 Welcome back. It's theCUBE here live at Hadoop World in New York City. I'm Jeff Kelly with Wikibon. Dave and John are, I'm filling in for Dave and John now for our next segment. We're welcoming Rick Farnell, a co-founder and president of Think Big Analytics. Thanks, Chad. Thanks for being here. We're talking services. I want you to tell us a little bit about Think Big Analytics, what you guys are all about, and kind of how you fit into the Hadoop ecosystem. Sure. So, Think Big Analytics, we started the company last August for a professional services company. Providing professional services both on the engineering side of Hadoop ecosystems as well as data science and analytics solutions on top of Hadoop. So, we don't sell software or infrastructure to take referral fees. We strictly have the expertise to deliver solutions to enterprise clients. So, tell me about the role, as you see it, of services in this Hadoop environment. We talk a lot about challenges around implementing Hadoop and really getting value out of it. What role will services play as the ecosystem matures and as organizations are looking to get actual real business value out of Hadoop? Yeah, so, I think the big role to Think Big Analytics plays is we're kind of a mini version of a large global systems integrator. We 100% focus on Hadoop-inspired architectures. So, we work with clients to figure out what does Hadoop do? What type of value does it bring to the organization? How do I plan for it? How do I budget for it? What skills do I need to bring into my organization to manage it, to build solutions on top of it? So, I think we play a really unique role in the ecosystem right now because the deals in the last year, year and a half have been kind of more pilots and getting going. And yes, there's some enterprise clients, but I think from an ecosystem perspective, we're really bringing a lot of solution creation on top of the platform. So, folks like Cloudera and MapR and kind of the Hadoop vendors, Hortonworks, they provide support services and distributions on top of Hadoop, but then we kind of come in and help clients build solutions on top of it. So, there was a lot of talk this morning in Michael's keynote about kind of that next, taking that next step, building those applications on top and really bringing business value. So, that sounds like a great opportunity for service providers. And that's exactly the space that we fit. So, we really bring some velocity to the table with clients. So, finding these skills, whether they're pure Hadoop skills or the data science skills, proficient in these technologies is really, really hard to find. So, as a firm, that's exactly what we're bringing in. So, we're bringing people in, we're training them ourselves and then we're putting them back out on client projects to really bring that velocity to the client. So, maybe the client could have done something in six months or nine months, but when they engage with Think Big, we can get them there in a couple of months. Okay, so tell me about the kind of the technical versus the business side of your practice. I mean, you've got the technical challenges, but you've also got talking to business users and executives that might not understand the big data, what the approach is all about. Tell me about those two different worlds and how you approach them. So, I think our approach has been to really lead with what we call a brainstorm engagement. It's a two week engagement that really allows the IT and technical folks to really sit together with the business strategy folks. And we kind of brainstorm what types of analytics they would like to do and why they can't do that with their existing infrastructure. And then we kind of come up with a goal architecture using Hadoop and the ecosystem of products that are available today. And then we kind of move forward and pilot that. And then in the eight week scenario, we're kind of standing up something that is useful. It's not a throwaway POC. So, kind of the business sees immediate impact. They get visibility into some reports or some analytics that they couldn't do before or would take months to ask the IT organization to develop. And kind of we repeat that process. So, this notion of a big data solution factory is really something that we're kind of instilling in our clients. So, they work with us. We take them from prioritization to the technology to the analytics and solutions that sit on top. And then it's a continual process to really leverage the asset over time. It says, as we all know and we've heard in all the case studies today in the sessions, kind of originally what these clusters originally stand up to do, very often the organizations find new things to do with it. So, once that word gets out, like wow, I have all this compute power, wow, I can take all of this new data that we couldn't analyze before, it starts to really grow on the business side. And that's kind of where we really bring marriage to the IT organization and to the business organization. I mean, that makes a lot of sense because I think one of the real benefits or one of the real benefits we're seeing in Hadoop is the ability to start doing some kind of analytics that you never even thought of before. So, you've got to have that flexibility. When you think of these new ideas, you'll be able to experiment. And when you find a winning formula to put that into production. So, in really that turnaround time to analyzing these new ideas, so our, the notion of a big data solution factor is make it possible for the business side of the house to make a thousand mistakes in their analysis at a really, really low cost and little bit of time to get to that one thing that's really going to create a game changing and new service for that business. So, of course, a lot of talk about the competition heating up in the Hadoop distribution business. I just wanted to get your take. We've got Cloudera here at Hadoop World. Hortonworks made a splash with their entry a few months ago and now their recent announcement. What's your take on the competition, the different business models? And specifically, how does it impact your business? Do you have to tailor your services to the different distribution? How does that work? How does it impact your business? So, I think from our perspective, the one thing that all three players really have at their core is following the Apache Hadoop distribution. So, from our perspective, we have services that sit on top and really focused on building the solutions on top of Hadoop. Now, as far as the distribution, that it really ends up being the winner. Maybe it's going to be different verticals, different industries, different geographies. From our perspective at Think Big, we really want to be known as building the solutions on top of the ecosystem. So, again, when it comes to the competition going on and also the related technologies, there's AsterData's here, HP Vertica's here. How do those fit into the Hadoop landscape? And is that something that you help your clients with and kind of leverage both Hadoop and other related big data technologies? So it's funny, what we see in just the last six months alone is with Hadoop and the distributions really making a major play and really landing mainstream, it's made the MPP vendors not look so emerging. So now all of a sudden enterprises are like, wow, okay, that Hadoop thing, that may be a little bit out there. This MPP world, that's great, I'm okay there. So if anything, the organizations that we work with that have made those decisions are really embracing the proliferation of those MPP stores across their organization and kind of using Hadoop for where it does its best work, which is really large-scale data processing of unstructured data. So it sounds like you would agree with the premise that Hadoop is really a complementary technology to a lot of these other big data technologies in the existing IT infrastructure. Absolutely, and in fact, a lot of our enterprise clients, both in the online advertising space and the technology space, telecommunication space that we work with, we see kind of that marriage of the two, use the right approach and the right technology for the right job. So the MPP vendors have a total place with the business side of the house and then Hadoop as an ecosystem has a place to store the unstructured information and kind of feed the strategy behind the MPP vendors. So tell me a little bit about your customers, the use cases you're seeing and talk about the evolution of Hadoop in terms of we know the use cases at LinkedIn and Facebook, et cetera. Talk about moving to more traditional enterprises. What's that, where are we on that spectrum and what are your customers, what type of industries are coming to you? So I think early on, a year ago, what we're seeing is a lot of enterprise customers doing pilots and proof of concepts and now we're really starting to see these organizations pick the staff. So they've made a decision on their data warehousing, they've made a decision on their MPP vendors and now they're saying, all right, how do I bring in this unstructured capability? So we're seeing it in the logistics space, we're seeing it in banking, financial, retail, certainly the online advertising space was kind of first mover there, doing analytics with unstructured data and quickstream data. So yeah, we're really excited about just the opportunity to do more with data. It's kind of like the internet back in 1996, people would say, what does the internet do? Give me the use case, right? It's kind of like today, tell me what Hadoop does. What is its use case? And it's very, very different for whichever organization you are or whatever vertically you're in. So in our last question, what would you, what advice would you give to organizations out there? They're watching this, they're learning about Hadoop. Sounds like something that could help them, but not really sure where to get started. What are some of the first steps they can take? So I think the most important piece that we've seen is make your first projects really successful, give them the best shot at success, because with this emerging space, there's some folks inside the organization that are taking some risks. The last thing you want to do is take that risk and not have the project go well. So bring in some experts and really do it right the first time and give yourself the opportunity to kind of grow with the solution over time and be known as a visionary inside the organization. All right, well, Rick, thanks so much for joining us. It was a pleasure having you. Think big analytics, check them out. It was good to talk to you and enjoy the rest of the show. Thanks so much, we appreciate it.