 Wikibon.org's exclusive coverage of Hadoop Summit 2013. I'm John Furrier. This is theCUBE, our flagship program. We go out to the events, extract the signal from the noise. I'm John Furrier, the founder of SiliconANGLE. Join with my co-host. I'm Dave Vellante of wikibon.org. Welcome, everybody. Ben Werther is here, longtime CUBE alum. He's the founder and CEO of Platformer, a company that's bringing sub-second interactive BI into Hadoop. Ben, welcome back to theCUBE. Thank you. Great to be back. Yes, so. No, I'm just saying, CUBE alumna, you've been from the beginning of theCUBE, and now you're a big-time CEO, big financing, growing, big company. What's it like? Yeah, it's really, really exciting. I think we've, you know, I'm coming on when we were at the point where we had a concept, we had the beginnings of a product, and then I think, like, join the guys around the time we launched that product. Yep. You know, now we're in market. We're seeing, you know, we're adding, we added a couple of 4,500 customers. We're really getting momentum. It's, you know, across different verticals, and it's fantastic to see that. So Dave, Dave and I were talking the other day, and we're talking about the changing nature of this modern era, and it's one of the things that's going on in the enterprise right now is you have the old school and the new school, and I think, you know, it's really clear to us, that we've talked to us in the past, old way, new way, and I think at this show, enterprise-grade, Ben, has been key, and you guys take a different approach, so give us an update on what you guys are doing, and then let's talk about what you guys are doing differently, and how are you guys enabling that innovation for the customers? Sure, absolutely. You know, I think the old way is, the question is sort of how do you go rebuild the old data warehouse on this new stack of technology, which I think there are use cases where that makes sense, but one of the things that sort of struck us more and more with the customers we work with is, hey, the kinds of data you're putting into Hadoop, and you want to mix together, these are not data sets that you want to treat the same old way. You don't want to do traditional sort of state business reporting against these event logs and click-stream data and sort of social graph data, there's so much more interesting questions about behavior and insight you want to drive from those, and so I think it's really pushing towards not just how do we make BI work in this environment, but really how do we allow people to kind of express these things that today take custom development, they take a year of smart data scientists, and make those questions that a business user can just sit down and ask visually this afternoon. Well, that's what I like having been on, John, because let's face it, a lot of the platform vendors here, they're coexisting, they're working with other large database companies or traditional BI companies, and they've got to be politically correct, and you are actually quite kind just now, but you've been more forceful about, look, yes, you can do that, but there's so much more business value that you can drive if you kind of rethink the way in which BI is done. And we've talked about this before, that BI in many ways has just failed to live up to its promises, so what are you seeing today, and what gives you confidence that your vision will be able to live up to its promise? Yeah, I mean, I think the clearest indication is customers using the product. Nothing gets me more excited than going into an organization, and there's often naysayers who say, hey, we have these existing investments, how are you going to leverage whatever, the micro strategy and the other tools I have, and our point is, okay, look, that's fine to have for the existing use cases, they're good products, but let's talk about the kinds of things you're trying to end, so the kind of data you're bringing together, and let's look at what you're trying to achieve, and we rapidly see there's business users, disenfranchised, data sets that often have much more interesting character. If I'm getting clickstream data, every record, it may have dozens or hundreds of different tags of different things that I can use for interesting segmentation, different types of behavioral analytics, I can look at combining these data sets in surprising ways, and the idea that you're going to try to do that, the idea that even if you made the traditional stuff work in Hadoop land, which I think is a dead end, honestly, because when you get there, you realize that that's not success, you just recreated a model that had a lot of inherent flaws in it. So when you go into an account, if you're talking to a line of business person, the last thing they're going to say is that their objective is to preserve their current data warehouse infrastructure. They don't know it, they don't care about it, but there must be a segment of the population that says, okay, yes, we want all these great insights, but we also want to leverage this investment that we've made over the last 20 years. What do you do in that situation? Do you run, not walk? No, I think we're very clear with them, which is that you're not going to throw away any of your existing investments, and there are a lot of good use cases that are being served by them. But I think the biggest learning that companies have is they start out saying, okay, I have Hadoop, and I have a data warehouse. I add Hadoop, and I want to pre-process data in Hadoop and put the arrow goes from Hadoop into the data warehouse so that the real work happens in the data warehouse. And I think the challenge is you end up with silos of data, you end up with a model where Hadoop doesn't have all the data, and the data warehouse doesn't have all the data, and you're frustrated customers, frustrated users. And the next step of maturity is you flip the arrow and you start putting all that data into Hadoop. So you still have your existing systems, but there's a whole class of new questions that you can enable because you now have data that may span much like a wider variety of silos. Some of the banking customers we work with, they're thinking about how do I do a 360 degree view of a customer analysis with all these different silos of data that if I was to try to integrate in a traditional sense, it would be a decade long project, but just landing that data in Hadoop can be the beginning of doing this very, very rapidly in an agile fashion. Well, the problem with that, what you described is you get business processes established for each one of those data silos that are very rigid. So talk about how your customers are changing their business processes. Yeah, I mean one is we sidestep that a little bit because we don't try to replace these existing systems. They're doing transactional work and it's working in those environments. That's good, we don't want to be in that business. But I think that the key is that data is a resource that can be combined with other things in a way that we're not trying to go in and replace the existing, we platform your reports. We're trying to help you answer more interesting questions that aren't being answered today. So the bar is very, very low. And so once you get those data sets, as long as you can start to unify some of the common, if I'm thinking about 360 degree of a customer, what is a customer? Do I have keys that I can match up in some way? Can I view this in a holistic way? But then I can, if I have new data being generated, if I get into mobile advertising and I have all these different new events related to mobile behavior, as long as I can key that to customer, now I can weave that in, have this sort of dimensional, entity-centric view of it rather than the traditional style schema which becomes like this just heavy, heavyweight thing to manipulate. I want to ask you about some news here. You got some certification. You guys are certified with Hortonworks now. I see you certified technology partner with Cloudera as well. You're in the ecosystem, right? So you're in the middle of the hard of the action. What's the state of the union, if you will, of the community here? Because you're seeing everything from all sides. And then let's talk about the business value. So two questions. One, first, the state of the ecosystem, the community of developers and vendors, kind of they're rowing in the same direction and both are hitting each other a little bit here and there, but for the most part, things are going well. And then the business value conversation. So first the ecosystem and then the business value is in all this. I think the ecosystem level, great. It's maturing. It's solidifying where we do great work with Hortonworks, Cloudera, working with MapR and Pivotal and even the Amazon guys. There's so much interesting- So you guys Switzerland? You guys kind of like- Yeah, we're a platform. We really do, at some level, we want to make it easy to drive business value against all of these. I mean, we'll obviously have good working business relationships where they're bringing us into opportunities to help show business value more quickly. And we're likewise trying to be very neutral but help identify and surface opportunities for all these guys. I think the key is that layer of the stack is now pretty mature and there's some good new capabilities coming in around the SQL interfaces, which we think are very positive. The evolution towards Hadoop 2 and Yarn and the idea that Hadoop can be a much broader platform, which I think is a fantastic evolution. So we're trying to stay on top of all these things and partner- You guys have to invest in that. So as CEO, you got to put a little investment on continuing the partner and staying up to date. In terms of solutions that you guys are putting out there, the questions that's come up, this is the theme of the show, obviously enterprise grade. It's the meat and potatoes, it's the rubber hits the road, the sizzle and the steak, right? Whatever metaphor you want to use, the clients want business value. That's the proof, right? Absolutely. So can you describe that when you walk in, what is the business value that you guys are hitting for your customers? Yeah, absolutely. And I think that the thing that still startles me is how much people have been attuned to living in a world where things take a year or more. I mean, the number of times you walk into a company that's where they have a Hadoop roadmap and plan where business value is something off in the horizon once they start to, you know, they've proven a whole lot of things, they've brought this data together, they build out some test things and at some point they imagine they're going to put this in front of users and validate that it actually is solving a problem. Being able to go in and, I mean, we often will be up and running for a, we'd like to do a demonstration against their data to show them what's possible, not even a POC necessarily. Usually in a day, we're up and running and answering questions. So who calls you in? Who's calling you guys in? Because actually, you know, you've mentioned, you're basically saying, okay, speed, right? So that's the number one thing you're hitting, basically speed. You know, SAP. But also democratization. I mean, how do you, I mean, we love to find, we often talk about the angry business user. Like to say, somebody who's throwing at that data. I got to work this weekend. Geez, missed my vacation. Well, it's like, I know there's data in there. Don't tell me there's no data in there. I want to get, here's my question and don't tell me I got to go queue up and wait six months to get an answer. And so showing that person how they can help themselves get the data and solve their problem. And so giving this platform where IT can actually be a hero because it lets the business users get stuff done, which is very different. I mean, most of these solutions, honestly, are still, they're not about people. They're not about people solving problems. They're still low level plumbing for developers. We really want to focus on, I like to imagine somebody who's at some insurance company, this whole big data wave is missing with their career plans. They're trying to figure out how are they going to be successful as the currents of change are hitting here. And we want to help them see a path where they can win. And they can also be successful. I was talking to a big insurance company, they have a billion dollar operating IT budget. I was talking to one of the top guys and I was in Boston there a couple of last months and he said, look at telematics has changed our world. I mean, obviously big data, they're measuring everything, right? So now they're sitting there with all this data, kind of just sitting in a batch going, what do we do with it? Exactly, exactly. And so is that when they call you in and you guys come in as a SaaS model? You can put in appliance in? What's the products? Yeah, so we sell software. We'll run it on commodity servers that they'll have on premise. Typically if they're in the cloud, then we can run in the cloud, that's fine. But we're not hosting the software. But typically it's at the point where they've usually got some data in Hadoop. They've realized that there's this gap of capabilities and they could either start down a long process of trying to build something custom, take all the emerging open source projects and hope that they get to something that is useful enough. Or they're interested in coming in and talking to us and having us sort of show them. So we talk to folks all the time. In SAP, for instance, we're at SAP Sapphire and obviously Han is the big thing they're going to ride that horse. And they tried out some pretty significant numbers, right? They say things like, hey, it was 13 weeks to run this query, now it's 13 minutes. It's a significant order of magnitude of saving. I mean, you're talking about basically that can go on vacation for 13 weeks to 13 minutes. Those kinds of numbers are just amazing. So do you guys have similar kind of order of magnitude? So I like to think of a different pivot on the same thing. There was an example of a big online retailer we spoke with, they described their process. If they wanted to change one column that showed in one report, so they wanted to bring a new field through the entire stack from ETL to data warehousing to BI. This was 18 months, three outsource firms, monthly risk mitigation years. They wanted to add a data point. Yeah, exactly. 10 to 15 engineers for that entire duration just handling the fragile coupling of working this through all these layers and hopefully not breaking something along the way. And so when we show these guys that literally in our model they have a dynamically created aggregate against the raw data, like a shopping cart they add the extra field they want and they say, I want this in there. The MapReduce jobs automatically change, build out the in-memory structures. In five minutes, they're working with that new data. I mean, that's just, it's actually a credibility jump because they say, well, how could it be so easy? You guys have been exploiting obviously in-memory, but in-memory's been around since database, in-memory database around since database has been around. So why now? Why is there such a fever pitch around in-memory? Yeah. Well, I think there's a lot of different meanings of in-memory and I think that the thing that is hard about in-memory in this context, in an analytic context, and why, you know, is because you, you know, how do you reconcile big data within memory? Particularly, big data's about data that's growing faster than Moore's law. You know, there's more and more of it, so I'm never going to have enough machines to, you know, it's going to be, I'm scaling out to keep up. How do I use in-memory in a practical way? And, you know, a lot of vendors will talk about, well, I'm going to manually cash in chunks of data, process on them, throw them away, and I'm going to have to do all the sort of manual shifting and moving of stuff. All kinds of gymnastics, right? Yeah, I mean, in our model, it's, you think of it more like this intelligent aggregate cash, so it's really like, the analogy I sometimes use is, it's like, in Google Maps, you look at, you know, you look at some view on the screen, you don't see all the pixels behind there, all the way down to the finest grain. You see levels of detail appropriate to the question you're asking, and knowing that you can zoom in and change your view. And so, use it in-memory intelligently as a sort of closed-loop feedback where you can see what's interesting and you can, if you find an interesting segment of users or something else, you can just go there and it'll build it out for you dynamically, instead of waiting for IT and waiting 6, 12 months to do that. So my last question is, you talked about the angry business user, you know, maybe forming partnerships with IT. We had Merv on yesterday from Gartner. I love Merv. And Merv was saying that he said that his prediction was histories, you know, we're destined to repeat history here, where, you know, distributed computing and even the websites and the internet, where the lines of business went off and did their thing and just like they're doing with big data now and so IT just sort of finally comes along or somebody mandates that IT gets involved, are you telling a little bit different story? I'm inferring from what you said that you're seeing partnerships in your customer base between the angry business user and the IT lines. Is that rare? Is that common? Are they real IT heroes? Is that a typical scenario or not? I think it's going to be interesting to see how it evolves. I think today, typically the group that brought in Hadoop, it may be brought in by the business. It's typically an IT team in one sense or another. They may not actually understand the way the business is using Hadoop. There are cases where people are pushing data and they're querying it and they're just providing, the IT team is just providing the infrastructure. But I think that we're still at a maturity level where if IT isn't involved at all, it's probably, I mean, like somebody's paying for support around Hadoop, somebody has to make it real to get going and that's probably an IT person today but I think we evolve beyond that and I think the real interesting question is 12, 18 months from now when Hadoop is like the dial tone that anybody can just turn on, you know, are people doing kind of self-service or sort of departmental shadow use of the stuff? Does it go well beyond, I mean, does it go beyond the sort of the IT managed infrastructure? I don't know, it'll be interesting to see. It'll be interesting to see. And we got to get going here but I want to just get one more question before we break. We're going to have another entrepreneur come on. You're an entrepreneur, founder, CEO. Give us the update on the company. I'll see, we're impressed. I mean, we always love having founders on because entrepreneurs, it's not easy to build a company. You've done a great job. I mean, obviously going from conception to growth and then the pain is just beginning because you now have some big financing. Give us the update on funds raised and then your growth strategy. What's the plans for you guys? Yeah, so we've raised now two rounds of funding. We raised it back in August of 2011, 7.2 million and then raised 20 million in Series B. So this is from Andreessen Horowitz. This is, you know, fantastic. Battery Ventures, Sadejo Ventures, Incutel. Every one of them a beautiful, fantastic investor. We've... Well, they're going to hold your feet to the fire. They're good investors. They're beautiful and friendly now. But you have to execute a growth strategy. Give us the growth, give us the growth plan for you guys. Yeah, absolutely. And then again, we'll see what happens. So we, I mean, we've seen the customer uptake that we wanted to see, which is allowing us to hit the gas. And so today we're about 60 people. We just moved into a new office. We've got space for about 180 in our office. So we've got some growth to go. And, you know, we're focusing on building out the sales organization, building out field, customer success, services side of things, as well as even though we're very light services wise, just enough, we want to ensure that customers just have an amazing experience with the product. You know, and then everything else that goes with that, more engineering, more product design and the rest. So, you know, I think the focus is, you know, we want to run fast. We have a huge opportunity here. You know, we have, I mean, just every interesting company we talk to wants to use our product and we want to make sure we can make it successful with it. So we just have to move fast enough to keep up with the interest. Well, good luck. We'd like following you guys, been following your progress from day one. Very impressive run. Continue to the journey. Good luck. And that will be following you guys. A good friend of theCUBE. We appreciate you coming on, sharing your perspective. And obviously good luck with the venture. We'll be tracking you guys. This is theCUBE. We'll be right back with our next guest. I'm John Furrier with Dave Vellante. We're here live at Hadoop Summit 2013. We'll be right back with our next guest after this short break. All right, thank you very much.