 Okay, we're back, this is Dave Vellante. We're live from IBM IOD, thinking big. We've been thinking big all week. This is IBM's big data conference, it's really transformed from kind of a staid information management, governance, you know, legal council event to one that's really dynamic and moving at the speed of data. So we are here live, this is theCUBE, SiliconANGLE TV's production, this is Big Data Week. We're on our way to Strata, we're packing up theCUBE, flying the red eye in, we'll be broadcasting tomorrow, so keep the tweets coming, you guys have a great audience, really appreciate you hanging with us here, I know it's late on the East Coast and really thank you for your continued support and watching us. I'm Dave Vellante, I'm here with my co-host. I'm Jeff Kelly, Big Data Analyst with Wikibon, we're here with our next guest Inhi Cho-Sue, who is the vice president of product management and strategy in the IBM software group, information management, welcome to theCUBE. Welcome back. Thank you, excited to be here. We had you on at Edge in June. In Orlando, it was great. It was great, smaller show than this, but very focused storage, near and dear to my heart. Big Data and storage, they go hand in hand, you've got to store it. I know, where's the storage guys here, I don't hear enough about the storage companies. They have all the types, right, flash and memory, tapes coming back in Big Data. I believe it, I believe it, people don't talk about it, but tape is coming back, why? The cost, right? The price is just amazing. Well, it's an order of magnitude, you know what somebody said today is, Hadoop is the new tape. Did you hear that? Hadoop is the new tape? Hadoop is the new tape. No, I haven't heard that yet. So, so how you been? I've been good, this conference is fantastic. We hit over 12,000 attendees, you know, I had an opportunity on Monday to be on main stage. That was a first on that kind of... Were you there with Jason? Yeah, right after. Yeah, right after. All we did was push a button and then he just went, scream a consciousness for... He's like an energizer bunny, you know? Like I thought I had pretty high energy, no, no. This guy runs on something else. He's very smart and inspiring, I tweeted out, don't watch this video, it will blow your face off. Oh yeah. It was really fantastic. So talk about your keynote, I would never have a chance to see it because we're doing the Q&A. What did you tell people? We revealed the new Pure Data system. So on main stage, Pure Data is the newest member of the Pure Systems family. It's built on the same tenets as Pure Systems, built in expertise, integration by design and simplified experience. And I talked about the three models of Pure Data. And Pure Data is all about data. We looked at kind of the workloads clients care about most. So data and analytics, transactional applications and analytic applications and said, okay, how do we optimize the systems? Everything from the design to the life cycle of deploying, you know, database deployment or entire clusters to running really advanced and complex in database analytics. I mean, we really tune this thing end to end. You've got strategy in your title. I want to talk about strategy a little bit because IBM is, in my mind, really defining, redefining and defining the big data space. You kind of got the guys we're going to see this week at Stata, you know, the cloud heirs of the world. They did their definitions. You redefined the big data space, really bringing in your analytics mojo to that big data space in a way that I think is very impressive. Talk about that a little bit. Was that deliberate or did it just happen? Very deliberate. Very deliberate. Why? Because you've got to think about, clients have spent millions of dollars on investing in infrastructure and capabilities in their enterprise already to be able to deliver services, customer warehousing capabilities for campaign management or doing fraud detection capabilities. They're already running systems and now we're saying, hey, there's some new technology that's available that can augment what you're doing. Now, in order for clients to be successful in doing that, you've got to take them from where they are to this new place and link the two, right? And to link the two, you have to do it in a thoughtful manner. That's why we talk about four Vs of big data, right? From variety, velocity, and now veracity, truth, and data because data governance and quality matters. I want to add value. It's a fifth. A fifth value. The analytics, information and analytics is the priority, one of the top priority growth areas for the entire IBM Corporation. So Jenny Rometti's been very clear our CEO. Our chairman has said, you know, this is the area where we're going to progress forward. We've spent $16 billion. Why? Because context matters, context, excuse me, context matters, right? Precision matters. Watson generating answers that are 50 answers doesn't help. Watson generating a few answers with a high probability of it being correct helps. That's just understanding large sets of data is one element. Turning that information then to insight is the second. So. There's also a big emphasis on integration. It's a classic IBM playbook, right? We're not just going to throw out point products. We get this ridiculously amazing portfolio, complex portfolio, and we're going to stitch it together in ways that add value for clients. Talk about the integration play. Oh, sure. Well, we have this thought on a couple levels. So one is at a technical level where you say, you know, now more than ever, when you think about big data, there's multiple information coming at you from multiple sources, right? Machine generated data, data generated by people, different types of content, structured data. So how do you unify all of that in a way that it's consumable? So that's one piece. Then you have to think about the way the businesses run. So we have this notion of systems of records, right? Systems of records are traditional systems that are running businesses today. This is where your account information sits. This is where, like, core customer information sits. And now there's kind of this emerging thought of, well, clients want to invest in and understand capabilities to understand systems of engagement. And what's the integration between the systems of engagement and the systems of record, right? It may not care as much or not be upset as much if you load a picture on some site and it's like of a family member or it's, you know, some event you already had. You'd be a little disappointed if that picture got lost, but you would be really upset if it was your paycheck picture photo that, you know, a bank lost, right? So there's a level of integration and quality and security and governance that you want in how clients are dealing with their end-to-end sort of business capabilities. So do you see the world moving from a transaction emphasis to an engagement emphasis? I think it's a balance of both. I mean, 80% of most businesses invest still in transactions. Why? Because commerce matters. So commerce isn't going away. Order management isn't going away. But yes, engagement is exciting. Why? Because consumers are now controlling more of the power and they want to interact differently. They want faster response time. They want simplicity in the tooling. So it's an emerging set of needs. We're responding as quickly as possible to it. And a lot of the growth and strategy that we're investing in, like social business, smarter commerce, it's about recognizing those systems of engagements. It's a huge part of IBM's growth. I think it's a virtuous circle too that actually the engagement leads to a transaction ideally. Oh, absolutely. Absolutely. More engagements drives more transactions. Yes. That's the idea. So I want to talk a little bit more about the pure data system and the work that went into that. We were at dinner last night talking a little bit about some of the design, all the hours of design that went into it. You told an interesting anecdote if you could share about the people lining up to have their picture taken with the box. Oh, yeah. But tell us a little bit about why that kind of, you know, it's a really just looking at the machine. I mean, it's a great looking device. We talked a little bit about design. That's beautiful. It's a nice design. Oh, it's amazing. You know, we launched this in Singapore on October 9th and it was amazing. So you forget when you're working in enterprise software, like how difficult it is for people to tangibly touch, you know, tactically touch that or experience it until after they've deployed it or are using it for some time to see the value. And for the first time, on the day of a launch of something, we actually saw the immediate response, not necessarily to their, you know, experiencing and deploying it, but actually just this year, industrial design of it. We call the door, the door is incredibly cool. It's called a triplex door, three dimensional, very slick blue. And the design time took about 12 weeks, just the design time. The team thought through the aerodynamics of it for airflow. We actually even used some baby powder to test the airflow, you know, insulation for soundproofing, thinking through energy levels, power consumption. I think the team went through about four or five total iterations to modify the design. It is an amazing door. So what happened in Singapore is we introduced the box after the meeting. You know, it was on the main tent stage. People were lining up to take a picture next to the box. It is, it is awesome. It was awesome. So you were at the Singapore launch? Yeah. Yeah. I was talking and did the hot topic on pure data. So I introduced the new pure data system to everyone there. And we did dive. We were in Boston. It was a good event. Right? You guys were in Boston with Arvin and Bernie. Yeah. It was the original pure systems launch as well. Oh, in April. In April. Okay. And it was good. I've said several times, IBM was a little late to the party but came in with guns of blazing. Of course, the IBM doesn't agree with that, my analysis there. But you guys do a good job in that space. Well, you know, it's a whole different level of thinking. We're sort of hitting an inflection point and kind of the timing of the technology. And I think we hit the cycle every 25 years or so. But where you have, the clients are saying, you know, I have to deliver my services faster and better. There's some degree of pressure and time in terms of what's lost and them trying to figure out all of the specific components and integrate all the pieces themselves and spend too much time really on the, what I would say, assembly and management of systems rather than focusing their time on delivering the services for their business, right? So pure data is really about saving our clients a lot of time, money and energy and resource. So you can then put into adding value or adding value, which is they want to run the values. They want to run the analytics. They want to run their applications. I mean, they shouldn't be spending time trying to like construct and tune general purpose components to get the optimal performance when we really designed it from an outside in view that says, okay, what are the workloads that matter? What's the optimal way for it to be, you know, work? So I'll give you an example. We've thought through things like the balance of in memory versus disc. And we've actually put that and prescribed it in the system. So you don't have to think about it. That's the ideal scenario for transactional workloads or in the analytics. We actually put the storage closer to the compute, you know, because it, it makes sense from an, I mean, the network, sorry, the network closer to the compute because of the path physical distance it has to travel in order or the analytics to run. I mean, these are levels of detail that we've gone through in the entire system, the cabling on the back. I mean, if you've ever walked into a data center, it's like a spaghetti mess, spaghetti mess, right? We actually designed and developed patents just around the cabling so that it's not only done for the initial deployment, but as you scale the box, you don't have to recable and you change compute nodes. So how do you spend your time these days? Oh my gosh, that's a loaded question. Customers, how do you break it down for us? So here at this conference, a lot with customers. I mean, probably the demand and interest in big data is really hot, huge, huge interest in integrated systems. A lot of interest in industry specific applications and dimensions. I mean, I'm probably spending every day at least at this conference easily with anywhere between 15 and 50 clients a day, depending on the day and the number of meetings. So share with us, what are they asking you? What are their, what are their big challenges? Yeah. So okay, so one client is saying, you know what, we're kind of wanting to transform what we do around enterprise data warehousing and saying, hey, let's do this in a much more creative way and in a new way. How do I bring together both my structured information with unstructured information? So that was one dimension. Another client is saying, you know what, my performance around my SAP applications just are hitting a max. Should I be investing in kind of alternative solutions or how can I improve the performance of that? What's the underlying infrastructure about it? The other topic that's been coming up is big data and security, right? There is none, meaning, you know, think about it and how is IBM investing in security? And we've spent a tremendous amount of investment over the last year and actually Robert LeBlanc has set up an entire security division around it. Cloud, cloud management, managed service providers I've met with a few saying, you know, in this kind of new world where we're trying to deliver more services, we've got to figure out a way to more easily consume the infrastructure capital costs too in the way we operate our business. So the range has been pretty broad. Another client said, you know what, I want to apply big data analytics to understand kind of new services. One of the clients on stage actually was Conoco Phillips on Monday about well drilling and well placement. I mean, think about it, Iceberg, in trying to place a well in an ocean moving full of glaciers is not an easy thing. That is a big data challenge. Big data challenge. So you mentioned, the first one you mentioned was the enterprise data warehouse, like the transform. To me, that's kind of a euphemism for, there's a lot of frustration out there existing enterprise data warehouses. And so, Jeff just wrote a great piece talking about how, you know, data warehouses is critical infrastructure but in a way it failed to live up to the promises and now we're seeing with big data, new hope. Do you sense that from customers? I do, I do. Well, the possibilities, right? What's interesting is when I engage with clients, they actually give me new ideas. So one of our clients is John Deere and they've been using some of our technology around Vivissimo but other capabilities across our software business. But one of the things that they're trying to evolve to is smarter farming. And what does that mean? Well now, you know, these tractors, I'll just put it very simply, can actually send a picture image of let's say a 10 by 10 meter square foot of the plot, send it to headquarters, they run the analytics on what, based on the topology and soil content mixture, and then sends a message back says exactly how much water or fertilizer that should be spread across that same space and then the tractor can memorize it and repeat the pattern. So then the question is underlying in the technology pieces is how do you capture that data? How do you capture the GPS location data? How do you run the analytics as fast as possible? How do you dispense? And then that has an entire implication to the supply chain of that entire industry. But you think about something like that, that is transforming even the nature of the business that a company like John Deere is even in. I noticed, I mean, I've observed and it's pretty obvious I guess that IBM's really attacking these problems on an industry by industry basis. I mean, obviously you've got some more applications. But why is that? I mean, talk about that a little bit. Well, because we live in a world where the information is so transparent, right? And everyone has, we live in a world that's hyper connected. Everyone has access to the internet. Everyone has, and that's created this kind of need that's fueling another need, which is the quick response, faster response, faster precision, transparency and pricing, transparency and quality of service. And then because of social context, people have a greater voice, regardless of let's say their prior experience or stature or role in a particular industry or supply chain. So when you think about that and that competitive dynamic, if you don't really understand the mechanics of a particular industry, you can't really support the data requirements because most industries actually are kind of mixed in terms of the degree of regulation, the types of data. The data could be standardized and have unique requirements. The taxonomy and ontology of the data is very different by industry. So another good example, there was a sports apparel company. They designed like running shoes as an example and they were able to compress the design time to a matter of a couple hours, meaning in terms of the response, how quickly of how well the shoe's going to sell by putting it in the open sort of social kind of crowdsourcing area and then feed that back in. Historically, that would have taken like a year because you go through qualitative research, you have a focus group, you decide whether or not they're going to like it and then within like a matter of few hours, they actually know very quickly how well this product's going to do and what segment of the market, what price range it should be at even before they go into production of the shoe. I mean, this is a whole different kind of world we live in. I want to ask you about the innovators dilemma. I mean, if you're familiar with the concept. So a lot of people think it's a fate, a complete that a large company with a big install base is going to have difficulty managing. I'm sure there are challenges. Why, I mean, I'm sure IBM is cognizant of that. It's not like you're asleep at the wheel. You've seen this movie before. I mean, IBM, the whole company changed because it couldn't, almost didn't cross the chasm, you know, whatever, 20 years ago. Why and how do you manage that old and new? How do you guys do that? And why will you be successful? You know, that is a tough question. And I think anyone in the technology industry struggles with it. But quite frankly, the answer is easier than you might expect. And the reason is, is you got to focus on extreme client value. And if that is the driving factor, then the innovations will drive from that. So extreme value. So let's say if you think about the capabilities that you deliver and how clients are consuming it, unless you're going to give them significant amount of cost savings, right? On the order of 30, 40, 50% of what, against what they're already currently doing, you're not going to be able to capture their attention, right? Because of the, let's say, the challenges of switching, the skills requirement, cultural change required. So cost is one element. Performance. If you get something that gives you 10,000 times the workload performance, improvement of something you're already doing versus a 10%, that's a huge difference in the factors. Even in terms of some of the things that we're doing in analytics, which I can't fully talk about yet, is we're actually looking at some capabilities that say, okay, now, how do we optimize, not just for specific types of tactical queries, but entire analytic workloads? And could we do that and multiply that by 100 times? And if we do it by 100 times, how does the fundamental engineering change? I mean, Netease is a fantastic example of it. They simplified the integration of the entire appliance and leveraging FPGA. FPGA has been around for a while. But the way in which the workload and elements of some of the work was done before, you've actually improved the performance of the entire warehouse appliance, right? So these are some of the techniques that we're also thinking about in the whole engineering. So what can you do analytics? What are we doing around compression? What are we doing around scaling of data? So it's, I think, focused on extreme value. And I think risk factors into that value equation as well. I mean, IBM de-risks the engagement and the solution in a large way. People don't buy from startups because they want you, they buy from startups because they have to. If you make it harder by closing that gap on performance or cost. That's an interesting way of saying it. But IBM does that. They wrap that big blue blanket around clients and they say, okay, yeah, maybe it's a little bit more expensive in the transaction, but in the long run, it's all about the value. So I think that's how you win in this game. And you say you've got that model down. I mean, it's... Well, we really are trying to put the client first in almost every scenario. And even if you look at what we do from a technology roadmap, we do it in increments of five, 10 years. And we say, okay, what's going to be the next wave in terms of new areas of investment? Whether it's security, analytics, systems management, cloud, big data, mobile. I mean, we're really on the edges of that. Yeah, and I should say that. You got it down in your software business. I mean, the software business, the transformation that you have made in the software business has been phenomenal. So really one of the bright spots. I want to ask you about IT spending. And since Nick Carr wrote this IT matter, IT spending as a percentage of revenue has declined. While his premise of this book was off base, it was symbolic. And in a lot of ways he was right, just for a lot of the wrong reasons. But nonetheless, IT spending has declined. Do you think that big data has the potential to reverse that trend by delivering hyper value to clients and getting CEOs to say, you know what, let's start spending again? Yes, because I do think big data has that potential. And the reason for that is because big data, people see it as a revenue generator. Not just as a, can I improve the operational efficiency of an existing process, right? Sometimes technology is leveraged for operational efficiency or compliance reasons in terms of the initial purchase. But when you think about new revenue sources and strategic intent and brand association, those are new spend categories, which force then new investments. Now, what most IT clients are saying in their budgets are their remain relatively flat. So how do they optimize within the existing investment so they can allocate that new spend appropriately into big data? I would contend that spend around technology is actually going to increase in the next two years. Why? We do an annual CEO study. And we've been doing this for several years. So the new CEO study showed for the first time, technology in 2006, 2004, sorry, last eight years. So technology in 2004 was the number six factor in driving the most important factor in organizational transformation. Now CEOs are saying in 2012, the number one factor is technology. Technology hasn't been number one ever. Ever. Ever. Oh really? Based on the study. Okay, yeah, we probably weren't doing it in the early days of the PC productivity. So the top factors were skills and market economy and globalization. Those were the factors for the last eight years. What's happened is technology has moved from six to one. And I think the reason is, is because of going back to the fact that we're hyper connected, people realize they can't just compete based on the traditional ways in which they've set up their business models. They've got to leverage technology to give them an advantage in the things that they could leverage their valuable resources doing the work that they should be doing. I think we're seeing that reflected in the, the CMO now is becoming as important in terms of technology spend as the CIO. And that's, people are predicting that's actually going to, the CMO is going to be one of the more important people when it comes to spending around IT. How does that impact from a strategy perspective, product perspective, how you engage? That's a really interesting question. You know, the CMO kind of agenda initiative and smarter commerce has been incredibly successful so far. And what's also interesting is for some clients in some of the meetings, we're actually introducing the CMO and CIO together because it's been such different portions of the organization. And now with the need to drive more, let's say, awareness and understanding a brand sentiment. Now, why? Companies have spent years, 20 years building a brand and building an entire organization. And with the social and internet kind of transparency, within less than 20 seconds, a company could be ruined, right? So you think about that kind of, that dynamic. Second is because of the choice and you know, certain industries, there's a greater push toward commodization or it's easier for clients to switch vendors or preferences for different products and services and the only way to differentiate is to actually understand what is it that they value, what are the core brand attributes and then try to build off of that. So it's a huge opportunity and there's every bit of that supply chain if you think about it in terms of how you engage clients, how you market to them, how you grow, retain and supply your partnership. It's a huge opportunity. That's interesting. One of the big trends of the last decade was the consumerization of IT. And it kind of made the enterprise a boring place even though companies made a lot of money, there was a lot of consolidation. I mean, clearly free cash flow was good but innovation was kind of down in the enterprise last decade. Do you think that the enterprise is figuring out that consumerization piece and embracing that in a way that can have beneficial impacts to the enterprise tech business? Oh yeah, absolutely. Probably the best example of that is mobile, mobile applications, mobile devices. I mean, yeah, you know, 10 years ago it was never bring your own device to work. Now it's something that is a top of mind item for most CIO, CTOs and even organizations that say, okay, there's such a blending of the way people work and live and smartphones and devices are a good example of that. And now you think about, okay, how do I service those applications? So we had a bank yesterday talk about the need for clients to be able to take a picture of their paycheck and then process that very quickly and how do you do that in a secure way? That's a new application. That means your ability now to response is very different. You don't have to live near a, you know, ATM and or a physical bank in order to bank with that company. You got my ATM with me. Right, you're walking ATM, right? It completely changes it. I think about every industry, it's happening. I just talked to you about the farming industry. I mean, energy utilities, telecommunications. The number of call detail records that happen on a daily basis for a lot of these telecommunication providers is staggering. Like one client, one Asian global telecommunications provider handles six billion call records a day. Six billion, right? So that's all driven. Why? Because of mobile devices and applications, but they want to make sure their quality of service is good. Now they want to figure out, okay, if this is a walking device that not only is indicating where a person is at what point, what they're looking at, what's of interest, how they communicate, could I use that also as a vehicle to, you know, market to them at any given point? So one of the questions we actually had a discussion was, you know, imagine you're in the subway and all of a sudden the billboard changes because they know that you're standing there, right? Based on your preferences, which is I know that you like to bike now. There's a brand new, right? You see, but that brings up a very interesting point around, and you hear this word, you hear the word when people talk about the privacy, you hear the creepiness factor in the big data. And, you know, how do you balance, just, you know, I think I've written before about how, just because you can do something with big data doesn't necessarily mean you should do it. So you've got to balance, you know, the... No balance, we're going balls to the wall, you know, all out, just changing the world. Forget the balance. It's all about the reaction you engender in the customer. So if it's the creepiness factor is played up too much, then that kind of backfires. And you can use analytics to understand that as well, what works and what doesn't work. Yeah, and there's also, a lot of this has to do with respect, both for your clients and the partners and the industries that you're a part of, and we realize that every industry is connected. You know, the world is interconnected. We talk about that. That's really the genesis of a smarter planet, which is there's got to be a smarter way in which we do things. It doesn't mean that there aren't necessarily repercussions of certain types of investments or certain types of activity, but you've got to be a little bit more thoughtful about the energy consumption. You've got to be thoughtful about privacy and protecting privacy. You've got to think about security elements and individual security as well as national security, as well as organizational security of licensed IP. There's multiple elements. And we try to balance that. That's a core element of, I would say, forget our solutions and technology for a second. I would say that's a core element of the value of IBM in terms of the way we operate. But don't you think that society is comfortable with things like, I think about search. When I search on something, it's throwing, and Google's throwing ads at me, and I'm very comfortable. In fact, a lot of times I want them to throw the best ads at me so I can find a supplier, but you think about, I don't want to have to go find this stuff. I want it to find me. So, I mean, I think there's a cultural shift in where I think people are going to become much more comfortable with sharing information about themselves, because they're getting more value out of that. Well, part of social business, which is one of our strategy areas and investment areas, is really about the shared community thought, because you're a part of it, and you have a voice. And what that means is, as you learn things, you share back to the community. And I think people appreciate that there is a level of truth that comes out through those relationships, and that whether it's done intentionally or not, or maliciously or not, right? So, in this kind of new context, I think people appreciate when things are done thoughtfully for them, right? It's a higher level of service. You like it when they know your preferences. You're going to have a better experience. It's like the ultimate hotel experience. When you go, and they know exactly what your preferences are, you're greeted in a certain way, all the shampoos and soaps are exactly the brands you prefer. Let's say you had the mattresses a certain way. Any service industry. I mean, really think about it. Well, that's why I respect the fact that Senator Rockefeller in Congress is asking Equifax and Experian, Experian, what data are you collecting? I want them to protect me at the same time. The potential of value creation by sharing our own information is so enormous that I think it's just going to swamp the current mindset that we have in society. I think it's important we, as an industry, have that conversation and more effectively communicate that message before legislators who perhaps don't understand it quite to the degree that people in the industry do, take actions that could potentially constrict what we can do. If people create more value than they extract, it's, you know, that'll all work out with my philosophy. So, thank you so much for coming on theCUBE. Really appreciate you coming on. Always a great guest. And please come back. Thank you. This was fun. Great to see you. All right, keep it right there. We'll be back with our last guest of the day before we close out and pack up and head to Strata. Keep it right there. We'll be right back. This is theCUBE.