Dashboard Insight recently spoke with David Smith of Revolution Analytics about their DeployR tool and R-based analytics.
Dashboard Insight: Can you tell us about the history of Revolution Analytics?
David Smith: Revolution Analytics was founded as Revolution Computing in 2007 as a spin-off out of Yale University. Our original focus was on parallel computing, as well as fostering the continued growth of the 2 million user-strong R community and support the growing needs of commercial R users.
In 2009, we brought on industry veteran Norman Nie as our CEO. Norman has a distinguished background in the analytics space--he was the first individual to bring predictive analytics capabilities to the enterprise when he founded SPSS in the 1960s. After building up a strong team of analytics veterans around him, Norman relaunched the company as Revolution Analytics earlier this year, with a heightened focus on producing enterprise-ready advanced analytics solutions built on R, as well as continuing to evangelize R and support the continued growth of the R community.
DI: Where does Revolution Analytics sit on the BI Stack?
DS: We sit right in the middle of it, between the database and presentation layers. Our DeployR tool allows you to embed R-based analytics into the stack.
DI: What makes Revolution Analytics unique?
In a word--or even better, a letter: R. While we're not the only company that has integrated R into an advanced analytics solution, we are the only company producing software and services with R that’s uniquely tailored to enterprise needs. It really wasn't until this past year that R began to expand beyond its roots in academia towards more widespread enterprise adoption (we've been working to produce an enterprise-ready version of R for years). Where other vendors are simply embedding R into wider applications, we're making a custom version that addresses the most common adoption hurdles for business users--namely, ease-of-use and scalability.
DI: I have seen the term “predictive analytics” in the news quite a lot lately. Do you think
predictive analytics is getting more popular?
DS: "Predictive analytics" is more about marketing than anything else--it's "statistical modeling" by any other name. That being said, it's definitely fair to say that the practice--and the wider discipline of data science--is gaining more traction within the enterprise. Businesses are generating more data than ever before, but generally lack sufficient resources to leverage it for operational insight and decision-making purposes.
Even several years ago, the term "predictive analytics" would have drawn a look of confusion and curiosity from most CIOs. Today, though, it's becoming an increasing priority as businesses strive to enable data scientists to better leverage their data. It's also worth noting that there were several noteworthy use cases of predictive analytics before the rise of "Big Data". Wal-Mart, for one, used predictive analytics to better understand the preferences of their customers across different locations and adjust store inventories accordingly to better match demand. This was one of the major factors that led to them separating themselves from the pack from a competitive standpoint.
DI: Who uses your products?
DS: We work with customers from a diverse array of verticals--everything from pharmaceuticals and financial services to entertainment and life sciences. R is an extremely flexible language and its use cases tend to vary greatly. Revolution R is used by financial services companies like Bank of America for performing quantitative analyses, biological research firms doing advanced genomic research and by pharma companies like Merck and Pfizer for clinical drug development, to name a few.
DI: With the drastic shift in the global economy last year, was Revolution Analytics affected? If so, how did you adjust?
DS: New market conditions introduced by the global economic downturn really affected Revolution -- in a positive way. IT departments across the board saw their budgets slashed and CIO and IT managers were instructed to find cost-effective alternatives wherever they could. We offer a product that automates much of the decision-making process and thus frees up man-hours for other tasks. On top of that, we're an open source vendor: we offer advanced analytics software at half of the price charged by leading proprietary vendors--sometimes even less.
DI: What is the process if someone wants to evaluate your solutions?
DS: Our team of experienced sales consultants are ready help companies who want to evaluate how Revolution R Enterprise addresses their analytical needs. You can call 1-855-GET-REVO or contact them via our website at: http://www.revolutionanalytics.com/aboutus/contact-us.php
We also offer Revolution R free-of-charge to academics and students. R was born out of academia and many of the leading R users and package developers are from academic backgrounds. It's important to us to give back to the community, as well as to ensure that today's statistics students--tomorrow's data scientists--continue to learn and innovate with R.
DI: What can we expect to see from Revolution Analytics in the coming months?
DS: We'll be announcing the release of version 4.2 of our Revolution R offering later this month, which will include functional upgrades and expanded platform support. The major item on our product roadmap for 2011, though, is our forthcoming user-friendly GUI, which we'll be releasing later in 2011. It will bring advanced analytics capabilities to line-of-business users, which will help spur enterprise adoption of R to even greater levels.
David Smith is VP of Community for Revolution Analytics.