 Okay, we're back everybody. This is theCUBE, SiliconANGLE TV's continuous coverage of IBM's information on demand conference. We're here live in Las Vegas. I'm here with my co-host, Jeff Kelly. Jeff, I think this is the 100th time we've been to Las Vegas this year, but. It feels like it. But it's good, this is a good event and we've got a great guest here. We're really excited to have him on. Jim Kobielus is IBM's chief big data evangelist. I added a little something to your title there. I'm a chief. But welcome to theCUBE. Woo! And theCUBE a lot, what's not for you. Great to have you on again. Maybe that's inappropriate, but it may go. All right, we're cool, it's just theCUBE. So welcome back. Thank you very much. Pleasure to be here. And David and Jeff, we're your old buds of minds. Yeah, you've had you on before and you're just mentioning this is your first IOD. You've been to many IODs, but this is your first as an IBMer. Yeah, that's right. So I'm a different creature. I had been an analyst and now I'm an IBMer who trades on the fact that he's an ex-analyst. Very nice. So this is day two for us, Jim. It's like day six for you, right? No, it's actually day three for me, three of six. Yeah, okay. So you're, Let me keep you busy. Oh, you better believe IBM keeps all of our employees busy as beavers to keep this show running smoothly. So you, as you were saying, you've been to every IOD as an analyst. You got a rich history as an analyst at Forrester, current analysis, et cetera. Talk about why you chose to come to IBM. As an analyst, you could have, you were famous, still are. You could have chosen so many companies. Why did you choose to come to IBM? People ask me this all the time. You know, I could make some, I could have some flip answer like Ka-ching, but that's actually not true. It's actually not true. When he talks at BS walks, people, you heard it here first on theCUBE. But no, that's actually not the reason. I've been in the industry, you know, people know I'm a graveyard. I've been in the industry a long time and I've evolved throughout my career. And there's, I don't really have a career plan. I sort of follow my instinct about what I'd like to do and the kind of organizations I'd like to work with and for and the sort of things I want to do, the skills I want to gain. And the broadest sense, I had been with a solution provider on two occasions very briefly in my career in the past. And I'm not going to name them and everything. But I thought, you know, at a certain point, I'd been an industry analyst for about 12 or 13 years straight. I wanted a change. I wanted a new challenge. And I'm quite familiar with IBM, the good folks from the infosphere, the web sphere, the T's, the SPSS, Cognos. You name it, I was quite familiar with IBM and all of our products from long back. And I'm quite fond of many of our competitors too in the sense that as an analyst, I consulted to many solution providers and I also consulted to their customers. You know, really, you know, life is a funny thing. IBM knew me and said, Jim, we'd like you to be our big data evangelist. And what that means is, you're a thought leader, people follow you because you say interesting things. And you do research and you're sort of pushing the envelope and oh yes, everybody check, oh no, everybody. This is obviously, God, this is an ego thing. But let me just keep on going here. So they said, well, people read your tweets and your blogs and so forth. And do you want to join us and continue to do those same things but as a thought leader within IBM? And I thought long and hard for about five seconds and said yes. So, we were having a conversation earlier. Jeff, as you know, created the industry's first big data market sizing report. And it was fun actually. It was a little bit of tongue in cheek action there. We said, hey, we can do it. Let's just do it. Let's do it. Why not? Our open source philosophy allowed us to get a lot of really great feedback and take some arrows. But that's, that's what we do. But so IBM was one of the leaders but didn't come out on top. And we were sort of debating. Shame on you. IBM number one. Did we not pay you guys enough under the table? No, I'm just kidding. No pay to play here. These guys have total integrity. Thank you. Just hit edit if you don't believe it. Hit it and contribute. But so here's the reason I'm asking this. So I was reading a Barron's article this weekend about the end of the PC era. And it's essentially saying, you know, Dell and HP are in big trouble and some of these emerging guys, certainly Apple. And then when it got to the big data section, it said big data. And of course EMC is going to do well there. Of course that, you know, hats off to EMC, great marketing. But my question to you is, is IBM number one in big data and why? Well, big data is such a huge area, a huge market or paradigm. You got to start to break it down to components. And each of which is a huge area. Business intelligence, data warehousing, advanced analytics, you know, data governance, you know, Hadoop and so forth. So is IBM number one? Well, you know who I work for. So let me just, you know, break it down into okay, if you look at what the core of big data is. Big data is essentially focused on analytic databases with scalability, with scalable architectures, radically scalable, clearly, to the petabytes for real time to handle multi-structure data and to, you know, those databases and data persistence or data delivery vehicles are optimized to serve advanced analytic applications, statistical modeling, prediction analysis, blah, blah, blah. Okay, if you look at what the core of big data is, first and foremost, traditionally and very much practically in terms of where enterprises have invested, enterprise data warehouses, massively parallel enterprise data warehouses like IBM, Natesa, like the IBM Smart Analyzer, InfoSphere Smart Analytics System and so forth are the core of the big data market and we have many fine competitors and so forth. But if you look at the three Vs, which is what I'm talking about, the volume velocity and variety, big data has been around for a number of years now as a distinct market segment. The name itself has evolved or become, you know, hip in the last few years. If you look at who are the leaders in enterprise data warehousing, well, look at IBM because we have a rich portfolio that I just mentioned. And so in many ways, I'm not going to cite any work that I did previously in terms of the evaluations I made of various vendors, but IBM is very much the top tier of data warehousing and has been since basically the start of the industry. IBM in terms of the new approaches like Hadoop were one of the very top providers that have had Hadoop solutions for the most scalable requirements. If you look at the announcements, just yesterday here at IOD, we've evolved big insights. We've added additional solution functionality that are targeted at particular industry requirements for Hadoop projects, whether it's telco or finance and whatnot. So IBM continues to deepen our product portfolio in all things to do both with the platforms, the tools, but also the tailored solutions for particular business problems on top of data warehousing infrastructure, on top of Hadoop. And of course we have stream computing with InfoSphere Streams. So if you look at who provides not only data warehousing but stream computing and also best debris statistical and predictive modeling, also best debris BI, best debris data integration and governance with the InfoSphere portfolio, you know, so on and so forth. Who is that? IBM by far has the deepest stack of best debris products across most of the segments of what we generally refer to as big data. So really many ways IBM is number one. Now so thank you for that answer, by the way. I hope you have a lot of time here because we could, I have a lot of topics that I want to cover. I have time for you guys and I talk fast, so try me. Jeff Kelly, I want to put you in the spot. So you just heard Jim talk about IBM's strengths. What do you think? What do you think IBM's biggest challenges are in the big data world? I think the biggest challenges, Jim, are you mentioned the portfolio and it is a wide and deep portfolio, but I think what we're hearing from our community members is a little bit of confusion around the, bringing that portfolio together in solutions that are very easy to kind of translate into business value, talk to the business, help them understand who might not be so interested in whether it's Natesa or Big Insights or whatever it may be under the covers, who wants to know how you're going to solve business problems and put those together in a way that speaks to the business. So I think that's one of the biggest challenges, I think. So what do you say to that, James Kobielus? Well, what James Kobielus says, the IBM Big Data Evangelist says to that is, among other things, IBM is highly, yeah, we recognize that we have to continue to deliver and simplify the solution story of big data across different use cases or outcomes. If you were in the general session this morning, perfect example of how we're continuing to do that is if you followed what my colleague, Faruna, I'm sorry, Faruna, Alarakia, you got her name right, her demonstration of the next best action signature solution that we've rolled out for marketing and customer relationship management, perfect example of how we're delivering through a growing portfolio of solutions, quick value on some fairly complex projects that involve the advanced end-links, involve the big data, involve your marketing platform like a Unica and so forth, but in a way that the way she laid it out was beautiful because she actually laid out how the product works in, let's say, a call center environment or in a marketing environment. In other words, what we're doing at IBM is we're doing the solution cell through increasing bundling and integration and tailoring of a product portfolio that in many ways is general purpose. You can deploy our next best action signature solution across a wide range of use cases in customer-centric channels. So we not only provide these solutions, we provide the business analytics and optimization professional services that can help you in a consultative fashion to assess, first of all, what are you trying to deliver in terms of value in a particular application? What set of tools and components and platforms are key enablers for that? What offerings do we provide already as it were quote-unquote out of the box, I'm going to use that in air quote, that not only contain, incorporate those components, but also bundle in the business content, the predictive models and the business rules and the orchestrations and so forth that are tailored to your specific needs in your industry or your specific need in the business process that you're trying to say automate or make more agile, you know, be it finance, be it marketing or whatnot. And so we work with customers to the whole way in a consultative fashion to make sure that you realize that value and we have domain experts in all these areas I described that we can bring to bear on those kinds of engagements. If the customer wants to go there, we don't force them to use us for professional services. If they have all the expertise in-house, we have solutions. So we can go, we have a wide range of partners we can bring into these kinds of engagements as well to flesh out the overall value story, ultimately focused on the customer. So that's what we're doing, you know, we've been doing for quite a while and I think we do a really good job of probably better than most of our competitors on the solution sale or the solution value proposition from the very start driving the whole engagement. And what about it kind of engaging with smaller customers? I mean, I think certainly, you know, the 4 to 500 enterprise, think of it as IBM customers. What about the SMB, the mid-sized organization that thinks, well, this is really interesting what IBM's doing, but, you know, we can't afford that. That's not in our, we can't do that. It's just not going to work this year, even the next few years in terms of the finances. Well, of course we have a broad range of small to mid-market tailored solution packages across most of our product areas. In fact, we had an announcement yesterday of an SMB focused offering. I urge you to look at the press release on that. I did a blog, in fact, last night. What I'm saying is that we are very attuned to making sure that we have the right solution tailored and priced and licensed appropriately for each market segment from large enterprise to small business. We have cloud offerings for small and mid-market. We have, you know, expert integrated solutions for a wide range of sizes in the Pure Systems product family. So we, you know, at IBM, we want to make sure that we can deliver value to you in a way that won't break your budget and will help you to realize our why on that overall project. So we have, I think we've gotten better in recent years about focusing on the smaller customers who really in many ways drive most economies because most startups, startups by the very nature, start small. And at IBM, we want them to be an IBM customer from the get-go. And so we've got to give them, you know, favorable pricing. We've been talking about going down to Strata this week and totally different conferences, even though a lot of the- It's a great show. I love Strata. I wish they were holding theirs on a different week. I would be there. Yeah, I mean, I'm sure you would. And of course, now it's Strata plus Hadoop world. We should mention that because this was originally Hadoop world and it sort of morphed into Strata and Hadoop world. But the conversation there is similar, but there's a stark difference. And one of the big differences is people will constantly ask the question, what are mainstream businesses doing with big data? Now, you don't hear that question so much here. I mean, you hear it, but a lot of people hear walking around in suits, a lot of business people. And we've predicted, many have predicted, it was pretty easy prediction that the traditional BI, data warehouse worlds, the analytic worlds, the legacy worlds, if you will, and the new Hadoop worlds are going to collide together. And that's clearly what's happening this week at Strata. But I wonder if you could give us your angle on that. I don't think it's so much collision, Dave. I think it's the fact that the new worlds of Hadoop and those sequels and so forth, graph databases and the like, are the nucleus of how, where the industry is evolving into. A great many data warehousing solution portfolios including ours, integrate out of the box now with Hadoop, whether it's Apache or Big Insights. In fact, I'm speaking tomorrow, I'll plug myself. I'm speaking tomorrow on how Hadoop Big Insights can fit into or factor into your data warehousing strategy with, and I'll be discussing particular deployment models for Big Insights in a data warehousing context. That really highlights something that I, was a big theme of mine prior to joining IBM and it remains one of my core themes, which is that Hadoop in many ways, you can see it as the nucleus of the next generation enterprise data warehouse in the cloud. You know, when I use the word enterprise data warehouse I have to do that in air quotes because that term is an old term. You know, now we have cloud analytics, comprehensive cloud analytics, I just blogged on that this morning. So in other words, the terminology itself, let's not let the, or big data as a term, let's not let that get in the way of understanding the new patterns of delivering solutions, analytics and data into new types of applications. And by the way, when I said, Colada, I didn't mean in an antagonistic sort of competitive way, I really meant it in a mashup way. So those two worlds coming together. And that's really what we're seeing. Oh, definitely mashup and interpenetrating. In fact, we have, we IBM, in fact, in our team specifically that I am on, we have people at the strata Hadoop's world this week and because we can't afford to miss it, we're a big enough vendor that we, we can divide and conquer as it were. Most of us are here though. So I'd love to get your perspective on this. So it seems like you got, you know, get that Hadoop layer and patching Hadoop. Great, all good there. And then you get the applications and we'd love to see more going on in applications. And it seems to be, you know, getting some traction there. There's really interesting battleground in the middle now. We saw MapR introduced a new platform today. We saw Hadaap last week, you know, Cloudera's got something coming, Hortonworks and Microsoft announced some stuff. And Teradata came up with something. Teradata and Astrodata announced and Continuity Software is announcing there's a lot of action going on in the middle. Can you talk about that a little bit and help us squint through that? In the middle. What do you mean? I want to know what you mean by the middle. So you got the Hadoop layer, right? It's open source. You got the application layer up here. And then in the middle, being the sequel and the NoSQL guys coming together, you got, you know, Cloudera trying to add value. You got Hadaap now bringing in some new infrastructure. You got MapR doing its thing. There's just a lot of innovation going on sort of a land grab going on for that. Like what I'm calling the middle space in between the app layer and the core Hadoop infrastructure, HDFS. Yeah, you know, I would interpret the word middle in this context to refer to the tools and the prepackaged models and algorithms and libraries for MapReduce and R and so forth. And the vendors who specialize in providing tools for modeling and managing and optimizing and doing governance on big data and doing search and all that stuff. Protecting it is another big thing. Yeah, the whole middle needs to be continued. What we've made and continue to make deep investments in the quote unquote middle in IBM research. And, you know, for example, big insights continues to evolve. In fact, we have announcements this week on new functionality there due to our deep investment ongoing in building out all of those tools and making it all work together more seamlessly. Not only within, you know, the Hadoop universe, but Hadoop is just making it work together seamlessly with your data warehouse with your existing data integration or ETL tools and the like. So in terms of the middle, you know, there's a huge and very interesting space of vendors, many of whom are IBM partners. For example, KarmaSphere on the modeling side. You have a number of others like revolution analytics on the advanced analytics with R, so forth. At IBM, we partner with a great many of them. We ourselves are doing investments in all those areas. We are evolving our portfolio, especially the big insights, but also InfoSphere streams, to work out of the box with the middle layer of tools. Which is the layer of tools and infrastructure and services you need to make big data more robust, more scalable, more manageable, easier to do root cause analysis, easier to ingest the data. Like data click, for example, we announced that the other day, you know, more user friendly. So you don't need to have to be out, you don't need necessarily to hire expensive talent off the street who've got some grounding in MapReduce that it all just sort of works out of the proverbial box. That's what I'm describing there is really, in many ways, the focus of our ongoing product development and partnering in this whole evolving arena. We're getting a hook, but I have to ask you the one last question around the whole database space. Three, four, five years ago, you'd go to a party and somebody said, I'm in the database business, and you go, oh, I'll pour you. And now the database business is like the hottest thing going. It used to be boring. It used to be boring. And Sybase is now a mobile play for SAP. You got Oracle and IBM doing the urinary Olympics around who was first with multi-tenant databases. You're an area Olympics. I love that. Because IBM was first with a multi-tenant database, folks. Oracle did not invent a multi-tenant database for the record, but now you've got a spate of NoSQL guys coming out and some unbelievable innovations there. What's your angle on what's going on in the database business? And then we'll break. Yeah, I'll try to keep this really brief. This is the golden age of database innovation. You know, all the NoSQL by itself is a humongous catch-all for key value stores and graph databases and columnar and memory and whatnot. That is hugely hot. And clearly not only are we monitoring and doing investments and we're continuing to do, as it were, surveillance of that space. Because IBM makes strategic acquisitions. We recognize that there's probably some areas there that we're not the innovators on. That, you know, we bought Natesa. Natesa was an innovator in data warehousing appliances. We reserve the option of, you know, pulling out our checkbook when it makes sense strategically for us. It's a hot space. IBM writes checks and code, folks. But not physical checks. I don't know. Maybe Ginny Rometti does, but I do. All right, Jim Kobielus, thanks very much for coming on theCUBE. I wish we had more time. It was a fantastic segment. All right, keep it right there. We'll be back with our next guest live from IOD in Las Vegas. Keep it right there.