 Live from Las Vegas, Nevada, extracting the signal from the noise. It's theCUBE covering Informatica World 2015. Brought to you by Informatica World. Hello everyone, welcome back. We are live in Las Vegas. This is Silicon Angle and Wikibon's theCUBE, our flagship program. We go out to the events and extract the signal from noise. I'm John Furrier, founder of Silicon Angle. I'm joined with our new analysts on the Wikibon team, George Gilbert. George, welcome to theCUBE. First time on theCUBE, welcome to the team. Good to be here. As our new analysts in the data, data extension, data meets the world, data is eating the world, whatever the thesis you have, we're going to discuss that. So welcome to theCUBE. All right, well, just to sort of the frosted mini-week kind of version of this thesis is that we're seeing, we've lived for 30 years in a world where we had these systems of record where captured business transactions then moved them over to a data warehouse to report on historical performance. But now we're seeing an explosion of data from interactions, both from people and machines, but the systems are changing. They're not about business transactions. They're about first engaging people, but the emerging ones are about systems of intelligence. But what they all have in common is a new data layer with many more types of databases. And then the glue to tie all these things together and they have to happen much, much faster than we've had before. So this basically means that, we used to look at data as Hadoop, you store the data, you apply it, actionable insights. So data is kind of all over the place. But now what you're saying is we're looking at it from a perspective of if you look at it horizontally, we're moving up the stack, if you will, to have much more of an impact on applications. We had these sort of one-off engines fill out the Hadoop ecosystem. But what we're trying to build is a coherent end-to-end platform. The internet-centric companies who pioneered this architecture, the LinkedIn, the Googles, the Facebooks, they could sort of source, make, operate their own platforms. But for the mainstream enterprise to build these sorts of apps, they need someone like a Microsoft or an Amazon or a Google to put these platforms together. And once they do, then we can see an explosion of these types of apps everywhere. So I got to ask you, as you go out and talk to companies, what are you looking for? What kind of companies are you looking for? What kind of topics and interests do you look at exploring? What are those puzzle pieces? What is your thesis? And how does that all hang together? And what do you hope to deliver to the end-user community in terms of research? Okay, so first, for the leading-edge enterprises, the guys who are the internet, sort of the next generation internet-centric enterprises, whether it's the Airbnb's or the Uber's, they're aping somewhat the architectures pioneered by the Googles and the Facebooks and the LinkedIn's. But the mainstream enterprises, once you get beyond your, once you get into the telcos and the banks and beyond them, they need the platforms that are pre-integrated because they can't sort of stitch that stuff together themselves. So we're always going to see really innovative data management solutions around the edges, but then we're going to see the platforms for the mainstream guys. But what's different about these apps from the old systems of record, the legacy apps, they were about business process efficiency and mainly in the back office. The new ones are about first engaging customers, but even more important anticipating what they're going to do and trying to influence that. That's the systems of intelligence. Those are just emerging now. And they're about data. And this is a completely different mindset than saying, oh, we're going to get into the bowels of the infrastructure, infrastructure's a service, you got platform as a service. Data is a competitive advantage. And is it your thesis that if companies do not use that competitive advantage that they are wasting a killer resource? Yes, and not all the data though can come from them. And it's, see what was interesting about systems of record was once you put it in, you sort of consolidated it and tried to rationalize it and make sure it just, it ran pretty much like everyone else's. But with data applications about systems of intelligence, you're always adding more data and more analytics because you're trying to get a richer and richer picture of your customer or of your suppliers. And so these applications are always in flux. What are some of the big companies you'd be covering and what are the companies you hope to be unpacking and breaking away from the field in terms of looking at the data and sharing insights from this research? Okay, so to start with there, the core Hadoop distro vendors who put the platform together for, in this case right now the banks and the telcos and some of the Uber and Airbnb type companies. This is the Clyde Arras, the MapRs, the Hortonworks, the Pivotals, the IBMs. But then as we move more and more mainstream, we'll see more and more traction among Azure, Amazon, Google Cloud platform. But that's the platform level. When we start moving up into the applications, we're going to see types of apps we've never seen before where it's, 15 years ago we saw these B2B marketplaces where companies would organize sort of a hub where many buyers would organize through many sellers. We're going to see data-centric versions of those in the future. Who are you bullish on right now and who do you think needs to do some serious improvement? I think we're in the middle of a, I don't want to say the B word as in B-U, B-B-L-E, but I will say we're in a boom and that we've got a lot of innovation going on at a level of sort of investment that may not be sustainable. And usually when that shakes out, we'll see a bunch of innovators at the edge, but we'll see the big integrated platforms sort of really emerge as the standards. Are we here at Informatica World 2015 in Las Vegas? What do you think about Informatica and their prospects? Obviously they're going private, which is actually in my opinion a good sign to get out of the public markets at this phase and then retool and regroup and grow. What's your take? So Informatica has a, there's this saying in Chinese, danger when you translate it equals, or no, sorry, crisis equals danger plus opportunity. And so for Informatica, they ruled the world where we had these systems of record and we integrated them point to point. But what's going on now is we have so many data systems to put together that the methodology by which we do it is changing. They can grow into that world. The business model has to change, the technology has to change, but they're talking about that change and perhaps going private is what's going to give them time to do it. Well I think one of the things I'm excited about about this event is that they are really singing our praises in terms of our vision of our research that we're moving into, which is much more comprehensive. They're moving from what I would perceive them as a data warehouse, this fenced off data model into much more comprehensive, horizontally available data fabric if you will. And I think to me, I've always said, we've talked about this when you joined is, I believe that frictionless data traversal is absolutely going to be the critical thing in the future of business, future of humanity. And I think whoever can tap into that flywheel and provide frictionless data transfer will be the engagement solution platform. And that's a zillion dollars beyond unicorn status. And so the trade off is they're putting together something that is end to end tightly integrated and would be appropriate for someone who can't sort of put together all the components themselves and test them, integrate them and operate them. They're going to give the sort of integrated solution. So that looks like it should be appropriate for the mainstream enterprise. But meanwhile, the leading edge companies today are all the ones who are taking off GitHub, all the open source projects and putting them together themselves. But that might be just an artifact of where we are in the market's evolution. Final question for you. What are you most excited about as you take this next step in your research career in terms of what you're going to be acquiring for data and the hopes of the reports you will be putting out there? At the base technology level, we're seeing hardware architectures change so that databases will no longer have to make a trade off between fast and big. That's going to be profound. In other words, the big things that do the cranking on predictive models in the background overnight versus the ones that sort of stream frictionless data immediately, those may merge over the next five years. Then above that, we're going to start seeing the industry specific applications that are driven off data where they're, as you add more data, the models that they use to predict and recommend actions or actually take actions continually change. It's a smarter machine. It's the concept of getting smarter. It's a smarter machine intelligence. It's about insight, cognitive computing, context. These are amazing concepts. Yeah. Okay, George Gilbert, new to the team here, the Wikibon team, Wikibon analysts, covering the big data and beyond. We've got an all new focus here with Wikibon, so please welcome George Gilbert, who are new analysts. We're live in Las Vegas for Informatica World 2015. If you have any questions for George, obviously you can contact them at wikibon.com. Check out the site, all the content there. If you want to get his research agenda, reach out to him. Happy to include you if you're relevant in his area. This is theCUBE, we'll be back with more in Las Vegas, Informatica World after this short break.