 We go out to the events and extract the citizen's noise. We are here for Strada Hadoop coverage for our special big data NYC event live on the ground like for the day show with the windows behind us and literally right around the corner from the Javits literally 100 yards away is where all the action is happening. It's part of the big data NYC event this week and I'm John Furrier with Dave Vellante kicking off second segment of our kickoff with special host, analyst, guest CEO of Shiseida Abimetta, Cube alum, six years in a row. Six years in a row. We've been on the Cube. We've been at Hadoop World now called Strada Hadoop for six years. This is our six year covering Strada Hadoop. It's quite a streak. Thank you so much. It's quite a streak and I guess I got a promotion. I'm now guest host co-host. I could never my father would be very pleased that you've made me equal to the two of us. ESPN brings the coaches on that are substantial Super Bowl champions and you are CEO. So you're in the trenches. We want to get your perspective as someone who's building a company, profitable company to say they've been on many times, but you're out in the trenches. You're out doing business. You are part of the ecosystem. You're part of this fabric of the big data business. What's happening? What's new and what's different this year? What's different? I think the three of us need to create the difference. We need to change the conversation. The conversation needs to dramatically go from this obsession with technology, which of course we come from the tech industry, so it's good to be obsessed with technology, to really understanding something that we haven't changed our perspective on individually and as a company in my case, but even having spoken to you before, that the future truly belongs to how technology is enabling the next generation business model. I am now on a new mission to make sure the conversation actually changes. We cannot keep talking about or missing the point on this revolution. What it's enabling is a automation system, a automation ecosystem that can take human tasks that needs brain power, intelligence, and deliver decision systems at scale. And I hope, John, to answer your question specifically, I hope that starting with Big Data NYC as we go into 2016 the conversation changes into a new alphabet. I have a new alphabet for you, right? The ABCD in our Big Data ecosystem should be analytics, big data, cloud, and decision sciences. It's no longer about the data, it's about decisions. ABCDs of business. So I got to ask you, okay, so one of the things that we're seeing, at least I'm seeing over the past six years, and certainly looking at cloud, the 70 events that we covered this year in the cube, you're seeing that it's almost like a trainwreck in the ecosystem right now, and to my standpoint you're seeing way too much pressure coming from the business side, customers who want scalable, large-scale solutions, and it's as if the Hadoop ecosystem has just been slowly patching, moving incrementally along, adding features, even Hadoop leader Claude Aireft, throwing a haymaker out there, feels like a Hail Mary, throwing out storage, it just seems so late to the game when there's so much demand for solutions. Do you see that same thing? And what does that do to the ecosystem? Does it force vendors to make medieval acts and do things crazy? Does it force the big guys like EMC and IBM and Oracle to come in and say, hey, you know what, we can fill a big gap here, we're used to a large scale. That's a real interesting dynamic. You're seeing IBM dominating, you're seeing Oracle, you know, spamming the event out there with taxis and billboards. So what's your take? I fundamentally believe that the infrastructure story that Bolt has sailed, you know, it sailed when Oracle won the America's Cup and we spoke about that a while ago. The obsession with growth is causing this turmoil in the ecosystem. It is my take on why you see this medieval, what do you call the medieval bloodbath. It is almost regressive to believe that we, in six years, six continuous years of covering what we have always said is a business revolution. We were the first ones to say this is a trillion dollar ecosystem, not a billion dollar ecosystem. Michael's and a good friend of yours, good friend of mine came out and said the last year, right, this is a trillion dollar value generation ecosystem. The reason the confusion is being caused is going from raw data to actionable intelligence is hard. It's hard if the only focus we have in our conversations is tech driven. If you keep worrying about backwards integration and not forward integration, so to your point, why are we talking about storage now and not analytical applications, tool sets, the reason being without a deep knowledge of the particular domain, we call them data domains, it's very hard to have the conversation. So when you have these massive valuations, John, and you guys know it, and you have these massive valuations and the only way to fill into it is growth, you go and try to sell the easiest and lowest common denominator, which is, in this case, storage. Not going to solve business problems. I got to ask Dave a question because this is coming back down, because that was a good thread. But the fact of the matter is, adoption is slowly, is not there for Hadoop. Merv Adrian put out some Gardner data this morning, big adoption trends, steady increase in investments in pilots. I mean that's the code word for saying, and then he says slow production growth. Dave, Hadoop is not moving into production as fast as it could be. What's your take on that? Is it a bigger tam? Is it a slice of a bigger tam? What's your take on that? I mean our data shows 60% of organizations are doing something with Hadoop. And you know, a decent size, a decent number of those are in production. But the problem is, you said it best last year, the ROI has been reduction on investment. Most people have not gotten the return that they wanted to get. And they're struggling through that. But I want to break down your alphabet, if I can. So the VCs, the analytics, the big data, and the cloud, it seems to me, we talked about this five years ago, six years ago. We talked about the new business models. We talked about the paradigm shift. It seems like organizations got to be focused on two things. One is the ability to capture all this data, ingest it, analyze it in real time, and affect the business outcome. But the other piece is your domain expertise and your decision science to continuously improve my ability to compete, to differentiate, to add value. And that's where the decision science comes in. So you got sort of the infrastructure piece, which is the hardcore tech. And we sort of checked that box. And we're still trying to figure that out. But it's complex. But I wonder if you could talk about that a little bit. Where should organizations be investing? I would love to. And I would love to get your feedback too. Because you talk so much to the tech ecosystem and you always push my thinking. I will give you the business perspective. We are yet to meet a CEO. And to say that this year is going to expand into healthcare. In banking, retail, and healthcare who does not believe that the next frontier is taking complex decision sciences that have still now been human. Because you need a person as smart as Dave Vellante or John Furrier to extract a signal from the noise. The signal from the noise as you build your platform out should be automated. The automation of decision science is the next frontier. Not one CEO, Dave, to answer your question that we have spoken to, will disagree that the ability to run organizations that are 300,000 people large, which is the average organization size of a large bank, by the way. A large bank globally has 300,000 employees. There is no way you can compete in a capital and resource efficient manner unless you have automated what we earlier called the Data Factory or what is now called the Data Pipeline. So the ability so what is the challenge? The challenge is no one has been able to talk to those CEOs and have a conversation to explain to them how will you automate the decision systems. And that is where the secret source comes in. You know it. It's the combination of deep domain knowledge with the ability. The platform, I completely agree with you and John, the platform for massively parallel computations aka the ability to build and monetize cheap supercomputers is done. Whether it's in memory, off memory, stored, doesn't matter. The platform is done. The solutions your word, the solutions don't exist. And that's where it comes to say the reason why we are profitable, we walk in and don't, we have to stop selling Hadoop. And we need to start selling anti-money laundering massively drug resistant organizations, organism health outcomes and next best offer engines for retail. That's the difference. I think the big thing that we're seeing and Dave hit on this the last time he did the MIT event, we're talking about the new Bapachiano at IBM, which is, and I said on the cube, that there's going to be diversity. There's going to be diversity in the infrastructure and software market where the religions don't matter. The two religions that we're watching are horizontally scalable with commodity hardware and vertically integrated. So scale up, scale out is concepts that we all know. Here's what I see and the trend that's disrupting this ecosystem here. I think it's catching everybody flat foot. If you look at Cloudera, what they're doing is obviously got them flat footed and others is that they're betting on one religion or the other. And every customer I talk to wants both scale out and scale up. Software and big data, if it's not pre-packaged software you brought this up with Bapachiano, which is big data is about integration not about silos. That is a huge issue Dave. It's bringing that integration to the application world and we've always said there's a lack of real application solutions in this space. And to add to your question of diversity, the thing I miss is there were these early vagabonds they've all come through, the Vikings of this revolution, right? They've all come and crossed the path at the cube and those voices are missed. We have to celebrate different voices not to mention one of the voices I miss the fact that Jeff Harlbacher Kevin Wheel, the head of Florida Twitter maybe Future CEO at Twitter but they were the same, I think myself, Jeff and Kevin spoke at the cube six years ago at Hadoop World and those voices that were not worried about Jeff Harlbacher has one of my all time favorite quotes, which is the smartest minds of our generation are making people click on ads. Now they have the ad blocker software. Exactly, so I think... To take from your point on diversity, one of the smartest advertising campaigns on big data was created before big data the term was coined. It was called Smarter Planet by IBM and having been on both sides as you know, been a customer of large tech companies and now selling my own solutions, the ability to make the planet smarter now that IBM has abandoned the marketing I guess I can use it, the ability to make the planet smarter with 7 billion people, how many devices now 14 billion devices and IOT, all these buzzwords will fail when if you keep worrying about the internet of things if you keep worrying about the network and not the signal from the network we will fail. The ability to take data at scale I love your team model, the horizontal scalability and the vertical expertise, the vertical focus they're not mutually exclusive and the ability to integrate them in a very key word, integrate the ABCs analytics, big data and cloud, integrate that in a solution, not for infrastructure and deliver decision science. I think a key word we have to add to our vocabulary is decision science. We always joke on the key word it's going back to the old IT days, information processing data processing, decision support, we're back to the old days we are, and we should be ashamed as an industry I am my worst days in the industry are when we create terms like the hub or the warehouse it tells me that we as a human race, we as a technology ecosystem aren't smart or creative enough to come up with the right ideas, it's absurd to think data lake, it's absurd to think that we will create data hubs, lakes big data will be successful, we've got to better democratize democratize the access to data, not centralize it we've got to break now because we've got to work over our time but I want to get a quick bumper sticker for you guys what do we expect to see at the end of the show of big data NYC, NYC, NYC, NYC, NYC what do we expect to see at the end of the show of big data NYC, NYC, NYC, NYC, NYC at the end of the show of big data NYC and Hadoop world what do you expect to see at the end of this event what's going to happen I think what will happen is you guys will be asking some very tough questions to people around what does the maturation look like but more importantly what is the road map when intelligence gets automated that's what I expect the two of you to do yeah I think we're entering the era of confusion and those leaders that can help us squint through that it's going to be the winners confusion of course not a problem for the Cube we extract the city with the noise that's what we do we're here live all week here in New York City we'll be right back with more after this short break live for big data NYC part of head strata Hadoop we'll be right back after this short break