 Live from Las Vegas, Nevada, it's theCUBE at IBM Interconnect 2015. Brought to you by headline sponsor, IBM. Okay, welcome back everyone. We are live in Las Vegas for theCUBE, our flagship program. We go out to the events and extract the seeds from the noise. I'm John Furrier with SiliconANGLE. My co is Dave Vellante, chief researcher at Wikibon. We are live at the GoSocial, social media lounge. We're interconnectgo.com is the website you want to go to for the digital experience, powered by CrowdChat, powered by the CrowdChat platform, VIP influencers, all the amazing crowd activity, all the people on Twitter, all the data is out there. Certainly the analysts will be coming shortly. And our next guest is Inhi Chusa, the VP of Strategy and Business Development for IBM Analytics. Welcome back, great to see you. You look marvelous. Nice seeing you. As usual. Thank you, thank you, John and Dave. So you're doing a lot of meetings. Three shows into one. So three times more customer meetings. Three times more activity. How are you feeling? Three times the fun. Three times the fun, Aerosmith. I mean, we're going to be rocking tonight. I can't wait. Oh yeah, that's a great concert. I'm excited. So what's going on? Give us the update what's happening in the show for you. We've got a number of things. Let's start with some of the cloud announcements. We have a number of focus around cloud data services and new capabilities that we want to bring to market. We've also have new capabilities in terms of Twitter actually flowing through our Big Insights Hadoop service in the cloud on Blumex. We've got also a higher level partnership announcement. I don't know if folks have had the opportunity to read about this yesterday, but we forged a strategic partnership with Juniper. And this is all around transforming the way CSPs can actually perform and operate and begin to improve the level of personalized services. CSPs meaning communication service providers in the industry by embedding analytics actually directly into the Juniper service gateway network. That's exciting. That's really exciting. So break down the analytics. So IBM has, you have a software group now it's kind of sprinkled, software is eating IBM right now in all different groups. You have different divisions now. So the software division has gone and you're in the analytics division. It's a Watson division. Can you explain like what your focus is in your group and the trend of analytics is embedded everywhere. You see system Z talking about in-processor analytics, analytics in different engines. Is that your group or has it all? So before you get to the highest level, Ginny flattened the organization, right? Yeah, absolutely. It's about speed. Yeah, that was a key element of it. And the other is to actually orient the way the markets oriented. What clients actually care about is being able to get to whatever business outcome that they want. And in order to do that, you're going to need a combination of software technology capabilities. You're going to need services and consulting, and you're going to need real deep domain and or industry understanding of applying that technology and delivery in the context of whatever solution you're solving for, whether it's energy and remediation of disasters or if it's a predictive maintenance and quality within aerospace engineering or whether it's fraud detection and AML within risk and financial crime or it's the combination almost, whether you talk about cloud, you talk about commerce, you talk about analytics, clients are going to want to be able to apply those kind of layers of the technology, the data, the analytics as well as the domain expertise in context. Okay, so tie that back to John's question of the organization, specifically the analytics group. Yep. So what's in there? Sure, so we have Bob Picciano as our senior vice president and leader for IBM analytics. And within IBM analytics, we have a team that's focused on horizontal platform capabilities. What I mean by analytics platform and horizontal is they think about the entire information, the analytics stack of technology such as the relational database, such as warehousing, such as BI, business intelligence and reporting. So think about our capabilities around Cognos or SPSS. They focus on also the team focuses on Hadoop, right? Emerging technologies in terms of new types of analytics and new analytic applications and programming models, including innovations that we want to do and accelerate around Spark. We also have folks on that team focus around stream computing as capabilities around real-time stream processing. But the notion of this platform is really about all the horizontal capabilities that you can imagine. There's also another layer above it which we call cloud data services, which is what are the set of data and analytic services that you want to be able to expose and compose in the cloud. And this is to accelerate new types of application development, as well as much more of a self-service environment, right? That's right, all around data and analytics. So it may be things like Cloudant is part of that sort of capabilities, the big insights Hadoop and Bluemix, DataWorks, that's all exposing that next layer of data services in the cloud. And that lives within Bob's group. That's also in Bob's group. Then there's a layer called analytic solutions. And the analytic solutions are things like predictive maintenance and quality, or PCI around customer insight for certain vertical applications and industry solutions. The Now factory, which is a set of capabilities around telco analytics for customer service providers, network operators. So the solutions team really thinks about a vertical orientation of the data and analytics stack to apply to different roles and professions and industries. And that's how Bob's kind of organization is. And you've got services within that organization. That, absolutely. And industry specific services as well, or anything that's data related. Both, both. It's the professional experts that we have on the team are a combination of the consulting experts within GBS's consulting practice that have moved into the IBM analytics unit that are going to be specialized by vertical industry. So we'll have a team that are experts around financial services. And then in banking, is it core banking? Is it retail banking, commercial insurance, personal casualty property, energy, utilities, management, travel transportation? So you can imagine kind of the way that the deep domain experts are aligned. And you said databases in there as well? Yeah, database is part of our platform set of capabilities. So if you think that's part of the technology level. So... So DB2 lives in... In IBM analytics. Yeah, and IBM analytics. SPSS lives in it. It's all things having to do with data and analytics, essentially. So you get the technology responsibility. And it's growing too. And it's growing. Last quarter grew, I think 6% was the number. 7%. 7% is huge. So how does that... So you got technology, you got the enabling with the cloud fabric kind of interface, and then you get the vertical and the solutions group, so solutions. That's right. How does that relate to the Watson team? What do they do? That's a great question. So part of what we want to also enable within Watson is how you begin to compose different aspects of the technologies in such a way that you develop Watson cognitive applications. Within the Watson unit, we're really engaged at deeper levels of transforming and providing kind of next generation of cognitive applied to the domains of insurance, domains of medicine, domains of wealth management. Recipes of the technologies that are applied, almost applied in analytics. Well, yeah, and there's kind of a couple phases of it. One is you have to have enough data and information, both structured and unstructured, right? That you're curating. Meaning there's got to be evidence from which you're actually asking questions. And a key element of Watson is the ability to ask it very rich questions and to interact in a very human way via natural language, but also the inference and capabilities and the other aspects within the engine itself. And so I would look at clients really trying to get their data and order, their analytics, who their audiences are, their domain experts, and we're really helping clients regardless of where they are in their journey. And I look at it as an entire journey for everybody. Okay, and now you're doing partnerships, doing deals, the Juniper announcement. Can we talk about that a little bit? Yeah. We're talking off air a bit. I don't think people really understand it. So take us through what it exactly is and why it's so important. Sure, I'm excited to share it actually because my new role is to run strategy and business development for the analytics unit as a whole, reporting to Bob. And the first partnership we've announced this year is with Juniper. And just very candidly, if you step back and you think about the world, there are just natural points of what I consider centers of where a lot of data either resides or is through putting, right? And the network is one of them. And what's amazing about that is that Juniper is uniquely positioned to extract as much data at the network level than any other of its contemporary kind of companies. Now, what IBM has to bring to bear is the ability to augment that data and understanding, knowing what's actually happening in that data flow, what applications are running through it. So we're embedding some of our unique capabilities from the Now factory actually inherently in the network router for Juniper to be able to augment that data with key metrics that can help things like bottlenecks of latency, performance, optimization, as well as things like customer service. Because then as you think through understanding that data and processing it, you can then visualize that information in a way that if I'm the network operator, I can begin to change in real time and see different types of application usage and different types of customer service usage. I mean, I would just give you a simple personal example. When I'm at home and my kids are streaming something, right, either on Netflix or YouTube or name the video they prefer. And my husband, Dave's on his business application. I'm maybe on my system. All of a sudden you can feel the latency on the system. Well, as part of it is because the network's not smart enough to know what's the combination that's being used by the various subscribers in the home. This is an opportunity for us to actually unpack that knowledge in such a unique way to improve the quality of the experience. Well, quality of service too. Networks are the bottleneck and with peering, you're seeing Google has their own peering network for their cloud, you've got to get down and push into the network. So talk about the deals. Is it a joint business? Go market, technology development, sharing? It's a strategic deal too. And what we plan to do is innovate around the engineering. So there is joint engineering involved. There's also joint go to market involved because as we go into both the communication service provider marketplace as well as to even large enterprises, there are a lot of large enterprises that procure their own networks and manage them themselves, especially in financial institutions as a good example. Of course they get the network service potentially from one of the carriers, but they actually manage the internal policies, let's say. They want that level of visibility which they haven't had before. And this is a unique opportunity for us to be able to bring IBM's breadth and depth of analytics to what Juniper has really in this particular scenario of exposing the data in such a unique way that we can help them scale what they're doing. You mentioned it, is it an exclusive deal? Yeah, I was anticipating where your question was going and I could see your face and so that's why I started to mention it. So why Juniper? Well, one of the key things in terms of the partnership is that it's not exclusive. However, what we want to do is be very thoughtful and strategic because it's truly a first of a kind. Neither of us have innovated this particular way in the industry in terms of any, let's say, leading analytics company or a leading networking company. The second piece is all of the data that Juniper is able to expose in their network is pretty amazing. What we're doing is applying KPIs and metrics and knowledge and algorithms and mathematics in a very unique way so that they can now automate things like and remediate through predictive understanding of bottlenecks and throughput, latency, performance. And Juniper's focus on CSPs is sort of a natural place to start, it's probably easier to focus and smaller company. Absolutely, and this is really a partnership where you're bringing kind of two very innovative companies that have actually had a very long-standing partnership for a while in different ways to reinvent what's possible moving forward in this particular space. By the way, this is one of a couple elements of IBM strategy. I mean, we announced the partnership with Twitter in the October timeframe because this was about extracting the insights from the social conversations and the pulse of what every individual citizen, professional is thinking and doing in a very meaningful way to impact business decision-making. When you think about here in the CSP scenario, here we wanted to get close to understanding the data that's flowing through the network. So you're going to see from IBM a number of kind of strategic sort of developments and relationships that accelerate our ability to allow clients to extract the insight from the data. How far along are you with that with the Twitter partnership? Can you expand on where you guys are with that? Yeah. Is it prototype? Is there actually solutions in the marketplace? Is it just kind of tinkering around? You know, we love the Twitter data. You know our love for Twitter data. So we're curious. You are avid users, I can vouch. Groupies, groupies. We work for Twitter, but we don't get paid. Twitter, if you're watching, that's okay. We'll pump you up. Groupies, that's funny. Snapchat's on their tail. You know, Snapchat's growth is phenomenal. So anyway, back to Twitter. So where are you with the Twitter? There's this good buzz around the show here on this one point. The partnership is doing great. And what we've really done in the last, since the end of October is when we announced it, is actually developed a whole series of internal training for our global consulting organization. Because we've declared to the market that we're going to train, you know, thousands of consultants around the use of Twitter data and certifying them in very unique ways on delivering Twitter within a business context. So that training is actually started in the middle of December. That's for the insight piece too, right? And that's really for the insight piece. There's another level which is flowing Twitter data naturally through IBM analytics software capabilities, like Watson analytics, like big insights for Hadoop. So those set of capabilities, we've already enabled the big insights for Hadoop on the cloud. The Watson analytics is forthcoming very quickly, so you'll be able to see that. And we've actually enabled Twitter also within our Bluemix environment for application development. So there's a number of things that we want to accelerate around. What I consider the ability to play, innovate, build, kind of new services, new applications, new insights using Twitter. Then there's a whole set of solutions. And our intent is to actually announce a set of integrated solutions with Twitter starting in second quarter. So you're going to have to wait to hear a little bit more on that. So they're engaged with you guys. This is not like Twitter doing a, hey, you guys are using our fire hose. Oh no, no. We have engineering relationships. We have engineering relationships. We actually have joint consulting and expertise relationships. We actually have regular committees in terms of the technology and business and client engagement. We have a number of clients actually that have also done POC engagements and really want actually bigger solutions, if anything they want faster. That's super exciting. So I got to ask you, so two years ago we were at the Tableau conference interviewing Nate Silver and you were there. Oh yeah. But then so we, also on Twitter, we were like crazy about it. So we were poking at him, asking him about Twitter and its predictive capabilities. And he made a statement, again, two years ago, the data's not there. The data doesn't exist. And so we were like, very, I guess it does. He's wrong. He's a hardcore statistician. Now maybe he's writing that kind of structure framework. He's not even a data site. He's just more of a user. So it's two years on, you got this, you got to bring in your resources to there. The corpus of data is enormous. Is the data there, is it starting to be there? Not to pit you against Nate, but I'll give you the, it's two years on. So things that could have changed. But I mean, what do you think? Is it just different type of data? I mean, I know it's not structured surveys from political polls. Yes, yes. Or predictions on whatever, who's going to win the election. The value of the data is always in context. And having that as a social element in terms of how that conversation is happening at a certain time, certain frame is really important as an element. It might not always be the element, but it's actually one of a combination. It's been pretty consistent for us, and I've seen it, I believe we're really entering what we call kind of an inside economy. And in an inside economy, you're going to have to marry data sets from a variety of different sources, including your own internal enterprise organization data. But it may be things like combining social data with other types of industry data, even government open data, to marry, to extract a higher level of understanding, whether it's around a customer, whether it's around an organization, whether it's around a set of products. I would say a different way is that the size and the conversations that actually happen on Twitter are as close to sensing what the pulse of the planet is. And that's kind of what we talk about. And there are very few places in the world that represent the corpus of human thought, and this is one of them. This is almost one of the most modern day, and you get the most extremes of the mundane. It's human signal, it's human signal. Right, absolutely. Mundane to, absolutely insightful in that pool, and it's how do you find that one needle in the haystack, and we have the analytic capabilities to do that, and to do that, tying back to key business process and workflow. It's really genius, I got to say, and you guys, this is such a great move for you guys. We love it, 100%, I think it's the future. You nailed it, doubled down, keep rolling. But I got to ask you, Internet of Things is big data. The Twitter example means Internet of Things, people are things. I mean, thing one, thing two is a cartoon, a book. So I got things on the edge of the network, talk about the edge of the network, probes on sensors, there could be refrigerators, whatever it is, oil refineries, every vertical's got things, machines and people. Absolutely, absolutely. So the people is the Twitter thing. That's the Internet of Things application, get that. Machines and probes and that market, what does that look for you guys? Is Bluemix hot? You're seeing Bluemix big data, Internet of Things are the top conversations at this show right now. Yeah, and you probably saw the main tent stage yesterday afternoon, and the Silver Hook power boats. Yeah, they were on theCUBE. Awesome, one of my favorite interviews. Their business outcome is pretty specific, win the race. Win the race, win the race. And live through it. A lot of sensors. A really good example actually is work that we did recently with Pratt and Whitney, developing and innovating around, they are the market leader around airline engines, right? And in that manufacturing and engineering space, one of the key elements is how they've innovated their engines for fuel efficiency and economy. One of the things that they thought they were going to be able to save because of the optimization and the engineering was on fuel, but however they also had a lot of unexpected down time around the product in terms of some of the quality. And they didn't understand why. One of the unique challenges they gave us was, could we help them determine and predict what was likely to happen? So they had actually captured about two years worth of data and they gave us 18 months of it and asked us to predict what was going to happen in the remaining six months. And we did, our team actually applied some of our predictive maintenance equality and asset optimization capabilities, all built off of a combination of our IBM analytics portfolio like SPSS and other elements. We did a pattern detection and understanding and we actually predicted with close to 98% accuracy on what was going to happen in the next six months, which was the truth. I mean, it was that close to what they actually saw in the data. Now did that lead to some kind of business capability? It did, it actually transformed the way they thought about servicing and the follow on new innovations that they could actually offer to their downstream ecosystem partners. I mean, the opportunity around the internet of things is just unparalleled because what people care about is not only just the connectedness of everything, as well as the security around everything, but it's how do you extract the inside of things, right? The inside of the connected things. It's not just the internet of things themselves. Can we talk about, you and I were in it, Duke World, Strata, the state of SV last week. And the big talk was, well, one of the big themes was ODP. Big announcement, Mike Olson put on a blog post saying, oh, it's all Huey, Hortonworks and others, you guys responded saying, no, it's not Huey, it's real. Why does the world need an open data platform? Oh, you know, it's part of what I consider being able to help accelerate true enterprise adoption at large scale, and the reason for that is you have to have certain degrees of standardization in order for clients to be able to extract value out of that data, reuse that for new application development, and having a partnership around the community ensures that consistency to protect, actually, the investments by, most importantly, many of the clients, as well as the application programmers that are working in the industry. That's a key element of it. So, I mean, on the one hand, Mike was sort of criticizing, and we know Mike really well, he's a friend and he's a great guy and a straight shooter. He was criticizing sort of the pay-to-play aspect of it, and that's not so much of a concern, you know, it's not over the Hortonworks. It's really important, it's competitive with Hortonworks, but the point he does make, which I'm sort of torn on this, I'm really trying to understand it, is why do we need standards when we have standards with Apache? We've already got open standards. Why do we need more standards? You do have open standards with Apache. It's also about, actually, I would say, one of the most important things to clients is they want some headlights into certain directions. So, if the community knows architecturally, even if the base has to go in a certain direction and can give a little bit of headlight, enterprises can actually invest properly in that and understand how they have to, where they want to emphasize in terms of certain branches or forks, in terms of the project, because Hadoop, unlike some of the other open source projects within Apache, it has multiple branches, right? There's a number of initiatives under that, and it's very hard for a single enterprise to be able to be on track and on top of every layer of all of the initiatives in a meaningful way. Unless you're a really large institution and you have, you know, thousands of application programmers and developers and data architects, then you're in a business where that's the core of what you do and that's why you've got that. So there's a purist. But there's set of folks that really can't afford that. So you're saying there's purist and speed. People can handle the purist nature and the speed and the slower, which is like built around investment protection, where you slow roll the open core. I would actually say skill. Skill is probably one of them. Quite honestly, I think the Hadoop market should have a lot bigger than what it is right now. Well, I was going to say. So you can't scale something if there's not a lot of standards in terms of how people can actually drive the next level of innovation, whether it's doing in-system analytics and applying R because it's much more pervasive in a broad scenario. You can imagine what's going to happen with Yarn and Spark. You can imagine what's going to happen in the SQL space. You can imagine what's going to happen in terms of text analytics and machine learning. So it's going to explode. It's actually going to be faster. So do you think then that there has not developed fast enough? I mean, Hadoop should be much bigger, you're saying. And it's not because there's, you know, it's a lot to track. Well, you must laugh at when you do the endless thing and all we talk about is Hadoop, Hadoop, Hadoop. And Hortonworks goes public. It's got about 30 million revenue. It did 12 million. It did 12 million in the last quarter. If you look at IBM's business, it's enormous comparatively. Why is it that we talk about it, Hadoop? Hortonworks innovation started it all, right? It started the whole meme, I guess, but it's fun. You know what's, but it also, the thing that I really am most excited about it is the fact that it allows new types of discovery-based applications, right? In traditional warehouse analytics systems, it was questions and you get an answer, right? Here's the question I wanted to ask. What's my sales for the month? Who are my most profitable customers? Using technologies like Hadoop mixed with search and mixed with text analytics, you actually allow people and organizations to ask much more reflective and discovery questions. You're not just asking a question for an answer. You're actually kind of playing with it and maybe trying to find out relationships you didn't expect. That's kind of the new class of applications that's possible and that's what's so exciting. So talk about the next phase of growth for your group. Obviously you got to set the table. You and Bob are going to attack the analytics part of the division, which is the core stuff. You're also the buyer out there for startups. You guys are the customers of the VCs we interviewed. Ping Li, Frank Artali on our big data panel, and I asked him, IBM and others are the buyers for you guys as the VCs. You're peddling up the startups, the ones that can't make it. So, but they have some technology, AccuHire potentials, portfolio, product portfolio, white spaces. What's your view on that? Can you share? Honestly, you can't tell the plan, but you're doing strategy, you're doing biz dev, you're doing deals. That's right. What's the M&A outlook look like for you guys? I think it looks positive. I think the industry looks positive in general. If you look at the activities and just kind of the signals of what happened last year in terms of just overall market, VC investment in the space has grown, but for us it's positive because what's nice about the way we're aligned to be enabling the solutions and the markets we want to go after, like IBM analytics, IBM commerce, IBM security, is that we can actually move faster and thoughtful about what are really the components that actually drive accelerated new growth, new skills growth, new application growth, new technology growth and prioritization. It makes it much, it goes back to the speed at which. Do you have a list? So do you have a list? I'd love to shop. Who doesn't like to be shopping? How big is the list? I mean, is it like this? I mean, is it long? Come on. I can't see. Have you seen my closet? We got some things for you. We'll talk after. No, but M&A is big right now. You're going to see, well, our thesis was consolidation certainly in big data. There was databases down to three now. I wouldn't say the word consolidation though, because that's not actually the lens through which I think about it. I actually think about it as, what are the classes of applications and technologies that we actually think are going to be innovating and driving growth in various industries? And so I'm actually not thinking about it from a consolidation standpoint, but a really scale. Well, there's going to be acquisitions and there's going to be a few more companies maybe in some category, but if you're right, there's another wave coming. I think there is. And it's hard to tell. Maybe it's IoT, new apps. Well, this is the speculation we've been covering, is that if you get the big boys that have overfunded the VCs, they're startups. You guys have a partnership strategy. We talked with Doug and we talked with the folks in the blue mix group. They're a collaboration space now for like, if you're under 50 million and you're not generating sales, if you're a startup and you have no sales, but a product, the question is, how fast can I get sales? The VCs aren't funding B and C rounds because there's no sales. So they're a perfect, stuck in the middle of things. Perfect opportunity to either put them in the marketplace or use them. It's got to, you know, I have to go back to, it's got to align to where our strategic priorities are and where we think the innovation's going to happen next. And quite honestly, I'd like for us to be able to innovate as much within IBM because we spend a tremendous amount around innovations, internal innovations as well that we want to expose. Our research assets are pretty amazing. So we're very thoughtful about what are kind of the adjacent spaces that are natural kind of accelerants to our business. Okay, we're getting the hook here. Thanks for coming on theCUBE's final word for you. What's the vibe of the show? What do you think about your new role in doing deals? And just in general, the pulse of the analytics group? Well, first of all, interconnect is great. I mean, this is probably just massive in terms of the attendance and the facilities and all of the topics, mobile, cloud, security, DevOps, I mean, you've got the gamut, analytics. So really excited. Obviously, IBM analytics, huge, huge opportunity for us to transform every profession, every role, every industry. And for me personally, I'm really honored and excited to be part of this team. Well, we're honored to have you on theCUBE and it's so great to chat with you. You're always awesome to share information. You're very candid and open. Thanks for taking the time out of your busy schedule to share with us, appreciate it. This is theCUBE, we'll be right back with our next guest after this short break. I'm John Furrier with Dave Vellante. We are here live at interconnect. Go.com, interconnect conference here in Las Vegas. We'll be right back.