 Hi everybody, this is Dave Vellante of Wikibon.org, and this is theCUBE, SiliconANGLE.tv's coverage of IBM's Information On Demand Conference. For those of you who weren't able to watch the show yesterday, IOD is really a show that's evolved over the years. It's IBM's premier software event. The software group here at IBM is led by Steve Mills. He's the chief honcho. Many at IBM thought that Steve Mills would be in line to be the next CEO. Ginny Romady actually became the next CEO, but Steve Mills, many people believe, is the heart and soul of IBM's transformation in the software business. I've known Steve Mills for a number of years. He's a super geek, but also a tremendous business person, and this event really has been about the manifestation of IBM's strategy over the last several years, bringing together not just the traditional transactional systems of the likes of DV2 and then later on InformX, but really bringing in the analytics component of IBM's business, so the Cognos acquisition, the Nates acquisition, more recent acquisitions like Vavissimo, who we heard from yesterday who does unstructured data search. Now I'm here with Jeff Kelley. Jeff, welcome back to theCUBE, my co-host today. Thanks for having me, I appreciate it. And John Furrier, of course, our other colleague is flew the red-eye last night, is in Strata. He just landed in New York. A lot of biz dev going on down in Strata. A lot of people setting up. The Cube is on its way south from Massachusetts, and so we will be broadcasting live from Strata tomorrow, Wednesday, and Thursday, but we're here all day today at IOD. As I was saying, Jeff, this conference is really about the transformation of IBM's business. It really is an information management conference. Information management is a topic that is kind of boring, actually. It's all about governance and the federal rules of civil procedure and things of that nature, and things that, frankly, aren't that exciting. It's about general counsels and information risk and how you defensively dispose of data. It puts a lot of people to sleep. At the same time, it's very important because if you don't handle that properly, you're going to be subject to lawsuits and the like, and we've seen a lot of very high profile lawsuits to that effect of people who've had to pay huge fines. But, Jeff, you follow this business very closely. IBM has really one of the leading, if not the leading portfolio in big data analytics, and this show is all about big data. IBM has used the term that Thomas Watson coined of think. It's IBM's mantra, and they're using the term, Jeff, think big. What do you make of all this? You know, I think, first of all, like the slogan, I think it works, but I think really what we're seeing here is the, we're beginning to see the culmination of all this work around, IBM's been doing around acquiring analytic companies. They spent over, I think, 15 billion over the last several years acquiring, it might be up to two dozen or so, analytics-focused companies. So, the big job, of course, is to integrate that into a cohesive big data portfolio. And I think one of the things that IBM's been knocked for recently is, indeed, as you said, certainly has a very comprehensive portfolio. It pretty much has its hands in just about every type of analytic function. The issue around, with customers, I think, has been around a little bit, around confusion, around exactly how to bring that to market, how to package that in a way that makes sense speaks to the business, who isn't necessarily concerned with each individual component, but wants to know how big data and analytics is going to solve real business problems. So that's kind of been, IBM's challenge, in my opinion, has been really kind of knitting that cohesive portfolio together into products and solutions that can be delivered and translated into the business value. So a huge part of IBM's success, Jeff, still, even in software business, relates to its mainframe business. I mean, it's got huge margins on those mainframes and huge margins in the software and services that it provides to mainframe customers. At the same time, it's strung together a portfolio, assets like Cognos, SPSS, Vivissimo, Netiza, who are some of the other ones that really are driving their portfolio? Talk about that a little bit. Yeah, I think, well, you mentioned a couple of big ones. So Cognos acquisition was in the around 2008 timeframe, and that was when we saw the major consolidation in the business intelligence space with business objects going to SAP, Hyperion gobbled up by Oracle. So there's been a lot of pressure, I think, on IBM to make good on that acquisition. And Netiza's really the other big piece, I think. We've seen in the last several years, maybe the last five or so years, the development of what we're calling kind of the next generation data warehouses, which take advantage of MPP architecture, data compression, columnar architectures, to really drive really fast, deep analytics. In addition to Netiza, we saw, obviously, there's Vertica, since acquired by HP, Green Plum since acquired by EMC, and Aster data acquired by Teradata. So really, that's a very important part of their big data platform, and really one of the underpinnings along with their big insights platform. So I think what's key for them is to continue to show the results, show the business value that can be brought to bear now through their pure data line and other products. We had Rob Thomas on yesterday. Rob Thomas is the group vice president for the information management and the software group at IBM, and heads up a lot of the M&A. He actually did, was the executive, led the Netiza acquisition. I asked him, why did you buy Netiza? You had the pick of the litter. Really, IBM was the first company, Netiza was the first company to go. We saw subsequently Vertica go, Aster data went, and so forth, Green Plum. And I asked why, and I thought he was going to give me a technology answer, Jeff, and he didn't. He said it was the people. I got to know the people. They delivered on their promises. They executed, obviously they fit into our strategy from a technical standpoint, but it was really the people. Rob talked about what IBM looks for in an acquisition. They look for team. They look for traction, and obviously, yeah, technology, but it didn't start with the technology. I found that very interesting. Yeah, it was interesting. I think, from my perspective, I think that's really telling because they were not looking at this as simply a tactical acquisition, trying to fill a gap. They were looking at this, how is this going to fit into our larger portfolio in terms of our approach to analytics? That said, I think there were certain technical aspects of the Nantesa line that was probably attracted to them, and I think one of those things was the appliance model. Really, it started to really take hold in the data warehousing market several years ago, and Nantesa was one of the first analytic databases to really start packaging their products with pre-configured hardware and these kind of really easy to install, drop the box into your data center appliances. And we've seen that now evolve into the pure data systems, again, taking that kind of that approach with all the hardware and software in a box delivered, ready to go. So, we've talked a lot on theCUBE on SiliconANGLE and Wikibon about data becoming the new source of competitive advantage. People being able to actually get insights out of data is what it's all about, creating business value from data. And I've often been very critical of the notion in Nick Carr's book, does IT matter that the premise of the book being you cannot gain sustainable competitive advantage from information technology, complete nonsense in my opinion. However, it did underscore symbolic shift in spending within IT that CEOs really had an attitude that IT is this big sucking sound after Y2K. Now, having said that, we really do believe that as many have said, data is the new oil, it is the new source of competitive advantage, and Jeff IBM has really tooled its business, to talk about smarter planet, but really the whole data analytics business. Now, you earlier this year did the industry's first market sizing of the big data market. You came up with about a $5 billion market size for 2011, growing to 50 billion by 2017. And you did a market share estimate. Now, of course, granted, these were rough estimates. First of all, you got to define big data. It's a fuzzy definition, but you really did a great job in trying to figure it out. IBM came out number two, and I've been thinking about that. I went back and looked at it. I think IBM is actually number one in this business. I think it's bigger than HP. Now, HP was bigger only because it had the vertical acquisition, but IBM has more assets than HP and big data. What do you think about revisiting that? What's your sense? Do you think my premise or my gut instinct is right that IBM is actually the biggest in this business? Do you think that's valid? Well, I think there's no question they have the broadest portfolio number of products, and certainly with their services organization, are doing a lot of business around what now is called big data. Perhaps maybe a few years ago, they were getting started in that space, but really wasn't called big data. You mentioned the whole smart planet initiative, and that really at its foundation is about making better use of data. And in this day and age, that means big data. So I certainly think it's possible. I mean, we're definitely going to revisit that report. It was neck and neck between IBM and HP because they're the two largest companies, so of course they're going to just by their sheer size. Right. Again, depending on how you define big data, but they were right there, and I think that's going to be an interesting, part of it's a definitional exercise. The other is the portfolio. Now, the other thing I want to talk about is, we're going to be at Strata this week. A lot going on down there, different event. This is a business event. A lot of business partners are here. We've heard from many of them. A lot of guys walking around in suits. A lot of business being done. This is a classic IBM, and of course it's the transformation of IBM. So it includes a lot of legacy businesses, a lot of DB2 businesses. You got people talking about IMS even here at this event, as well as some of the new emerging folks, and you've got some startups. We're looking at the couch-based booth, for example. The Tableau booth is here, for example. So there are some new and emerging companies, but Strata Jeff, it's all about the startups and the new and emerging companies. It's Cloudera, it's Hortonworks. Certainly Tableau will be there. Couch-based, the guys from Squirrel there, the Hadaapt data stacks, and on and on and on. And certainly IBM will be there, and NetApp and EMC will be there, with Green Plum and HP will be there, but really it's a show about the small guys and the innovation, right? Absolutely. So what do you expect there at that event this week? Well I think there's two areas, well three actually, that I'm really interested in seeing. And anytime you go to a Strata, and let's not forget Hadoop World event, now Hadoop World is now basically a co-event with the Strata Conference in New York City this week. But anytime you go to one of these events, it's all about the ecosystem. And so you're going to see a lot of partnerships. The nature of this ecosystem right now is there are a lot of startups that are focused on discrete parts of the big data market. But the reality is to make big data work in the enterprise, you've got to knit these together. So there's a lot of partnerships happening between the Hadoop distribution vendors and the data visualization vendors, and the more relational database, traditional type vendors. So you're going to see a lot of partnership announcements. But I think the more interesting thing, from my perspective, we're going to see, from what I'm hearing, a lot of talk about real-time components or real-time capabilities, I should say, making their way into the Hadoop stack. And when we say real-time, we should define that. And that doesn't mean streaming type of real-time analysts, but we're talking about SQL query type of real-time, query the database, get an answer in sub seconds. So we're going to see some announcements around that, and it's going to be very interesting to see how the ecosystem and the community responds to that. Okay, we're going to talk more about that today. There's other stuff going on. Apple's got its iPad mini announcement. The stock market's all red today. DuPont, 3M announced. IBM, of course, announced, I think it was last week, or a week before I can't remember now, and announced slower revenue growth. A lot of people are concerned about the economy. The debate last night, people are saying, no matter who wins, it's bad for the economy. Obama's going to raise taxes, and Romney's going to start a trade war with China. So the market is sad about that, and S&P is pressuring downward, so maybe talk about that a little bit, but we're here at IOD, this is theCUBE, SiliconANGLE.tv's continuous coverage of information on demand. We'll be right back with our next guest, Bill Hartman, who's the president of Terra Echos, a very interesting company, who portions of its IP were spawned out of the US Navy. We're going to talk about what they're doing to actually take data and turn it into value. So keep it right there, we'll be right back.