at the time, this was 15 years ago, that was a great idea, right. It wasn't solid state. Heads crashing into hard disks. >> Moving parts. >> Seagate, so this is a great idea. Every hard disk in every laptop should be like it. So we get in the car, we go to their office, and the receptionist says, Oh, they're running late because they're on the phone with IBM. IBM is really interested in using this technology for the IBM PC laptop. Keep us waiting, keep us waiting. And they get out, and, Yeah, IBM was really, they're so excited, they're ready to move. And I, like, we're really excited. And finally I said, Give me the jist, what is your technology, is it like some special chip that detects gravitational fall, it's too fast, it's got to be hitting the ground so it parks the head because it recognizes motion or whatever. And I swear to God, I swear to God, he brings out this piece of foam and he says this is military spec foam. So we take your hard disk, we put this foam thing around it, and we put it in the laptop. And I swear to God, I was having an out of body experience. >> You're telling me-- >> I drove all the way here-- >> That your proprietary technology is putting foam around the hard disk, and IBM is excited by this foam. So welcome to my life. >> So what are you up to now. Talk about your evangelism. I know you're a (mumbles) Mercedes. You have a bunch of things going on. You've been very prolific in social media. You were on the suggested user list from day one on Twitter. >> No, I wasn't. >> Oh, no, you weren't, that's right. But you have a zillion followers. >> That's why I have never forgiven Twitter for that. >> I thought they put you on. >> Guy: No. >> Okay, I stand corrected. >> You had to be an actress. >> Some tech people got on there, I know. >> Guy: Yeah. >> But I was not on. >> There you go. >> Measly 20,000 or so. But you got a million and a half followers active. You've really been prolific in a good way. (laughing) Engaging with communities. >> Yeah. >> What have you learned and how do you view this next generation of social because you're seeing the Facebooks, you're seeing LinkedIn. There's siloed platforms. Is there hope? What's your take on it, is it going to grow? >> I've come to the point where I always believe things are never as good or as bad as they seem. So I don't think it's as bad as people say. If these social media sites are selling my data, they're going to go broke selling my data. (laughs) I don't know how you could look at my data. First of all, I never look at ads, so go ahead, sell my data. I'm not going to look at the ad anyway. It doesn't matter. I think the ability to spread ideas, arguably good or bad, the ability to spread ideas with social media, all things considered, is better. It's going to be abused and all that. My father was a state senator in Honolulu, and we were into banner ads way before anybody else. Banner was literally a piece of cloth with his name on it that you staple to the side of a building, saying Vote for Duke Kawasaki. That was the nature of banner advertisement back then. Do I think that social media targeting and all that for sales is a good thing? Yes, I do. If you're a real estate broker, and you wanted to reach people who live in Silicon Valley, age 50 to 70, female or male or whatever, in such-and-such an income bracket, how else can you do it but Facebook? >> It's good and bad. >> That's why Facebook is so successful. >> The metadata is all about the clan and the culture, and I think putting ideas out there is a way to send your ideas into the ether, make it happen. So, that's key. Now, we're here at a developer conference, so one of the things that's also a big part of this community is the notion of how open source has become a tier one citizen, and it's really running the world. Which is also grounded in community as well. You have this ethos of community, ethos of software open. >> I believe in open source. I believe that the more intelligent people pounding on your stuff, the better it is. I'm an author, and what I do is, speaking in the sense of open source. So right now I'm about 80% done with my book. I put out a post on social media saying anybody that wants to review my book, test my book, send me your information. So I do this, I cut it off at about 280 people. I send them the Word document, the entire Word document of my book. Does that mean they can take it and publish it in China tomorrow, yes. But, from that, I get hundreds and hundreds of comments. >> John: Wisdom of the crowds, self-editing. >> Yeah, and they point out stuff that I never would have noticed because I'm too close to at this point. So is there a downside, yes. Is there piracy, yes. Arguably, would those pirates have bought the book anyway? No. >> Our content's all free. We're really big in China because they actually take it and translate it in the native language. >> Guy: Which you would never have done. >> With all the jargon, you can't hire a-- >> Guy: You would never have done that. >> Yeah, exactly. >> Guy, great to catch up with you. Thanks for coming on. What are you working on now, you mentioned the book, what's the book about? >> The book is called Wise Guy, and it's a compilation of the stories that have influenced my life. So it's not an auto-biography. It is not a memoir. Have you ever heard of the book Chicken Soup for the Soul? >> John: Yeah, yeah. >> You know, it's inspirational stories. This is miso soup for the soul. (laughing) So I'm working on that, TV evangelism with Canva is just going gangbusters. Brand ambassadors for Mercedes Benz. I'm on the board of directors of a company called Cheeze with a zee. It's an anti-social photo-sharing and vidoo-sharing app. And that's it. >> You've been an inspiration to many, great job of the year has been a big fan of your work. Thanks for coming on theCUBE. Really appreciate it. >> Thank you. >> Guy Kawasaki here inside theCUBE. We're at Devnet Create. This is Cisco's cloud developer conference. Different from their core Devnet Cisco Networking developer, and this is all about dev ops open source. And this is theCUBE bringing you all the action here in Mountain View, California. We'll be right back with more after this short break.

>> Announcer: Live from San Jose, it's theCUBE, presenting Big Data, Silicon Valley, brought to you by SiliconANGLE Media and its ecosystem partners. >> Welcome back to theCUBE. Our continuing coverage of our event, Big Data SV, continues, this is our first day. We are down the street from the Strata Data Conference. Come by, we're at this really cool venue, the Forager Tasting Room. We've got a cocktail party tonight. You're going to hear some insights there as well as tomorrow morning. I am Lisa Martin, joined by my co-host, George Gilbert, and we welcome back to theCUBE, for I think the 900 millionth time, the president and CEO of DataTorrent, Guy Churchward. Hey Guy, welcome back! >> Thank you, Lisa, I appreciate it. >> So you're one of our regular VIP's. Give us the update on DataTorrent. What's new, what's going on? >> We actually talked to you a couple of weeks ago. We did a big announcement which was around 3.10, so it's a new release that we have. In all small companies, and we're a small startup, in the big data and analytic space, there is a plethora of features that I can reel through. But it actually makes something a little bit more fundamental. So in the last year... In fact, I think we chatted with you maybe six months ago. We've been looking very carefully at how customers purchase and what they want and how they execute against technology, and it's very very different to what I expected when I came into the company about a year ago off the EMC role that I had. And so, although the features are there, there's a huge amount of underpinning around the experience that a customer would have around big data applications. I'm reminded of, I think it's Gartner that quoted that something like 80% of big data applications fail. And this is one of the things that we really wanted to look at. We have very large customers in production, and we did the analysis of what are we doing well with them, and why can't we do that en masse, and what are people really looking for? So that was really what the release was about. >> Let's elaborate on this a little bit. I want to drill into something where you said many projects, as we've all heard, have not succeeded. There's a huge amount of complexity. The terminology we use is, without tarring and feathering any one particular product, the open source community is kind of like, you're sort of harnessing a couple dozen animals and a zookeeper that works in triplicate... How does DataTorrent tackle that problem? >> Yeah, I mean, in fact I was desperately interested in writing a blog recently about using the word community after open source, because in some respects, there isn't a huge community around the open source movement. What we find is it's the du jour way in which we want to deliver technology, so I have a huge amount of developers that work on a thing called Apache Apex, which is a component in a solution, or in an architecture and in an outcome. And we love what we do, and we do the best we do, and it's better than anybody else's thing. But that's not an application, that's not an outcome. And what happens is, we kind of don't think about what else a customer has to put together, so then they have to go out to the zoo and pick loads of bits and pieces and then try to figure out how to stitch them all together in the best they can. And that takes an inordinately long time. And, in general, people who love this love tinkering with technologies, and their projects never get to production. And large enterprises are used to sitting down and saying, "I need a bulletproof application. "It has to be industrialized. "I need a full SLA on the back of it. "This thing has to have lights out technology. "And I need it quick." Because that was the other thing, as an aspect, is this market is moving so fast, and you look at things like digital economy or any other buzz term, but it really means that if you realize you need to do something, you're probably already too late. And therefore, you need it speedy, expedited. So the idea of being able to wait for 12 months, or two years for an application, also makes no sense. So the arch of this is basically deliver an outcome, don't try and change the way in which open source is currently developed, because they're in components, but embrace them. And so what we did is we sort of looked at it and said, "Well what do people really want to do?" And it's big data analytics, and I want to ingest a lot of information, I want to enrich it, I want to analyze it, and I want to take actions, and then I want to go park it. And so, we looked at it and said, "Okay, so the majority "of stuff we need is what we call a cache stack, "which is KAFKA, Apache Apex, Spark and Hadoop, "and then put complex compute on top." So you would have heard of terms like machine learning, and dimensional compute, so we have their modules. So we actually created an opinionated stack... Because otherwise you have a thousand to choose from and people get confused with choice. I equate it to going into a menu at a restaurant, there's two types of restaurants, you walk into one and you can turn pages and pages and pages and pages of stuff, and you think that's great, I got loads of choice, but the choice kind of confuses you. And also, there's only one chef at the back, and he can't cook everything well. So you know if he chooses the components and puts them together, you're probably not going to get the best meal. And then you go to restaurants that you know are really good, they generally give you one piece of paper and they say, "Here's your three entrees." And you know every single one of them. It's not a lot of choice, but at the end of the day, it's going to be a really good meal. >> So when you go into a customer... You're leading us to ask you the question which is, you're selling the prix fixe tasting menu, and you're putting all the ingredients together. What are some of those solutions and then, sort of, what happens to the platform underneath? >> Yeah, so what you don't want to do is to take these flexible, microdata services, which are open source projects, and hard glue them together to create an application that then has no flexibility. Because, again, one of the myths that I used to assume is applications would last us seven to 10 years. But what we're finding in this space is this movement towards consumerization of enterprise applications. In other words, I need an app and I need it tomorrow because I'm competitively disadvantaged, but it might be wrong, so I then need to adjust it really quick. It's this idea of continual developed, continual adjustment. But that flies in the face of all of this gluing and enterprise-ilities. And I want to base it on open source, and open source, by default, doesn't glue well together. And so what we did is we said okay, not only do you have to create an opinionated stack, and you do that because you want them all to scale into all industries, and they don't need a huge amount of choice, just pick best of breed. But you need to then put a sleeve around them so they all act as though they are a single application. And so we actually announced a thing calls Epoxy. It's a bit of a riff on gluing, but it's called DataTorrent Epoxy. So we have, it's like a microdata service bus, and you can then interchange the components. For instance, right now, Apache Apex is this string-based processing engine in that component. But if there's a better unit, we're quite happy to pull it out, chuck it away, and then put another one in. This isn't a ubiquitous snap-on toolset, because, again, the premise is use open source, get the innovation from there. It has to be bulletproof and enterprise-ility and move really fast. So those are the components I was working on. >> Guy, as CEO, I'm sure you speak with a lot of customers often. What are some of the buying patterns that you're seeing across industries, and what are some of the major business value that DataTorrent can help deliver to your customers? >> The buying patterns when we get involved, and I'm kind of breaking this down into a slightly different way, because we normally get involved when a project's in flight, one of the 80% that's failing, and in general, it's driven by a strategic business partner that has an agenda. And what you see is proprietary application vendors will say, "We can solve everything for you." So they put the tool in and realize it doesn't have the flexibility, it does have enterprise-ility, but it can't adjust fast. And then you get the other type who say, "Well we'll go to a distro or we'll go "to a general purpose practitioner, "and they'll build an application for us." And they'll take open source components, but they'll glue it together with proprietary mush, and then that doesn't then grow past. And then you get the other ones, which is, "Well if I actually am not guided by anybody, "I'll buy a bunch of developers, stick them in my company, "and I've got control on that." But they fiddle around a lot. So we arrive in and, in general, they're in this middle process of saying, "I'm at a competitive disadvantage, "I want to move forward and I want to move forward fast, "and we're working on one of those three channels." The types of outcomes, we just, and back to the expediency of this, we had a telco come to us recently, and it was just before the iPhone X launched, and they wanted to do AB testing on the launch on their platform. We got them up and running within three months. Subsequent from that launch, they then repurposed the platform and some of the components with some augmentation, and they've come out with three further applications. They've all gone into production. So the idea is then these fast cycles of microdata services being stitched together with the Epoxy resin type approach-- >> So faster time to value, lower TCO-- >> Exactly. >> Being able to get to meet their customers' needs faster-- >> Exactly, so it's outcome-based and time to value, and it's time to proof. Because this is, again, the thing that Gartner picked up on, is Hadoop's difficult, this market's complex and people kick the tires a lot. And I sort of joke with customers, "Hey if you want to "obsess about components rather than the outcome, "then your successor will probably come see us "once you're out and your group's failed." And I don't mean that in an obnoxious way. It's not just DataTorrent that solves this same thing, but this it the movement, right? Deal with open source, get enterprise-ilities, get us up and running within a quarter or two, and then let us have some use and agile repurposing. >> Following on that, just to understand going in with a solution to an economic buyer, but then having the platform be reusable, is it opinionated and focused on continuous processing applications, or does it also address both the continuous processing and batch processing? >> Yeah, it's a good answer. In general, and again Gatekeeper, you've got batch and you've got realtime and string, and so we deal with data in motion, which is string-based processing. A string-based processing engine can deal with batch as well, but a batch cannot deal with string. >> George: So you do both-- >> Yeah >> And the idea being that you can have one programming model for both. >> Exactly. >> It's just a window, batch is just a window. >> And the other thing is, a myth bust, is for the last maybe eight plus years, companies assume that the first thing you do in big data analytics is collect all the data, create a data lake, and so they go in there, they ingest the information, they put it into a data lake, and then they poke the data lake posthumously. But the data in the data lake is, by default, already old. So the latency of sticking it into a data lake and then sorting it, and then basically poking it, means that if anybody deals with the data that's in motion, you lose. Because I'm analyzing as it's happening and then you would be analyzing it after at rest, right? So now the architecture of choice is ingest the information, use high performance storage and compute, and then, in essence, ingest, normalize, enrich, analyze, and act on data in motion, in memory. And then when I've used it, then throw it off into a data lake because then I can basically do posthumous analytics and use that for enrichment later. >> You said something also interesting where the DataTorrent customers, the initial successful ones sort of tended to be larger organizations. Those are typically the ones with skillsets to, if anyone's going to be able to put pieces together, it's those guys. Have you not... Well, we always expected big data applications, or sort of adaptive applications, to go mainstream when they were either packaged apps to take all the analysis and embed it, or when you had end to end integrated products to make it simple. Where do you think, what's going to drive this mainstream? >> Yeah, it depends on how mainstream you want mainstream. It's kind of like saying how fast is a fast car. If you want a contractor that comes into IT to create a dashboard, go buy Tableau, and that's mainstream analytics, but it's not. It's mainstream dashboarding of data. The applications that we deal with, by default, the more complex data, they're going to be larger organizations. Don't misunderstand when I say, "We deal with these organizations." We don't have a professional services arm. We work very closely with people like HCL, and we do have a jumpstart team that helps people get there. But our job is teach someone, it's like a kid with a bike and the training wheels, our job is to teach them how to ride the bike, and kick the wheels off, and step away. Because what we don't want to do is to put a professional services drip feed into them and just keep sucking the money out. Our job is to get them there. Now, we've got one company who actually are going to go live next month, and it's a kid tracker, you know like a GPS one that you put on bags and with your kids, and it'll be realtime tracking for the school and also for the individuals. And they had absolutely zero Hadoop experience when we got involved with them. And so we've brought them up, we've helped them with the application, we've kicked the wheels off and now they're going to be sailing. I would say, in a year's time, they're going to be comfortable to just ignore us completely, and in the first year, there's still going to be some handholding and covering up a bruise as they fall off the bike every so often. But that's our job, it's IP, technology, all about outcomes and all about time to value. >> And from a differentiation standpoint, that ability to enable that self service and kick off the training wheels, is that one of the biggest differentiators that you find DataTorret has, versus the Tableau's and the other competitors on the market? >> I don't want to say there's no one doing what we're doing, because that will sound like we're doing something odd. But there's no one doing what we're doing. And it's almost like Tesla. Are they an electric car or are they a platform? They've spurred an industry on, and Uber did the same thing, and Lyft's done something and AirBNB has. And what we've noticed is customer's buying patterns are very specific now. Use open source, get up their enterprise-ilities, and have that level of agility. Nobody else is really doing that. The only people that will do that is your contract with someone like Hortonworks or a Cloudera, and actually pay them a lot of money to build the application for you. And our job is really saying, "No, instead of you paying "them on professional services, we'll give you the sleeve, "we'll make it a little bit more opinionated, "and we'll get you there really quickly, "and then we'll let you and set you free." And so that's one. We have a thing called the Application Factory. That's the snap on toolset where they can literally go to a GUI and say, "I'm in the financial market, "I want a fraud prevention application." And we literally then just self assemble the stack, they can pick it up, and then put their input and output in. And then, as we move forward, we'll have partners who are building the spoke applications in verticals, and they will put them up on our website, so the customers can come in and download them. Everything is subscription software. >> Fantastic, I wish we had more time, but thanks so much for finding some time today to come by theCUBE, tell us what's new, and we look forward to seeing you on the show again very soon. >> I appreciate it, thank you very much. >> We want to thank you for watching theCUBE. Again, Lisa Martin with my co-host George Gilbert, we're live at our event, Big Data SV, in downtown San Jose, down the street from the Strata Data Conference. Stick around, George and I will be back after a short break with our next guest. (light electronic jingle)

>> Announcer: Live from Las Vegas, it's the Cube, covering Dell EMC World 2017. Brought to you by Dell EMC. >> Hello everyone, welcome to the Cube special coverage of Dell EMC World 2017. This is the Cube Silicon Angle's flagship program where we go out to the events and extract the signal from the noise. This is our eighth year of covering EMC World, but now called Dell EMC World. I'm John Furrier, your co-host on our set one and with my co-host Paul Gillin this week as well as Kieth Townshend and John Walls and Rebecca Knight on set two. Double barrel shotgun of content here at Dell EMC World with you. Thanks for joining us for three days of wall to wall coverage. Paul, so much to talk about here this week. Digital transformation, little bit boring theme, it's being played out in real time. But this is a historic moment because one, the Cube started at EMC World in 2010, eight years ago. But, this is the first official EMC World where it's Dell EMC World, kind of a mini event in Austin, but since Michael Dell took over, or I'm sorry, merger of equals, a combination. >> Paul: Combination, as they call it. >> (chuckling) Combination. This is the first instantiation of EMC World as Dell EMC World. Jeremy Burton's now the CMO of Dell Technologies which is the holding company for all the companies. It's the same EMC World flair, now the integrated content. Notable absent Cube alumni and executives from EMC. We'll talk about that in the EMC Mafia segment shortly, but (chuckling) your thoughts because now Michael Dell's puttin' the rubber to the road. Kind of nothing earth shattering in his keynote, but certainly private company, all guns blaring, smiling and dialing, he's got the swagger on stage. >> Well, Michael is nothing if not an optimist. He's always good at seeing a brighter future, and at his keynote this morning, as you said it was blissfully free of content, but it did talk a lot about digital transformation which is of course the buzzword of the year in the IT industry. Little surprised that Dell adopted the same buzzword that HP and Cisco and all these other big companies are adopting. What happened in the keynote is less interesting than how the mood changes here, and this is the coming out party for Dell EMC. Yeah, there was a conference last October, a month after the merger, but this is really, things have finally settled out, now six months later and it's a chance for customers and for the partners to get a sense of how well this is all working out. >> And one of the things I'm watching is how the story's unfolding 'cause now you're starting to see the big companies, certainly in the consolidation side of the business market of infrastructure and data center and enterprise IT, it's a consolidating mature market. It is transforming, there is a cloud story requirement, there are new software requirements, software defined data center, as well as new growth opportunities, so what I'm looking at is what is the story? What is Michael packaging and how does that compare to the competition? We're going to hear from HPE at HPE Discover coming up, the Cube will be covering that for the seventh consecutive year. We're seeing Amazon's story playing out in real time. Oracle's story, everyone's got their story. And it's certainly digital transformation but what's interesting is Michael's got the packaging. He's packaging it up, your thoughts. >> And Michael kind of dissed the cloud this morning, actually in his presentation. He said, you can't have a successful business, or your business is not going to grow as quickly if you're 100% cloud based. He was very much making a pitch for data center infrastructure. Really not surprising coming from Michael. One thing that will be a sub-theme here I think is how this merger is working out, and as we wrote on Silicon Angle this week, if you go back to the history of big mega mergers, particularly in the hardware industry, going back to Burroughs Sperry, DEC Compaq, HP Compaq, Wellfleet Synoptics and NCR AT&T. I mean, it goes on and on and on. Pretty much all disasters, and we really haven't seen a merger anywhere near this scale between two IT companies that has worked well. All indications are now that they're doing the right things, they even have some people on board with Dell EMC who went through some of those mergers. But it's going to be interesting to see how they break a pattern that has been decidedly negative. >> Great point, I loved your post by the way, and I would add that interesting observation, at least from my perspective is, as we sit down with these billionaires and interview them one-on-one on the Cube is, you look at Amazon, Andy Jasse and Jeff Bezos, Bezos in particular. Larry Ellison and Michael Dell, you have essentially captains of industry at the helm. Michael Dell is no spring chicken, but he's also not over the hill either, he's 51 years old. >> Paul: He's a kid relative to most leaders in this industry. >> You know, you hear Jeff Bezos talk and I was watching his talk in DC just this week, he's saying we're taking the long view. If you look at Amazon.com's CEO, Bezos, look at Michael Dell, look at what Ellison's doing, they're all playing the long game card. Now I don't know if that's a hedge against we don't have our story right, or give us more time to bake out our stuff, but I think what's different about Dell Technologies is, Michael's 33 years into the business, one trillion dollars later in sales and he's young, so I think that is a wild card. Ellison's still running the show, Bezos is still running the show, Dell's certainly running the show. I think the wild card on this is the fact that you got a strong founder, and a privately held company. >> And Ellison, it's questionable how long Ellison will be able to run the show, I mean he is over 70 at this point. Dell certainly will be around for a long time. You have to take a long term strategy. If you're not Amazon, you have to take a long term strategy 'cause what other choice do you have? You've lost in the short term, so it's not surprising to hear these guys going that way. I'll be interested to hear from Michael and from his team about the cloud and how they really design and differentiate its strategy. I think IBM has staked its position in cloud out pretty well. Even HPE has got a differentiated position. HPE of course has the configurable hardware, that's a point that Dell I think has to come back on, and the big question is software. John, as you pointed out the other day, VMware is worth more than HPE, by a substantial margin at this point. They've got this huge asset in VMware, not to mention Virtuestream and Pivotal and the other good software assets they acquired. What are they going to do with them? Are they just going to let 'em go free like Michael has done in the past, or are they going to try to mold these into some kind of coordinated whole? >> Well, great point one is on the HPE valuation thing market cap, VMware's actually worth more on market cap and public markets than HPE. Interesting, but not significant in my mind yet, but it does point to the fact that Michael Dell's rhetoric on stage today, he didn't take any shots at HP. Last year he took a big shot at HPE. It's been his rival from day one. I used to work at HP when he was just a mail order company selling white boxes and then he grew that business, obviously the rest is history, but no shot at HP because VMware has to work with HP. Right, (chuckling) so that's interesting. Two is, on the software side, Dell is a hardware company, let's face it. But they have more software now than they've ever had before so that is a good point, we're going to be getting into this date software defined data center to find out how much they actually have. A couple core themes that I see already popping out of the keynote, one, Pivotal. Pivotal and Cloud Foundry's instrumental in the keynotes. NSX was mentioned, Pat Gelsinger's going to be on tomorrow. NSX is VMware's secret play. If you look at what NSX is doing with the Amazon public cloud deal that they did recently this year, NSX could be the real lever in that intellectual property, that lock in, that kind of differentiation. The cloud is not a place, it's a way of doing IT is another message we heard all day today. To me, and your point about bashing cloud, I actually think that's a stake in the ground to kind of hold the line, because they have no cloud strategy. Now, their cloud strategy is kind of hand waiving right now with multi-cloud, which I buy, but multi-cloud is still a fantasy in my mind. Latencies are too low, there just isn't the kind of plumbing yet in place on the clouds for multi-cloud, but certainly hybrid-cloud I think will be multi-cloud roll, so those are the key things and then I'm going to ask Michael directly. You blew 60 billion dollars on this deal. Is there any cash left for M&A? >> Paul: Acquisitions, yeah. >> M&A right now is hot market, you can do some nice tuck ins, fill in the white spaces on the products. Get those software assets and really start cobbling together a growth strategy. There's no doubt in my mind, Paul, that they're going to win the mature, classic business school move of consolidated market. Own the consolidated market, and try to get a growth strategy. To me, that's going to be the big question. What is Dell Technologies and Dell EMC's growth strategy? >> And you would have to think it's either through M&A, perhaps an acquisition of HPE if the valuation continues to go down. Or it's in software It's a good point you made about VMware. Vmware also has a strategic alliance with IBM, so if you're Michael Dell, it's hard to give a compelling keynote speech these days because you can't really offend anybody. His companies now are in cahoots with all these other firms, and of course dissing the cloud is even dangerous because Cloud Foundry is such a critical part of the Pivotal strategy. I think it's an important point, you've got a company that is almost trying to reassemble the old IBM, the old IBM of the '80s which dominated every segment that was important Dell is almost doing that now, I mean the only piece they really don't have is networking. To make a big play, to become the mongo IT company in the world, can they raise the kind of funds for that? >> Yeah, and we're also going to talk about the cloud transition as well as what I'm calling the EMC mafia, folks that have been on the Cube and big executives at EMC. We'll get to that in a minute, but I just want to talk about that cloud play, because you're right, the growth strategy has to come from software. I just don't see the cloud growth yet for these guys, although Michael, in the hallway, conversations are growth in the cloud is doing really well for EMC, not sure. But on the growth strategy, Pivotal, Boo-Mee, Vmware, Virtuestream, and Software Converge Infrastructure are interesting plays, so I think that's where we have to look here. I still think there's a lot of holes in the product line. To me that's important. Now, trends so far, and what we're expecting to hear at the show is, some of my notes Paul, I'll share with you, and get your reaction on. All flash arrays are going to be big, continuing to grow that. Hyperconverge VX rail, we heard that on stage today, claiming to be number one. Power edge 14G. Again, back to speeds and feeds, (chuckling) you know. Storage. Storage is the bread and butter of EMC and now Dell EMC I still think is going to be a real critical beachhead that they going to continue to expand, storage is not going away. Obviously the ice lawn all flash is coming out, and then SSD's, data protection in the cloud. You're starting to see them going where their roots are. Cloud stuff is coming out of the data domain, kind of their core storage first, make sense strategy wise, while they buy their time to fill in the cloud. >> Well, it's a good point about storage. They have a comfortable lead in storage. According to the latest IDC figures, they're a good 15 points ahead of their next biggest competitor. They have a comfortable lead in the hyper converge infrastructure. Four different product lines in that area. These are beachheads that they have to shore up. They have to be sure that their market share doesn't erode in those areas. The question is where does the growth come from? You look at a company that's going through a very similar transition right now, Cisco, which has finally really bought in to software defined networking and is remaking its company around it. That company is having to change the whole culture in response to a technology trend. Now the same thing's going on in the data center. Everything's being remade as virtualized and Vmware is at the center of that, so Michael Dell has the asset to be able to lead that conversion, but are they psychologically going to get there? >> Great point. One, I would agree with you that the whole Cisco example proves the same channel that Dell EMC is. Can they move up the stack? In this case, they're hardware guys, can they add software. Cisco, they're transforming themselves to be more cloud native. The classic move's happening. Cisco have been trying to move up the stack for over a generation. They're plumbing guys, they're networking guys. These guys are hardware guys. Can they get the DNA to truly become software providers, not in the sense of selling software, just providing a software fabric that's going to be the key differentiators, because digital transformation is about IT transformation. That is certainly the reality, what we're seeing when you start to peel back the onions. And that to me is going to be the big discussion because as David Gooldun said on stage, apps provide the value. As the enterprises build more apps, you got to have a platform, you got to have a cohesive horizontal end to end software fabric, and the question is, do they have it? >> Well, they certainly have the foundation for it, I mean they have Pivotal, there's a whole developer community around Pivotal. Dell itself doesn't have a developer community, nor does EMC but they have elements of that to build upon. The interesting thing about the conversion to software, about software defined infrastructure, is that it requires thinking from an application perspective and that's not something hardware companies have ever been inclined to do. So, how does Michael Dell make that transition, has he made it himself, is there other leadership he's going to have to bring in who are going to make it for him? The whole leadership of the Dell EMC company right now is ex-Dell and EMC people, it's hardware guys. >> I'm going to put pressure on Dell, the question on software. But you wrote a two part series on SiliconAngle.com, worth checking out, getting a lot of viral buzz around open source and the value of open source, because if you look at say Cisco for instance, what they're doing with the cloud native strategy, they have actually pivoted and Chuck Robbins, the CEO has acknowledged, actually re-tweeted one of my tweets the other day, with as we were talking about this new program called DevNet Create. They're taking the developer program from Cisco and moving it into an open community model, which basically is the toe in the water for saying, we have to figure out open source. All the critical, big vendors that are transforming from called the old guard, as Amazon calls 'em, Amazon Web Services, Andy Jasse. Dell's an old guard guy, but still young, but they got to get to open source. What are you finding is the success parameters there because you got to play in the open source, be a contributing member. Again, back to the DNA of the culture, and two, there's real value there. >> Well, there's no question that open source has won when it comes to infrastructure. I mean, the biggest IT companies in the world which are Google and Facebook, are both built on open source platforms. Game over. This is where IT infrastructure is headed. Cisco, interesting case because they are an infrastructure company, and they are being eroded, their traditional market is being eroded by open source, they've chosen to embrace it through their developer community. Cisco is one company I would never bet against. They're such a great company. If anyone's going to make the transition, they will. Open source is still an infrastructure play. I don't see open source in the applications area being a major driver, but Dell is an infrastructure company, so you have to assume that everything they're doing in managing, in securing storage and servers is going to be under pressure from open source at some point. They have to embrace that as Cisco is doing. >> Paul, we had thought leader chat with some experts on our digital panel, software crowd chat, everyone knows crowdchat.net, check it out. And comment and conversation was taking place among the influential folks saying, what is a software company? You go back to the web, shrink wrapped, download software, to now fully SAS based and Saas now platform, what is a software company? So, the question was, is Facebook a software company? Or are they an app company? Which begs the question, you have to be a software company, but it's not the classic software company category, business model. You need software (chuckling) to run stuff, so you can be a hardware guy, like Michael Dell, and have Dell Technologies. You can be a network company like Cisco, but you've got to be a software company in the new way. >> Well, I spoke to a Forester analyst in writing that piece on open source who had a great point, he said Facebook and Google are two big successful software companies, neither of which makes. >> Any money. >> Any money, a little bit in Google's case licensing software. They created business models that have nothing to do with the traditional software model, but that have leveraged their expertise in the software that they've developed. And maybe that is the business model, ultimately the business model is building software in order to do something else with it that customers will pay for. >> I think you're on to something. I think your post illuminates that. I think that this is going to be one of those things where in the history books of the tech generation, as we're on our whatever wave of open source generation, this is it, it's not about the business model of the software, it's how the software's being used in the business model of the transformation. That is really really key. Paul, I want to just talk about, really quickly about my observation at EMC. A little bit of editorial moment here. Because, Dell took over. Dell EMC. We've interviewed now eight years, pretty much all the executives at EMC over the years, but there's an EMC mafia developing. There's a lot of people who have left EMC, that we know, we're friends with. Guy Churchwood, CJ DeSai, Josh Conn, Rich DePellatano, Brian Gallagher, BJ Jenkins, Sanjay Murchandani, and many more have left because of the consolidation. Certainly you can't, EMC's going to get consolidated down, but no major layoffs but still enough that some eagles have flown from the nest, as they say and are running other companies. So you have this EMC culture out there of very sales oriented, very customer centric, now running other companies, and I want to give a shout out to all those EMC alumni and mafia out there. Good luck on your new ventures, but the impact here to Dell is a mashup of the two cultures. What's your observation, what's your reaction of that. Have you heard anything? I have some thoughts, but I want to get your reaction because okay, some eagles fly away, you still got the worker bees inside EMC, and now Dell coming together. Thoughts on the culture clash. >> Well, I live in Boston, and so I've been through the acquisition of Prime Computer, through EMC acquiring Data General, through the DEC acquisition by Compaq. All of which were disasters, and all of which where the cultural issues were much bigger than the technology issues. So, I think that that is something that Dell has to be front and center for Michael Dell, is how do you mash up these two cultures. As you pointed out, EMC, very aggressive, take no prisoners, enterprise-oriented sales force. Their sales people make a lot of money. I used to live in a neighborhood where everyone was EMC salespeople. >> John: Buying new houses. >> They were making a million dollars a year. And you've got Dell with its direct model, with its channeled model, and without a particularly strong roots in enterprise sales force and how do you coordinate those. It's not surprising to see people leaving. Of course, in the early days after an acquisition, choices get made, people get promoted and moved in new positions. Those who lose out tend to leave the company. But, I think the sales issue would be something to delve into too. Does Dell want to adopt EMC's sales style, or the other way around? Or is there some way that they can live both in harmony? >> You know, I follow a lot of companies in Silicon Valley as well, I'm out there on the west coast, left coast, as they say. Where all the crazy ones are, as they say. But I got to say, there's been some shrinkage on EMC, but for the most part, I haven't really heard any really negative horror stories. Actually, it's been going pretty well, and I think you bring up an issue of effectiveness with the sales folks. Dell's an efficiency guy, right so you got effectiveness and efficiency coming together. But I think they've handled it well. I really haven't heard any real horror stories. Again, I think that has to do with the founder being actively involved, they're a private company, so they have some room. And I think they've invested in making that happen, so I think generally, props to EMC folks and for the Dell folks on the acquisition. Still not clear the woods yet, it's going to surely be in the products and the revenue, but for the most part, we're going to unpack that. So Paul. >> But you can't, I just wanted to jump in just quickly. You can't minimize customer touch, and EMC was always a high touch company. Outstanding service, they put people on a plane in the middle of the night, charter a private jet in the middle of the night to get someone on site at a customer to fix a problem. As you mentioned, Dell is an efficiency company. That's not a very efficient way to operate. Can they absorb the best of EMC and the best of Dell at the same time? >> Yeah, well we'll certainly tell, I mean they got a lot of competition, Michael Dell saying on stage. (mumbling) startups, essentially what's he's saying is Amazon, there in my opinion, although that's not probly what he really meant but that's my interpretation. But I'm expecting to see the same old EMC world with a twist, and that is, we're doin' good, the messaging's out there, we're going to see how the products compare vis a vis the competition. I'm interested in Vmware piece. Paul, what are you looking forward to? >> I'm looking forward to hearing how this is all going, how this company is culturally, what kind of a cultural chimera they're putting together here that's going to make sense, that the market is going to understand. I also want to hear how they're going to differentiate in cloud, internet of things, we just heard a little bit about that this morning. That's something where I think you're seeing Cisco. The way Cisco's dealing with the cloud these days is to say, don't worry about it, it's all going IOT. It's all going to distributed intelligent devices, the cloud is already history, is what they're saying. So, does Dell have a similar differentiated position on that. I'm least interested in hearing about the new products because it's speeds and feeds. But really, how is this company going to dominate an industry, how is it going to get over some of the speed bumps that we've been talking about for the last 20 minutes that have foiled so many merger attempts in the past. >> One of the tell signs that I look at a conference when I see a lot of AI washing. The good news is, there's not a lot of AI being talked about here, 'cause usually that's just lipstick on the pig, as they say. Except for the case of Google and Amazon Web Services, they do have some AI story, with some real products to back it up. For the most part, you're not seeing EMC glob on the whole machine learning, rah rah. They did talk about it but it wasn't like a big theme. I think they really talked about the packaging of the value. Of the brands together, comments around costs for public cloud, nice little ding there. I'm going to dig into the story. I'm going to really test the story, and I'm going to look at the customer traction. I really want to see who they have on stage, I really want to hear who's really going down the road, how that growth strategy, 'cause I think they're going to win the data consolidation market pretty handily, and the question between HPE and Dell, for instance, 'cause that's really to me the two big horses on the track. Who's going to win the growth. Who's going to be able to lock in their beachhead on the core market, traditional market, and have access to the growth of what cloud will bring and IOT and among other things. >> I think at this point, HP has a better story in that area with their configurable infrastructure, with their pay as you go on site model, really interesting models. I was at HP World in Europe in December, and I came away from that feeling like these guys have some unique talking points here. At least they have a strategy that I think I understand and that is different. Dell is still working through this huge merger and that's a big catch. >> Bottom line is, Dave Donatelli, who's an executive at Oracle told me, he also was an EMC executive, and HPE. The business of provisioning servers and storage (laughing) is not going to be the growth strategy. Now, it might be a component of the overall business model, like software, but ultimately, that business is in decline, and that's a fact. Okay, this is the Cube, bringing you all the coverage of the kickoff from day one at Dell EMC World 2017. Our eighth year, three days of wall to wall coverage. We have two sets, the blue set and the white set. Go to SiliconAngle.tv to find the coverage, also go on Twitter, follow us on the Cube, I'm John Furrier with Paul Gillin, kickin' off Dell EMC World 2017, back with more, stay with us after this short break. (atmospheric instrumental music)

>> No. Yeah. Wait. >> Hi, everyone, and welcome to the big data. Deep Dive with the Cube on AMC TV. I'm Richard Schlessinger, and I'm here with tech industry entrepreneur and wicked bond analyst Dave Volonte and Silicon Angle CEO and editor in chief John Furrier. For this last segment in our show, we're talking about the future of big data and there aren't two better guys to talk about that you and glad that you guys were here. Let me sort of tee up the this conversation a little bit with a video that we did. Because the results of big data leveraging are only as good as the data itself. There has to be trust that the data is true and accurate and as unbiased as possible. So AMC TV addressed that issue, and we're just trying to sort of keep the dialogue going with this spot. >> We live in a world that is in a constant state of transformation, political natural transformation that has many faces, many consequences. A world overflowing with information with the potential to improve the lives of millions with prospects of nations with generations in the balance way are awakening to the power of big data way trust and together transform our future. >> So, Gentlemen Trust, without that, where are we and how big of an issue is that in the world of big data? Well, you know, the old saying garbage in garbage out in the old days, the single version of the truth was what you were after with data warehousing. And people say that we're further away from a single version of the truth. Now with all this data. But the reality is with big data and these new algorithms you, khun algorithmic Lee, weed out the false positives, get rid of the bad data and mathematically get to the good data a lot faster than you could before. Without a lot of processes around it. The machines can do it for you. So, John, while we were watching that video, you murmured something about how this is the biggest issue. This is cutting edge stuff. This is what I mean. >> Trust, trust issues and trust the trust equation. Right now it is still unknown. It's evolving fast. You see it with social networks, Stevens go viral on the internet and and we live in a system now with mobility and cloud things. Air scaling infinitely, you know, these days and so good day two scales, big and bad data scales being so whether it's a rumor on you here and this is viral or the data data, trust is the most important issue, and sometimes big data can be creepy. So a. This really, really important area. People are watching it on DH. Trust is the most important thing. >> But, you know, you have to earn trust, and we're still sort of at the beginning of this thing. So what has to happen to make sure that you know you don't get the garbage in, so you get the garbage. >> It's iterative and and we're seeing a lot of pilot projects. And then those pilot projects get reworked, and then they spawn into new projects. And so it's an evolution. And as I've said many, many times, it's very early we've talked about, were just barely scratching the surface here. >> It's evolving, too, and the nature of the data is needs to be questioned as well. So what kind of data? For instance, if you don't authorize your data to be viewed, there's all kinds of technical issues around. >> That's one side of it, But the other side of it, I mean, they're bad people out there who would try to influence, Uh, you know what? Whatever conclusions were being drawn by big data programs, >> especially when you think about big data sources. So companies start with their internal data, and they know that pretty well. They know where the warts are. They know how to manipulate. It's when they start bringing in outside data that this gets a lot fuzzier. >> Yeah, it's a problem. And security talk to a guy not long ago who thought that big data could be used to protect big data, that you could use big data techniques to detect anomalies in data that's coming into the system, which is poetic if nothing else, that guys think data has told me that that that's totally happened. It's a good solution. I want to move on because way really want to talk about how this stuff is going to be used. Assuming that these trust issues can be solved on and you know, the best minds in the world are working on this issue to try to figure out how to best, you know, leverage the data, we all produce, which has been measured at five exabytes every two days. You know, somebody made an analogy with, like something. If a bite was a paper clip and you stretched five exabytes worth of paper clips, they would go to the moon or whatever. Anyway, it's a lot of bike. It's a lot of actually, I think that's a lot of fun and back way too many times one hundred thousand times I lost track of my paper. But anyway, the best minds are trying to figure out, you know, howto, you know, maximize that the value that data. And they're doing that not far from here where we sit. Uh, Emmett in a place called C Sale, which was just recently set up, See Sail stands for the computer signs, an artificial intelligence lab. So we went there not long ago. It's just, you know, down the Mass. Pike was an easy trip, and this is what we found. It's fascinating >> Everybody's obviously talking about big data all the time, and you hear it gets used to mean all different types of things. So he thinks we're trying to do in the big data. Is he? Still program is to understand what are the different types of big data that exists in the world? And how do we help people to understand what different problems or fall under the the overall umbrella of big data? She sells the largest interdepartmental laboratory and mitt, so there's about one hundred principal investigators. So that's faculty and sort of senior research scientists. About nine hundred students who are involved, >> basically with big data, almost anything to do with it has to be in a much larger scale than we're used to, and the way it changes that equation is you have to You have to have the hardware and software to do the things you're used to doing. You have to meet them of comedy's a larger size a much larger size >> of times. When people talk about big data, they, I mean, not so much the volume of the data, but that the data, for example, is too complex for their existing data. Processing system to be able to deal with it. So it's I've got information from Social network from Twitter. I've got your information from a person's mobile phone. Maybe I've got information about retail records. Transactions hole Very diverse set of things that need to be combined together. What this clear? It says this is If you added this, credit it to your query, you would remove the dots that you selected. That's part of what we're trying to do here. And big data is he sail on. Our big data effort in general at MIT is toe build a set of software tools that allow people to take all these different data sets, combine them together, asked questions and run algorithms on top of them that allowed him to extracting sight. >> I'm working with it was dragged by NASA, but the purpose of my work right now is Tio Tio. Take data sets within Davis's, and instead of carrying them for table results, you query them, get visualizations. So instead of looking at large sets of numbers and text him or not, you get a picture and gave the motivation Behind that is that humans are really good into pretty pictures. They're not so that interpreting huge tables with big data, that's a really big issue. So this will have scientists tio visualize their data sets more quickly so they can start exploring And, uh, just looking at it faster, because with big data, it's a challenge to be able to visualize an exploiter data. >> I'm here just to proclaim what you already know, which is that the hour of big data has arrived in Massachusetts, and >> it's a very, very exciting time. So Governor Patrick was here just a few weeks ago to announce the Mass Big Data Initiative. And really, I think what he recognizes and is partly what we recognize here is that there's a expertise in the state of Massachusetts in areas that are related to big data, partly because of companies like AMC, as well as a number of other companies in this sort of database analytic space, CMC is a partner in our big data detail, initiatives and big data and See Sale is industry focused initiative that brings companies together to work with Emmet T. Think about it. Big data problems help to understand what big data means for the companies and also to allow the companies to give feedback. Tow us about one of the most important problems for them to be working on and potentially expose our students and give access to these companies to our students. >> I think the future will tell us, and that's hard to say right now, because way haven't done a lot of thinking, and I was interpreting and Big Data Way haven't reached our potential yet, and I just there's just so many things that we can't see right now. >> So one of the things that people tell us that are involved in big data is they have trouble finding the skill sets the data. Science can pick capability and capacity. And so seeing videos like this one of them, it is a new breed of students coming out there. They're growing up in this big data world, and that's critical to keep the big data pipeline flowing. And Jon, you and I have spent a lot of time in the East Coast looking at some of the big data cos it's almost a renaissance for Massachusetts in Cambridge and very exciting to see. Obviously, there's a lot going on the West Coast as well. Yeah, I mean, I'll say, I'm impressed with Emmett and around M I. T. In Cambridge is exploding with young, young new guns coming out of there. The new rock stars, if you will. But in California we're headquartered in Palo Alto. You know we in a chance that we go up close to Google Facebook and Jeff Hammer backer, who will show a video in a second that I interview with him and had dupe some. But he was the first guy a date at Facebook to build the data platform, which now has completely changed Facebook and made it what it is. He's also the co founder of Cloudera The Leader and Had Duke, which we've talked about, and he's the poster child, in my opinion of a data scientist. He's a math geek, but he understands the world problems. It's not just a tech thing. It's a bigger picture. I think that's key. I mean, he knows. He knows that you have to apply this stuff so and the passion that he has. This video from Jeff Hammer Bacher, cofounder of Cloud Ear, Watches Video. But and then the thing walk away is that big data is for everyone, and it's about having the passion. >> Wait. Wait. >> Palmer Bacher Data scientists from Cloudera Cofounder Hacking data Twitter handle Welcome to the Cube. >> Thank you. >> So you're known in the industry? I'LL see. Everyone knows you on Twitter. Young Cora heavily follow you there at Facebook. You built the data platform for Facebook. One of the guys mean guys. They're hacking the data over Facebook. Look what happened, right? I mean, the tsunami that Facebook has this amazing co founder Cloudera. You saw the vision on Rommedahl always quotes on the Cube. We've seen the future. No one knows it yet. That was a year and a half ago. Now everyone knows it. So do you feel about that? Is the co founder Cloudera forty million thousand? Funding validation again? More validation. How do you feel? >> Yeah, sure, it's exciting. I think of you as data volumes have grown and as the complexity of data that is collected, collected and analyzed as increase your novel software architectures have emerged on. I think what I'm most excited about is the fact that that software is open source and we're playing a key role in driving where that software is going. And, you know, I think what I'm most excited about. On top of that is the commodification of that software. You know, I'm tired of talking about the container in which you put your data. I think a lot of the creativity is happening in the data collection integration on preparation stage. Esso, I think. You know, there was ah tremendous focus over the past several decades on the modeling aspect of data way really increase the sophistication of our understanding, you know, classification and regression and optimization. And all off the hard court model and it gets done. And now we're seeing Okay, we've got these great tools to use at the end of the pipe. Eso Now, how do we get more data pushed through those those modeling algorithm? So there's a lot of innovative work. So we're thinking at the time how you make money at this or did you just say, Well, let's just go solve the problem and good things will happen. It was it was a lot more the ladder. You know, I didn't leave Facebook to start a company. I just left Facebook because I was ready to do something new. And I knew this was a huge movement and I felt that, you know, it was very gnashing and unfinished a software infrastructure. So when the opportunity Cloudera came along, I really jumped on it. And I've been absolutely blown away by the commercial success we've had s o. I didn't I certainly didn't set out with a master plan about how to extract value from this. My master plan has always been to really drive her duped into the background of enterprise infrastructure. I really wanted to be as obvious of a choice as Lennox and you See you, you're We've talked a lot at this conference and others about, you know, do moving from with fringe to the mainstream commercial enterprises. And all those guys are looking at night J. P. Morgan Chase. Today we're building competitive advantage. We're saving money, those guys, to have a master plan to make money. Does that change the dynamic of what you do on a day to day basis, or is that really exciting to you? Is an entrepreneur? Oh, yeah, for sure. It's exciting. And what we're trying to do is facilitate their master plan, right? Like we wanted way. Want to identify the commonalities and everyone's master plan and then commoditize it so they can avoid the undifferentiated heavy lifting that Jeff Bezos points out. You know where you know? No one should be required, Teo to invest tremendous amounts of money in their container anymore, right? They should really be identifying novel data sources, new algorithms to manipulate that data, the smartest people for using that data. And that's where they should be building their competitive advantage on. We really feel that, you know, we know where the market's going on. We're very confident, our product strategy. And I think over the next few years, you know, you guys are gonna be pretty excited about the stuff we're building, because I know that I'm personally very excited. And yet we're very excited about the competition because number one more people building open source software has never made me angry. >> Yeah, so So, you know, that's kind of market place. So, you know, we're talking about data science building and data science teams. So first tell us Gerald feeling today to science about that. What you're doing that, Todd here, around data science on your team and your goals. And what is a data scientist? I mean, this is not, You know, it's a D B A for her. Do you know what you know, sheriff? Sure. So what's going on? >> Yeah, So, you know, to kind of reflect on the genesis of the term. You know, when we were building out the data team at Facebook, we kind of two classes of analysts. We had data analysts who are more traditional business intelligence. You know, building can reports, performing data, retrieval, queries, doing, you know, lightweight analytics. And then we had research scientists who are often phds and things like sociology or economics or psychology. And they were doing much more of the deep dive, longitudinal, complex modeling exercises. And I really wanted to combine those two things I didn't want to have. Those two folks be separate in the same way that we combined engineering and operations on our date infrastructure group. So I literally just took data analyst and research scientists and put them together and called it data scientist s O. So that's kind of the the origin of the title on then how that's translating what we do at Clyde era. So I've recently hired to folks into a a burgeoning data science group Cloudera. So the way we see the market evolving is that you know the infrastructure is going to be commoditized. Yes, mindset >> to really be a data scientists, and you know what is way should be thinking about it. And there's no real manual. Most people aboard that math skills, economic kinds of disciplines you mentioned. What should someone prepared themselves? How did they? How does someone wanna hire data scientist had, I think form? Yeah, kinds of things. >> Well, I tend to, you know, I played a lot of sports growing up, and there's this phrase of being a gym rat, which is someone who's always in the gym just practicing. Whatever support is that they love. And I find that most data scientists or sort of data rats, they're always there, always going out for having any data. So you're there's a genuine curiosity about seeing what's happening and data that you really can't teach. But in terms of the skills that are required, I didn't really find anyone background to be perfect. Eso actually put together a course at University California, Berkeley, and taught it this spring called Introduction to Data Science, and I'm teaching and teaching it again this coming spring, and they're actually gonna put it into the core curriculum. Uh, in the fall of next year for computer science. >> Right, Jack Harmer. Bakar. Thanks so much for that insight. Great epic talk here on the Cube. Another another epic conversations share with the world Live. Congratulations on the funding. Another forty months. It's great validation. Been congratulations for essentially being part of data science and finding that whole movement Facebook. And and now, with Amaar Awadallah and the team that cloud there, you contend a great job. So congratulations present on all the competition keeping you keeping a fast capitalism, right? Right. Thank >> you. But it's >> okay. It's great, isn't it? That with all these great minds working in this industry, they still can't. We're so early in this that they still can't really define what a data scientist is. Well, what does talk about an industry and its infancy? That's what's so exciting. Everyone has a different definition of what it is, and that that what that means is is that it's everyone I think. Data science represents the new everybody. It could be a housewife. It could be a homemaker to on eighth grader. It doesn't matter if you see an insight and you see something that could be solved. Date is out there, and I think that's the future. And Jeff Hamel could talked about spending all this time and technology with undifferentiated heavy lifting. And I'm excited that we are moving beyond that into essentially the human part of Big Data. And it's going to have a huge impact, as we talked about before on the productivity of organizations and potentially productivity of lives. I mean, look at what we've talked about this this afternoon. We've talked about predicting volcanoes. We've talked about, you know, the medical issues. We've talked about pretty much every aspect of life, and I guess that's really the message of this industry now is that the folks who were managing big data are looking too change pretty much every aspect of life. This is the biggest inflexion point in history of technology that I've ever seen in the sense that it truly affects everything and the data that's generated in the data that machine's generate the data that humans generate, data that forest generate things like everything is generating data. So this's a time where we can actually instrument it. So this is why this massive disruption, this area and disruption We should say the uninitiated is a good thing in this business. Well, creation, entrepreneurship, copies of being found it It's got a great opportunity. Well, I appreciate your time, I unfortunately I think that's going to wrap it up for our big date. A deep dive. John and Dave the Cube guys have been great. I really appreciate you showing up here and, you know, just lending your insights and expertise and all that on DH. I want to thank you the audience for joining us. So you should stay tuned for the ongoing conversation on the Cube and to emcee TV to be informed, inspired and hopefully engaged. I'm Richard Schlessinger. Thank you very much for joining us.