 Okay, we're back, this is Dave Vellante of wikibond.org and we're here with Ed Dumbbell, who's the conference co-chair of Strata and Hadoop World. Ed, welcome back to theCUBE. Thank you, it's been quite the week, huh? Always a great guest. We really appreciate everything that O'Reilly does for us and your time and Alistair's time. We didn't get Tim this week, maybe next time, but you are always been a fantastic friend. So yeah, it has been a great week. I think back to the early days where theCUBE was here and the early Hadoop World days, we've been to other Strata events. It's great to see those two come together. It's given a lot of new energy, hasn't it? It has, you know, I think one of the most important things is that Samantha Rivich was saying this morning, is you don't need to develop the tools in isolation from the applications. And when I was creating Strata and the program, it's always the applications that are very important to me and of course the tools are enabling, but these things need to happen together and so bringing the conferences into on place makes a great deal of sense and it's brought a lot of energy. Yeah, and so we've talked about a lot of the themes that we've seen a lot about bringing together some of the old world and a new world, a lot of discussion, it's kind of techie geek stuff, sequel and no sequel, a lot of discussion about ETL or no ETL, you're seeing a lot of the vendors sort of flexing their muscles my ways better than this way, but it's all about the business value at the end of the day. You talk to the practitioners, they can solve these problems. They need the tools and like you said, but it really is about the applications and we're starting to see that traction which we've been expecting now for several years, right? It is, I mean one of the things I added to the show this year was our bridge to Big Data Day, which was really all for the IT organization and CIOs about how to start with a big data strategy and we started out at this top level. We had Bill Schmazer on, a favorite guest of yours. The Dean of Big Data. He loves that and we started out and he was very much that they were what are your company's aims, right? That's where he started, what are your goals? Look in the annual report, what's the CEO saying? And that's the kind of stuff that's got to orient you, use of data, but then we drilled away to the bottom of enterprise data architectures, because now there's enough, there's enough experience that we can start to say what real world Hadoop or in real world Cassandra, no sequel, enterprise data architectures look like. Yeah, I mean, I think that's great advice, right? All too often we focus so much on the technology, but it really does start with what are those main business objectives and how do we achieve them? The technology is almost the last decision that you have to make, at least in my experience in working with practitioners. Absolutely, but as technologists, we can get it completely backwards half the time because we make some great tools, but the real important thing is that we understand, and this happens with data too, you can have a lot of data, but if you don't know what questions you're setting out to ask, it's just a lot of data, whether it's big data or small data, and some of the most important leadership questions now are where are we going to look, what questions do we want to answer, what problems do we want to solve? These things are eternal, to be honest, we're doing the big data now, but these are really solid questions. Somebody asked me to ask you about the sensors. Excellent, yes. Tell us about the sensors. Right, so I brought one of these Gizmos in to show John yesterday, so I decided it would be great to instrument the venue with the sensor platforms, because what we want to do is really demonstrate the entire data science cycle. Start, we believe that big data and important things to do about data reach out into the real world with sensors and robotics and AI and all that stuff's coming down the pipe, but sensors most important in industrial and retail and lots of control applications. So we had people, a whole crack team creating these from Arduino, 50 sensors measuring temperature, humidity, amount of people who walk by, noise level, put them all around the venue. Now all that data was streaming on a wireless mesh network up into the cloud and that's been put up on Amazon and that data would be freely available for people to download and have a look at and try and visualize. Mix that up with the tweets, mix that up with photos you find from the event, with the schedule, we've got data from usage of our wireless access points. So I want to show data science from soup to nuts, right? From sensing to making sense. So where can we see that data? Well, so it's up right now, we're sending in our newsletter, we're about to publish the location for it. Yeah, but it said, I think it's bit.ly.com slash sense lab. Okay. So bit.ly.ly slash sense lab, we'll do it and that's the- It'll show us the outcomes of your- Yeah, capture. Absolutely. We're releasing all the source code on GitHub. We released the model for the enclosure. We 3D printed the cases. That source code's available. So everything's going up and people can download to themselves. It's classic O'Reilly. It's a great job at innovating and finding new ways, making us think about such things. So we're rejoined by my co-host John Furrier. Welcome back, John. Great to be here. I was just walking the hallway going bio break because we're going nonstop. And Charmilla stopped me from ClearStore. She's like, I love theCUBE. You ask really good questions. I go, yeah, I've been around the block. But it's okay. She's awesome. She's truly a tech athlete. It's nice that you know it's great about the collaboration that we have is the keynotes are limited and they're great. They're 10 minutes and they're fast and it forces people to really get their message across. We can go deeper, 20 minutes, sometimes longer. And it's a nice compliment. I'm impressed by her. I'll tell you why. I mean, I thought her keynote was very tight and it laid out the typical value proposition as a stealth mode company. But she has such good experience and she's been part of pioneering work at Kiva. Those application servers, very strong pioneering work there. Netscape, I imploded kind of after she joined but that was all another story. But they did the pioneering work. Opsware, we're doing cloud, that whole cloud thing. So she brings a perspective. One of the things we were talking on the hallway, Dave, and this kind of summarizes the show really is a point that I wanted to make it. The wrap up was that the ecosystem is so dynamic. The Hadoop worlds, they're focused on this little box and they're looking at each other's moves and yet there's a whole huge opportunity that data is creating that is exposed now that everyone is seeing and it's beyond just the competitive movement and space that they see, it's so massive. And I think that they haven't really reflected the competitive strategies yet because the competitive strategy for these companies is no competitive strategy. There's enough room on the beach for everybody. And it's like huge real estate. I mean, do you agree? I agree. I think next year is going to be thrilling, right? Because of exactly these companies like Clear Story coming through, very compelling, that are just coming at it from the other end. They're starting, maybe starting at the business problems and moving inwards, some of them. And I'm really excited by a lot of the new companies. And what's more, they're not from unknowns. They're from real well-known people like Joe Halestine, for instance. Yes. TriFactor, who've been in this game for a long time and really know how to meet the actual user's needs. So, very exciting. You know, I have to laugh because we at Wikibon, Jeff Kelly, our lead big data analyst, last year it took on the sizing of the market. It was a classic sizing exercise. And I laugh because we're working on a premise at Wikibon and SiliconANGLE that practitioners are going to create much more value than the supply side. So a classic supply side so undercounts the value creation that is going on. You're not even going to be able to count this market. We kind of did it tongue-in-cheek. We created some value because there's some market share data in there, but it's actually not countable in our view. It's right, you can count the market if you look at it as an analytic tool market, right? If you look at it the same way you did the BI market, that's right. You can maybe count it, but when you look at the fact that actually big data means a production generating new value, driving whole new business and business units, that's not a countable market in that same way. It's just enormous. The other thing about O'Reilly that I want to point out to the group out there, this is our, I think, third or fourth strata. We've been involved in all the stratas. But one of the slogans that Maureen and Jean and I were talking about is O'Reilly is an integrated media company that work on things that matter. And this data problem that we're having, and this is what Shamila pointed out, is that our own technology has created this data problem. When we were on we were talking about the internet of things and it's here, right? This is a serious problem. So my friend Andy Kessler wrote an update for the Wall Street Journal about computer science degrees back in our curriculum in high school and college. And it's the same math that was around when we went to build the Brooklyn Bridge. And so there was a call to arms for engineers to build infrastructure back in the late 1800s. Now we need engineers to build new solutions to solve this data problem. This is a real problem, right? So I believe that this data geek community is going to fuse quickly with the business community. And strata's kind of just bumped into this, I believe. And I think we talked about in your segment about the bold move of business and geek. And I think this is just the beginning of a South by Southwest like experience where, yeah, there's some cool people, there's some suits, but there they need to be together. That's been exactly what I planned from strata or from the start. And actually, you know, for O'Reilly, that was a bit of a bold move for them at the beginning because O'Reilly typical, you know, the audience you might have seen was developer, hacker, open source convention, another conference I chair. But you know, going after the fact there's business applications need to go side by side. It's not something somewhere we've been before, but it's turned out to be the exact right thing because data is about people and organizations as much as it is about machines. And it's exciting and intoxicating at the same time, but there is a real problem. And that opportunity from an entrepreneurial perspective and companies that have deep pockets have problems. This is like, like we always say the enterprise is sexy, but it's not just the enterprise, it's government, it's society. But the enterprises just have this problem right now and they have deep pockets. So like, I know a lot of guys working on some consumer startup tabs are like, oh, I don't have any traction. Look at, stop what you're doing and stop that game app, that casual game app and move over. I am so excited that people are going to be building startups that do things and seem to have value right now. I love the fact that enterprise startups are really on the rise. Yeah, awesome. Dave, what's your final thoughts on that? So I wanted to, before I get there, I wanted to ask Ed, so what's next? Take us through, I mean, you guys are just, you know, you end and then you start. Absolutely, no rest for me. I know what your head's probably just so full right now, but just give us an idea of what you guys are thinking for the next time. Well, you know, let's look at 2013. We'll be there in Santa Clara in February. A couple of twists that we're bringing in there. I mean, several things. One, going to build on this whole CIO IT organization approach, because that's definitely solid information that needs to be structured and get out there. Second, looking at switching around a bit, how we treat UI and visualization, right? I don't want people to think that just the pretty pictures. Someone this morning said, you know, design and visualization is the entire process. Every single user interface you touch while you manipulate the data is important. So that's going to be called a design track and we really focus on that as a very important issue going all the way through. The other thing we're going to do is have a track called Connected World, which is going to bring together internet of things, mobile sensing, and try and draw that story together. You know, what we like to do is when we sense something is coming up, rather than just put it in a grab bag, we try and find the story and knit it together. We think it's called Connected World, not just the world reaching out into our data centers, but our data centers reaching back out into the world, communicating with us, new UIs, Google Glasses, whatever, make that possible. Ed, we think, we really think highly of you. You've done a great job with Strada, one in working with you and the program you put together. Obviously, directionally correct at this point. Check, golf clap. Let's talk about your next setup. I know you're going to stay with Strada and everything else, but you're doing some other work that I want to make sure we get on the record here, because it's really important. We were talking in the hallways on the day one, you're doing some real in-depth curation and building out of content. Can you share with the folks out there what this project is? I can, yeah, thanks very much. So I'm actually taking on the role as editor-in-chief of a new peer-reviewed journal called Big Data. So this is, you know, some academic, bridging academic, academia and industry. I want to bring the two together to report not only experience, but new research. And the reason is for this, that I think if Big Data is streamed more than a buzzword, more than one of these trends that we reflect, ha, do you remember the big day-to-days? What a bubble. Right? What a bubble, right? Come on, last night's party, what a bubble. But what it needs, it needs some solid underpinnings, right? It needs theories, it needs an integrated approach. There's a lot of work to do. There's a lot of work to do in making this. We know there's a thing here, right? But we need to mark out where all the parts of this story are and in a way that people who are contributing can have a forum. Just right now, if you've got distribute database people, they're over there, right? Social media people are over there. Design or UX are over there. Government are over here. Security's over there. But we know that this is an integrated topic. Yep, yes. And so that's the point of this journal. And also a lot of R&D, people at HP Labs, for example, and IBM and all the top companies, Intel, they have a program where they work at academia, but I've always been critical, it's just been too slow. So you don't have to replace it. You can accelerate it with a bridge. I think that's what your idea is, isn't it? That's it, really, to get that feedback loop between what's really going on and what the research is doing. Quite often what we're having, finding out now, look at Hadoop. Hadoop was deployed for several years before you had academics actually writing papers about what was going on and understanding it. Just to kind of create that culture and sharing, the other thing is you find this really nifty, big data work going on, let's say, in astrophysics or biotech, right? Now these approaches can be transferred. But because they're only published in certain places, they're not out there. You're breaking down the silos. I want to, just like big data breaks down silos, I think this journal can break down silos. You know, at Silicon Angle, one of the things that Mark Hopkins and I always talk about, because I'm one of these students of journalism because I'm not a journalist. I never went to journalism school, but I'm in the journalism business. And I've been looking at the disruption of journalism. And one of the things, if you look at the newspaper business, like the New York Times, for example, everything's organized by the science department, the science section. So you have silos. So what happens is you don't have that horizontal traverse because who makes a story selection for science if it's related to big data. So what I'm seeing is that those walls have to come down and blogging has brought that to the table, but blogging hasn't gone far enough. Most of the bloggers out there, like TechCrunch, Venture Beat, all great for creating new stories, but they don't really say anything. They're not really providing provocative, in-depth coverage. I think there's a real demand for solid, real solid work. Actually, it's kind of a kick back against exactly this breakdown that's happened. There's one thing I wanted to mention to you that I'm excited about, about the Big Data Journal, is that we're publishing open access. So this is important. There's a lot of disruption going on in academic journals. This means that all the research papers are free for everybody to get, right? No need to subscribe to the journal and do that. Open source. I'm going to make them free for authors to publish. So some open access journals require authors to pay to cover the costs. We're not doing that either. We believe that the only way that an integrated dialogue can happen is if the information is accessible to people in industry and you can search for it on the web as to people in universities who've got it through their packages and their libraries. Well, we will certainly cover it on SiliconANGLE.tv because our goal is to cover where all the action is. If it's boring, we won't cover it. If it's a lot of action, we'll cover it, so I'm sure you'll make it not boring. I'm very glad I'm here. That's all I got to say. Okay, Dave, anything else you want to say as to wrap up? Well, I'm very excited about the February strata, especially, particularly the CIO track, because that's my crowd, you know, and they've been, now they're diving in. Lots of planning going on, and they're trying to figure it out, and so I'm thrilled to see you guys guiding that group. Matt Madsen and John Acre are kind of leading the charge on that, so if you know those guys, it's fantastic. Okay, so that's a wrap for strata. We are excited to end an amazing big data week. Started out for us here in Vegas with information on demand. Started for O'Reilly and the team here early probably last week, setting up. I, O'Reilly, did a great job. You guys did good. Great Maureen. Shout out to Maureen Jennings, making it all happen for us and all the great support from O'Reilly, Cloudera, MAPR, top sponsors, and of course, we're excited to share all the content with you for free. Go to youtube.com, so I'm still going to go for all the videos and big data week. My prediction is going to be like the South by Southwest for data geeks, for meeting and intersecting with business. Maybe New York City might be a bit pricey for those kinds of that crowd, but maybe we can get some discount on hotels next time. But, it's been a great week. Thanks guys, Dave, Mark Hopkins, and our new guy over there. Thanks so much. Kenny? Kenny. New guy. Where you going, new guy? New guy over there. You know, we're good. And all the people back at the ranch, Kristen, all the bloggers, blogging away and everything, Art Lindsey, Jeff Kelly, I believe early in Stu Miniman. So everyone, thanks a lot for watching. That's a wrap from Strata Big Data Week in New York City. See you next time.