 Okay, we're back live at Stratoconference. This is the conference of big data, and this is siliconangle.com, siliconangle.tv's flagship telecast, where we go out to all the top events and technology and talk to the smartest people who can find, CEOs, entrepreneurs, venture capitals, whoever's got the signal from the noise, extract that metadata, share that with you. 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 we're here with Dave Rich, who's the CEO of Revolution Analytics, new CEO, you've been on just a few weeks. David, welcome. We broke that story at siliconangle.com. Yes, you did, yes you did. Yeah, so, well, welcome to theCUBE and welcome to Revolution Analytics. Welcome to big data, although you've been in analytics for quite some time, right? Coming from Accenture Analytics, so you got a big background in analytics and services. Yes, sir. So, what brought you here? Well, to this event, obviously, this is one of the premier events. I think, if anything, it really gives you the heartbeat and the pulse. If not, the brains of the business, and as I was commenting to some of my colleagues, is I view it as the end of the beginning. What do you mean by that? Well, if you look at this year's conference, and certainly in the exhibit hall, some name brand companies that might not have shown up in force as perhaps otherwise would, people like EMC and Microsoft and Oracle, and I actually view it as a good thing. What that says is that the enterprise adoption curve is about to go skyrocketing, which is exciting to me as a professional who's been in the business three decades, and certainly as it relates to the Revolution Analytics, we think we're in a great spot to take advantage of that. You guys have great popularity and notoriety amongst the tech geeks and the alpha geeks that people have been using are. It's been a great tool for people playing with data, partying with data, and all the good stuff. You're now the CEO. You've come from a business that people can relate to, Accenture, and they've been usually talking to clients about improving their business, and it's a consulting, management consulting company, process improvement, blah, blah, blah. Big data is offering probably one of the most unique opportunities right now to change business, landscape, across the board, financial services, healthcare, society, everywhere. As a CEO of Revolution Analytics, what's it like now that you have this vision of R going mainstream? You mentioned Microsoft, IBM even has you on the price list now. You guys are a great brand, and it's still the opening bell, if you will, of this marketplace. So what's your strategy? What's your to-do list for the company, and what's your vision for Revolution Analytics? That's kind of interesting. I brought a little of my to-do list for my previous role and my previous employer, which what I saw when I was there was that we were at the beginning of a big business transformation. I likened it to what business process re-engineering was back two decades ago and the wave of innovation, technology innovation has sort of accompanied that as the enabling platform, if you will. I think what business process re-engineering was to client server, e-commerce, a few other things, we called it decision process re-engineering, and that's the next new big management wave is just taking a look at the fundamental ways an organization makes decisions, critical decisions, and then the promise of what big data, and certainly increasingly, almost endless sources of potential data to bring to that process and to make people more informed decision makers, that's certainly what we were about, being as you pointed out a management consultancy leading that wave. I had the opportunity to come to the other side sort of bottoms up to say, well, we could be the enabling platform, if you will, we and our partners to enable businesses to do those types of transformations to your point. We have at Silicon Angle a new vertical that we launched last year called Services Angle and no one's really covering the services business and I wrote in a post yesterday on Forbes about big data here at Stroud and some of the trends changing the world and I said the statement in my post that in this tsunami of innovation and creation and this invention that's going on with big data, there's a lot of products, companies coming out of the Hadoop and everything else, SaaS, infrastructure as a service, platform as a service, but the side effect of all this is a boom in services business. Every startup I talk to, every company, they say, yeah, and we're launching as a service first to learn the market requirements. One, do you see the same thing? And two, what's happening in the services revolution? If this is truly a side effect, what kinds of value chains will be disrupted? What kinds of services will we see from drawing on your experience in the management consulting services business? I mean, we're hearing EMC's doing well on the consulting side Hadoop with Cloudera. They got great revenue. Every startup that's out there has to sit down and go hand to hand with clients and there's a big services component. This pure place service startup's coming. I think that's right and frankly, as long as there's technology and new technology, there'll be technology consulting and associated services, but I actually think there's an opportunity to even take it even a step further, which there's a term out there in the services parlance called knowledge process outsourcing, which is sort of the next new thing after a business process outsourcing. And if you think about what the potential of having data, having the ability to quickly sift through it, and more importantly have the data scientists, which are hard to come by by the way, and then marrying that with good business people to come up with insights, I think you're gonna see a whole range of businesses, maybe illustrative, people doing fraud as a service or people doing customer acquisition and retention as a service and be much more outcomes based, much more reliant on a platform and reliant on data and marrying that with the services capability and then the commercial arrangement with a client would be a gain sharing type model. And that will totally disrupt, I believe, the typical time of materials services and consulting business in profound ways. And I think that that's the next new convergence is people with data, people with platforms, people with business insights, bringing that together and the form of an integrated service will be the key next wave in my view. Do you see peer insights as also having an impact? In other words, the ability of a crowd to operate on those analytics in a way that maybe here to four, only a large consulting firm could? Well, I think, I'm glad you said that. The reason I joined a very enthusiastically revolution and great to take this on is I think revolution as the opportunity, as the storefront, if you will, of the community, to crowdsourced with the help of the community and the involvement of the community. And again, I'm drawing on my experience in the past coming from Accenture where we had a very robust knowledge exchange which tied all of our 250,000 professionals together to where we shared in our knowledge capital, our know-how and frankly, that was a closed community. Could you imagine if you were much more open where knowledge was being shared and captured and I think that the opportunity for a revolution is that we could effectively orchestrate that, facilitate that, that knowledge exchange, if you will, and in fact be much more of a two way perhaps where you could actually crowdsource business problems, you go down to the community. And in fact, if you have the right mechanism in place, they can even contribute to the collective knowledge capital. When you joined Revolution Analytics, what impressed you about R? I mean, because obviously you're going to a company that's doing very, very well, but they have a good product, right? So was that the product? Was it the team? All the above, what got you really fired up to come in and take over the helm at revolution? Well, I do think it, first of all, it's a good team. I think the team has been assembled there, has a passion for what this could be, as well as what it is. The products themselves, I think the work that has been done over the last two years, not just to create the market presence, but to create the first set of foundational products, I think is excellent. And I do think that it's at that position to really take off. And my hopeful contribution will be the fact that the last three decades, in some form or fashion, I've been a student, I call myself a cultural anthropologist, except that the culture I'm talking about is what it takes to go into an enterprise and essentially insert new technology and watch the assimilation occur. And I think that we're at that point. And the revolution I think is in a position to take advantage of that. So you guys are all about our big user base, probably a couple million users. But for those who don't know, let's talk about what is R and why R and then why revolution analytics. So why don't we start with what is R? In the advanced analytics world, there's basically been two major programming languages. So think of it like COBOL, if you will, back in the mainframe days, SAS and SPSS. A community came along, most of the academics to start, but there's an open source community that created a language called R. And again, I'm an old timer. It reminds me of the promise of object-oriented programming, but it's just a lot easier to do and take advantage of lots of things. So the new emerging language, and if you go on campus and you ask anybody coming off campus what they're doing, probes and stats and any other course that they have, it's in R. Like it's like SPSS in our day, you know what I'm saying? That's right, yeah. So there's now a third language emerging on the scene. And it really, it does remind me of the shift from COBOL to C++. We've seen the movie before in other types of IT technology and I think this is where we are really. And it's a classic. You talk about the end of the beginning. IBM buys SPSS, we're an SPSS shop. They totally changed its pricing, jacks it up. We're like, ah, a heart attack when we had to go renew. And so along with the sort of modernity of R, we've got the legacy guys just trying to squeeze as much profit out of the bases they can. Okay, so that's good. Now, why revolution analytics? Well, we think it's actually a good thing. In fact, when Oracle recently announced that they're standardizing on R, we actually thought that was a great thing. Because the same thing happened with Linux. If you think about what happened a decade or so ago with Linux, it was sort of similar. Some of the legacy customers were tired of paying the high license fees. And so they put Red Hat in business. And I think that we, in fact, we say that quite often is we're the Red Hat of R. And we think we're right in that exact same inflection point that Red Hat was at, Linux was at. And that's why we're so excited about our position. So, talk a little bit about with your experience in analytics and business intelligence. Do you see, I mean, obviously these two worlds are coming together, right? But I remember the days of, and they're still here, dashboards and KPIs and balanced scorecards and it really became a staple of reporting and everybody wanted to get beyond reporting into predictive analytics. And, you know, kind of happened, but it wasn't the epiphany that we feels like now with big data. Are those two businesses coming together? Absolutely. What are you envisioned for that? Yeah, I think the way I describe it is, is that rudimentary management reporting, don't confuse management reporting with predictive analytics. But I do think that performance management, meeting predictive analytics at scale is what the opportunity is. And so, in my former role, you know, I used to say that BI or descriptive analytics is all about the what. That's the data. It's the what, what happened. And what it really doesn't do is give you the so what, or more importantly, the now what. And so that's the promise of the marriage of the two, is being able to do a quick situational assessment and then, you know, with some of these predictive analytics techniques, helping clients gain not just the insights, but then perhaps even inform better decisions, which is why we say, decision process re-engineering is really going to be the next new management wave. What's the strategy for you guys this year? So now you guys got some good partnerships, obviously great traction. What's next? What's your, what's your outlook and strategy for the company as you take it forward? Yeah, being, taking the foundational building blocks that we have and creating what I call role-based workbenches. So things that if you are a programmer, view it as like a programmer's workbench, or a designer's workbench, or an installer's workbench, or if you're actually in the stat department, you know, it helps you be able to, to effectively create better use cases and what have you. So we're focused on creating those, what I think would be critical to any kind of enterprise adoption. Those role-based templates and tools to improve the productivity, both of the people that are in the IT department or the people responsible for the environment, and as well as the practitioners, you know, needing to have productivity aids to make it easier and more accessible. Talk about some of the partnerships you guys have done as an example of the kind of relationships you have in the marketplace, and talk about the kinds of things you'll be doing going forward. Well, I think you mentioned one. I think we were just recently added to the price list for Netiza and with IBM. So that's a great partnership and we're excited about that opportunity. And there's more to follow. I know that Teradata and others are companies in EMC, Green Plum. I mean, I'm sure there'll be more that will want to do that, but we're particularly excited about our relationship with Clodera and just, you know, getting into the whole world of Hadoop. And so we're gonna be a little bi-directional in some of our thinking. And what I mean by that is, is that there's still a lot of on-premise environments out there, yet increasingly there's gonna be a lot more that are gonna be off-prem or some hybrid solutions. So we need to have platforms that are either for the cloud or private clouds, and then some that are more in the traditional data appliance arena. So okay, so where our goes, you go and make it better along the way. That's really the strategy. All right, David. David Rich, thank you very much for coming on to theCUBE. It's great having you. Good luck with the new role. Thank you. It's a pleasure seeing you. Okay, thanks for joining. Welcome to theCUBE.