 Live from Boston, Massachusetts, extracting the signal from the noise, it's theCUBE, covering HP Big Data Conference 2015, brought to you by HP Software. Now, your hosts, John Furrier and Dave Vellante. Okay, hello everyone, welcome to day two coverage live in Boston, messages of Silicon Angles, the CUBE, our flagship program. We go out to the events and extract the civil noise. I'm John Furrier with my co-host Dave Vellante with wikibon.org, and day two is really about the continuation of day one, which is HP's Big Data Conference, talking about, you know, really architecting the next generation of big data with practical solutions today, with a bridge to the future. Dave, keynote today was Nate Silver, Ken Rudin from Facebook, you know, obviously Nate Silver, heavy hitter, predicted the elections, now we're ESPN, and Ken Rudin, who I hosted a panel with a couple of months ago on analytics, it's from Facebook, which we know, and for the folks who aren't following, the deep analytics driven culture that Facebook has, it's in their DNA, it's basically ridiculous how much Facebook uses analytics, truly Facebook uses analytics as a competitive advantage, and their performance as a stock in revenue certainly show that. This is kind of our theme, right? Big Data Analytics is huge, it's a competitive advantage, it's a revenue growth driver, I'll allow Facebook. Nate Silver, obviously predicted the elections, got a little sex appeal to it, probability, theory, stats, data science meets business, I mean, what's your take on day two keynote from HP? So I thought that was very good, so a couple things, we've seen Nate Silver speak before, we've had him on theCUBE, he basically took his same talk that I have heard before in some of the themes that we talked to him about on theCUBE, I tweeted that out on the crowdchat.net, crowdchat.net slash HP Big Data 2015, but he had basically three things, big data equals big bias, more data equals more complexity, and he has this thing of feature or bug, one of the things he showed was this Google Maps, so the most direct way to get from point A to point B in New York City where he lives, and then he showed another map where the cab driver went through Central Park twice in this sort of convoluted route, and it made him late for a meeting, so it's an old story, and his point was more data does not necessarily mean better answers, although I tweeted out, John, that he did that chart before Waze, who's Waze went out smart of the traffic, but Nate was very good. I asked him, well he mentioned, he didn't think Trump was going to win the election because he has a 2% probability of winning, and so I asked him specifically, what's the probability that if he runs as an independent candidate, that it will affect the outcome, and he actually said he can't predict whether or not Trump will run as an independent, but he said if it does it very clearly it will siphon votes away from the Republican nominee, so that was interesting, so very low probability of him winning the Republican nomination, and if he becomes the independent candidate, he said a very high probability that will siphon off votes and help whomever the Democratic candidate is, which right now, the front runner, of course, is Hillary Clinton, so his point was think in terms of probabilities. The other speaker was Ken Rudin, who I thought was very good, head of analytics at Facebook, you know Ken, I think you've had him on before, have been in the panel with him, and he was very good, he said, I'd like to take issue with one of the things he said, I don't necessarily disagree with it, but I want to put it into context, he said Hadoop is not equal to big data, it's not synonymous with big data, and while I would agree with that, his point being look, you need in-memory technologies, you need sequel technologies, you need no sequel technologies, there's all kinds of technologies around Hadoop, or big data, but big data's really about driving business, I would say this, John, and I'd love to get your take on this, while Hadoop may not equal big data, Hadoop changed the whole conversation, the idea that you should send five megabytes of code to petabytes of data and chip function, as opposed to trying to stuff all the data into a big God box, changed the way in which we think about data, and I think it spawned the big data movement. I got a phone call from you late at night one night, I said get in a plane, go to New York, we're covering Hadoop world, and I said what, what's that? So you were on top of this trend, you remember those days. I mean Dave, I mean Hadoop is one of those things where, I mean I could be super critical of Hadoop on one hand and then totally love it on the other, but here's the bottom line, we had an editorial meeting this morning with our team, and one of the things we discussed was the future of Hadoop, because it's not a mutually exclusive environment from a technology standpoint, again we heard Maribel Lopez yesterday say, it's people, process technology in that order, and we're finding that one of the key challenges of today's market of big data and certainly cloud, is the fact that it's the people transformation, not so much the technology, although they're both going on at the same time, really a perfect storm in my mind, but here's what's going on. Hadoop is changing its relevance piece of the overall equation. It was all in like, oh Hadoop is big data, that was the part of the hype cycle to generate awareness to this new paradigm shift. Cloudera rode that wave, and certainly a stone breaker pointed out, it changed their perspective on that, it became much more of an engagement hub or data hub, aka Impala, and they're still kind of pivoting and navigating and changing their vector, but their North Star is still the same, and you talked to Cloudera, you talked to them in 2009 when they started to today, ultimately it's the same kind of mission, they did have to navigate like a sailing vessel, changing courses a little bit, to kind of catch the wind, but then you've got Spark. Spark is totally hyped up right now, and that's not the end all, be all right now, certainly in memory is exciting, it's basically data warehouse on steroids, but again, that's going to die from the hype perspective, so that's converging. Hadoop and Spark are not mutually exclusive, those ecosystems will continue to flourish, bullish on Hortonworks, I think that they're going to have to change a little bit of their tactics in their business, just a bit to accommodate some of the things that Spark is telling them, but Hadoop is in no way is going away, now you can see the ecosystems kind of stall a little bit on the Hadoop side, mainly because of the competition or attention that Spark's getting, Dave, but the real driver is going to be underlying technology, and to me, that is ultimately powering the next generation analytics, and HP's message is very clear, they have a comprehensive platform play that's going to span Hadoop, Spark, and other stuff, in cases different proprietary stuff, IBM is the same thing, they got their own streaming technologies, you know at some point, if you're a company, why build something when there's like five versions of something that take streaming, there's like five different versions of streaming out there, why build it, you can go with Vertica or someone else, again, this is kind of the market, so I'm still bullish on Hadoop, certainly it will evolve, but again, Hadoop is not dead in any way. Well, I'd add, if there's any kind of so-called stall, it's that all the stuff's for free, I mean, for years nobody paid for anything, I mean, less than 25% of the people actually pay for Hadoop distribution, so the core of it is free, all kinds of open source software around it, so, and then you can store data now for one-tenth of the cost that you used to be able to store it on a big iron. Yeah, we're all over this, we're all over this, George Gilbert, the new answer at Wikibon, you know, is pretty bullish on Spark, but also Hadoop understands the challenges, we will be in New York for big data NYC when Strata Conference, Strata Hadoop goes on, we're going to have a companion event with that event, and really unpack this emerging business model, open source innovation is thriving right now at an all time high since open source became a practice and now commercialization. So the point I want to make on that is that the real money to be made in big data, and Ken Rudin talked about this, he says it's not just getting to insights, it's not getting to actionable insights even, it's actually taking action on those insights and somebody owning the change and being the change agent in the organization, that's where value is going to be driven and that's where money is going to get made. Yeah, and I think it's going to be right now kind of the vendors jockeying, but the customers are voting with their wallet, you can see what they're deploying, and ultimately what HP's message is, is that the low hanging fruits are starting to see the practical commercializations of big data technologies, and it's not a one trick pony. If you are a one trick pony, you are in trouble and I think that's where people on the vendor side of them providing the solutions where it's open source or combination are realizing that I need to make a move, I can't be stuck in the middle between a wannabe platform and a killer tool. So this is the dynamic and ultimately that's independent of the customers. The customers ultimately decide and we'll be talking to them here and we're hearing things like Kafka is really hot, you're seeing people really bullish on that. I was talking to PayPal last night at the Tammer Vertica party and there's a lot of great conversations happening here from the real practitioners and the people providing the technology and the architecture. So again, this is, again, still early innings. I still think it's early innings, Dave. So again, super fun for us. And again, George Gilbert at wikibon.com is putting out probably the best research in the business right now around systems of intelligence. You're going to see a lot more editorial coverage on siliconangle.com to really kind of go into our three pillars, big data cloud and infrastructure. That's where the action is and that's now dictating what's happening at the consumer level. Internet of things, consumer cloud. This is all being now kind of converging. So it's super exciting. It's just great to be out in the cubes and getting on more data. Hi John, we got a big day today. We're here all day in Boston at the seaport and big lineup, heavy, heavy dose of practitioners. We got HP executives, partners coming on more on the ground. Yeah, and we're going to talk to the customers. And that's ultimately our focus on this event. We talked to all the HP folks yesterday. We want to talk to the guys that are architecting the next generation platforms. Really to enable that asynchronous, real-time DevOps consumer. And this is theCUBE. We write back our flagship program. We're out here in Boston live for the day two coverage of HP Vertica, HP Software, HP Big Data Conference 2015. The hashtag is HP Big Data 2015. Go to crowdchat.net slash HP Big Data 2015. Join the conversation. We'll be right back.