 The Cube at IBM Impact 2014 is brought to you by headline sponsor IBM. Here are your hosts, John Furrier and Paul Gillin. Welcome back everyone, we're here live in Las Vegas for IBM Impact. This is The Cube, our flagship program. We go out to the events, we track the ceiling from the noise, talking to all the tech athletes, all the brains behind all the action, certainly at IBM, customers, startups, CEOs. We'll talk to anyone who has a ceiling from the noise. I'm John Furrier, The Frown of Silicon Am. I'm joined by Paul Gillin, my co-host and one of our favorite guests in Heechos, the Vice President of Big Data, governance, integration, welcome back again to The Cube. Great to see you. Thank you, John. Excited to be here, I always enjoy The Cube. I know Dave's jealous, Paul, you're lucky because we always have a great conversation. So first, what's happening? Tell us what exciting thing happened to you today. Yeah. Where do I start? So many things. First of all, we've made some kind of announcements around new set of services, actually data-oriented services on Bluemix. So when you think about Bluemix, really focused at the application developer. One of the things that we wanted to be conscious of what were the data set of services, and we've kind of packaged them in two categories. One are what I call data access and management services for both SQL and NoSQL. So we've got SQL database service, we also have Cloudant, which is a NoSQL, database access for mobile application development. We also have things like time series data. And then a second category, what I call more about analytics for data. So such as map reduce services, blue acceleration for more structured SQL and memory, as well as geospatial analytics, which leverages some of the capabilities of our stream computing. So really giving app development kind of an extra data buzz and data injection. So really excited about that. And then we also announced some additional capabilities around what we call real-time actionable insight. How you can marry things like stream computing with predictive capabilities around SPSS, plus operational decision management, really tying into the rules and the workflow to make it actionable. So on the event here, it's a customer event. So I got to get your take, because I know that every time we talk, some of the events are more industry-oriented and you're always out in the front lines with customers and you must have a zillion customer meetings. So I got to ask you, what is to the top conversations they're asking you? I mean, they're not saying I want blue mix. That's what you guys are doing. So what are they saying in their language as they share? What's the metadata that you're hearing from the customers? Well, I actually have gotten a lot of questions on metadata. So a majority of the clients I've met, I've had the opportunity, we've got like over 9,000 attendees here or 10,000 attendees, I've been swarmed, but the top topic has really about how do you create much more of what we call an enhanced 360 view of the customer and how do you virtualize that information just in time? Just in time at the moment of business impact. And the way, let's say the clients are kind of verbalizing some of this is, do you have kind of next generation of MDM capabilities? What are your things around? One of the conversations was around Data Lake and we've been talking about it as more of a data reservoir because a reservoir is actually managed, a lake you kind of, it could be much more static versus you're really thinking about the metadata aspects and referencing and- Well now we have streams. So we have lakes, reservoirs, streams, and no one is using my ocean. I'm trying to get the data ocean into the narrative. I love the ocean, ocean's huge, it's complex. It's in motion. You love it, you can kill you, you know what I mean, you don't want to take the ocean stitch with it. It might be, it might be, that might be a good example. Are you finding that customers generally know what they want to do with big data? I mean they have ideas or are they asking you for direction? It's a mix, it's a mix depending on the vertical industry and the size of the organization and how skilled they are. So for most clients, I would say, majority of them are looking for top-line growth and the top-line growth is driven by a couple things. Either better cross-sell, upsell of their portfolio products or capabilities and services and they want to leverage big data and analytics to understand how they can better do targeting. Another is really around managing risk and risk meaning everything from fraud to security to intelligence to all aspects. Third area is what I consider much more operational analysis and optimization of asset-intensive industries. So you look at power, energy, utilities, automation, travel, transportation, anything that's instrumented. We're really seeing pretty advanced things in those areas. Healthcare is also a huge hot topic because of patient records. Really, when you think about personalized medicine, you're talking about even instrumentation of the intensive care units. We're seeing a lot of opportunities. There's a lot of heavy industry-specific stuff. Now, they generally have the skills inside or can they acquire the skills to put these applications into place or are they looking to you for that as well? It's a blend. Actually, I also met with many partners here at the conference that are part of our broader ecosystem, our big data and analytics partners that do both services work, consulting work, as well as implementation delivery work. I would say for most clients, they're writing new applications that they haven't written, leveraging things like streams with SPL as a stream processing language and being able to develop a streams application in a matter of three weeks or so. We have clients that are becoming much more current. I mean, I think what you're seeing, also even in a Hadoop world right now is what I would consider a bigger push around SQL as another way to both access and query the types of questions and insights that clients want to access from Hadoop. I think kind of the landscape is evolving. Now, when you think about it, they're more knowledgeable folks than you're going to have MapReduce. You're also going to have folks in the application development world that understand Java and C and C++, but they're very quick to be able to learn SPL. So I got to ask you as I'm sitting here posting your videos from previous cubes on our crowd chat because I realized we've interviewed a bunch of times, you always have a good take on fresh topics. So I got to ask you one about social business because there's a big data angle with social business, huge, you can tell about instrumentation, metadata. These things are all kind of like all big data systems and infrastructure. Yeah, you make money from it, but the social business impact has societal benefits as a technology angle. What's your, how do you talk about the social business trend from Enhi's perspective? That's an interesting question. Now that you've posted, it's kind of processing. So there's probably two angles. One is what I consider, we're entering a culture of sharing, right? The fundamental nature of social is about sharing. You're seeing entirely new business models, right? Car to go, i.e. leave your car in one place, someone else fixes up, so forth. But the notion of data sharing, what does it mean to actually share information that teams and organizations have that historically have been kind of kept or limited and wasn't shared because, you know, for security privacy reasons, wasn't shared because of it wasn't easy to replicate or federate that information. It wasn't shared because you didn't have the proper analytics or control mechanisms on a governance standpoint. So I think data sharing is kind of a new area that I'm thinking about very differently, which is, you know, how do you provide a lot more unified sort of collection to information that individuals, organizations, teams can actually begin to leverage, and it could be open data, it could be internal data, it could be social data in a much more current and both hybrid and public kind of cloud dimension. And then the second piece on social is the thing I've been tracking, which is really interesting is, you know, people want to track things for crowdsourcing and social incentive, but, you know, human nature is, you never know how people are actually going to respond. And being able to apply analytics to have a deeper insight in, you can make estimates and guesses around how people are going to operate versus the way they actually do, right? Or you think by all indicators they're going to operate a certain way. And this goes back to, I think I had mentioned it one time around profiles of dating and personal attributes that relate to kind of indicators for insurance companies to understand life changes and policy changes and when someone may have the propensity to want a particular offer at a certain time, to make certain contacts, so. And you're talking about disruption, really. When you talk to some of the collaborative economy businesses that are starting up now are disrupting traditional businesses because they handle data more efficiently. I'm thinking of Uber, the ability to track where vehicles are really in real time and assign them to where customers may be. Are you, do you find that your customers who are in more established traditional businesses are aware of their potential for disruption thanks to big data? Oh, absolutely. I mean, I would actually throw out that if you're not disrupting yourself, you're going to be disrupting it. And if you're not actually thinking about the power of data actually being the basis of your competitive advantage, you're already behind. And I don't say that lightly. I say that quite seriously based on the sheer volume of clients I've had the opportunity to engage globally. So we're seeing a huge culture here. I want to bring the development angle in here because, and get your thoughts here. I'm going to think out loud because it's kind of off the wall topic. We're talking about this maker movement that's happening in tech, in the data center, open compute, you have the homebrew kind of hacker culture now at a whole new level of cloud and big data. So people are bringing and hacking these new solutions together. So I got to ask you what crazy things that you see that are brilliant out there that's on your radar? I mean, something that could be in big data but something where it's not just a PowerPoint slide, it's real actual construction or making or it could be Raspberry Pi meets some analytic visualization. I have no idea, but what do you mean? Well, we actually had a mini maintenance session on Monday and we had John from Kiwi. I don't know if you know what Kiwi is. It's kinetic with wearable kind of devices and the devices could be everything from a little device where we had demonstrated a chip that could be embedded in a smartphone that when a person, as an example, we actually mocked up an application and ran a live demo of this that said, hey, could actually detect all aspects of a person's movement, whether they're hitting a racket, whether they're jumping up and down or they've fallen. So one of the applications we had kind of developed was, what if as part of the smartphone and the device and the wearable that we could actually detect how a person falls or doesn't fall and you don't have to necessarily then call but the system can actually automate the call that says I've fallen and I need help. I can't get up, my team is coming back. Well you didn't fall too hard, sorry, we're not setting any ambulance. You can get up on your own now. But what's interesting is you can actually, I mean, we added a lot of humor to the application so that was kind of one scenario. The other was people talk about being able to generate real-time offers and contents based on location data. So what we did was we processed real-time data, location data in kind of the Las Vegas visual map of connected cars and people with mobile devices that have opted in for a service based for a restaurant or for a grocery and said, okay, who might be most apt for a coupon for dinner, you know, free chicken dinner. So I got to ask you the Watson question because you are very much for the customer. So I got to ask you, explain to the folks out there what is Watson's value as a product, as it renders itself in the product market? Is it the brains behind the big data? I mean, it integrates a lot of different components. You see the Watson foundations in a lot of the middleware. It's not like, you can't say if you can't buy Watson. It's not like a one, oh, you can't, but like what is the product market for Watson? And what are those capabilities in the market? You know, so first of all, Watson is so inspiring because it just begins to fire up your imagination about what's possible. So if you think about just kind of stepping back when you think about cognitive, it really is about how do you marry some of the human attributes and machine together in kind of a completely new way and cognitive meaning around ability to perceive and ability to reason and ability to understand. And we've been able to deliver a cognitive system for the first time. Now, when you think about it and you say, oh, how do I embed specific application capabilities like deep QA, like natural language processing, like machine learning or deeper text analytics, that could be embedded in a service. That could be a call service for a call center. That could be embedded in services that are automated or augmenting a knowledge worker or an expert in the industry. So I think the possibilities are really endless. For clients, what they're really wanting to do is really understand how they can take advantage of data for their organizations. Not everyone will absolutely need cognitive at this moment in time. I do think everyone will ultimately be on a journey for cognitive, but the entry points are going to be varied depending on both the sophistication of the company, their challenges and what their drivers are. And I look at Watson Foundation as really the enabling capabilities for clients to not only reach that journey, but also be able to understand how you process and access and manage the metadata. The zones thing is very interesting to me. The whole zone. The zones architecture. Yeah, yeah. The zones architecture. Oh, I've gotten great response from that. That's been unbelievable. Yeah. And the patterns are- So one of the things about the zones architecture, it gives, I actually met with an enterprise architect today who said, you know, this is a completely different way for me to think about my IT environment because we haven't really laid out the architecture in a modern way. And we've tried to stretch the limits of traditional systems for new applications, but we never really thought about it with the data lens. And so the zone architecture makes you kind of forces yourself to step back and say, how do you virtualize information differently depending on who's the decision maker, the type of application, the speed at which the volume of the data is coming at you, the level of predictive capabilities you want to embed in the service. We've been calling the term data first, which is a completely different mindset. Yeah, that's great. Yeah. Like data oceans, no one will ever pick up it. So if I say I know. I'm going to have to use that. I'm going to steal it. Data first, data first. Creative comments. What's the big potential about big data, of course? I've been saying all data. All data. Okay, now I'm going to practice data first. Okay, sorry, Paul. So we're a mobile person, we still love that. One of the big potential, the big data people will get excited about is one-to-one customer relationships. Oh yeah. But the flip side of that, of course, is the creep factor. And we see from recent surveys that a few of the 20% of consumers actually trust retailers with their personal data. Do you find that the executives that the user company is dealing with are exercising the appropriate amount of caution about the creep factor? I think the ones that are more serious about what they want to do when they understand their fiduciary duties, understand that. You know, it's a reflection of time, it's two dimensions. Time, culture, and technology. So, and let me talk about time and culture for a second. The available, let's say, you know, if you think about the millennial population, they're willing to share a lot more information than older generations because, and they're very comfortable sharing it. And they're also comfortable, not only in terms of the mechanism of sharing, but the type and level of detail they're willing to share for value. So I think there's a cultural shift that's happening in the industry, and that's a time dimension and a culture dimension. Then there's a third piece, which is really about the enabling technology. So we have been really at the forefront of enabling what I would consider data security, data privacy governance around big data. We're the first and the only actually vendor to provide data security privacy for Hadoop. We do it for real-time stream computing. We do it for a SQL and no SQL type repository. We've gone through kind of those aspects. The other piece is kind of baking in privacy, not after the back, but up front in the application. And so that's something that we're really trying to focus on. So some of the data services actually in BlueMix are the only data services in the cloud that actually have security baked in, that we actually put in the encryption and masking services so that you're already thinking about it consciously, or it's kind of part of the system. You don't have to think about it at the same level. So you're on board with BlueMix then? Oh yeah. And it's, you guys move really fast with that. So we'll see, keep tracking it, we're watching it. So I want to get to final word to you, because we're going to grab, okay, sure, absolutely. Are you meeting with people this week about the title of Chief Data Officer? Yeah, I would say at this particular conference there's probably less, but I will tell you, I've actually met more Chief Data Officers in the last six months than I have, probably the last three years combined. Typically what background do you come from? They're a mixture. Some actually sit in the risk office, some have been a part of the COO office, some have been in the IT organization. They are not necessarily, maybe technically proficient, but they actually understand the value of data, what information is really being used to answer what's in a business question in the organization, and they have to play the role of a steward. Not a data steward as in a data architect or DBA, but a data steward, true steward that says, this information is a strategic asset for the company, and we have to operate and provide access to it in a very different way than this information. And by the way, they also were conscious of as the value of the data increases, the risk may increase or decrease, and they understand how to operate that and think about it prolactively for the life cycle kind of aspects of the organization. Any thanks for coming on theCUBE again. I know you're super busy and you're really talking to customers, so I take a quick break out from the briefings, the Big Imagine Dragons concert tonight. I'm sure you'll be taking Dance on the Storm, Dance on the Storm, I hope to see you there. But I want to give you the final word. Share with the folks out there your personal perspective on why this inflection point right now is so impactful around customers and their businesses. Oh, the moment's now to act, and it's an important moment because it's the intersection of data, cloud, social, mobile, and now is the time to experiment. If you're not experimenting now, I think in you way, you're going to be behind, you're really going to be behind. But more importantly, the only limitation is really the limitation of the ideas that you have. It's really not the technology or the cost. Unleashing creativity, computer science, meets social science. Great, he was on earlier, he was phenomenal, he should watch that video, he was just. Oh yeah, he's very impressive. We wanted another hour, but he had to fly to Hawaii. A legend, a legend. I'd be a fellow, great, great guy. This is theCUBE in heat, you saw it with us, and we'll be back with our next guest, right after this short break. This is theCUBE live in Las Vegas, here for IVM Impact.