 Okay, we're back live here in Las Vegas. This is SiliconANGLE.com's theCUBE, our flagship program, got to the events and instruct us to look at the noise. This is IBM's information on demand conference, their premier conference about information management, big data, analytics, all kinds of great stuff happening. I'm John Furrier, the founder of SiliconANGLE. I'm joined by my co-host. I'm Dave Vellante of Wikibon.org. Welcome to theCUBE. We're live in Las Vegas, IBM IOD. We're here with Mark Kettering, who's the CEO and president of Brightlight Consulting, an analytics company that works with IBM, works with the T's to help customers get the most out of their data. So Mark, welcome to theCUBE. Well thanks Dave, appreciate being here. Yeah, so we're here at IBM at the IOD. This is their big information management conference. IM has sort of become this sort of stodgy old term. Now it's think big, big data. So you've seen, you said your company's been around for about eight years. You've seen this sort of transformation from business intelligence, a lot of compliance and reporting and now all of a sudden it's exploding into big data. We're actually seeing the promise of BI put forth as, we maybe recast as big data. What do you think about that? Well, for us it's like a dream come true because in the world of business intelligence and data warehousing that Brightlight lives in, we always were attracted to the higher end of that market, it's a large multi-terabyte, the really complex requirements of a business to want to really interrogate their data to gain more insight. And of course for us, getting better answers means asking better questions and it's not just the standard monthly report, it's really about the idea that comes up in the conference room and someone runs out of the room and comes right back with the answer so you can take action. That's what's interesting to us and that's where we think data really provides the biggest bang for the buck and that's what big data I think is really all about. I mean, little data, data marts, the monthly report, that stuff's been around forever and will continue to be but big data is when you're really getting that extra insight that makes you move ahead of your competition. So I mean that existed with big large data warehouses but it certainly didn't exist in anything that came close to real time. That's right. You know, very much looking in the rear view mirror. That's right. Maybe doing some mathematical models to try to predict and do some advanced analytics. That's changing. It is. It's changing because what people are calling data today is not stuff that necessarily fits into columns and rows and a table. It could be emails. It could be a comment in Twitter and often that's what it is. And so interrogating that kind of data that's unstructured is the new challenge and going through tens of terabytes of comments out of Twitter in order to glean what people are saying about your product or your customers or your company. That's the new challenge and that's where big data really has relevance. If I think about traditional business intelligence and data warehousing infrastructure, it's sort of this patchwork because the problems are and were so hard that people would throw the latest and greatest at it as a result. They've got this mixed collection of stuff. It's bubblegums and band-aids. It's one of my clients that it's like a snake swallowing a basketball. Now you hopped on Netiza early. Yes, we did. Talk about why, what that type of architecture brought to your business and then where we're going. Yeah, yeah. So when we formed Netiza eight years ago, I'm sorry, when we formed Brightlight eight years ago, we wanted to focus just on the most challenging data warehouse and BI projects. And we very quickly saw that Netiza was taking that on and defining this space of a purpose-built device where the operating system and the database and the storage and the CPU were all hacked on to just focus on analytical processing. And that created such dramatic performance improvements that we wanted to be part of it. It was also nice. They didn't have a professional services department. So we kind of became virtually their lead partner for doing that kind of work. Now, as they've almost broken Moore's law and continue to grow the capacity and decrease the price point of what they offer, you know, they're getting into petabyte implementations. That for us and the 60 people inside of Brightlight, that's what they love to get out of bed and work with those really large, complex implementations. What are some of the barriers that you got your facing when you go into an environment? Because that's where they all see the blue sky, like they see the transformative nature of big data and analytics, as we said, it's SAP Sapphire, running at the speed of business is what people want. To get an iPad, they go, wow, I want that, right? So then comes that from the CEO down, I want that on an iPad, which basically means analytics in real time. And so everyone goes, okay, great, new work order, new job, new investment, which is great. Now, the reality is it's got to start somewhere. So take us through that process, help make the sausage and the sausage factory, as we say. And what are some of the barriers that need to come down? You know, interestingly, the biggest barrier we find people really being in a place where they want analytics is if they're doing too well. Companies that are succeeding and succeeding on their own, you come in and show them the value of increased insight in your business, and you just see the eyes roll to the back of their head. They still believe they can get where they need to get based on their own gut instinct. And that's kind of the old business model, but it's often business that are hitting some sort of a wall of challenge, either from competition or their growth curve has stopped or there's some paradigm shift in the marketplace. Those are the folks that are saying, if I don't get under the cover beyond my instincts and look at real hard data to really correlate what's happening in the marketplace that I can bet on, then I'm probably gonna fall behind my competition. Like this morning in the keynote presentation, they said companies that invest in meaningful analytics are, I think it was 3.6 times more likely to outperform their peer group, because they've made that investment. And it's the ones that either want to zoom ahead of their competition or feel like they may be falling behind, those are the clients we find are most motivated. The other barrier we find is some of the other companies that are out there, they look at analytics and complex data as just another database application. You look at Oracle, to them it's just another note on the grid, no difference, no purpose driven device type stuff. Didn't Oracle invent big data? Well they invented a cloud, hit flash, that's right. Dot, dot, dot, I'm sure they'll take credit for all that. It's all for service. Next year they'll take credit for something else. That's right, exactly right. Probably your tie. The cube. Yeah they did, they copied it. That's right, but when we've been in competitive situations to them Exadata and what they call an appliance, it's sun hardware and an Oracle database pushed together. Beyond that it's not very purpose built, but the stuff coming from IBM and these announcements on pure data, I think it's fascinating because they're acknowledging that different kinds of data compute tasks require a different architecture. What's your take on pure systems? Because we're trying to tease that out and kind of unpack the pure system, pure data approach. Yeah and compare it to Oracle because you listen to Oracle and they put up the numbers, you know, you're coming down the escalator in Vegas and it says Oracle 20 times faster than IBM and then of course you read the fine print and you say okay that's the three generations ago of IBM. That's right. But you hear Ellison talk, very compelling, very dynamic speaker, you're, at least quasi-independent, you could use anybody you want. You don't have to use Matisse, you're not part of IBM, so you chose that as an independent. So talk about that a little bit. Well, you know, again, I think it's the acknowledgement that Oracle is the big player for relational database and tools around relational database and then thus applications involving relational database. To them, when I truly listen to what they say their BI and analytics and data warehouse strategy is, it sounds good marketing-wise, but as soon as you get into a POC, competitively and you're looking at what they're doing, they treat it just like any other database application. They don't acknowledge a lot of the differences. Analytics is a completely different data model, it's a completely different way of navigating through data and you need to organize the data very specifically to get performance out of that. Oracle, I always say they can do it, but they don't build it to do that. To them, it's a grid with a bunch of nodes and the data warehouse is just another node on that grid. So as John was asking, so compare that to pure, so pure data was announced a couple of weeks ago, what does that all mean? So pure, the pure data systems, and I listened to the presentation this morning, they're acknowledging that whether you're doing transactional reporting or deep analytics or operational analytics, those are three different functions that require a different appliance, a different system with different architecture and now what they've done is they've, they use Natesa based systems for the deep analytics, using that MPP, they use DB2 which supports a lot more concurrency, so you can have more hundreds of users doing what they call operational analytics. And then they have this other transactional thing which I think is the ISAS, the old ISAS DB2 application, but they've worked on it and really honed it down for its particular function, so a client gets more out of the box ready to go as opposed to just a database that you got to change it for this or for that or for something else. I think it's, it's pretty sharp. I have to pressure you a little bit on that because help us understand this. So Oracle's got exolytics, they got exologic, they got exadata, so they got different exes, are those just packages or, you know, that's putting lipstick on a pig, my words, not yours? Well, you know, I'm not the most technical guy in my company, so I'm sure one of my consultants could give a deeper answer as to what's under the covers, but what I can tell you is that when our customers have done POCs, comparing Neteza and Teradata and Oracle, the two things we notice is the performance from Oracle for pure analytical processing, for pure data warehousing, always lags. Yeah, which makes sense that it would. Yep, and then second, and secondly, the work they have to do to get it to even its best performance is significantly more dial turning and indexing and partitioning, and they say, oh yeah, give me another couple of days, I can make it do that, whereas, you know, like Neteza and these pure data systems, they come much more ready to do that right out of the box. So you're saying dials and knobs, think of the past, we prefer not to have that, we want to focus on the business problem. I wouldn't say it quite that binary, but yeah, less dials and more ready-to-go functionality is better in the long run. Mark, I want to ask you kind of on a different tack, more on the business model side, so you guys are growing organization, and you're in the hot space, right? Obviously, big data, and IBM, they are the 800 pound gorilla, and when they do things, it affects the market, both internally IBM's business as well as around it. We've been covering on Silicon Angle a new site called Services Angle, and we started it mainly because no one was covering the services business, including web services, cloud services, but consulting services, customer services, essentially the channel. Yes. And so the question is, this is so transformative, this big data opportunity, it's accelerating change, not only for customers, but also the delivery side. So the old guys, the Capgeminis, they want to be the outsourced partner now, they want to be your, whatever their latest thing is, I'm using them as an example, the same is true for Ascension and everyone else. Those cycles are longer, and they're getting shorter, and they're not really built that way. Right. So share with your perspective, as someone who's in the trenches, you're in the vortex of this opportunity, what's it like as a channel, as an integrator, as a developer, as you're talking to customers, you've got to deliver solutions and work with IBM. So explain that whole market, what's the dynamics, what's it being disrupted, and what are some of the business angle there? Yeah. I've always loved, you know, I've been in the consulting and high tech world for over 30 years. I love this space the best of any space I've ever worked in because the opportunity to be deep in technology, and yet so quickly be directly connected to the business user, is more evident in BI and analytics than anywhere else, because it's very technical on the one hand, but it highly influences the day-to-day job of the business user. So from that perspective, the consulting opportunity, the services opportunity is really fantastic because you get to do the technical services, which a lot of my consultants love doing, but there's another group of our consultants that really love showing the business user how the technology will affect them in their everyday work and really make a difference to their decisions, their corporate performance. I have to admit- Disruption, how about the disruption? Because, you know, client server, that was a gravy train during those years, and we've been saying on theCUBE that this big data revolution is like the PC revolution and the client server together times 10 at a shorter cycle. So that's going to possibly decimate incumbents. Like the big guys out there. So what do you see as disruption points out there that affect the economics and opportunities and profits for consulting firms and the new boutiques that may grow into- Yeah, well I know you guys know that any time there's paradigm shifts, it's disruptive, you know, 50% of the market falls out because they're not able to work their way through. I'll give IBM credit. I think of all the big players over the years, they have always seemed to find a way to push through a lot of paradigm shifts and they're doing Hadoop work with big insights while they also still have a great mainframe business going on in the background. It was a period in the early 90s that didn't look like they were going to push through. I know, I completely agree. Amazing. It's an astounding. They've done an amazing job. But in terms of disruption, I think the fact that what data is is changing so quickly and where that data is going to be stored and how cost-effectively you can manage it, you know, the whole unstructured data thing is hugely disruptive. It's changing all the rules as to how we look at data, how we analyze data, you know, how we correlate different parts of data. That's going to open up a massive amount of new products and for a company like mine, Brightlight Consulting, it, we're constantly in room saying, how can we incorporate this new capability into some of the more traditional things we used to do? You were talking earlier about sort of what I would call the deeper business integration that analytics enables. That's why you're so excited about this. I feel like, I just always remember this in a flexion point, John, when Nick Carr wrote the book, Does IT Matter? And the premise of the book was essentially you can't gain competitive, sustainable, competitive advantage from technology, which I think we, most of us in this business, took offense to that. I said, oh, you've got to be kidding me. But CEOs listened. I mean, it was symbolic. And since that time, IT budgets have been down. IT as a percentage of revenue has been down. People, the mantra of doing more with less and cost cutting and budget cutting. And that is really, you know, to me underscores the fact that CEOs kind of bought into that. Ken, do you see the point at which analytics, will it live up to its promise in your opinion? I'm asking you to make a prediction here, whereby the business will actually get meaningful productivity gains from big data analytics and it will change, this is the prediction part, will it change the IT spending pattern so that it will actually increase as a percentage of revenue? Well, the first part, I think what's going to make it, you know, really be success is not the technology as much as it is the people issue. We find the companies where analytics is having the biggest impact, is when you have a visionary executive, you have an executive champion that sees the power that it could provide and basically wills the organization to wrap their arms around it, not around just the expenditure for IT to build the system, but for the entire user community to incorporate the analytical process into the fabric of the culture, how we do business, how we make decisions. You know, we go back to the data constantly and we look at the data and we ask new questions about the data and we demand a system that will respond to that. Now in terms of how it will affect the IT spend. Yeah, wouldn't IT spending be proportional to that? You know, my experience is that there's been paradigm shifts all along the way and the IT spend drops other things. I really don't see it that way. I don't see it causing a big spike in IT spending. Because of the advancements in technology, because more is lost. Yeah, yeah, I really do, I see that. I see the big opportunity with analytics is how it empowers end users and end users getting more self-service oriented. Expecting less from IT. IT, I need that report, when can you get it to me? No, it's more like I can go and get that report myself. So I actually think it's going to happen. I just think it'll be, you won't be able to count it because it's going to be so blurred, the lines between technology and business are going to be so intertwined and so blurred, you won't even be able to meaningfully count it. I mean, Dave, I think that book is so off base because it's like, it's so going to happen, but the thing that we're trying to track down is how. And one of the things that we've been trying to vet out and we're dancing around it and talking about it here, Mark, is on the consumer side, it's pretty clear. Personalization matters, right? We had some user experiences with Jeff Jonas. The resistable experiences solves the privacy problem. Interesting angle there, but okay, so personalization's good, but now you look at a business, how do you apply that kind of personalization to business processes? App store. We had the guy on from IBM Answers talking about stuff that they're doing. So this is going to create kind of a whole new mindset around IT. I think it is too. You have a perspective on that? Well, I just see that if you look back through the history of IT, it was about, it was always almost like a service bureau. You knocked on the glass wall and asked for things and IT produced it for you. And then suddenly about 10 years ago, there was this focus on service levels. IT's starting to treat their customers like customers. And now I see it almost like IT is going to evolve to where they're a fabric, they're in the background and they're running things, but it's all self-driven. It's all user-driven. They don't have to ask IT for things. IT just delivers up all the interfaces for anything and you ask your own questions and data. And IT fabric like. Yeah. I see that as really possible and of course the cloud is going to drive a lot of this because if you don't do it and if you're not cost effective, out to the cloud and your department's liquidated. My last question, if Dave has one, we can go there, we got to go to our next guest but consumerization of IT, converging infrastructure, all that's happened, software-led infrastructure, we're calling it. Shoot the arrow forward five to 10 years out, knowing what you know. You've seen a lot of business cycles. You're excited about the tech and the business, touch points here. Yep. What's your vision for the next five to 10 years? With big data and more compute, ingestion of tsunami of data, vertical markets, just green field opportunities for new kinds of apps. Self-service enterprise, this kind of thing. What's your vision? How do you see the half-shaped marking shaping out? I think we're all moving to the matrix. I think that's, and I say that facetiously but in a sense, I see us moving to a real-time world eventually where the data is always just flowing and you start pulling what you want out of the data, out of the river. It's almost like you're fishing because instead of the data being something you have to go get, it's just moving in front of you all the time. You've just got to pull it out of the river, out of the water. You've just got to pull it out of the river and you'll have monitors that say, well, the data that's going past us is saying this and you pull it out of there and you can see it. I see that happening. IBM Streams product is starting to, it's a very complex product now to use but utilities, they're starting to use it in utilities so all of your meter readers are constantly pulling data and it's just moving in real-time and then you just grab it and put up results. I see that's probably the trend where all this is ultimately heading. Yeah, we had a CUBE interview with the CEO of Bleco. He was involved in Firefox, Netscape, and he's an old-time tech geek like us and he said everything that was ever invented will be invented was on Star Trek. So I'll add that the vision is the matrix plus Star Trek. There you go, there you go. Mark Kettering, thanks for coming on theCUBE. We appreciate it. Bright Light Consulting, congratulations. Folks, go see Bright Light Consulting. Great, great friend, we got to know them. They're our neighbors here inside theCUBE. They're booths right next to us, great group of people. Enjoy kind of hanging out with them here. Live at IBM's Information on Demand, this is SiliconANGLE and Wikibon's theCUBE, our flagship program. Extracting the signal from the noise, we'll be right back with our next guest after this short break.