 Okay, welcome back to day three for us. Day two of the conference. We are here live at the Stratoconference with the most authoritative big data conference around the future of the world. Society, technology, and O'Reilly Media is putting on a hell of a good event here. And we're here covering it, SiliconANGLE.com. This is theCUBE, our flagship telecast, where we go out to the top tech events and we talk to the smartest people we can find, CEOs, entrepreneurs, tech geeks, VCs, whoever has a signal from the noise, we want to extract that out, share that with you. This is theCUBE, SiliconANGLE.tv's flagship telecast, and we're here, I'm excited. I'm John Furrier, the founder of SiliconANGLE.com, and I'm joined with my co-host. I'm Dave Vellante of wikibon.org, and John, this is day three for us, it's always a good event. Last year was one of our largest events. Stratoconference, big data, a lot of infrastructure, a lot of application stuff, a lot of really interesting use cases coming out, and so John, let's talk investments. So we're here with Mike Dauber, who's a venture partner at Battery Ventures, which is a very well-known venture capital firm. His focus is big data, he's been in the trenches, he's been making some big investments, personal investments, and Weeby Data, which they changed their name, I guess now, it's officially Weeby Data. You invested in Continuity with Todd Papiano, who's been on theCUBE multiple times, great guy at Yahoo Pioneer, and had to do his co-founder, Jonathan Gray, essentially the guy with HBase, one of the core contributors of HBase. Mike, you're in the trenches, we met online, we chatted at big data conferences before, you're on the street, you're making investments, you're doing personal investments, you get the landscape covered up and down, like we are, we're covering a blanket with the media, you're covering it from a VC standpoint, so welcome to theCUBE, your first time on. No, it's exciting, I've wanted to be on here many times, so I finally made it. So my question to you is, you're doing some real good work, what are you seeing out there right now? The VC landscape is obviously hot on big data, you're not a newcomer, you're not a bandwagon investor, you've been there from the beginning, like Ping Li and Frank Artali and a slew of other ones we've invested in, we've talked with investors, what's going on? I mean, Big Data Fund by Excel was really kind of groundbreaking PR kind of event within the mainstream media, New York Times has big data on the front page, and what's happening? You know, it's funny, right, three years ago, anytime you got a pitch, people tried to figure out how to, a way to put the word green into the pitch, right? You had nothing to do with anything that was remotely clean, everyone wanted to figure out a way to make it green, or they tried to figure out a way to put in cloud. The number of business plans that we just see that just randomly get submitted that have nothing to do with big data, but find a way to put those words in there, it's amazing to me. Is that big data washing? We should coin the term, cloud washing was a hot thing during 2010. Yeah, it's big data washing, but I will tell you what, certainly what we think is going on, what we're excited about is, look at the infrastructure layer, the Cladera's, the Hortonworks's, the MapR's, the world, you know, these guys have already gotten a lot of money. I think the infrastructure layer is going to be built out. I think in Q4 last year, MapR, Horton, and Cladera alone raised $90 million, right? So a ton of money is going to that infrastructure layer. But if you just move just one click up the stack, there isn't a lot going on. I mean like, so everyone can name those guys. Explain that for the folks out there. One step up the stack, what does that mean? So you've got your infrastructure layer, the guys who do commercial support for Hadoop, or commercial support for Cassandra. But if I'm an end user, and I want to do something in an application, right? There aren't, all right, so I got my Hadoop up and running. Now what, right? I want to, you know, ETL my data, and I want to go do something with it. You know, really the only company out there that we were seeing last year that really had any level of traction was Datamir. I think Datamir is a great company. I think Stephon is a great job of the company. But we weren't seeing a lot of activity around that. And that was what led me to get to meet Christoph at the time called Odiago. You know, he was someone who was really focused on on-prem analytics. And some of the things that they've done, I think that he's been public about with Atlassian, in terms of targeting, targeting, marketing, and sales activities, Wikipedia, and some of the work they've done with Wikipedia, and figuring out, you know, making sure that, you know, John, you're not going out and editing lots of New York Yankee sites, because we know what you do if you're editing Yankee sites. Have a Red Sox fan. Yeah, you're a Red Sox fan. Rewriting history. And Todd, you know, Todd and John's background, but Todd being from the enterprise space, but also running that, you know, a big chunk of Cloud Infra at Yahoo, we thought, look, there's got to be an opportunity for people to start to build things up the stack, and not just focus on, you know, this base layer. Okay, so let me ask you a question. So Dave and I have, you know, obviously we wrote this earlier, but it's pretty clear from this conference that 2010 was what it said to do, 2011 was big data is a viable business opportunity. 2012 is really about platform maturity. That's right. And the new applications are emerging, as you mentioned, it's pretty green field right now, embryonic, if you want to call that. And 2013 is going to be the year of money, right? People are going to make money, people are going to make money, value from businesses, top line revenue, business models will be changing in the marketplace, not just for the startup companies, but you know, services companies and product companies. So one, do you agree with that? And two, what is the application areas that you see that you wish the entrepreneurs were working more on? So Mike, just to clarify, a follow up on one, we were saying this is the year of application innovation. Do you think we're too early? Do you think it's actually going to be this year or is it going to seep into next year? You're seeing it already this year. I mean, you saw, I saw him stand over here before, Abhi made it, right? Gave a great keynote yesterday at Strata. He was on theCUBE, yep. Abhi's a great guy. If you look at what Abhi's doing with Trasada and their product around mortgages, right? And how they give mortgage intelligence to the banks, right? They don't go to the banks and tell them, hey, we have some big data solution for you. The banks don't care, right? What the banks do care about is improving their mortgage portfolios, right? That's a big pain point for them. And if Abhi can leverage big data infrastructure to solve that problem, I think that's a great application space. I think you're seeing things in the healthcare space. Anywhere where you have large amounts of data that doesn't already exist in a highly structured way, right? Like if I'm Visa, right? Credit card data is already highly structured. I think Visa has applications around unstructured data as well, but you know, credit card transactions, you know, email headers, things like that. It's highly structured data. People have lots of good solutions for that. So we're not trying to go out and reinvent the wheel. What we see happening though is, you know, for 30 years we had this relational data model and everyone built applications on top of these relational data stores. Now all of a sudden they have to deal with relational data and non-relational data, right? And to us, that's really the core of the movement of big data. So anybody who can take an application and play off of this sort of heterogeneity in the market, I think has a great opportunity to make a lot of money. So you mentioned, Trisada, now that's really largely a vertical application for financial services. Are you looking to invest in more vertical applications, horizontal applications, both? How do you see that checking out? Both, you know, so for me, continuity and Weebie data are more on the horizontal application space, but you know, I know of a deal coming down the pipe right now in the hospitality space and saying, look, look at all the data that sits around in hospitality, right? You know, how do you go out and price, you know, think about like what hot wire does and what price line does and all these guys, TripAdvisor gets his reviews, but all these, there's a ton of rich data around who's staying and what hotels and all the pricing related to it, but the hotels are still relatively blind as to how they're pricing their properties, right? And everyone wants to optimize what they're doing. So I think there almost isn't a market that I can think of, you know, the federal government is looking heavily right now at sort of big data solutions. You know, Palantir, sir, I think led the way around security solutions. By guarantee you, there'll be a dozen more companies like that, not necessarily in the visualization space, but sort of the extracting signal from noise. Do you see the applications business as disrupting the existing applications business or largely incremental to what's out there? Yeah, I think a little bit of both. I think there are going to be some cases that are going to be incremental and I think there's some cases where I think you can be massively disrupted. So I think you can, in the same way, look, the enterprise to me always works in these sort of stack replications. So you had a whole suite of enterprise software and now all of that has been replicated with SaaS. And the guys who won in the old model don't win in the new model, right? You know, look at someone like Workday. It was the same core team, obviously, that sold to Oracle, but you have people soft. You need to have a new solution to do that, to do that on a SaaS model. And then the other thing is you get companies like we're invested in Marketo. You know, Marketo is something that wasn't really possible before you had a SaaS delivery model. I think you're going to see the same types of things in the big data space. I think you're going to see there are going to be companies out there that just do a better job of the existing applications because they pull in more data and they're able to give you a lot more analytics. But I think there are also going to be new companies that we haven't thought of yet. They're going to be able to do things that weren't possible before. What's the areas that you're seeing that are venture-backable? Because with big data, there's opportunities to create a lot of slew of different kinds of, I don't want to say lifestyle, but nice little small businesses. We had Scott Detsin on from Pure Storage earlier talking about some of his history of web logic and we had Mike Olson on and we're seeing the 40-something entrepreneur come back, the systems guys, right? Like me, my age. But also Scott talked about this data ISV concept as one area he liked and so you're going to see all these little niche opportunities that look like a feature. It might be a little lifestyle business, it might be service oriented because there's services in here as SaaS or whatever. That might spawn up obviously self-funding. So there's a huge self-funding thing going on. How do you as a VC look at these opportunities and hey, I want to bank that one. Obviously there's going to be a good market opportunity, but how do you separate and filter out ones that you say that's bankable, that's a fundable deal, that's venture fundable? I think there's two directions. I think there's the market-related questions and I guess there's a separate topic that we haven't touched on yet, which I think is a big deal in this space, which is the talent pool. I don't know if you notice, if you go around the trade show floor here, Facebook has a booth solely for recruiting, right? And I've never been to an event where a company like Facebook has a booth just for recruiting HR purposes. I think it says a lot about what's going on here. Normally, if you come in and pitch me, one of the things I'm going to try to understand more around is your go-to-market model. More companies fail because of go-to-market than because of bad technologies. Lots of smart engineers in the Valley come up with great technologies, but what's your path to market? I think there's a wrinkle in this space that's different than any other space I've worked in, which is the separation between the guys that get it and the guys that don't talent-wise. That gap is enormous, right? See, you talk about- Can you give me an example of that? Yeah, I think John Gray is a great example of that, right? I mean, John is, when we announced the funding with our investment partner, Andreessen, John, I got a number of emails about John and people saying, wow, you know, you guys landed John Gray. He's the guy in HBase that everybody knows. That affords you two things. One, it gets you a lot of attention almost immediately. It also gives you the opportunity to recruit other really, really, really good guys who know John and want to work with him, right? And the gap between the strong teams and the almost the strong teams, I think you're going to start to diverge. I don't think there's going to be a middle class, if you will. I think they're going to be the haves and the have-nots. And so when I see a team, one of the key things for me is, who's the core technical team and is that core technical team, is it strong enough to sort of attract other A players? Because there just aren't a lot of people in each of these verticals. There just aren't enough of people out there, right? This stuff is still relatively new. There aren't a lot of good teams out there. So you must love the Cloudera dynamic then. Yes. With that bench. Well, and absolutely. I mean, there are a couple of guys at Cloudera that were they to leave, I think they'd be assaulted by 50 VCs instantaneously. Well, we recruited a key person out at Cloudera and that was a coachable. He's a grad student. Pink still talks to you? Well, he wasn't coming back. He ended up helping me out, helping our data project out. And then he took a full-time job with another company. I mean, very lucrative position. So obviously the talent are going to make some good money. And oh, by the way, SiliconANGLE is hiring a database scientist. So if you're out there, we're recruiting as well. We don't have a booth. We have theCUBE, but. Forget going to work for Facebook. Yeah, screw Facebook. You can work for John. I would say that the analogy I always like to use within my partnership, it's someone should make a movie about this. Right after World War II, we did something called Operation Paperclip, right? It was the U.S. What became the CIA, the OSS, had a list of the top rocket scientists in Germany. And we wanted to make sure those guys didn't fall into Soviet hands. And guys like Von Braun, who led the Apollo 11 rocket project, all came out of this land grab of going out and getting key scientists who just knew this material better than anybody else. There weren't that many people in the world in 1945 that knew rocket science, right? And you had to go out and get the key rocket science. I think we're seeing a rehash of that today in 2012. There aren't that many people who get this core big data. And if you've got a key HBase guy, if you've got a key Hadoop guy, if you can grab someone who knows how to write applications on top of this infrastructure, they're orders of magnitude more valuable than other engineers in the same space. And you're seeing that, right? A Hadoop engineer today can get a $250,000, $300,000 salary. Well, Mike Dowber, we got a break. We got a schedule. Thanks for dropping in. Thanks guys. This guy is a young gun rising star in the venture community. Obviously big data is a massive surge. Completely new industry being constructed from the ground up. You're going to do well. I think you keep your nose to the grindstone as they say. You're going to make a lot of money. Great to see you spending a lot of time in there. So Mike Dowber from Battery Ventures. Thanks for coming on theCUBE. Thanks. Okay.