 From San Jose in the heart of Silicon Valley, it's theCUBE, covering Big Data SV 2016. Now your host, John Furrier and Peter Burris. Hello everyone, welcome to our special edition of Big Data SV hashtag, Big Data SV. We are live in San Jose for Big Data Week, which includes Strata, Hadoop, right across the street, and of course SiliconANGLE Media, Wikibon, theCUBE, here live for our, I think we've been here for all the Hadoop worlds, and I'm with my host, Jeff Frick and Peter Burris, and also pleased to announce Peter, is now head of research for SiliconANGLE Media. Congratulations, blog post went out, great to see you. Great, thanks very much, so honored to be here. The exciting thing for me is, is that SiliconANGLE Media started in Cloudera, Jeff, you know the story, when they had like 17 employees, you know, Hadoop wasn't even on the radar screen, and you know, we went to the, what I would call the first Hadoop world, really kind of was one before that, that was kind of more of a meetup, but this was the first commercial Hadoop world, and we've been here ever since, and I think the community that we know and love, we've got to know a lot of people, and the relationships here, but more importantly, we've seen it grow, we've seen it kind of, not slow down, but almost the winds were shifting, but now we're seeing huge uptake in big data. What's your thoughts? I mean, you've been here watching from the front row as well. Yeah, absolutely, you know, Omar Awadallah tweeted out earlier today with a picture of the 2009 registration desk, and there was Mike Olson behind the desk taking the registration, so it's really, it's grown a long way. I think one of the interesting things is in San Francisco this week is also Microsoft Build really focused on the cloud, and it's interesting how the cloud and the power behind the cloud combined with big data has really been an enabler for both of the technologies to accelerate, and we're really seeing that more and more, the integration of the two gets a one plus one makes three effect. And the exciting thing also, and what's going on is the absolute intersection between the big data industry, which started out as a dupe, and then also expanded to the legacy, transforming itself into figuring out where it fits in the new world, but the growth of the cloud, you mentioned the build at Azure, and you see IBM, and Amazon, and Google, and even Facebook to some extent, you see with the Oculus Rift, all this is kind of coming together. Peter, one of the things that you've been covering and you've been passionate about is that these are digital data assets, and the confluence of all these things coming together really is the big tipping point, at least from our view and your view, as you pointed out, I know you have a different perspective, I want to get your take on that because you now have, it's not a pure siloed industry anymore, it's not like, oh, the big data market, there's a market, sure, but it's also enabling, and the technology's maturing, you're seeing the operational, straight and narrow for companies that are saying, okay, I see a path. What's your thoughts, is this the confluence of big data meets digital business, meets the digital assets? That's a great point, John. I think what we're looking at generally is a couple of things. The first thing to note is that there's a lot of investment in big data today, and we're getting that investment precisely because the experience of the past with things like data warehousing, for example, is starting to come to the fore, so we're looking for ways to fix past problems with some of the new technologies and the investment is significant. As we do that, we're discovering that we can apply big data technologies to the challenges of engaging customers digitally, and that's probably where a lot of the focal point is right now. We have a pretty good idea of how to utilize big data technologies to improve operations through better benchmarking of what we do and how we use those operational assets. Now we're trying to figure out how to solve the problems of demand, the problems that are fundamental about what to build, how much to build, when to build it. To do that, we're gonna have to be much better at, again, applying the lessons learned from past experiences with these very, very complex systems to discover and predict how technology can be applied, but also how the business should behave and find ways to operationalize that expertise. So I think the three themes we're looking for here are, number one, a lot of investment in new technology that is maturing rapidly, number two, how it applies specifically to the challenges of creating digital business opportunities, and number three, ensuring that IT and professionals start to operationalize those capabilities so that they do become a core piece of business. One of the things that's coming up on our crowd chat, by the way, you can join our community conversation live at crowdchat.net slash Strata Hadoop, which is also the hashtag for the Strata conference as well as big data SVR event that we're having in conjunction with Strata. Peter, I wanna get your thoughts on getting some chats from Meddew who's on our crowd chat in our Cube community, among others, use cases are big. People are looking for the playbook in how to get the job done. And it's different by company. I mean, the beauty's in the eye that beholder as the expression goes. So what's your thoughts on use cases? And you got all kinds of different technologies out there. You got Cassandra, you got Spark, you got a variety of different Hadoop commercial databases. What is the big deal about use cases and how should companies look at use cases? It used to be, oh yeah, this is how you implement it in this reference architecture. What's the challenge around use cases and what should people look to? Well, a use case provides a number of crucial elements as we think about adopting new technology. So for example, a use case is a way of driving consensus overall about what is it that we need to do? So by looking at how others have done it, we can learn something specifically about how we might want to do it. So it's a crucial element overall of just conceiving what problem we're trying to solve. Once we conceive of how to solve that problem with things like use cases, then we can look at the process that we follow. Certainly, big data is, as you use the word, confidence, it is a confidence of things in the market but also things within the business itself. There's a lot of different moving parts in different functions and different sources of expertise and the use case can provide clues as to how to bring that together so that everybody can act as one in a coherent, managed way. And then the final thing that I think use cases provide, which are crucially important and I think are often not fully appreciated, is that the use case should point to ways of developing metrics that can help us understand whether or not we are succeeding and what new types of investment or how we course correct as we run through the process. Not entirely or not limited to ROI, although that's a crucial element of it, but ultimately provide a way of conceiving how we measure progress so that we can do that course correction, bring more people into the process to ensure that whatever we build in fact solves the problem, the business problem that we're trying to solve. I want to get your thoughts on some of the big mega trends in the market. I mean, we hear our words last night, I was talking to some folks prior to coming on, you hear words like completeness, are we complete? What's that look like? Integration, the innovation of big data and how we integrate that into production, hybrid cloud, these are kind of the areas that people kind of, you know, topics they're dancing around. So, you know, you and I were talking about some of the things you're focused on this week, Peter, on, you know, where the tech is, how complete is it, is it maturing, slowing down, growing, the digital transformation is the buzzword where we are at with that. And ultimately, how do you put this stuff in to make money? I mean, customers, customers want to make money. Yeah, and so let's start with this notion of digital transformation because that is an overarching theme for virtually everything. The whole concept of digital transformation is how do I let data do the work of the business that previously might have been done by people? And that's probably the simplest way of thinking about it. And the little saying that we have, John, is it ain't digital if it ain't data. And so that's probably the first thing, is identifying how best to incorporate data from various different sources and translate it into software and analytics and other resources like IoT is a big part of this as well so that we can build out the software that's necessary to run the business. I think the second thing to note here, and we talk about completeness, I don't think there's any question that we are nowhere near complete in terms of what the toolkit looks like or the expertise. We're talking about very, very complex problems that business is trying to apply big data to. And we're gonna learn a lot about those problems as we go through the process of solving them. And that those learnings will be then diffused into the community, the community that we're serving here about how to build new tools, how to evolve new tools, how to apply the new tools, where to get the expertise. We're gonna see an enormous amount of change, perhaps some of the most profound change we've ever seen in the industry over the next five years as we try to understand how those tools and the problems come together. So we can expect a real roller coaster ride in the big data marketplace and how it's applied to business for an extended period of time. You mentioned community Jeff, I wanna get your thoughts because we're proud to be here again for the next consecutive year of Hadoop worlds, try to do whatever it's called now, but ultimately it's the Hadoop Community Not Big Data. The Cube has a great community and we're thankful for the folks watching and part of our community. But Peter mentioned community, let's talk about the community from your perspective from the Cube and the events we go to and how that translates into this new digital transformation because we're seeing a lot of stuff going on at the Cube across all the different events that people involve, the sharing, what's your thoughts? Well, you know, we've seen it live and in person last year, you know, it was Docker, right? And our community was all suddenly at the Marquis at DockerCon, which wasn't the first DockerCon, but it was kind of the breakthrough DockerCon and we're looking back to going back to DockerCon this year in Seattle. We've seen our community grow up around OpenStack in a cloud, not to mention the fact we're at AWS re-invent. We're at VMworld and kind of the cloud shows and on the big data side specifically, you know, we did kind of a run by of Spark Summit 2015 in San Francisco last year, but this year we were out at Spark Summit East and really a lot of people are moving talking about the transition from data at rest to data in motion, it's all about streaming. A lot of our same community people now are integrating and adapting Spark as part of their big data plan and will again this year be at Spark Summit West on the newer version. So what's exciting to me is the big data-ness of it is kind of, feels like it's kind of going under the covers really. It's really kind of a platform or an enabler to now a whole new set of technologies over the top. And then as Peter said, what I think is really exciting is the application. I mean, to me watching this whole autonomous car thing happen so quickly, I mean it feels like we're just spinning into reality on that and all of that entails, especially you combine that what's going on with Apple and the FBI. I don't know if you read this morning that the FBI pulled the case back and said don't worry we already got the data. So how they get the data, did they crack the phone? Did they just go get it off a server somewhere? You know, we're living in really exciting times John and it's fun to be right at the Vanguard, right at the pointy part of the spear and then there's the whole, you know, Oculus Rift and not only virtual reality but most people are more excited about augmented reality and machine learning and how's that going to help us? As Peter said, use data to make more of the decisions so that people can concentrate on the bigger decisions and then, you know, the Google getting rid of the Boston Dynamics Robot Company. I mean, those are great videos of those guys knocking those robots around but you know, I think we are really starting to get the infrastructure, the big data and the cloud and the horsepower to see some really transformative things just around the corner. Peter, what's your thoughts? Because you know, we talk about the community certainly with theCUBE and Jeff mentioned some of these trends they're all intersected and you're seeing the role of the community obviously, you know, we're very community based that's what we do but it really talks about this new kind of interaction this new kind of engagement data, a hot topic certainly and there's a lot of stuff under the hood you hear about machine learning, AI these are cutting-edge trends and Oculus Rift this is kind of like the sexy front end application of what is really under the hood but it's a new kind of data source this engagement data that really lends itself well to these cognitive or learning oriented technologies so what's your thoughts on the role of the community? It's not just, you know, a master data, you know core system of record anymore there's a whole new set of engagement what's your thoughts? Yeah, well I think that Jeff raised this notion of the autonomous car. The thinking and the understanding of how that might work has been in place for a long time what's new is the technology can actually make it happen and so through technologies like Big Data and some of the other things that Jeff mentioned the community is now capable of starting to experiment and apply that and find and then learn and refine what they've learned to actually make some of these, you know George Jetson like stuff real and that's what's happening right now it's just the community is at this interesting point where we are finding ways of using new technology testing it, experimenting with it learning about it and then diffusing that back out to the rest of the community and using that as a basis for further advancing what we do with the technology and how we apply it. One of the key things to note here and it's a fundamental feature of what we believe within SiliconANGLE Media and Wikibon and that is that there's this interesting relationship between context which is the things that people do together and community which defines the community that's through context that communities get created because people choose to do things together and then the capabilities and what we're seeing is the community be even clear on what it's trying to do together creating those new capabilities that are further driving the things we can do together. As you say we're running low on time and as always at these events we have a special evening presentation on Wednesday so Peter I wonder if you could give people a preview of what we're gonna be covering Wednesday night not our regular CUBE program but our evening Wednesday program. Yeah, absolutely Jeff. So basically what we're talking about on Wednesday is this role or this relationship between big data and digital business and we're gonna cover a couple of things and we've kind of talked about it a little bit. The first thing is we're gonna make the observation of how the tool set is that is in place complete or not is actually garnering an enormous amount of investment. There's a lot of new tools, there's a lot of people utilizing those tools, a lot of new experiences getting created and that's crucial to drive the state of the art forward. The second thing we're gonna talk about is how big data and digital business are inextricably bound. The whole notion of digital business is we wanna use data to drive new behaviors, drive new sources of value, capture value differently, adjust the business model. So we're gonna talk about that. And the last one is all of this is great but this is, you guys have been at these events for three or four years now and in the past a lot of them have been for seven. So a lot of these have been, there's been a lot of kumbaya in the big data marketplace. I think we're gonna see different about this one is the degree to which people start focusing on bringing operational disciplines in ways that don't undermine the fundamental creativity and we're gonna talk about that as well. We'll have an analyst panel there and we're gonna have some great customers to talk about the experiences that they are having as they try to operationalize big data capabilities to drive new types of business behaviors. And I think that's the key to what we do in theCUBE. We love to extract the signal from the noise and I think getting the, having the rubber hit the road really is what's happening. Jeff, Peter, thanks so much. The big data world is about to explode, not implode. I put that out there in Twitter as a poll. I think unanimously it was, it's exploding in a good way. You're seeing a lot of lift. You're seeing a lot of operational paths. You're seeing people moving into production. You're seeing the realization of the data and the value that it can provide and that they can extract from that. So, this is theCUBE. We have exclusive live coverage here on the ground here at the Strata Hadoop Conference right across the street. And of course our event, Big Data SV, Wednesday night we're having big reception and panel. Follow us on Twitter at theCUBE and of course go to crowdchat.net slash Strata Hadoop where you just embedded the live stream and join the conversation from LinkedIn or Twitter or Facebook. Jump in and join the conversation. I'm John Furrier. We'll be right back. Extracting the signal from the noise here in Silicon Valley for Big Data Week, Big Data SV. We'll be right back.