 Live from Boston, Massachusetts, it's theCUBE at the HP Vertica Big Data Conference 2014. Brought to you by HP with your hosts, John Furrier and Dave Vellante. Okay, welcome back, we're here live in Boston for HP's Big Data Conference. I'm John Furrier with theCUBE. With Jeff Kelly, my co-host and our next guest is Lawrence Schwartz, VP of Market and Intunity. Welcome back to theCUBE. Cube alumni, great to see you again. It's great to be back. We'd love having you on one because you're a friend of theCUBE, but also you really have good pulse of what's going on in the market editorially and I want to get your take on a few things. One, give us the take of the show here at Vertica, the Big Data Show, what's the vibe? What's your take? Sure, yeah, I know it's been a great show this year. I know it's been the second year for them. We've really seen a lot more interest in a lot of real use cases. Last year a lot of people were kind of figuring out how they wanted to use Vertica, what they were going to do with it. And this time we've seen they have real kind of complex solutions they want to implement. We've heard people who are customers who are coming here and looking at using Vertica as a target, using it as a source, how do they do disaster recovery, how do they manage it over wide area networks and do things like internet of things over wide areas. We hear others thinking about tiered storage now between Vertica and Hadoop and other systems that they have, so it's been a great show. It's been some really meaty discussions that we've had with people who have come by. Yeah, so we've done some research at Wikibon around big data use cases and kind of adoption models and really what people are really doing with it. And you mentioned last year, you saw a lot of people either kicking the tires with Vertica and some of the other solutions out there, trying to grasp kind of where they are and what they can do with the technology. But through our surveys, we're definitely starting to see that shift from some of that kicking the tires to people actually experimenting and some even moving to more production workloads. But of course, data integration is a key part of the big data ecosystem. So Hadoop gets a lot of coverage, some of them know SQL data stores, the analytic databases like Vertica. But talk a little bit about your value proposition and the larger ecosystem. I mean, one of the things that they show for sure is that Vertica wants to display all their partners and kind of the ecosystem play. And that's, there's a reason for that because it's important in order to tie this all together and make it real. So where does the tuning really fit in this ecosystem? Sure, and I think, you know, I know you guys had Colin on here yesterday talking about the value that people are getting out of it. Yeah, Coleman and GM of Vertica. Exactly. And I think the analogy that he brought up was the Ferrari, right, or that came up there. And he said, well, it's even more than that. It's Ferrari Fright Truck or something even larger. It's a new type of vehicle that people can do a lot with or not used to. So when you think about data integration, if you want to kind of bring that analogy one step further is you've got to get the data into the truck, right? You've got to get what you want in there. And that's part one. That's where data integration comes into play. And then once the truck is moving, how do you change the data? It's in there. How do you keep it up to date? Well, it's moving at 100 or 150 miles an hour, however fast you can drive it. So data integration plays a key part of how do you get started? How do you make sure everything's loaded up so you can then go and run off and start doing these amazing analytics? And then once you get the ball rolling, how do you keep it up to date and make sure everything's moving? And that's where we come in and play and really make sure that process is easy to do. Simplified when you've got a lot of sources that you're pulling it in from. And making that not the focus, right? You want to get your focus out of the analytics, right? You don't want to spend all your time setting it up. So you take care of that. Right. We hear that a lot from practitioners. 80% of our time is spent getting data to the right place or massaging it to get it into a form that we can actually do some analysis on it. So to the extent that you can provide either tooling or other services that help make that easier, obviously that's going to be a big value proposition. But another kind of one of the key tenants of big data is big data is heavy. You don't want to move it unless you have to. You want to bring the compute to the data rather than the data to the compute. And so what I'm interested in hearing is from a player like Attunity, how does that impact a data integration player such as yourselves? In the old world, it was a lot about ETL, batch loading from here to there. And it was pretty boring stuff. Everyone kind of got it. But in this new world, there's so many more data sources. There's these key concepts like kind of leave the data where it is when you can. So it would seem to me that it's particularly disruptive to the data integration space. So how do you fit into that? And how are you trying to take advantage of some of these changes that we're seeing that are associated with big data? Sure. Well, it's definitely changed the model a little bit. But there's still a lot of concerns that people generally have. Even if they want to address it in place or do something like that with a dupe, you still have to have a lot of legacy sources or other areas that you need to pull it in from. That's one thing. And then the other thing is that whole ETL model you mentioned, which is the extract, the transform, and the load. That's been changing a lot over the last couple of years because part of it is you would do that, and you might have an intermediate server, we do heavy transformations and whatnot, and then move it over. And now that you actually have so much compute power on these nodes and where it exists rather, you can actually focus more on getting it moved over there and then doing the work on it. So when you talk about doing ELT or extract and load as quickly as possible and then do the transforms with the compute power you have, that actually is right in our wheelhouse. We don't try to be the end-all, be-all ETL player. People really want to do a lot of heavy transformations. There are certainly ways to do that, but we focus on the performance, keeping it up to date, keeping it real-time. So it's actually complementary to what we're thinking of. So that's interesting. So you're saying, really, your key value proposition is that the transformation, use the power of these new systems, whether it's Hadoop or something like Vertica, wherever it is, and one of your real key value proposition then is, where are you going to help you extract and load that data as quickly as possible? And then use the power of the system rather than the old model of extract the data, bring it into some other system where you're going to transform it and then load it into the system. Is that really kind of where you guys fit? That's right, yeah. And there's still a lot of challenges with just that ELT part, right? It's again... Well, sure, it's not trivial at all, especially when you're dealing with the complexities of data sources that are out there today. So I want to talk about something else. So you're a marketing profession yourself. We talked a little bit about before we went on about how you come to these shows and you learn about technology and you see potential customers, but you're also as a marketer trying to learn how people are using data to do their jobs better. How are you as a marketer? Not necessarily a big data marketer, just a marketer. How are you adapting to this world? How has things changed over the years? Yeah, well, it's fascinating in that, for this show, as a running marketing fraternity, I always think about how to talk to the people in this space and that's a key value for the show. But I've actually gone here and gone to some of the sessions that have been valuable for the marketing professional. And I heard Pramod Singh of HP, he gave one of the sessions yesterday, he was talking about all the data that you get out of social marketing or rather all the social activity that you see going on. So he gave some amazing stats. The latest from last year, where you had I think the rate of about 100,000 tweets per minute and 700,000 status updates per minute. So as a marketing professional, I'm trying to see, okay, so what are people thinking about data integration or attunity in that vast ocean of data? All of a sudden, you know, the big data problem has come home to ruse for the marketing professional. Of course, HP has fantastic solutions with Vertica and Haven and other things that he talked about in his session. But those are things that we all have to think about. Now, how do you find the sentiment out of that? How do you rate it? How do you quantify it? And it's exciting because it's new ways to think about it and get a view of it because people's buying behavior are very influenced by their friends and their peers rather than the traditional menus of marketing. By the same time, it requires new tools, new ways of thinking and you see much more of interaction I have to do with our CTO and understand how the data is pulled out and do that value. Right, well, a marketer has to be much more technical these days and understand data much more than in the past. And John, I know this is right in your wheelhouse with what you're doing with CrowdChat and trying to both engage with the social web but also measure it and try to understand how to interact with it in a valuable way. I'm hardcore on this, you know me. All I do is pimp in CrowdChat. But for a reason is because CrowdChat to me is an example of an engagement container that measures everything and takes the active data and captures like a DVR for video. And rather than sending it to the junk pile of Twitter data that has to be pulled back, it's a data cleaning system that takes a lot of time. So I believe you're going to see real-time information in social channels be driven by big data techniques, predictive analytics, prescriptive analytics. Big data will be a driver for providing personalization and value proposition to the right user. So Tom, David Port was on for the author and I didn't get to this but this is the whole attention economy on steroids in circa 2014 which is putting the right thing in front of the user at the right time at the right place when they need it. Not retargeting the Hilton ad. When I don't want the Hilton, I just was checking if they had any availability. Now I see the ad. So retargeting is a great example of failed social. It works short-term, but it doesn't work long-term. I'm not as a buyer now, the brand is harnessed. So I was hurt by that because I'm pissed off. But I believe social sales, social business will be like the web was with e-business. And it's no brainer to me. And I think you're right on the money. Data is the key. And I saw that in the crowd chat yesterday when I was looking at that. And it was an interesting example because just last week, brought the whole family to the whole Orlando thing with the kids and now I'm still getting advertisements for it. I'm just not interested, right? It was great two weeks ago, but now it has changed. Your browsing consumption has changed and there's a term that I've been kicking around. I haven't talked about it publicly yet called trusted consumption. Trusted consumption is social graph consumption meaning I'm going to consume content from trusted sources, my friends, not Google search. In this case, the search to Orlando was just a fly by. Your intent was browsing, but now you're being shoved in ads. So I think this trusted consumption is going to be data driven 100%. So Jeff, I can rant on that all day, but social business is real. It's going to have infrastructure and software. You guys are doing a great job. So big, big fan. Okay, so Lawrence, thanks for coming on again. I know you had the tight schedule with a short window here. This is theCUBE live in Boston talking about big data, the impact of society, marketing, and of course, serving customers. This is what it's all about, future big data. This is theCUBE. Of course, we're broadcasting the data. I'm John Furrier with Jeff Kelly. We'll be right back. Thank you.