 We're here with David Champagne, who's the CTO of Revolution Analytics. Welcome to theCUBE, David. Thank you. Good to have you here. Big day two, last year Hadoop World one day event. I don't know, 800 people maybe, John, who are much more intimate, expanded to two days. John's predicted, John's on record saying, we're going to help 10,000 people next year. Give or take a few thousand. So, he got a little buffer there. But no, we're seeing a commercial adoption. Obviously, this has been the rage. Analytics is, obviously, we were at SAP Sapphire doing theCUBE at their event. All they were doing was talking about analytics with Ana in memory. So obviously, they're on at the dashboards and the iPad has generated great end user experiences. We're seeing the apps with visualization, data visualization. So, across the board, there's some nice touch points in the analytics space. So, what are you guys seeing and what are you guys doing in this area? Share with us your knowledge there. Well, I mean, analytics is really becoming an integral part of a business knowing how to run their business. What we're seeing is that, because all this data is being collected by all these businesses, in order to have insight to their customers in order to be competitive in the marketplace, they have to figure out a way to analyze and use that data and do something statistically meaningful with it. And that's where we're starting to see traction in large enterprises wanting to use R because R has so much capability and it's an open source project and it is what PhD students and people coming out of the universities are learning. And everyone, R is totally popular. Everyone, the geeks, the quant jocks, as they are called, are using R. But now we're hearing more news around R being more integrated with scripting and kind of integration. What's going on there? Can you guys are commercializing? Right. Yeah, so, I mean, we add capabilities on top of R to allow businesses to build data analytics platforms. So, whether they're integrating with Hadoop, whether they're running R inside of a database like what we do with IBM Natesa, whether it's taking advantage of traditional HPC clusters and MPI technology to do distributed computing. We're providing all the tools and the capabilities to do that. On top of that, we have capabilities on a web services API for deploying R into third-party applications like business intelligence, where dashboards and other kinds of user interfaces that need to have interfaces to advance analytics. So, we're seeing a lot of companies wanting to just integrate R in all their data sources. From a technical perspective, where do you see the landscape for analytics? And from your perspective, obviously you're close to it. Are we in the first inning, third inning? I mean, it's been around here and there, but with Hadoop, it's kind of changed the game. It seems to be much more of a different equation. What's changing and where are we in this opportunity from a technical perspective? I mean, because some of the more traditional sectors that have always made heavy use of analytics like finance and pharmaceutical, they're investing more and more in that because they have to in order to stay competitive. But with the big data play, I think we're at the beginning because people are trying to, they have all this data, they've figured out they can store it all. Now they got to do something meaningful with it. What good is all the data if you can't analyze it and get insights into your business. And it's not just taking samples or subsets of the data, it's using all the data to understand what is happening with your business. So I think we're just starting to see the beginning of it. What's your packaging strategy? You guys offer free stuff, open stuff? Can you, we've been talking about that all week. So talk about how you approach that and what your philosophy is there. So we, at the core is the open source project R and then we add capabilities on top of that and we provide our own distribution of R called Revolution R Enterprise. And that is what we sell into enterprises and corporations. We do have the packages that we recently released in September that work with Hadoop. We put those in the open source that are available on GitHub for download for usage and we're going to continue to update that project. So we have a little bit of both where we have enterprise features that we package and put in our own distribution of R for sale to enterprise customers. And then we have stuff that we put in the open source and then all of our software is free to academics. So we're encouraging the academic community to get involved in some of the stuff that we're building and make use of it. So okay, so your model is core is open source, layer some not open source stuff on top of that that you charge for. And keep contributing to the community. Is that, I mean, it seems to be the right balance, right? A lot of people have criticized those who don't put things into the open source. What is, you know, this community sort of, it's almost like a table stakes. It's an ante to get into this community. Yeah, I mean, you have to realize that, you know, you're making your business on top of an open source project and therefore you've got to embrace the community otherwise, you know, there's going to be potential problems there. So we really do embrace community. What's good for R is good for us and what we try to make sure that what we do is good for R as well in the community. It's the same message as Cloudera and Hortonworks have for Hadoop and other vendors. It grows the market. You guys take advantage of that, you know, SLA level support and needs. Is that the same kind of business model? Yeah. Yeah, exactly. I mean, if we, you know, we feel like if we can help embed R into these bigger corporations and enterprises, that's good for R. That's good for the community. That's good for, you know, making establishing R as the lingua franca of statistical and data analysis. Okay. Revolution Analytics bringing R to the masses. David Champagne, appreciate you coming on theCUBE and thanks for having me. Really, really wish you the best of luck. Right. Thank you. All right. Take care.