 Hadoop World in New York City, this is Big Data Week. I'm John Furrier, the founder of SiliconANGLE.com. This is theCUBE, our flagship program. Go out to the events and extract the signal from the noise and I'm here with the special guests who are actually running this conference at Dunbill and Alistair Crowell. Again, a fabulous event. We are proud at SiliconANGLE 2B and our third year covering Hadoop World and we've covered all the strats from the beginning launch, when you guys launched the conference, which was a bold move at the time because you kind of blend it together, a lot of things. Welcome to theCUBE 1 and let's talk about what's happening here in New York, guys. So give us a quick update. I know you're really busy, so we want to get right to it. Go ahead. We've got off to a great start this morning with the keynotes after a fun day of tutorials and sessions yesterday. I think really this audience has just swelled massively. Venue is packed, we're really happy. There's a lot of energy. And there's a sense that Big Data's really something, right? Not just hype, but we're putting a lot of the building blocks underneath it too. Yeah, I think, you know, any conference you see the first couple of years are what is this thing? And the next couple of years are why should I care? And now we've kind of moved into so how do I use it? And it's that, you know, people are starting to run into integration issues. They're trying to find real world applications that aren't just sort of making people click on ads more. We're realizing that this is, Big Data's fascinating because it's where humans touch technology. And that's where there are a whole bunch of sort of messy ethical issues, but also lots of potential to fix healthcare and finance and civil rights and all these other amazing topics. You know, I'd say SiliconANGLE when we started with the whole thing was computer science meets social science. When you guys started Strata, there was a bold move at the time because it was kind of outside the normal, the normal conferences in the tech business. Yeah, but I mean, to some extent, that's what conferences are supposed to do. We're supposed to anticipate the curve just enough to kind of, you know, get ahead of it and bring people together because you're skating to borrow a Canadian sporting analogy, you're skating to where the puck's going to be, right? And if the puck is going to be, it's really easy to see how this stuff has gone up through the networking infrastructure stacks and then through the sort of cloud and platform stacks and now you're up to the content and the people stack and that's where we're seeing an amazing explosion of stuff because suddenly this is relevant to, you know, everyone's a technologist today. I heard a great quote that 24 months ago, people were terrified of their phone, now they're terrified of being without their phone and that's like a sea change in the usage. You had mentioned on one of the key notes, I saw your introduction to, I think it was Tim from Digital Reasing, you said, Mark Andreessen wrote the seminal update on the Wall Street Journal, software's eating the world and if that's the case, data is its food. Could you just talk about that because that's a great way to look at the data side because data is important, it's exploding but explain more about what you mean by that. Well, I think on the one side, garbage in, garbage out, right? If you eat a lot of junk food, you're going to produce bad results and we don't recognize the issues. I remember presenting last year when Athens wanted to tax pools. There's, you pay a pool tax if you want to tax an Athens, if you want to pool an Athens. So about two years ago, 324 people filed their taxes on a pool. Someone went on Google Earth, found out there's over 16,000 pools in Athens and no joking aside, sales of green tarpaulins were up because people wanted to cover their pools because they knew they were using Google Earth. That's a garbage form of data that leads to garbage outcomes, right? And the downfall of the Greek economy may not be due to pools but it's certainly a factor. The second part is that if we're not careful about our information diet, if we're not careful about what we consume, how we consume it and then how we put it to work, this stuff can be used for very bad things as well as very good things. It can be used for huge violations of privacy, invasions of civil rights, all the stuff you read about in the sort of alarmist worlds. But if we feed it and nourish it and give it good stuff, it can make us healthy, it can make us wise. So it really is all about understanding that software is going to be how the world is run but the data is going to be whether it runs well or poorly. So guys, I want to ask you a question on that thread because really you're talking about people being a big part of the equation and that's coming out of some of the keynotes. Yeah, there's a lot of technology, these tools and platforms are becoming better and Ed has a prop, we want to get that in a second. But I talk about the people side of it because you now have instrumentation, you have things sensing data, you have machine data, you have people data, you have phone data, all the data, tsunami, yeah, it's all great, all the instruction, it's happening. However, people are still a big part of it. Can you guys comment on your insights around the role of people in this data explosion and this big data explosion? I think it's all about people. You know, those of us who actually spend too much time in IT conferences could be forgiven for thinking it's about software vendors and what to buy and so on. But all of this, the only reason machines exist is in service of people, right? And the real potential of big data is when it reaches out directly into our world. Thus far, you know, it's not got that far but now we carry the mobile phone, it's doing all this. So we both need to understand what data tells us about people but there's people we need to understand what data is telling us. So one of the things we really focus on is design, user experience and the whole interaction of a person with the data is as important as any analysis. That's how we really understand how to make decisions. And relative to data, obviously, using data is going to be an interesting way to do it. So like one of the things we use at the IBM conference this past week, we've been joking before we get on about the red eye we were on, but you know, IBM is an established player, totally endorsed and the entire messaging around information management has now shifted to big data. So you know, big blues putting a big check on the big data revolution but decision making is another important part and analytics play a big part of that. Alastair, what are you seeing in terms of the problems that are being solved out there that yet have not been completely checked off in terms of data? Yeah, so I think to Tia's point about people, we're looking at the track for Stratocentrary 2013 in February, please come. And Ed made a very good observation which is that we have these tracks about interfaces and user design and so on. And he said, look, we should just call it design. And there's a great quote, I don't remember who it's from that talks about design is helping people arrive at an outcome you want. And that's really a great understanding about design because all this data is just to help you get to that outcome. And I think we're now realizing that this data, I mean, just like we used to call it cloud computing, we thought it was new. It's actually just another tool in the IT toolbox. It's just computing, right? Cloud storage, we're just going to call that storage. Big data, we're just going to call that data. What's changing is that an organization used to make decisions based on guesses and whoever could guess best was right. And now an organization is going to make decisions based on asking good questions and analyzing stuff. And the organizations that will win are the ones that can turn that information into an outcome. And so that's a problem of organizational structure. It's a problem of decision theory. It's a problem of cultural change in a company. Those are all human problems. And so many of the analytics that we see today that just say, here's the right course of action need to be accompanied by sort of coaches that say you're getting closer to that action. These are the people who are resisting that outcome. How do you know, what are the obstacles in your way between you and that new outcome? And that's where I think programming the organization to go after the outcome the data has suggested is a completely unresolved problem. And to translate that into some industry trends for the next year, that means we'll need decision systems that can explain why they made decisions. If we're going to assist people running their businesses, we'll need to let them know why they're making decisions. Black box algorithms are not going to work. You need to understand why you made a decision. The second thing is we'll need, and you'll see this coming up, great metadata support, right? Talked about the garbage and garbage out. You've got to trace things through the system. You've got to understand how the transformed, what decisions were made, and that's what's going to come down into product in a database as support for this explaining decisions and kind of tracking the metadata as data flows through. I want to get to simplicity. I know you guys are tight. We've got a tight schedule. I want to get to the whole simplicity message, but first I want to get to your gadget there. You have some props here. So tell us about what's going on at the show. I know that, I'll let you explain, set that up. Yeah, so I'm very excited because one of the things I wanted to do was to prove this. Can you hold it up a little bit? I can hold it up. So really prove the whole data thing from soup to nuts because we're talking about sensors in Strada, and we're talking about data streaming off. So these little guys are Arduino setups with wireless mesh networking, XBs. They've got temperature sensors, noise sensors, the PIR to see who's going by measures humidity. We've distributed 50 of them around the venue and we're tracking all the data streaming up into the cloud. And then we have a team of data scientists analyzing this, mixing it up with photos. We've got stop motion camera and other things from around the venue. We have like hotel data, like coffee consumption going into this too. Yeah, right. And it's a whole new heat map. Data from the wireless access points. So we're going to see what we can create because we want to do the whole data science thing and while we're here. So a bunch of people came together from the lab and sitting downstairs. And this is a great project. I'm very excited. And I think one of the things you'll see is that at a conference like this, it's easy to accompany a call for proposals to speak with a call for data. So we could easily take that data set and say, hey, everybody mind that, come back to us next year and present what you learned. Let's talk about that while we're here. Talk about what's necessary. You said skating through where the puck is going to be. So tell us, where will the puck be on next Strada as you do your Strada program, which is now, I noticed in a lot of different verticals, you guys are expanding, there's a lot of demand. So share with the audience what you guys are looking for for those proposals. So I think Ed mentioned metadata. Do you want to expand on that a little? Well, I think that's going to be very useful. You know, beyond Hadoop, I think is a really important thing to consider. Hadoop is obviously a core engine, but it's what's unable to do a transformation, but it's not the whole shooting match by a long way. So we're looking to- Meaning Hadoop doesn't mean big data. There's other things involved. Hadoop is not big data. We already know from announcements like Cloud Errors this morning that interactive access to the data is crucial. And furthermore, that there's going to be the need to be able to systems that cope with streaming data is going to be very important next year. But I think there are other things beside that that we're looking to address. Alice has already mentioned the design, but we're also taking the fact that enterprises are now doing big data for real into account. We kicked off what we called a bridge to big day to day this week, and we're going to build on that. And that's really the plan for CIOs and people in the IT organization to develop a strategy, to walk through that strategy, and to at the end of the day also discover valid enterprise data architectures. So that's new to Strata as it actually starts to happen in the enterprise rather than just in experimental areas. And I think we're also going to see, as I mentioned earlier, when you move from the what is it to why should I care to how do I use it? You see the rise of sort of case studies and best practices referring necessarily there. So yesterday we had people like EMI and Beyond the Rack and others talking about how they're actually using big data. So probably more case studies, more concrete examples. The other thing, and this should be obvious from the things sitting on the desk here, is this, if there's an umbrella term for it, the Internet of Things. Because every device we carry is both a display surface and a data collector, right? The DARPA had a project a few years ago for a spike that you threw in the ground that would do heat sensing and motion sensing and noise sensing and it would broadcast things by mesh network. Each spike was only a paltry $10,000, right? The iPhone is DARPA's wet dream and we carry these things around and we voluntarily share our locations. So we've basically created- That's a cute quote right there. The iPhone is DARPA's wet dream. That's true. I'm a walking bumper sticker. So the reality is we've created this world where you can just harvest all this data very, very easily. And I think that model of feeding the machine is huge. We're going to put a lot of information in there and we're going to consume it in new ways. Okay guys, thanks a lot. Congratulations on a great program. Ed and Alistair, the co-chairs of Stratoc. It's blowing up its global. Congratulations. We'd love being here. Thanks for your insight. We'll be right back with our next guest after the short break. Thanks.