 Live from Las Vegas, it's theCUBE. Covering Discover 2016 Las Vegas. Brought to you by Hewlett Packard Enterprise. Now, here are your hosts, John Furrier and Dave Vellante. Hello everyone, welcome back live here in Las Vegas for HP Discover 2016. This is SiliconANGLE Media's flagship program theCUBE 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 Chris Sellon, who's the vice president of business development of the Big Data Platform at HPE. Chris, welcome back to theCUBE, great to see you. Good to see you, Chris. It's great to be here as always, both of you guys. So finally, Big Data is now sprinkled throughout all the products. We've got IoT tomorrow, we're expecting some big things. Today's announcement, you can see the data side of it. Really kind of filtering in. As we pointed out at your first event a couple years ago, that this was going to be a big part of it. And the vertical's certainly at the center stage, haven, all those coming together. What's the update? Give us a quick highlight of what's new with Big Data, what's going on in the business. Yeah, absolutely. I mean, if you walk around this event, or if you go to hpe.com, you can see the data-driven organization. So it's really big data, data-driven organization, our big data platform, our group, our products, and we're getting embedded in everything, in everything we're doing as a company. And we're becoming more of a solution-centric provider. I mean, that's what the new HPE is really all about. So we're expected to hear from some of the security folks this week on theCUBE. Obviously, that's a big data application. Everything's big data, certainly, how do you guys make that happen internally? Just share some color on how the products get rendered, how you guys are charging for the products, business model, et cetera. Yeah, well, you know, our group, we define ourselves as a platform group, we are a platform, and there are customers out there who are platform customers, who are looking for a big data platform to go solve problems. But then there are solutions as well, and we're rolling out more and more solutions, whether it's security solutions, you talked about IT management, network management solutions, or areas like internet of things, of course, right, more business-oriented solutions that are powered by and enabled by our big data platform. That's really, you know, it's embedding the platform in the solutions. So I just met with Rob Beard and haven't published the interview yet. CEO Hortonworks, I know you're partnering with them. Yes, we are. They're building a platform as well. It's a platform war out there. But the question I have for you out there is, big data was synonymous with Hadoop. And now Hadoop is more of a broader- Or say was, was that? Yeah. I don't know, I didn't hear you, so. It was. Okay. Hadoop was the thing that got everyone's attention. But now as the data warehouse business intelligence markets lifted and shifted over into Hadoop slash unstructured data, just call it unstructured data, there's been a real kind of integration between the old world of structured data, certainly Vertica from the column of store had extreme performance, but now it's just not Hadoop anymore. There's a lot of other things, Spark Summit's happening, we're live up there in San Francisco with the R-Cube team. What's changed? I mean, I just watched Bloomberg this morning with Diane Bryant, with CEO from Cloudera. Also Intel put $720 million into Cloudera. Yes. Is the ecosystem shattering? Is it coming together? What's your take? It's just bigger than Hadoop, certainly. We can validate that open source Hadoop is only one club in the bag, if you will. Yeah, no, exactly. I think it absolutely is coming together because what you're seeing in most organizations of size, what we like to call enterprises, right? The E and HPE is both. There's experimentation and deployment and you're starting to see some enterprise utilization of next generation technology, open source Apache projects, those types of things where it's Hadoop or Spark or Kafka is actually one. I would say of all the Apache projects of the customers we work with, Kafka has been adopted very, very rapidly. We're doing a lot of work with both kind of the open source community also with providers like Confluent and around using Kafka as an inject mechanism or an ingest technology for our platform. There's a lot of work going on around streaming right now. There's various technologies from Spark screaming to some of the other Apache projects. There's a lot of cool stuff and obviously there's, you know, none of this technology's new. When I made that reference to was before, I mean people used to talk about enterprise data warehouses, big data and then there was a lot of excitement around Hadoop and open source and now what you're seeing is those worlds are coming together. Because you're seeing, again, it's a shift to solutions. Companies aren't as interested in just technology anymore but what can I apply it to and what problems can I apply? Well, exactly, the narrative is changing. The narrative is changing. The technology's still there. It's evolving, the ecosystem's exploding maybe faster than it ever has but talk about some of the things that customers are asking in terms of business outcomes. I mean, we've done the Vertica, now the HPE big data event in the last several years. Your customers were early adopters of big data. What are they pushing you for now? Well, one of the things we're hearing a lot about and you're going to see it in some of the announcements that have been made and will be made around here. You hear about IoT, you hear about edge computing. It's moving analytics and moving analysis out more toward the edge of the network toward where the action is. Now that doesn't necessarily mean that central analytics go away but whether I'm running a transportation network or a telecom network or a retail chain knowing what's kind of going on out at the edge and also knowing how to then take that centrally and manage it and distribute. The sort of distributed analytics thing is becoming a big deal. So when you talk about streaming, you talk about data in motion, you talk about data at the edge but then at the same time, bringing it back to a big data analytics platform where it can analyze all of it is becoming sort of what the conversation is about. So you're expanding your sort of matrix, if you will, for data collection and data analysis and you're actually putting Haven out at the edge to enable that. Exactly, exactly. At the edge, in the center, wherever it's needed and the use cases are different because the definition of edge, edges can get very, very granular. I mean, some of the stuff, the conservation or international announcements we've made and we've been working with them ongoing for quite a few years now. The edge is a camera in the rainforest. You can't get much more edge than that. You're going to do a whole lot of analytics on the camera in the rainforest but then being able to take those images and analyze those and there's analogies to that at the same time being able to put something like we're announcing the edge line 4000, for instance, which is basically sort of a cluster in a box that actually will run Vertica, being able to put that out on an edge. Now, you're not going to put that in a rainforest but you might put that in a factory or you might put it in a transportation hub or someplace like that. So there's a lot of work going on around to kind of where the analytics belong, moving the analytics to the place where it's needed but the short answer is it's both. The edge analytics doesn't replace the central analytics. It's supplemental. So it's fast data, big data, data in motion, a lot of attention, a lot of need for streaming and a lot of customers. So that's really what we're seeing but it's all wrapped in how do I sell business problems? Chris, talk about the impact of real time in the moment now because analytics has always been, you can look at the past and you can predict the future and be prescriptive but the now is the big thing. You mentioned streaming. So talk about the impact of the in the moment analytics and specifically the data layer, how sharing the data across multiple silos is important. Those two areas. Let me give you an example. One of our customers who I think you guys know but I'll let them sort of tell the story themselves. I don't miss quote, but in essence what they're doing is they have logins set up around the world. So they have worldwide customer base. They're in financial services. If Dave Vellante logs in in Moscow and Rio de Janeiro five minutes apart, they know one of those is fraudulent. So on the one hand, they want to do a great job providing service out to all these nodes around the world at the same time. They want to be able to sort of pull that back and say, wait a minute, that doesn't look right. So, and you know, you want to be able to do that right there because obviously in a case, fraud's a great example as I said, because you really want to sort of solve the problem as soon as you see it or even you'd love to predict it, even be able to solve it before you see it. That's not always possible. But you know, we're seeing a lot of modeling. We're seeing a lot of analytics at the edge at the same time. It all comes back to central core because looking at that way, you might not know in that note over there and this note over here that something bad is going on. But if you put them together, then yeah, you can see, okay, that doesn't look right. So, Dave Vellante has a community called CXOs and it's on CXO, crowdchat.net slash CXO chat. He's got an open thread around some of the top customers. And you guys have huge customer base. So the question that he asked, I want to ask you is, have you run into the premise of customers asking themselves, how do I value the data? Is it a balance sheet kind of conversation? I mean, ultimately it's not yet. But I mean, we're starting to see, you know, CFO knows all the numbers. Yes. I know where all the assets are. Are you starting to have those kind of conversations where when you start talking about these critical things like fraud detection and also security attacks with the perimeter now dead, how do people value the data? Yeah. Well, data is becoming the asset, right? It's like one of the world's biggest taxi companies. You know, Uber doesn't own any cars, right? One of the world's fastest growing retailers, Etsy doesn't own any inventory, right? I mean, we talk about these sort of things all the time. So what's the company worth? What's the organization worth? It's the value of the data that they have around what's going on in their operation, what their customers are doing, and of course how they deliver service ongoing. So absolutely. Not to get too academic, but that data doesn't have asset specificity, like an oil drill, you know? You can use data in so many different places. Does the vagueness around valuing data, does that create a business problem for customers? In other words, for instance, maybe it means they don't secure their assets well enough or they don't protect their assets or they don't exploit them. What are you seeing in that context? I think, sure, from one of those providers I have to recognize that this is the core of my business, right? For customers, it's great. That's where I thought you were going with that question. But yeah, I mean, it's a core part of the value of the business, right? And there's so much going on, right? I mean, there's been so much talk around unicorn valuations and everything right now, right? It's an issue for the finance guys. How do I figure out what all of this is worth? Because it really is a new world right now. But the bottom line is data's the core of it, and your customers, your loyal customers who continue doing business with you, and they continue doing business with you because you're managing their data in a safe, secure, accessible, very customer-friendly way. That's really, that's what business is about these days. So. I want to ask you, okay. Yeah, okay. So it's certainly a change, but yeah. I want to ask you about Meg Whitman's transformation areas. I'm certain we're going to hear from Erkino this morning around an update on the transformation. Obviously, spinning out the ES Enterprise Services. But big data's at the heart of this new, transform, accelerate, grow, whatever the other one is. What's the other one this year? Transform. Security, workplace productivity, hybrid data center, hybrid cloud, and of course, big data. So what's some of the conversations that you guys are having internally around? How the role of big data is transforming HP and give some examples of some customer things that are cool and relevant that you could highlight at that point to that. Okay, well, you know, again, we talked about there's four core transformation areas that we just discussed. And, you know, big data is kind of its own, but it's embedded in the other three as well. One of the, actually, where I'm going right after I talk to you guys, I'm going to see Sue Barsamian's keynote. We're going to be talking about security analytics. And security analytics is massively important to this company. And we're doing so much work, as I said, in the beginning of our conversation to embed our platform, our big data platform in our solutions, including our security solutions. So we're working heavily with those guys and, you know, the security team and with our customers as well to really help them understand, you know, what's going on and, you know, what needs to be locked down, how to lock it down, what needs to be secured, you know, what needs to be opened. So, well, I mean, that's a huge opportunity for you guys. It's a massive opportunity. Security operations teams are just inundated with data. Exactly. They can't respond. And so understanding where to prioritize even, something as simple as that is really a challenge. You need to respond quickly. And ideally, you need to be able to also model and, you know, respond before it even happens. So that's what you'd like to do, to be able to predict. I mean, analytics is one of those, the two vectors, right? The other one is, you know, new security models like blockchain, okay, fine. But being able to use, apply analytics to respond to security incidents is the shift, isn't it? And we are building prediction into the products and machine learning capabilities into Vertica. You know, Jeff Fees, I know he's going to be talking tomorrow about Haven on Demand. Robert's going to be talking about that a little bit as well. So Robert Young-John's, during part of the keynote, I think today. Sue Jeff Robert, all coming on theCUBE. So we'll be unpacking. Yeah, I know. You'll be hearing a lot more from those two as well about, you know, machine learning, AI, prediction, modeling. So, and we're really building all of those capabilities into the platform because it's not just, you know, storing data and managing data and scaring data, which is usually important, but it's being able to do something with it, it's being able to apply it to problems. Do you find, Chris, that customers are, they have limited budget. How are they balancing the need to sort of spend on improving their machine learning algorithms versus expanding, we were talking about before, the IoT, the data footprint, ingesting more data, more API sources, more data sources. How are they balancing those challenges? Well, there's of course, you know, there's always what you have to spend and then what you'd like to spend and usually have to take a higher priority. And so things like security and compliance tend to rise to the top because they've got to get done. And you know, you can't have any issues there. So that has to happen, but there's more and more, you know, streamlining the operation, making customers more satisfied, making customers more loyal. I mean, if you talk about, as we just were, the entire value of the business being based on, you know, the growth of the data, which is driven by the growth of the customer base and the growth of the transactions, you know, being able to make sure we do all that. So there's not really as much of a line between what I have to do and what I want to do anymore. I mean, it's really about competitiveness. So it varies. I mean, it's hard to give a general answer to that because it varies by industry, it varies by the competitive environment our customers find themselves in. By being a platform business as well, we're in so many different verticals that we see. I guess what triggered that question was, can I rely on HP to do some of my machine learning heavy lifting and apply my other resources elsewhere? That's really- That's where so much of our core engineering is being applied right now. At the same time, you know, we're partnering. I mean, we're partnering with Microsoft, we're partnering with, you know, some of the other providers, we're partnering with Amazon who, you know, so we're both developing our own core technologies, rolling it out into our solutions, embedding in other solutions, and also partnering. Because it's really about doing the right thing for the customer. Final question to wrap here, developers, what's the update on the ecosystem? I'll see if you're a platform, you want to be an enabling platform. Yeah, I think we talked about this big data conference. We rolled out a startup program last year that's continued to grow the Haven startup, the Haven startup accelerator program, that's the right name of it. That's grown for us, our big data marketplace. We actually relaunched when we launched HP back in November when HP became HP. We re-platformed and relaunched the marketplace. That's continued to grow for us. So yeah, it's really about building, you know, we're certainly serving the enterprise. I mean, like I said, that's the E and HPE, but reaching out to the developer community as well. A lot of what I think you're going to hear from Robert today, I actually haven't seen what he's saying, but Jeff's told me about it. He's going to talk to that as well. It's really about getting to those grassroots developers and supporting them. So, and that's so much of what people have gotten excited around the open source technologies, but we're really doing a lot of work there. We were connecting those dots last time we chatted and certainly last year, your HP Vertica, now HP Big Data Conference in Boston, which is coming up as well. Chris Sellen on theCUBE here, breaking down the Big Data. Vice President of the Big Data Platform. I'm John Furrier with Dave Vellante. We'll be right back with more live coverage for HPE, HPE Enterprise, the E and HPE is Enterprise. This is theCUBE. We'll be right back after this short break.