 Live from the Mandalay Convention Center in Las Vegas, Nevada, it's theCUBE at IBM Insight 2014. It is your host, Dave Vellante. Hello, Mr. John. Hi, buddy, we're back. This is Dave Vellante and this is theCUBE, our live mobile studio. We go out to the events. We extract the signal from the noise. John Furrier and I have been going all day today. We'll be here all day tomorrow as well. Jim Kobelius is here. He's a big data evangelist at IBM. Former analyst from Forrester. Jim, it's great to see you. Always, always a pleasure. I always have a great time with you guys. I love you guys, like you're my brother. Sorry, we're family here. We're family. So, you know, the Insight, interesting. Give me a second of AR or AV, whatever these things. I think it came off my ear. All right, so while they're taking care of that, so the IBM, let me set it up. So the IBM Insight show is sort of an evolution from IOD, which is this sort of compendium of different parts of IBM. It's really come together with the analytics business and Insight, it's a very powerful name. And so, how's that working out for IBM? It's working out great. It's always been a great show. This is my ninth straight IOD slash Insight, believe it or not, my third as an IBMmer. And I'm not actually BSing. It was my favorite vendor show before I became an employee of this vendor. And it's retained its core value to the ecosystem in terms of its several days of just jam-packed announcements and tutorials and sessions and meet and greets and deeper conversations that customers walk away, analysts walk away, partners walk away thinking, I got something out of this event. It's worth coming to Vegas. It's always been an interesting show because it had a mix of a lot of different eclectic businesses that the big data meme sort of created a confluence of those, right? You know what I mean? The information management and data governance. And analytics. I've always had all that stuff. We've always jammed all that stuff into IOD slash Insight. Now there's just more stuff to jam in there. Well, but it seems like the connection points. We're diversified. But don't you think that, this is maybe just my perception, the connection points seem to be more logical now. And I think more thematic around data. Yeah. I think we're doing a better job than in years past of wrapping them all into fairly organic themes that make sense. And now it's cloud and engagement and big data and so forth. And you know, you caught the general sessions this morning in heat, tied it beautifully together as did Bob Bicciano and others in a way that's, it really hangs together. We make a lot of strategic acquisitions. We do a lot of organic development. We have disparate product teams working on different things. And so we announce them all. You hear it, you know, many of them here at Insight. And they hang together as a unified product portfolio really nicely. IBM has a good, does a good job. But I can see now from the inside of getting to the product teams to actually, you know, write, basically essentially, like I regard as composable applications within a broader, sweeter platform story. It was interesting. We were at Hadoop World last week. We were running our own sort of event within the event. And of course, IBM has always defined big data as a super set of Hadoop. But of course, when you're at Hadoop World, you get a lot of, you know, Hadoop, you get a lot of yarn, you get a lot of spark. Yeah, when you're at Hadoop World, and Hadoop's a great technology, obviously, and it's a lot of our customers have adopted it. When you're just a Hadoop vendor, everything is a Hadoop problem. And Hadoop's going to be the center of the universe of big data. And it's obviously not going to be that way. It's not that way now. It's a hybrid world. Well, but so the point that is that when you walk the floor there, the average age is sort of trending toward my age. So it's almost like the enterprise is coming into Hadoop or the Hadoop's getting dragged into the enterprise. And as a result of traditional data warehouse, BI tools, data integration tools, that's where the conversation was centered. Not no surprise to you, I presume. Market matures when there's nothing but gray beards like Dave and me at these shows. So that's a good indicator. Just go there and take photos of the average hair color of the attendees and you'll know if that market's maturing. But still, like John, more startups than you've ever seen before. It's every year, first of all, I would agree with you. It's one of the best shows because from a vector standpoint of the market, it's always been relevant. I mean, big data, you guys have always had a good vision on the track that you're taking and never wavered from it, right? And all Wall Street kind of concerns sides, there's money in those hills, big data. There's money in insights, as Bob Pasciano was talking about it, is that there is value in insights, not just business improvement. So there's a new generation, this new, I like his word, generation D for data, the new millennials or whatever you want to call it. So the meat's coming on the bone, as we always say, the sizzle and the steak. You know, every year we've been here, it's always been pretty much right on track, you know? It's hanging together kind of like that, you know, suited Nordstroms on the rack, you know, I want to buy that product. What's new? Obviously the cloud and stuff's yielding some fruit. We saw it's a-DB and we saw data works, all this stuff being announced in, he kind of teased that out. What is that fruit coming up that you share with the folks out there that's specifics of what's flowering from this event? So the flowering from this event are dash DB. We've announced our cloud in memory data service that incorporates DB2 with blue acceleration and it's available right now as an on-demand self-service data warehouse in the cloud. You know, it's a page ago cloud model. And so it's very much the technology, it's mature technology, it's DB2, it's blue. And it's for the new world of data warehousing where some customers say, well, I'm not, I can't justify a capital expenditure, maybe it's because it's a soft economy, but I can definitely justify operating expenses in terms of going and subscribing to a data warehousing service in the cloud. So that's the nature of, you know, in the data warehousing industry, it has moved towards a multi-form factor world in terms of it's not just software and commodity hardware, it's not just appliances. It's all of that, it's also the cloud option for small to mid-sized businesses and for others who, for various reasons, you know, that makes sense for the amount of price performance basis. So the thing is, IBM, we've put all of our databases and all of our data platforms into the cloud now in BlueMix, we have, most of them are in production, a few of them are still in advanced beta, but regardless, we've moved all our entire solution portfolio into the cloud in a major way and that's why that's the dominant theme of this showing will be in subsequent shows because it spans our entire portfolio of not just data but also analytics and applications. They've got the Watson developer cloud and so forth. People are taking these cloud platforms and they're building their businesses on them. It's not just small to mid-market, but it's also large enterprise customers moving deeply into clouds. Yeah, we had a great chat with Bob Papachiano. He loved talking about the sports analogies, but he's talking about like, you know, try to go for the single, try to go for the double, but he brought up something I want to ask you because he brought up this concept of, you know, good teamwork, what approach should people take and he brought about this IT and business team should team up together and have that kind of New York Giants kind of feeling, aka the World Series, to come back if you will, but there was also a comment on the crowd chat that Thought Leaders just had this at 12 o'clock, Brian Fonzo led the group and the question I want to ask you and related to what Bob was teasing out, how is analytics and big data affecting the relationship between IT and business leaders? That seems to be the big dynamic. I mean, we have data, I would keep on that show that, you know, IT gives themselves good grades in the Hadoop area, but this is like, hey, where's the beef? So there's the collision and dynamic between the teamwork involved. What's your thoughts around that, that relationship between IT and the business groups? Well, cloud and SAS options give business people the means to acquire the capability on their own without necessarily having to go through IT because you can get it on the IBM cloud or of any other public cloud. The same capabilities that in the past you've had to go to your corporate IT to provision for you. So it's created a bit of tension, but then again, IT is working hard and they're stretched thin, trying to deliver on lots of different projects and maybe it makes sense in a lot of organizations that have large IT staffs for the business people, the business units to acquire these capabilities on their own with IT's blessing. So the IT is not burdened. They don't have to hire the people to manage the data warehouse if in fact it's in DB2 in the cloud. As long as whatever the strategic provider of the cloud data warehouse is approved by IT and meets all the 24 by seven availability and all those requirements of an enterprise grade data platform. So I wonder if I could follow up on that because you're seeing obviously the cloudification or the SASification of all kinds of businesses IBM has acquired, I don't know what the number is but it could be hundreds of SAS products. Certainly dozens. And now you're sort of placing all those into the IBM cloud platform. I think about an initiative as complicated as say Oracle Fusion and how many years that took? Nine, 10, maybe it's still going on. What's IBM's approach to bring together those worlds? Blue Mix obviously plays a part but can you talk about that strategy? The strategy to put pretty other which worlds on? So you've got all these disparate SAS platforms and presumably IBM's bringing those into its cloud platform. Or maybe not. Maybe it's saying all right, just go run whatever cloud you want. We have one dominant cloud platform, that's IBM cloud, we have soft layer. Sure, that's what I'm saying. So you bring it into soft layer. It's a platform in its own right with its various layers and it's all, so in other words, we don't have multiple cloud platforms, we have one strategic platform. All of our products are going into that cloud platform or available through the IBM cloud market place. That doesn't happen overnight, right? No. I think maybe it's not hundreds but it certainly dozens of SAS products in various industries, retail, manufacturing, financial services, et cetera. But we didn't build IBM overnight anyway. It's over 100 years old as a company and so it's like clearly one year after another you make a strategic acquisition, you do organic development and so forth to build up an extensive portfolio that hopefully is meeting all customer requirements with your best to breed offerings. And when now that we move into the cloud we have to pick and choose in terms of, okay, which of our technologies are best suited for bringing into the cloud and which ones, older ones maybe are not so well suited and in some cases, we go out and acquire a strategic platform like a Cloudant that fills a specific need, in this case a NoSQL, JSON capable data platform for a lot of these new challenges in the cloud. So, in other words, going forward we evolve our portfolio to make it cloud ready to enable cloud first development of all applications. So what do you tell a customer that's got multiple IBM SAS offerings? And I'm going to say I'm a software customer. Is it sort of case by case as to how rapidly they get onto that platform and how about is integration an issue? Do I have to worry about integration or is it sort of running them as bespoke clouds? Well, first of all, we'd say to those customers, thank you for being an IBM customer. Okay, you're welcome. Yeah, okay. Now, let's say I want a common data governance, common security model, common provisioning model. I want a single interface to all those. That doesn't happen overnight, presumably. Well, we'd say it can happen overnight if you decide to put all of it into IBM cloud. We offer those services within the IBM cloud and not available to all the applications that are running in that environment. So how far in our, I mean, where are we today? If I go all IBM, if I go all blue with all those SaaS products, do I have that nirvana today already? I'm going to scale a one to 10. How close am I to that? I'd say you're about a seven. Okay. But then again, I'm not in the specific cloud business unit. I can bring you up to speed on how far along we need to go. So I'm going to punt on that one. Fair enough. I'm in database marketing, by the way. All right, so let's talk about, let's talk what the service fits in part of that. Well, you brought it up. Yeah, yeah, very much so. Cloud thing, which is really awesome leverage. So cloud business models today are all about land and expand. That's the buzzword. And you're seeing successes out there. Tableaus, Splong, others have come out and born in the cloud. Land and expand. I like it. I haven't heard that. Land and expand, you know, you grab a premium. The idea of coming in and spending a huge upfront license really is not compatible with how the cloud rolls out. You know, cloud has seen that success database as a service. So that means kind of the value is critical. So talk about the business model aspect of customers. Are they ready for that kind of consumption? Are they dictating that they want to consume the technology on that kind of, not freemium, but like pay as you come out, you pay by the drink, whatever you want to call it, but land and expand is the kind of the buzzword for the business model. You invest in some sales, get a position. They like it, then expands more to the different groups. Certainly shadow IT has grown that way. You know, what's interesting is now cloud is not a try before you buy offering. A few years ago, cloud wasn't yet mature as an approach for acquiring these technologies. So it was a try before you buy proposition from the customer's point of view. I don't think there's that perception anymore. I think cloud is so mature in the buyer's mind, in the customer's mind, that many of them, more and more of our customers are saying, well, cloud could be our strategic platform for whatever it is they want to do in the cloud. So this land and expand capability of the cloud is very appealing to customers. In terms of big data, the customers who want to do big data don't necessarily want to buy petabytes worth of storage and manage it all in-house. They want to scale up and provision that storage as needed and then scale it down when it's not needed and you can only do that in a cost effective way, in a cloud environment. That really describes the world of big data that many of our customers implement, which is that big data is not really about huge amounts of data. It's the scalability to scale up and down and out as needs change. To put some data in the cloud and keep some behind your firewalls. To put some of your workloads in the cloud and to keep some on your private, in your data centers and to mix and match public and private cloud segments based on various requirements, be it security, be it changing workloads and so forth. Customers want that flexibility to the flexible deployment capability that a hybrid public-private cloud offering like IBM offerings enable. That's really the way customers are going. James, what have you learned over the past year? And since we last talked here at IOD now, it's called Insight. What have you learned over the past year? I know you guys are very active with outreach. You're always talking to customers of great client base, obviously IBM. What's different this year? What are the new data points that you could highlight in terms of what's trending in the customer's mind? I see a lot of different use cases, but in general, what are the thresholds that you're crossing over that are really critical and on target for what they want to do? Well, what's hot in the customer's minds is simply speed, speed, speed, speed. And so in memory now, in many ways, the customers now expect in memory speed of thought, capability and whatever data platform they acquire. Which is why DashDB, for example, it's got blue acceleration inside. So it's DB2 with blue acceleration. So it's in memory, analytics and decision support and so forth, analytics for your mainstream data processing, your mainstream business intelligence and so forth. Customers expect that. It's the world of batch processing. So speed is number one. Yeah. Automation, orchestration, these are the buzzwords. But yeah, I don't know if it's a buzzword in the minds of the technical customers is in database analytics, which is you're executing your workloads inside the big data platform. Cause you have the scale of billing terms of parallel processing, but also you have the deeper, the deep libraries of algorithm, machine learning models and so forth that need that CPU, that need that MPP massively parallel processing capabilities. That relates to another key buzzword in the customer's minds which is machine learning. Machine learning is the heart of cognitive computing. So customers all over the map, the globe and in different industries for various applications are doing machine learning which is at the very forefront of cognitive computing. It's finding patterns in the data automatically through unsupervised learning which is customers are realizing they need to do it like that. They need to automate more of the pattern detection in large data sets because you can't hire enough data scientists, qualified data scientists to handle all the machine learning workloads that are coming down the pike. They're gonna have to be automated to a greater degree. So customers want automation, they want machine learning, they want deep learning and deep learning is machine learning but machine learning with artificial neural networks that's geared to extracting patterns from streaming data, streaming media, video and audio and music and so forth. In fact, that's another buzzword is streaming. We have InfoSphere streams and so forth. The entire world is streaming now. Everything streams. It's not just music and entertainment. Clearly it's all of that but it's also a lot of internal enterprise applications. We use a lot of streaming internally and IBM for training and education and whatnot. Customers want a big data analytics environment in the cloud that can do deep learning, can handle streaming applications with real time low latency capabilities. They want these capabilities on demand. They want these capabilities on demand to handle shifting workloads, deep learning workloads and machine learning workloads that come along. And a lot of it's security related. And find those patterns. Those patterns that might be indicative of fraud and so forth is something that has to, you're talking about multi terabytes of data all the time that need to be sifted and sorted by automated programs in the cloud. That can only be done with deep, I mean really best done with deep learning technologies. Inheachusa was at TED at IBM in San Francisco and she teased out this concept. She didn't do a drill down but she did introduce this notion of active data. Active data is really relevant in the real times you mentioned streaming is really hot right now. And that is actually a really important data source for machine learning. And we had Kurt Warren on earlier who just talked about machine learning as a fabric and applications can drop out from that robot as operational analytics and so on and so forth. So if machine learning is going to be a key ingredient, the brains, the heart, the nervous system of this new application engines of innovation. Talk about active data and what does that mean and how should people think about what active data is? Certainly in the moment programming the keynotes about live events. I actually hadn't heard, actually I hadn't heard any say that. Maybe I was eating lunch during the period when she said that but I'll tell you what my interpretation of active data is. I heard that like who? Yeah well you know my interpretation and I think I saw him he's just a little while ago. I think what you meant is a real time data that's actionable by an end user for some specific very pressing requirement they have now it may be geospatial in nature in terms of you know power and connected cars so they don't crash into walls you know whatever and so forth. So active data is data that is actionable and it's actionable in the moment. It's actionable in every situational context in which the user is or maybe moving you know in real time. So with that said we're talking about real time, we're talking data, we're talking about delivery of the data into all manner of increasingly mobile applications. Mobile another buzzword. More and more application development is done purely and simply for mobile applications on iPhone for iOS and so forth that is becoming you know mobile application ecosystem is really driving the world economy everywhere. Everything that humans do now and all aspects of their lives is enabled through mobile applications that just understand you as well or better than you understand yourself, understand where you're going or unlikely to be going give you the decision support and the guidance that you need. It's not decision support in the old BI sense it's decision support in the you know turn here and do that sense where you don't actually have to consult a dashboard rather it's your advice by you know. Well you guys are certainly doing great work Watson. Watson is a game changer certainly in the business side but even in the news today IBM has used data to fight Ebola on CNN's carrying a story today about that. Certainly we got the coverage of SiliconANGLE to the cloud and in the data center future of big data, big data 2.0 I actually think it's more like 3.5, 6. I hate this numbering schemes on Paralyze. Paralyze would have numbering schemes guys they're not products. Big data 2.0 was two, three years ago come on we're way beyond that now maybe a point release. You know like existentialism what was that? Was that like Play-Doh 2.0? I don't know. I totally agree. I just think it has to be relevant so certainly you guys are and then again the CNN story carrying that's pretty relevant. I mean that's exactly what we're talking about solving problems, good decisions at the right time. Hopefully that'll change. Thanks so much for coming on. I appreciate it. J.S. Cobalus with the big data evangelism really analyzing the market with us here inside theCUBE. Special presentation inside the social lounge where all the thought leaders are gathering a big part of the digital experience here with the folks at home. Thanks for watching theCUBE. We'll be right back with our next guest after the short break. I'm John Furrier with Dave Vellante. We'll be right back.