 I'm Dave Vellante of Wikibon.org, and we're here with Dan Kamen, who is in the SAP Business Intelligence and Data Warehousing business. Dan, first of all, welcome to the queue. Thank you. We're on day three, and we've kind of seen the evolution of the morning talks. You know, McDermott kicked it off, you know, very polished, snobby, connected with the audience yesterday, and Hasso and Vishal went pretty deep this morning. Hasso in particular was really deep into the technology, so you want to just explain everything he said to us? Yeah, I'll do it in two cents. But so, let's see, talk about what, you know, your role is at SAP, you know, what's going on for you at the show, and then let's get into the evolution of HANA. Sure, that's good. So obviously the evolution of HANA is one that continues, but my role at SAP is to focus on our, under the umbrella of database and technology, with the focus on HANA and BW and HANA, and actually the journey that we're taking with HANA, starting from where we announced its kind of strength two years ago to, as it continues to be, an in-memory database, et cetera, and many, and reiterating some of the things that Hasso and Vishal talked about on stage this morning. How do you describe HANA to a CEO? I mean, a CIO is going to get it, a CTO is going to get it. How do you describe it to a business person? Yeah, well, that's actually a good question, because HANA's often talked about in terms of its technology, but it enables things the business can do, and it's, what it enables the business can do that is really transformational, except sometimes that message doesn't always get across. So if you were to talk to someone and give the reader's digest version of what HANA does, I would say it really helps to expedite and make decisions in, within a time window needed to either reach opportunities, uncover problems, and really be reactive to the market. Okay, and then now tie that back into the journey. So it started, I guess about a year or so ago? Almost two years ago, and it did enter the market with a bang. To be, once again, we started messaging around more of the technology. It was an in-memory appliance, a combination of software running on hardware provided by our hardware providers. New hardware, like Westerner, and Sandy Bridge, and you need the greatest and greatest, you're talking some serious horse power here, because you're doing some serious work. Right, and it's kind of the sea change that's using a new technology to do things that were not really possible before with on disk-based operational type of system databases. So it's really meant for analysis, it's a standalone environment that allows you to take data and do wonderful things with that data, in terms of analyzing and getting at it, looking at the detail, looking at it from every different angle you want, and surfacing that data for people to actually make decisions that they otherwise might have been handcuffed in terms of doing because they can't get all the data in the way they want, or maybe IT had a few bottlenecks to prevent them from getting at that data. So this is a new paradigm in terms of how you actually get at, make sense of data, and make it available to others in the company. So you're completely changing the philosophy of the I.O., and I guess from an application vendor standpoint, that's important because it changes the way in which you write applications. You mentioned disk, and many of you might have seen, you know, you go to these shows and they have a glass-based disk spinning, it looks like it's going very fast, but in computer terms it's going, like, painfully slow, John and I sometimes call it the horrible disk stack, and it slows everything down. It's the only electromechanical part in computers. So you guys have looked at that problem and said, okay, we're going to put data in memory, which is not a new concept in computer science, but economics of that are making it more and more possible. So that was sort of the starting point. Yeah. Right? That was the starting point. And now where has it evolved and where's it going? Well, it's for many of our customers, they still look at HANA as an in-memory appliance, as a standalone environment for an analytic server that allows them to do all kinds of wonderful things at the top layer in terms of how business reacts and uses that data. So HANA, at its core, continues to be an analytic appliance, but it's evolving to be more things. So for example, right now in 2012, HANA will play a key role in being an in-memory database running underneath applications. So at its core of HANA is an in-memory database, and you can leverage that to be an in-memory database, not a disk-based database, but you swap out your disk-based databases like Oracle or DB2 and you replace it with HANA to run underneath, for example, SAP, BW, or data warehousing application. So that enables a whole level of performance and scalability and agility in BW that was never seen before when you're running on a disk-based system. So Snaba yesterday said, imagine a world where all data is in memory, using HANA, and you're not using any disk-based traditional database. OK, so now the next question is, is that really where you're going? So how do you protect that stuff? How do you back it up? That's sort of a snapshot of the vision, right? You're still going to need other infrastructure around it. Is that right? Or are you going to build out HANA so that it encapsulates other technologies like flash and persistency and even spinning it? That's a good point. I mean, obviously, then that comes to a disaster recovery and fault tolerance, et cetera. So obviously at the core of HANA, much of the data is in memory in terms of retrieval and analysis. But if the system were to fall over, we do have solid state disks based on flash that allows you to capture snapshots of that data in time. So if the system were to fall over, you can recoup that data back and solve the state disk. So that is a necessary part of the layer that makes up HANA. And you can let that ecosystem deal with it, however they deal with it, and offsite it, and protect it, and everything else. And I want to come back to the business discussion that we were having earlier. What you're putting forth is a vision where we're talking about massive increases in productivity for organizations. I measure productivity very simply, revenue per employee. And so in the last big wave of productivity that I remember that it really impacted the economy was the PC. We all remember we got PCs. It really changed the way in which we worked. How big is this? Is it that big, potentially? What do you think the impact can be to industry? Well, I think it can be huge. On two levels, let's look at one of the levels in which, if you look at any organization today, the speed at which people need to make decisions and be reactive to market conditions, you could say it's changed because we need to be in a more reactive situation because we have an economy that's constantly picking up and we need to be more competitive. But inside the organization, people's demands for getting that information and making decisions faster is based on this new real-time paradigm. When you're at home and you want to make decisions, you go to Google, you go to Wikipedia, you go to somewhere, and you make a decision, and you don't wait two hours for IT to serve you up something, that kind of sensibility you bring to the workplace, and you demand or you need that kind of quickness and response time. HANA allows for that kind of speed at decision-making, which, in essence, multiplied across the workforce and makes for a very productive workforce. But number two, it also enables a new breed of applications that can run on HANA to take advantage of these huge volumes of very fast data to surface that up into new applications such as smart meter analytics that allow you to really look at untold amounts of data and make sense of that data and then make it readily available for a decision that doesn't have to wait two months, but you can be very reactive in looking at the data today. Now, I want to talk about real-time a little bit. So what is real-time? How do you define that? That's a good question. So I define it as right-time. So real-time could mean, you know, in some organizations, you need to be reactive to the second. So you're on the shop floor and your factory lines are moving at the speed of per second and you need to know if something's breaking down and you need to be reactive to shut that particular line down. So that could be real-time. You need insight by looking at sensor data moving across the shop floor line and if something breaks down, you can't wait two hours. You'll have a huge shut-down. That could be real-time, but for some organizations, they just need it at right-time. They need to be reactive within the window of decision-making needed to make that decision. That could be, to the minute something's happening within your organization, that could be one hour later. That could be one day later, but whatever that decision window is, that's called right-time and that's where Hannah allows you to. Or to the second if you're serving up ads and you're trying to get a customer not lose a customer to a hotel reservation or whatever it is, okay. And then my other question was, why don't you talk about big data a little bit? Every company out there's talking about big data. You guys even talk about big data, but you certainly don't overdo it. I probably give you a hundred points for not big data washing. If anything, I would say you don't do it enough, but I'm so curious as to what your thoughts are on big data, what it means to SAP. Bill McDermott definitely mentioned it more in his keynote. I think he maybe once last year, probably 10 or 15 times this year, John Furrier coined the term big fast data. He said that's what SAP is really all about, is big fast data, maybe not huge petabytes, but big enough. Talk about big data a little bit, what it means. Well, big enough I think you just said it. So once again, big data could mean in the petabytes for some organizations that need to step through, following the social media data to find sentiment analysis and really understand what the customers are thinking. So you'll need access to that kind of data to do that kind of analysis. Now should all that data be held somewhere such as in memory or in one place or do you need to access it and bring it in as you need it, such as through Hadoop connection? So that's maybe all you need to do with big data. SAP's approach to big data is looking at it in terms of the data you need coming from any source, social media data, Hadoop data, that you need to bring into, for example, HANA and make sense of that data. And it could be five or six or seven terabytes of that big data, but looking at huge petabytes of big data all at once is usually not the needs of most organizations today. They just need the right size of that big chunk of data that sits out there in external and internal sources and makes sense of that to make fast decisions. Do you see that those two worlds coming together? I mean, today it's like the big data Hadoop tail is sort of wagging the enterprise dog. Do you see that those two systems will become together, the new emerging Hadoop big data pieces being feeds into operational data and those two worlds coming together? How do you see that and what's the likelihood that that'll actually happen? A bridge needed between the big data Hadoop world and the ability to analyze and make sense of that data coming together more through a bridge. I mean, bringing together all that big data into like say the HANA system of in memory doesn't ever seem to make any sense. We define things as hot data, data that you need to make decisions of within a very quick time window. And data you need to get out in an offline fashion and bring that into the decision making kind of server environment. So we see more of a bridge approach to looking at and getting at big data but not necessarily bringing those two worlds together. So all active data in HANA or in memory, in flash and then the wash, the exhaust as John calls it, out there. Yeah, because the wash is the wash. I mean, can you narrow down big data into any one format? No, big data, it's all data, whether it's structured and kind of internal data to a company or more importantly, the external data that's seen out there and social media, et cetera. It's funny you mentioned the journey of HANA and hearing you talk, you think about the benefits of HANA and it certainly is a breakthrough. But still, people just don't understand the value yet of what this means of big data. So one of the things we're trying to tease out of the conversation here is, how do you talk to folks who are really trying to crack it? I mean, you work at SAP and you're in the trenches here inside the company but for the folks out there in the world, they look at analytics and say, hey, I love a dashboard, I want the impact of analytics, I want data availability in all core and non-core systems in real time. Yeah. How do you talk to those folks out there? And how do you talk to them and say, here's how you get started, what are the benefits of data really? How should you be thinking about it? Well, I like looking at HANA because of the way it's kind of priced in scales, you can start small and go big. So you have one area of your business that's troubling you in terms of getting the understanding into that data in kind of the time window needed. It's not all data in the organization. If you're starting with maybe sales data, marketing data and you want to bring that into the HANA world to start really looking at it, turning it on its head, maybe uncovering effects on margin that you were never able to do before because it'd be the large volumes of data or the technology that didn't enable you to do that. So you can start small and target one area of your business that is in particularly need of a deeper insight. And then you can grow and start to combine it with other data to add more flavors to that data, dimensions of that data. And once again, data volumes usually is not the bottleneck because you start to grow out and start to collaborate with other data to really get new ways of looking at data. I think it's hard to tell someone you've never been able to look at your data and really uncover your data with insights and see your business in these new ways. So how do you give them the art of the possible? It's really trying to explain what is possible in terms of insights into your business to really uncover opportunities that may not have been there before. What about the final question we got a minute left here, disruption. Obviously, Shinabe was saying that, you know, risk-free approach could come in front of your data warehouse, which is really a clever way of just trying to simplify the concept of here's how you get started, press a button to create data. How is the data business disrupting data warehouse and business intelligence? What are the big disruptors out there right now? Well, in terms of disruptors, I mean, I think it changes the game in terms of how you can start to really look at and analyze and understand your business. I mean, when you're set in ways because you're confined by the technologies, then you just live with what you have. When you open the doors for new possibilities of looking at and understanding your business and really looking at new opportunities that uncover, I think that's a very disruptive way. New applications, unthinkable applications, as Christian Ritter said in Hilti, in building applications on top of Hanna that enable them to understand their businesses is yet another kind of new venture in how businesses will start to really uncover opportunities not seen before. Final prediction for the next five years, what's gonna be different with the impact of in-memory, cloud, mobile, social as data becomes a core fundamental asset for companies. And with the consumerization of IT, the consumerization of everything, as we say at Silicon Angle, what's, what is happening in five years? Well, I think the promise of information as a true asset in your company will be realized more and more over the next five years. So the ability to really look at information the way we've always wanted to, to really look at it and uncover opportunities and see problems before they happen and really get ahead of the competition by thinking smartly with that information as a true asset will become a reality in the next five years. Thanks to the new technology we're seeing, such as Hanna. New technology here at SAP Sapphire, the consumerization of business, consumerization of IT really is happening driven by the passive tsunami of new infrastructure, conversion infrastructure, social, mobile, cloud, great innovations, home of the generation. Dan, thanks for sharing with us here at your commentary and analysis. This is the Q, SiliconAngle.com, SiliconANGLE.tv's flagship telecast. We'll be right back with our next guest.