 Okay, we're back live here at theCUBE in Las Vegas for IBM Information on Demand. I'm John Furrier with Dave Vellante. Join the CrowdChat on CrowdChat.net and we're here with Les Wretchen, the General Manager of Business Analytics at IBM. Welcome to theCUBE. Thanks. I know you got short time and for the folks that have been on about 10 minutes, we're going to just jump right into it. So, obviously, business analytics and social business, big data analytics and social business, driving the market of the data economy and under the hood, you've got cloud and mobile and connected devices. So, the number one thing that comes up is we need more data scientists and we've got to get the data in the hands of users. So, talk a little about your vision there and what's going on here around that concept. Yeah, I think it's key here as we talk about imagining the future and leveraging big data analytics, we talk about infusing a culture of analytics everywhere in the organization. So, the key about that is to really create solutions that are fast, that are easier and that are, frankly, smarter throughout the organization. So, how does visualization play into that less? I don't know if you could talk about that a little bit because as a business user, you guys are describing the keynotes today, right? Somebody put up this spreadsheet and you're like, how can you make it easier for people to consume? Yeah, you want to have more rapid insight to action. This is all about whether it's predictive capabilities or we think about, you know, when you look at organizations today, you think about descriptive analytics. What's going on? And then you diagnose it. Why is it going on? You look at the future with predictive analytics and then even look at prescriptive analytics with things like looking at next best action and then even cognitive capabilities. What we really want to do here is make it a lot easier for users to not only visualize and explore, but to then see the patterns in the data to guide them. And what we're trying to do here is really change the whole analytic experience, how they make decisions, how information's presented in a much easier way. Let's talk about the difference in verticals. A lot of people have conversations around business strategy and also the solutions they put out were horizontal, were vertical, something, a very vertical approach, even a technical level with the stack or organization. You guys have to play in all the verticals. And the verticals have different outcome objectives yet, so that means different analytics. How do you guys deal with that? I mean, it's an opportunity certainly, but I mean from a technology and then solutions standpoint. Yeah, I think the key here is we focus on number one, taking advantage of all data, whether it's structured or unstructured, whether it's in motion or at rest. And then we want to deliver, as I mentioned previously, all analytic capability from descriptive all the way to cognitive and then all solutions. That's where you get then into the verticals. So telcos are looking at customer churn, insurance companies are looking at fraud, banks are looking at risk, public sector organizations are looking at reducing cycle time, and then medical institutions, really collaborative care with the patient. So what we try to do here is take that capability that we've got, all data, all analytics, all solutions, then apply it, pinpoint it. So for example, predictive maintenance and quality for industrial sector customers. So what you see here is we've announced a solution that converges that capability, again, makes it faster, makes it easier, makes it smarter to deploy. I talked with this EVP, CIO of Statoil, and she told me that they had their data and a silo for the exploration side of the business, but when they opened up new data sets that had nothing to do with their business like ocean data. Amazing, amazing transformation and improvements to their business. That's two different data sets. How do you guys enable customers to do that? One, do you do that? And these verticals have to kind of go outside their kind of data competency. Yeah. Can you talk a little bit about that? So really here, when you think about analytics and you think about social, mobile, cloud, we're looking at systems of engagement. We're looking at presenting information to people on the front line that could come from many heterogeneous data sources. So what we want to do is be able to bring that together. We have solutions that actually do that and then bring it together for that user, for that particular problem. Les, what does your business look like? I mean, you're running the IBM analytics, business analytics group. What's in the business analytics group? Yeah, it's a pretty big business. I actually came into IBM from Cognos. So that was business intelligence. That was about six years ago. I was the COO of Cognos. So business intelligence is the first piece. Second piece is performance management capability. So this is financial performance management, sales performance management, and disclosure management. And then you've got predictive analytics. So you get into statistics, you get into modeling, you get into kind of approaching some of the cognitive capabilities and finally risk management. This is financial, market, credit risk, governance risk compliance. So it's a pretty big business. We focus on customer related areas, operational areas, finance and risk. And then of course with our big data brethren, we focus on this overall big data and analytics opportunity. It's a global business. It's something that's very important to IBM. And it's really, when you think about big data analytics, about 15 cents on every IT dollar being spent. So you look at the Cognos acquisition. I mean, you could argue it's one of two of the major acquisitions that IBM has done. It's probably one of the two most important, that and PWC, right? I mean, it's really transformative. Did you, when you were a Cognos, did you ever imagine, could you even glimpse into the future as to what has become of this sort of big data meme? I mean, it's always been sort of the vision of the 360 degree view of the customer and all this stuff. But just the amount of data. Is that something that you guys actually envisioned and you're now seeing through? Yeah, no, I think we had, you know, it really has gotten to be much bigger than I would have ever dreamed of, you know? And that's the whole theme of this conference, right? It's think big, deliver big, win big. At the same time, we did have a view of where this thing would evolve to. We always talked about this whole all analytic capability and being able to present that to the user, being able to exploit the data that's out there in all the different shapes and forms. But it really has grown pervasively. We talk about, first of all, imagining it. You know, you've got the four Vs of big data, volume, variety, velocity, veracity. But we talk about having the vision and the value. That's the fifth and sixth V. Really imagining the future, being able to realize it with a big data and analytics architecture and then frankly being able to trust it in terms of security, privacy, and risk. Yeah, you guys, Cognos was a nice exit. Was it five billion? Was the exit when IBM purchased Cognos? Yeah, it was a five billion dollar from an IBM. Yeah, so you don't, do you think you undersold? No, I'm kidding. No, but the reality is you never would have been able to see that vision through as an independent company. I mean, the resources that you're required, whether it's the services, the hardware piece, the other big data analytics pieces, it's very hard for an independent company, I think, to compete with that. We were talking earlier about the little different parts of the big data ecosystem. You got the little Hadoop specialists, you got guys who have tried to remain independent, still doing okay, but IBM's got a lot of capabilities there. You mentioned in your keynote, Project Neo. What is Project Neo? Yeah, Neo is our next generation data discovery capability. And again, in the spirit of being faster, easier, smarter, what we're trying to do is make this visualization capability as well as the learning capability available to all knowledge workers, not just modelers. So you don't need to do sophisticated modeling. It'll come back and guide you through in a very natural language kind of way. And it's, we're really trying to change how the whole analytic experience happens. And underneath Neo, it takes advantage of some of the other capabilities. We talked today about DB2 blue, blue acceleration, and then our analytic catalyst capability, which really puts kind of the stats and modeling in a box and brings it to that user. So we're very excited. We're gonna be showing that today in our main tense session. So it should be a, you know, we're really, it's a 3PM, yeah, a 330 actually. So that's, so next generation discovery, that's on, across all data sets. Yes. And with analytics visualization built in for knowledge workers. You mean like a data scientist or like a worker on the front lines or the iPhone? What I'd mean like a worker, this would be any knowledge worker, but then we're also with analytics trying to make it more pervasive. We'll embed it in a business process, for example, like a next best action or things like that. So you're gonna have analytics go into the masses, embedded in a business process. But then here, this is all about really looking at in a descriptive way what different things you wanna see in your business in a very self-service oriented way. Awesome, awesome. What do you hear from customers? You're out in the field, you're running a big business of IBM that has a lot of legacy customers with computing platforms and paradigms that have been old school, if I'm gonna say old school, and a lot of new school rollouts and deployments. What are the top things that customers are asking for? And when you go out, if you had to dial out the top three, floated to the top, what are the top three? I think the number one thing that clients want here is outcomes. Business outcomes very quickly. They also want help on their journeys. As they look to evolve their analytic cultures, they look to evolve their platforms, they really want us to be able to go on that journey with them, help them understand their maturity, help them understand where they should be going, and really help them prioritize the key actions they can take to drive the outcomes. And then it's really, once you start, you focus on the priorities, then it's really helping them implement those. So we really look to our partner ecosystem as well as our services organization to help them drive those outcomes quicker. So a lot of activity, you'd call the market robust at this point. Very robust, again it's 15 cents on every IT dollar, it's a huge opportunity. It's very exciting. Certain analytics business, your TAM is 15 cents on every IT dollar. Yeah, the big data analytics component of IT spent. Yeah, I mean, sir, with service catalogs, self-service, with instrumentation of essentially value chains, I mean, everything is now instrumented for the first time in history of business. I mean, think about it. From oil exploration to hiring. So really appreciate your insight. Final question is what should people walk away with who aren't on site here, who are watching about what's happening here at IOD? There's so much happening. We're talking, I think there's a lot of announcements, first of all, taking advantage of all data, whether it's insights, streams, so we've got all data announcements, all analytic announcements, new solution announcements. But as we've looked out and we talked to many of our clients over the last couple of months, what do they need help with to be successful here? Because this is really all about outperforming. It's about continuously transforming in your business. They really want help imagining the future. So let's infuse that analytic culture everywhere in the business. Let's really realize the value here. So evolve our platform and architecture and then really do it in a trusting way to drive the outcomes. Les, thanks so much for your time. I know you're really busy. You got a lot of business to do, customers to talk to and speeches to give. Appreciate your time taking on theCUBE. Business outcomes fastest when people want the most help on this journey in a collaborative way and implement it, scale it up. So that's the future of business. Social business, business analytics and data and on to the hood, the engine of innovation, cloud and mobile social. This is theCUBE, we'll be right back with our next guest after this short break.