 Our guest is George Matthew, Group of Rights President and General Manager of Business Intelligence. We're here, we'll be talking about big data, mobility, analytics, business intelligence. This is where the sweet spot of the market is for SAP. Social, mobile, any other buzzwords we can throw in there? I'm just kidding. SAP are working night and day. These guys are tech athletes. We're gonna burn the midnight oil to bring us the technology to bring change around this big data tsunami. We're pumping out data here on theCUBE. Customers are using iPads and iPhones to pump out big data, Dave, and mobility is actually a big part of it, but we heard on stage from the co-CEO Bill McDermid that business intelligence is the game changer. You talked about social media, you talked about data. So, George, first question, big data. Is that new to SAP? Instead, we're hearing more things like fast data. Talk about the data, role of data in the show here at SAP, and also the business intelligence market in general. So, to answer the question specifically, is big data new to SAP? A lot of ways big data has been enabled and around from not only SAP, but many of our customers for a good part of a decade. I think the velocity and change of how big data is effectively consumed, the rate of increase is that's the differentiation, that's the change that's happening in market. What I'm witnessing now is the amount of information that's getting produced on a daily basis, on a weekly basis, is exponentially greater than it was even two to three years ago. And so, the opportunities and challenges that come forward because of the big data opportunities that are in market now are much more front and center. And now, it is a CXO, CIO level issue that becomes much more prevalent in the boardroom as opposed to something that was probably in the hands of a data geek or an architect previously. And the huge amount of that data is, of course, unstructured. 90% of it now, it's being created as unstructured. I think IDC said 1.2 exabytes of data was created last year, you know, yeah, 1.2 exabytes, which is 1.2 million petabytes, a lot of data. And mostly unstructured. Your business, from an analytics perspective, has largely traditionally, anyway, been in the structured base. So what's changing? How do you adapt to that? So there's quite a bit that has been traditionally in the broader analytics market about structured data. And certainly that's the markets that have been serviced by analytics solution providers like ourselves for many, many years. One of the things I've seen is that, even in the past half decade or so, we're seeing much, much more structured information derived from unstructured data, right? Creating meaning out of unstructured data. Bringing structure to unstructured data. Yeah, absolutely. So business objects actually acquired a text analytics product many years ago that's very much embedded directly into our enterprise information management capabilities. So when you can go ahead and take unstructured views of information, derive meaning structure out of it, and then be able to map that against more traditional analytic views that starts to bring forward a different way that you can consume information that you weren't able to previously. So how do you do that? Is that sort of a unified information management approach? Is it just require new architectures? Give us a little insight there. No, I think it's much more additive than that. In a lot of ways, business objects has been a pioneer in delivering what's known as a universe. The capability of being able to bring data from all forms and shapes in the enterprise forward into a view that business users can very quickly consume, whether it be on a mobile interface or on their traditional device. What we see is that you can, and we have, put forward the structured information in a way that you can move it directly into the context of a universe, expose that as how people would naturally want to see information in their structured world and have that composite view naturally being delivered to them. So in this world of analytics, you have this tension going on between the business guys who want what they want, they want it now, they want it fast, they want it functional, and then the IT group that's trying to standardize. And there's been so much acquisition and consolidation that exacerbates the challenge. So how are you guys, first of all, are you hearing that and how are you guys dealing with it? So I do see a few things that are happening. We are seeing much, much more prevalence of particularly the decision making around information really getting in hands of end users and business users. And so there's two schools of thoughts and there's two types of customers that I've seen so far. One is that IT has become much, much more agile. The ability to get solutions in the hands of those business users faster driven by an IT organization. The second is that a lot of forms of Agile BI and intelligence in general is largely getting very much directly in the hands of business users and it's a business user LOB driven activity. And so both are actually very much relevant. We're seeing much more increase of in-memory data marks directly built for a line of business. We're seeing much more increase in the fidelity of what types and shapes of data go into the corporate and enterprise structure. The data warehouse market, hence the business intelligence market has changed significantly over the past few years. Most recently in the past two years. What can you share with our audience out there from your perspective? And also you talked to a lot of customers, SAP customers, non-SAP customers. What has really changed? I mean, we're seeing trends out there, also style of state memory for faster caching and response time for low latency and fast data as we call it. And we're seeing movements like Hadoop or Cloudera as a market leader and an open source distribution of things like Hadoop. This is changing, radically changing data warehousing. And then the business intelligence market just wasn't that agile like Bill McDermott was saying, you know, things are happening in real time. So enter real time, enter big data, enter these changes. What's going on in the data warehouse market? What has to change? What architecture needs to be in place to support the new model? Yeah, so I think one of the fundamental things that I've noticed in the data warehouse market that's changed is that memory is the new disk. Disk is effectively the new tape and tape is dead, right? So you're seeing this natural continuum now of information that's stored in a very hot fashion, analytically exposed, available, immediately queryable, exposed to a mobile interface, exposed to business intelligence that is instantaneous in its responsiveness. Not, you know, I run the report, I get a coffee, I come back. Yeah, some fenced out warehouse, somewhere, it's like slow. At the same time, the data warehousing world is continuing to evolve, as you indicated, to really take into account the big data problems that are, and opportunities that are emerging in market. So the petabyte scale is now certainly something that is not unusual for most organizations to be considering. On a day-to-day basis. On a day-to-day, week-to-week basis, certainly seeing that kind of scale. And that really comes from information that's within the four walls of an enterprise, but also commingled, mashed up, incorporated with industry information, outside information, seamless information, and the social experience that comes through. And so what we're seeing now is that the use of Hadoop, the use of MapReduce-like functions almost behaves as the endpoint of a continuum, right? Where you want to be able to take the most unstructured form of information, but to bring that into your enterprise view. And then at the same time, have very fast analytic responsiveness at the, you know, in memory level that you can get a mobile experience for BI very much delivered in the hands of end users when they need the data at the moment they ask for it. Do you see those movements as complementary? Oh, absolutely. And then, so. Absolutely. There's a lot of talk about data scientists and new skill sets. Data artisans, data scientists. Do you see that, you know, creeping into the sort of traditional point on the spectrum? Or is that sort of still in the lunatic fringe? No, I think this is basically the year of the data scientists or the data artisan. I mean, these are the folks that were in the fringe for many years because they're kind of sat in the corner and munched data themselves and kind of came back with analytic insight. But largely, these are the folks that are the new content creators of Business Intelligence today. George, the, obviously, data is not like as elementary as say maybe just throwing a Ruby on Rails front end and cloud host something. I mean, you know, that's elementary computer programming. Computer science, there's a lot of science involved in some of this big data tech. You live that every day in order to get the kind of, you know, responses that you have. Like the early days of client server where you guys, essentially, your core company was born really through that massive growth at SAP. Cloud is kind of in that similar inflection point, some say. What is the role of standards? So standards are important for a lot of growth. Is it important when you have these kind of open horizontal stacks, or, you know, you got Oracle, obviously you want to go fully vertical. A lot of people are trying to own the stack. Hadoop, for example, is a new phenomenon. On structured days, a new phenomenon. Are standards important, or they don't think matter as long as there's some stack that can support the day they're sourced? I think in the early moments of any sort of revolution and shift that occurs, the standards are not the first thing that people think about. It's the use cases and what the opportunities are to take advantage of the shift that's possible. I think as you get into the maturity and really you get past the hype and the real, you know, business case. Meat and potatoes, meat on the bone, as we say. The revenue generation and the monetization of these technologies occur, then the standards definitely start to emerge. So for us at SAP, and particularly some of the team members in the Business Objects Division, a lot of what we think about is how to make sure that as we get into this era of big data, we make it more humanizable. We make it more accessible for end users that literally could not be able to consume that kind of information in a very easy to use consumable fashion, could get access to it in a way that isn't meant that big data is just for the statistician, just for the PhD. And so we see that largely being delivered by embedding services as best as possible into the stack in a way that when you expose it, you know, the big data elements into an end user, it's the most simplest consumption form possible. And right now, one of the most simplest consumption forms possible is what we're seeing in the mobile movement with iPhones, iPads, Android devices. So basically what you're saying is standards really don't matter, because they could be kind of holy wars, but really at the end of the day, de facto standards. In the early days, standards matter less. Like in the moment that we're in right now, I think the standards are too early to be set. I think as you get into the market starting to really monetize and have more and more business function around it, you are going to see those standards. So I'd say within the next three to four years, those standards are going to emerge. So the wave of data, data is flowing at us. This is a tsunami of data, as Mike Olsen at Cloudera quoted on the Cube in the past. Just the ingestion of data, the extraction of relevance out of the data, the intelligence out of the data, is it's just a massive bombardment to end users, to IT enterprises. And it's just this noise among the signal, right? So the noise barrier is high on the data. You know, obviously we can all think about Google search. You know, PageRank helps create good search results that makes a good filter. But now we have this omnidirectional network environment where this is a tsunami of data pounding us. We're broadcasting data here in the Cube. You guys have thrown out tons of data from the show. What's the new filter? Is the new filter the app framework that you guys are proposing? Is the new filter the data mining? Wherever there's a lot of data, there has to be filters. Semantic filters, some tech involved, and what's interesting is that you guys were showing on stage around the business intelligent is, well, if I can run scenario planning in near real time or real time being a query, you're essentially filtering the data. So you guys, you think about this every day, I'm sure. What's your angle on this? You know, you got a lot of data, it's all relevant, but you want the signal of the noise. How do you get there? Yeah, so a few years ago, I released a product into market which is known as Business Object Explorer. It was the first moment in time that BI became more consumable by a search and navigation, a filter that's in the process of really understanding how data moves. And so that was very much appreciated by the market and successful. I kind of see the next level of the filter emerge through social. So there's a lot of unused reports, dashboards, things that just aren't, you know, they're produced for the sake of production. And I see social intelligence largely coming from the fact that, what's the most frequently accessed? What's the most frequently commented? What's the most frequently shared? How do we feed that in a way? Interesting fish analogy that Snobby had on stage there. You know, school of fish. Sensor and response. And that's a crowdsourcing network phenomenon, right? Sensor network between the two fish, you know? I mean, that's a social dynamic. That's just tribute to computing, isn't it? It informed it is with a very human element to it. Absolutely, right? I think at the end of the day, there is a very human element to making sure that the things that are relevant to end user surface to the top, and you sense and respond around the things that aren't relevant, and those fall to the bottom. What's a secret to the social search in your opinion? I mean, honestly, commenting those are gestural data pieces, but is it mashing up of data sets? Is it the mash-up of data? Is that something that you're looking at? Is it, because when you intersect data sets, interesting things happen, right? So you can glean new data out of merged data sets. So you put A and B together, that creates C, right? Is that something that's relevant? Yeah, I think there's a few things that are progressing on the horizon around data, and what does that look like? The first and foremost thing is, I think when you create data, I almost feel that you need to always have a visualization that follows the data. So there's always kind of a default visualization that coherently goes along with any data that's ever produced. In a similar way, when you look at data and its forms, particularly as it becomes more usable by individuals, you got to get into forms that are more easily consumed by the devices that are now prevalent in the market, right? So I think that when you see where we've gone with a lot of our business intelligence solutions, we've invested pretty dramatically in not just what were the interfaces of the PCs that we have on this desktop, but also the mobile interfaces that are now emerging. And so on these interfaces on the mobile side, you have geo-located GPS-ready devices, right? So now you can take a time dimension to data, a spatial dimension to data, and bring it directly onto a mobile interface. And so that's what I see as kind of the next generation. What are the number one use cases? What are some of the use cases? Two questions, and then Dave, I'll let you jump in. I know you're chomping at the bit there. Well, the first question is use cases. What are some of the use cases that you're seeing now that tease out some of these future scenarios? Okay, that's one question. And the second, oh, answer that question, we'll come back to the other one. Use cases. You know, some of the description of what I made, say for instance, around time in geo-based understanding and how JDoS geo-coded better and being able to understand how things move in the context of analytic data. One of the examples that I see tremendously is logistics, travel, transportation, service management. So if you're doing a service workforce, right, that has to be routed effectively, and there are changes in what's happening in the information or where your assets are located, you need to be able to make that in real time, the changes, and be able to re-optimize and re-route. Dynamic, almost like runtime, as I say, right? And so in that case, if you don't have the analytic data, combining with the real-time view, offered up in a way that's delivered on a geo-map, right? You can't deliver it in a way that's going to be effective for the person that's in route, that's started his dad at nine o'clock and is gonna finish it at five, and he or she wants to get the most optimal experience of what they're responsible for. And so these kind of use cases are very much what I see as the next level of operational business intelligence in the enterprise. I'm John Furrier with SiliconANGLE.tv, with Dave Vellante, my co-host at BostonBasePokieBond.org, we're at SiliconANGLE.tv, the worldwide leader in tech, live event coverage. This is theCUBE, our flagship product, where we extract the knowledge from the guests and the show to report back to you and share with the world, sharing his power, that's our motto, and the smart nodes connect here on theCUBE. We're here with George Matthew, who's the VP and General Manager of SAP's BI business, and, you know. Can I ask one more question? Yeah, sure. My second question, and then you go. So, obviously, with the ecosystem here, big play for EMC, developers are actually a part of that, with the apps that teases out, hey, there's some developers, since you're not going to be the app company for everybody, as we were talking about earlier in theCUBE, white spaces for developers. Obviously, having a partnership strategy has been core to you guys. Absolutely. What are some of the white spaces and areas that you guys are looking for, or looking to for support and or rising tide, floats all boats kind of philosophy? Yeah. So, one of the areas that we didn't really cover in this discussion was just where the cloud continues to evolve. So, one of the things I'm seeing now is that there's quite a bit of convergence of certain leaders in this market, right? And anytime there's leaders in certain areas of the market, how two leaders in complementary markets, for instance, converge, always is done through partners. And so, I think there is an incredible opportunity for ISVs, in this case, SIs, who are building solutions in market, as well as just straightforward reselling and distribution channels. In what areas? Like the in-memory stuff? Is it the HANA? I mean, the analytic stack is completely ripe for particularly ISVs and SIs, right? And where they get that information? On your site, is there a specific? Oh, yeah, yeah, from our Eco Hub, as well as just our broader channel and ecosystem partner solutions that we've brought to market. We are very much delivering business analytics in the most partner-friendly possible fashion. What's the competition like? Obviously, there's an emerging segment here with analytics. Again, you guys have an advantage here. I mean, I got to go back and do some digging, but apparently from what I'm seeing and talking to some of your SAP labs guys, is that this in-memory thing is pretty huge. I mean, you're talking about a speed incremental advantage that kind of moves the ball down the field. I think developers will flock to that if they can figure out how to fit into it. So we see a few things. As far as competition goes, we have had a seminal year in 2010. If you look at the overall business, it was well into the range of approximately a billion euros. So it was a pretty significant business in analytics for us. It was the fastest growing aspect of the overall market. And when I look at the competition, even look at the Gartner share report that came the last two weeks, we literally saw business intelligence grow an entire market share point of 24% while other players in the market actually lost share. So they're clearly winners and losers that are emerging in the overall business analytics space. And you're seeing us deliver and continue to deliver being the number one delivery provider of business analytics. We have George Matthew, Group Vice President General Manager of Business Intelligence. I'm John Furrier with SiliconANGLE.com and we're talking about what's going on at SAP Sapphire on the ground, live coverage inside theCUBE. And it's a great event here, Business Intelligence and Analytics featured on both keynotes, extensively by both CEOs. And I'm sure tomorrow we're going to see it with the CTO. It'll probably show some lift the covers on some cool stuff. The analytics market is hot, obviously. How, what gets you excited right now? I mean, obviously it's an exciting year for you, you had good year revenue-wise, companies pumping on all cylinders, you're bigger than Disney. If you think about it, SAP is as relevant as a Disney given the fact that, if you look at all the game platforms, the entertainment platforms, the business platforms that are actually being powered by SAP, you guys are a player, okay? Your name out there will be a challenge this year, sounds like there's some good plans. But the tech side, the platform side, this is transformation, cool. What are you excited about today in the second half of this year as you look around the corner? Yeah, I think there's a number of areas that are still unfinished business for SAP. And certainly Jim started to show a few of those areas today. You saw the first version of Sales on Demand as a fully cloud-based offering that is very much a connected service back into an on-premise solution for CRM. And so we do believe that as the cloud continues to radically grow and shape itself, that we are a prodigious player in cloud-based services for analytics and applications. And so we're very excited in terms of what is the next generation of cloud applications delivered effectively as a hybrid. We're going to be talking with Mark Milford coming up after you, who's the vice president of business development. Yeah. What do you think his focus is going to be? I mean, obviously, you guys do a lot of business at this show. I mean, I heard greater than 50% of your business is booked during this event. You guys pull out all the stops. We certainly do. What's the business agenda for SAP? What's the focus? So, clearly, Sapphire is an event we bring our customers, our partners together to have the meaningful conversation of how revenue happens this year. And certainly, that's where Sapphire has been well-known in market. From a business development standpoint, we see this as a seminal moment where you understand the business direction that SAP is headed and really sets the agenda for the rest of the year, right? You see the big deals that emerge within SAP's ecosystem largely happen because it cements itself here or the idea that's planted here. And then it actually moves into a germination stage where it profits from itself certainly through the rest of 2011. Final question for you, George, running business intelligence. What's the next five years going to look like? Five years from now, shoot the arrow forward. Where are we as an industry? Yeah, I think I alluded to a few elements earlier in the discussion. It's certainly going to be a much more social BI experience. Certainly, there is no question that big data is going to be everywhere. It's going to be pervasive. You're seeing a broader adoption of users that aren't just going to be looking at things from here's a transactional application, here's an analytic application, much more composite views of data and analytics delivered when you want to make the right decision, being able to write it back to a transaction the moment you make that decision. And so that view of a much more seamless experience, not only in how your data works, but also how end users are exposed even from a mobile perspective is where I see the world going in the next few years. Seamless experience for users, an enterprise of social, business intelligence, big data, composite applications, visualization. This is the future of tech. I predict wearable computers and SiliconANGLE will have a Hadoop distribution. Great stuff. That's a joke, by the way. I know, that's why I laughed. George, Matthew, thank you so much for coming on Inside the Cube. We really appreciate it. Thank you again. Thank you for your time. Appreciate it. Good job.