 from London, England, extracting the signal from the noise. It's theCUBE, Cover, Discover 2015. Brought to you by Hewlett Packard Enterprise. Now your hosts, John Furrier and Dave Vellante. Okay, welcome back, everyone. We are here live in London, England for HP Enterprise, now called HPE, HPE Discover 2015. This is Silicon Angles theCUBE, our flagship program. Where we go out to the events and extract the signal from the noise. I'm John Furrier, my co-host, Dave Vellante. Our next guest is Jeff V, VP of Marketing and big data platforms at HPE Software. Welcome back to theCUBE, good to see you. Good to see you again. Good to have you all get the update. I'll see you are kind of teasing out in our last CUBE interview, talking about the software focus, the split operating prior to the official date on November 1st. It has happened. Now it's rocking, cloud front and center, clear message, infrastructure products are underneath the hood. You got some DevOps. You got some HPC vertical focus, we just talked with Brent earlier. Big data's in the middle of all the action. Yeah, well, there's the four transformational areas. And you're right, the last time we talked to us a few months ago, this was just a plan. And plans don't always work out. So it's pretty immense that a company fundamentally split its devils in the detail, but we're already feeling it working well. And coming to an event like this, that's as immense as it is, where there's nowhere to hide, you know? Literally there's nowhere to hide here. It's about bringing it together and seeing that it resonates. You know, it's not just about splitting the company in half, that's the action. It's about being able to focus and tune the business so that we can be far more agile and far more focused. And still a big company, you know, there are companies smaller, you know, we're still in the Fortune 1000, Fortune 500, but it feels like such a nimble company compared to the Hewlett Packard classic version, if you will. You know, you predicted that when we talked prior to the split, we were like, you predicted that it was going to be the sharp focus, and it is. Everyone we talked to here has a laser focus on their business. And you can see the kind of, I won't say they won't say M&A, but like organic growth and also they're focused. So, you know, congratulations on predicting that and it feels good here. So anything new to add from the vibe show here with the new marching orders and products? Obviously the transformation areas are there. Well, that's the two levels. And that I think it's important for the audience to look and hold us accountable for delivering on these transformational areas. You know, I would be not the first executive to point out these transformation areas are not necessarily new concepts. The one obviously that my business is most focused on, and I would argue is that the center at is empowering a data-driven organization. Now, I imagine you could go back 10 years, 20 years, even 30 years, do a Google search and find somebody use the term data-driven. That's not a new concept. But what's new is about the kind of data we're talking about, the scale of it, the velocity of it, and who's using it. And that's where we're talking about making sure the technology is actually accelerating it versus getting in the way. You know, we did a poll and we surveyed why people sometimes struggle with getting these data-centric deployments going. It's more than just an app. You know, getting an app up and running can be complicated, it can be non-trivial. But then when you're producing the data, the big question is does anybody care? Does anybody use it? And I think we talked about, you know, back in the summer that the monthly report is dead. Nobody cares. Yeah, real time is where it's at. It's got to be near real time, and that's not the exception. And that's where the focus seems to be going is data-driven means getting your data, be getting it in the hands where it can affect the business in a way that's meaningful. So I got to ask you on the transformation. I want you to explain this for the folks watching. There's four transformation areas, hybrid infrastructure, security, data-driven organization, and workplace productivity. I mean, different names, but generally those are categorically ones. Sir, the data-driven, we had a great talk about, the tooling and making that the one transformation. But your products and HP software cuts across all that. We talked with Sue and security. Boom, business model opportunities for her is data. I talked with wireless guys, Domo, or he's like, hey, it's in the data. It's not the price of the access points. It's what they're enabling. And obviously in workplace productivity, data-driven is also going to be embedded in applications. Talk about the difference in how HP software, and obviously we talked about the conversion infrastructure, synergy team, it's a software platform too. So what's your group do on the software side and explain outside of the transformation area the products that you guys are driving? Well, all the pieces come together and are all essential. So it's a little silly to say one's more important than the other, although I have my bias, but what I think the key thing is, is that data is really a living being, and it's not, you know, we're certainly still in the industry talking about big data, but I'm talking more often about making your data big. Sometimes we have customers that do have pentabytes of data and they need to work through that and find that needle in the haystack. Sometimes they'll take 50, 100, 200 terabytes, relatively, you almost can put that on a thumb drive today, and they take that across as hot data, and then they act on that. And it's not really the size of the data. It's often, is that data meaningful and can you use it? Now what we do is we have two franchises, and we've really repositioned them, and I'd love to share that with the Vertica franchise and then the Idle Enterprise franchise. Vertica is about blazing speed with traditional SQL analytics, database analytics, but we use what's called a column or store. That can be 10, 100, even 1,000 time faster than traditional databases. Now the key thing, and what we've introduced here at the show, is the Vertica Advanced Analytics Family. And this is where we have a claim that right now I can't find another vendor that can compete with, because we have core Vertica capabilities, which is about this high performance engine. But now we offer it in five different ways. We have a community addition, it's free. You can take it, you can run up to a limited amount of data, throw it into production and go and kick the tires with it. And customers love doing it because they don't want to just study they want to do. We have Vertica Enterprise, which is our flagship offering. That has the optimized file structure. That's what Facebook runs on. That's what Twitter runs on. That's what nature banks run on. If you want the optimal performance with all the functionality, we've added things like geospatial analytics so that you can actually bring in location and place into your analytics during your data analysis. You want Vertica Enterprise. But around that, we've added a couple other animals to the zoo. Those include not one, but two flavors of cloud. Not a lot of people know this. We have Vertica on demand. That is a pure SaaS offering. You pay either by the terabyte or the query, it is a SaaS model where it's subscription. You don't worry about the deployment, you load your data, and our guarantee is you can be up and running one hour. But the second one we have is public announcement for support for Amazon Web Services. So you can buy a Vertica license, you can go to Amazon Web Services, go to any of their data centers, and be able to deploy that license in a self-managed server. So you're not in a multi-tenant environment now, you're in that managed server. And then the final one, of course, is Vertica for Seagull for a dupe, where you can hear move, if you will, the analytics to the data, instead of the data to the analytics. And if you have large dupe clusters, run it there. So those five different deployment consumption models means that you can have it any way you want it. Now, some people would say, well, a company that's big, they're going to pick X. Well, I see increasingly big pharmas, they might take the cloud for a rapid pilot prototype, test out a concept, and then deploy on-site, or vice versa. And it's being received really, really well. And none of our competitors, they may offer one or two of those flavors, but we're the Baskin Robbins, the database is offering all these different flavors. And the Vertica On Demand is a hosted offering by you guys, that's a SaaS offering that you provide? Or is that? Yes, it was a Safted offering from us. We have partnerships on where we deploy it. It runs on Amazon Web Services today, and in the future, with our budding relationship with Azure and Microsoft that you announced about, I expect you can look for in the future where we'll offer that deployment option as well. So, okay, so there's a SaaS that runs on Amazon, then as well you can configure it in the marketplace on your own. Right, with the Amazon machine image. The distinction is, first one, you pay like you pay for electricity. Yeah, by the drink. The second one, you actually buy the license, and I have a great example for you. We had a company that had our traditional deployment. They bought a license, they deployed, they were happy, they made a change in their business model and said, we want to move our data center to the cloud. And that could have been incredibly disruptive. With this AMI model, the license they had, they simply took that license straight to the public cloud. They have to pass one penny. We provided the bits to be able to deploy it and all their queries ran because all of these run on core verticals. So it allowed a seamless movement that admittedly they weren't planning for. And you know what? You get extra credit today for that. I think it's going to be table stakes in the future to be able to have a multi-mode way to be able to run that. So seamless migration to where you want to run the workload, basically is what you're saying. Yeah, it's the ability to start and stop and expand where you go. And that is really what I think the next generation of analysts about. So our group, the Big Data Platform Group, is with Vertica as one offering described and then Idle Enterprise and with some exciting news around that. That's focused on unstructured. That is text, that is audio, that is video, that is text in video, that is audio in video. So you really mix it up here. And that is the ability to extract true insight from instruction information. Now, many competitors can do some primary things. They can do keyword searches. But the trick with instruction information is to look at the payload. You got to open the hood. You have to look at not the name of your PowerPoint file but what's actually discussed within it. And that is what the Idle Technology is flawless to do. If you look at Gardner Forest Reports we're the leader in enterprise search. And as part of the announcement we did today, we've taken that franchise in addition to Idle Enterprise that runs on premise to Haven on Demand. And today we've announced four purchase on the CPL, Haven on Demand API Library and Haven on Demand Search as a Service. The APIs are 70 APIs, more than a few competitors that are going around talking about certain things to begin with W. We have about three X the number of APIs that they have that go from simple to sophisticated. It could be format conversion up to face detection. Very easy to use and if the audience goes to Haven on Demand.com they can check it out. They can go run their data against it. There's samples there and you'll see exactly the code sample that comes back. And so important point there is this is analytics for the developer. This is to do an analytic app. A lot of people hear analytics and there is certainly a school of analytics that it's the data scientist running the analytic but increasingly it's going to be about developing services and applications that use the analytics in them. Companies like Uber that run a service, that's an analytic. It's getting you a car but analytics are what's doing that. That's the smartness that comes into it. And to be able to consume and bring that in to mobile apps and enterprise apps. That's the idea economy. I mean basically that's the meat on the bone of the idea economy. Well it's about consuming data within that service and so the APIs are one thing they were offering and then the other is a search as a service which is a curated search offering that lets people use Google and Bing all the time and it's great results, right? The results on page one give me the sports car. I can see how Manchester United did. If I'm here I can see not the 49ers not doing so well so we'll go with the Pats. You can see how your bare football team's doing. But Google and public search capabilities fall on their face often when it's enterprise search because the payloads that you look in are not public websites where you're running a popularity contest of did a million people before want to go there. Now you want to be able to look inside that PowerPoint file, inside that video, inside that email and you want to look at what's being discussed. You need a different technology, different approach and that's what Search as a Service does. Well if you use Google now and you type in like a search query for your flight reservations it's actually reading your email and it puts it right at the top of the search result. Oh your flight's whatever. We did that's kind of freaky but it's interesting. This is a new tooling. It's part of it but that's very very basic. The ability to identify key terms and go oh that's an address maybe we'll link to that. So what you're seeing now that we're able to do is look far deeper at the patterns that are being discussed and make those pattern connections across it. So there is some overlap where we're talking about a whole magnitude of intelligence that goes beyond picking out dates and phone numbers and address. So I want to connect the dots with something you said earlier. You said it's not just about the big data and the size of the data, it's about the velocity. It's also about you said who is using it and historically the whole data business has been about insights for the few. Decision support, you know. Analysts. And even the early day of right but you know 10 you know analysts right with all the power and even in the early days of the big data it's still today. It's the data scientists. So when you talk about the search paradigm and you talk about putting data in the hands of many or I talk about putting in data in the hands of many is that what you're talking about? I mean how do you go from where we are today? Few people have all the power. Is it the search piece that helps? Is it the combination of technologies? How are you operationalizing analytics? Well as simple as it sounds finding the data is kind of job number one because if you can identify and find the data that's relevant that you're looking for it's kind of a game stopper. But remember often we're moving from reporting to ad hoc discovery. And what I mean by that is you start to go within your data and you let the data start to tell you the insight and from that you're going to ask a second and a third question. That's why we call it data discovery. It may sound basic but most systems are not set up that way. They'll kick back some analytics, you'll look at them, you'll go well now I have three more reasons why that anomaly occurred. But that's where it's sorry, no moss. There's no more we can give you. The next generation of systems, the ones that we power allow you to do that double and that triple click. And the key thing and you brought this up is it's not going and creating a report that'll take another 30 days to run. Those days are over. That is your first line, line of business. It could be data scientists but also it could be just your line managers that want to be able to look at that information. And that is the changing that's occurring now is taking that data and the tools. And I'll repeat that. And the tools that can be consumed and used by the edge, by the business people that are making the decisions. So that you can actually close that cycle and do something about it. And that's the breakthrough we're pushing and that's a sea change. Does that mean the data center and the data it has and it's data lakes or not valid or useful? Not at all. On the contrary, you want those edge groups where maybe they've been practicing shadow IT to be able to leverage that. So it's actually bringing together we're seeing businesses from it. Here's the other thing, traditional data you had to know the question. Here's my five questions. Please answer them for me. And now it's about enabling discovery where you don't know what the next question is going to be. You just want to enable it to be asked. And that's a different mindset. And that's what we're seeing being demanded is that organizations don't want to hear about six month deployments, six week deployments and sometimes even shorter. They want to be able to have that data come in and really at the speed of business have the people that can act on it utilize it. And they'll find a way if traditional data IT doesn't. But that's where we're seeing the interest and the growth in the business. Talk about the performance of the team now. HP software, Haven, Haven platform, open source, all the things you mentioned. How's the business going? What's the top things you're working on? Can you share some insight into activity in the business? Well, of course we don't break out the financials and we just announced our earnings. But Meg did call out some of the very, very strong growth, especially around the Vertica franchise. 50% license growth year on year, right? So 50% growth year after year I'll take. And if that is a barometer of the business, it gives you a sense that if you can have the right tools that really make a difference, they will be adopted. Now the color I'm going to give around it is probably if I was talking to you two years ago, we talked a lot about data modernization and that's still occurring. There's a lot of legacy, it's rigid, it's expensive and it needs to move to the new world, right? And we're going to be Christopher Columbus and help them make that journey. But I'll tell you what we're seeing a lot of the energy really starting to come from are the new use cases. They can be in traditional companies or in new companies, but these are companies that, or use cases rather, where they're trying to do fundamentally new things with their data. Not so much, I want to run that monthly report and now I just want to run a cheaper, faster. This is model related stuff, right? That seems to be a pattern we're seeing on theCUBE here is that there's some sort of driver for growth. Yeah, there's some operational efficiencies with data, I see data center and getting the tooling, testing, understanding, success, value. But a lot of the pattern is business value. Well, it's incremental is not enough, saving 20% on my cost. It's not bad, people will take it. But what they're looking for is how can I have something that's going to have a material impact to the business? Because the realization there is it is this idea economy and if I don't do it, my competitor is and now it's not data after the fact. It's data driving the business. And so it's really changing the order of how data is consumed and used and that's pushing the adoption that we're seeing. One of the things we've noticed in the big data space is that a large proportion of the dollars being spent are being spent on services because it's so damn complex. Talk about that dynamic, is that changing? Are we able to sort of package these capabilities, this tooling into software that can scale better and actually be deployed more simply? Well, the example I gave with Vertica on demand where you can have a in the cloud, on demand data warehouse with the capabilities of Vertica and I can look you in the eye and say in one hour you can be up and running. That kind of shows you that those options are there. Now, what I'll connect to though is that other transformational area which is it is a hybrid world. The stats we're seeing is that even with all the hype we're talking 70, 80% and north of that are still going to be running traditional data centers. There's a couple of reasons why. For some companies it's about control the data security of it, but for others it's simple as the legacy. It's that's where the data is. They don't have to clean sheet of paper, they have to deal with it. Yeah, I mean, now you will have startups that today will start in the cloud, end in the cloud and may never have a server sit on premise, that is certainly viable. But also they're the shining star because they use data in a way that's elegant and relevant because they have a clean start. They have the cloud native and then they go use the data, they're data full, they're data rich in their deployments. It's not some fenced out park in the data warehouse. That's what Vertica is a great tool is performance, but like the new models, data's center of the action. Well, I think you're right. And at the same time what we're seeing is a little bit of a maturization. Your customers that say Hadoop is great and we endorse it and we're building around it. We've announced support for Spark, Kafka and some of the new innovations that roll out. But you're also seeing people say, I'm going to use it in this use case, not in this one. I think you're seeing the same thing also on cloud that it's a balancing. There are trade-offs between it and the company that I think is really going to win is one that offers you that choice without compromise. That doesn't have an agenda to drive just one flavor of computing. HPE and formerly HP has always kind of stood for that. That we're going to give you those kind of capabilities. And I'll tell you right now, that's the formula that's resonating with our customers. Customers usually don't like to be told they're stupid. And their investments that they made and made for good reason, they want to be able to preserve and take forward for very good reason. And that is where our conversation starts versus a kind of forklift and you have to do it this completely different way. And that is what I think is going to happen over the next, I'd say five years, this focus around hybrid computing and how do I do that well versus a tension focus of I'm right cloud, I'm right premise, you're kind of both right. It's a hybrid world, that G's out of the bottle. Final question I got to ask you, I asked this last time and it was a long bumper sticker. So I got to ask you the bumper sticker for this show, nice and tight. What's the bumper sticker for HPE this year? I would say focus and energy. I have never seen a more positive focused event. I've never seen an event where you truly see not just Hewlett Packard offering a broad set of capabilities but where it feels like the pieces, the machine is connected together. If you walk around here, even how this venue is organized, it's all organized by those four transformational areas. There is no hardware zone, there is no software zone. It's just about bringing solutions to address these things. And I like to say when you look at the marketing positioning and the go to market of a company, you should never be able to figure out their org chart. If you can, you can figure out, oh, that's this division because all their products use this color. HPE Discover used to be like that. You could literally see the org chart on the floor. It was quite different, not here. Now that we've moved past it, I can say, I don't think that's healthy. I think when you can look at a company and not be able to figure out the org chart because it looks like it's connected together, you got to do other things. But I think it's a decent litmus test. And right now it feels like a connected company versus maybe a more disparate one. Great point. And also the other thing I was saying is a lot of companies do cool, but they don't do relevant. And I see a lot of cool and relevant. You're not over hyping the Docker card. They're over here. You're seeing DevOps. So the cool stuff's here, but it's relevant. You know what I'm saying? So having a cool and relevant and practical is a very good benchmark. And if I can throw in real, okay? You walk around the show floor, the stuff is real. You can buy it. You can use it. Customers are deploying it already. We are talking in a, yeah, it's visionary, but it's grounded. And that's what HP does well. And I think that's what people appreciate. Jeff, thanks for sharing the big data perspective and sharing the data and insights with us here on theCUBE. Appreciate it. Always insights here from Jeff because that's the outcome we're looking for here. And again, cool and relevant. Data's at the center of the value proposition. Very integrated show. Congratulations. You called it in advance. Thanks for the telegraph on that one. HP's got a good spring in this. They're very focused, a lot of energy. This is theCUBE. Trying to bring the energy day too. We have three days of wall-to-wall coverage. Thanks for watching. We'll be right back with more after this short break.