Jeff Erhardt, the COO of Revolution Analytics, explains to IT Business Edge's Loraine Lawson how companies are using "R"-an open source statistical programming language. Revolution sells an enterprise solution for statistical computing and analytics using R. Recently, the company announced a new partnership that will integrate Revolution R Enterprise with the IBM Netezza TwinFin Data Warehouse Appliance.
"... companies are now realizing that if they're not analyzing and making business-driven decisions using this [analytics] data, they're going to fall behind their competitors and fall behind their peers."
Lawson: So what is R?
Erhardt: R is an open source statistical programming language. The easiest way to think about it is the largest commercial competitor in the states is a company called SAS, and while it's not a perfect analogy, one way to think about R is as an open source version of SAS. It's not perfectly correct, but for people who have not heard of R, that's one way to explain it.
It's used to analyze data-any kind of data that exists. That's really why R is becoming so popular ... we're really starting to enter this age of analytics. Because the storage costs have gotten so low for this data and because there's so much data being generated, companies are now realizing that if they're not analyzing and making business-driven decisions using this data, they're going to fall behind their competitors and fall behind their peers. There's this tremendous demand in corporations to be able to have tools to analyze and gain meaning from this data that they're collecting. There's a tremendous demand for analysts who can develop these models and basically extract the insight from this data, and then finally there's a need to, in a cost-effective way, implement these analytics within an enterprise and disseminate the knowledge across the enterprise. It's not something that can be done on a small scale and it's not something that can be done in an isolated way to truly get the business value out of it.
For all three of those challenges that these analytics-driven organizations face, R is truly the ideal solution. It's widely considered to be the most powerful and flexible statistics language in the world. It has become the lingua franca for researching and teaching and statistics, it's what all of the students in university are being trained statistics on and finally, because it's an open source project backed by a commercial company like us, we can help bring it to corporations at a price that's a fraction of what the existing commercial players-for example, SAS-are offering.
Lawson: What are some of the use cases you see for R and the enterprise?
Erhardt: It's incredibly diverse. It ranges from pharmaceuticals for drug developments, biostatistics, gene analysis, genetic analysis into finance. It's very heavily used in hedge funds, quantitative finance risk, credit analysis, fraud detection, understanding customer churn, understanding customer behavior, pricing optimization forecasting. We have customers who are entertainment or gaming companies using it to understand buying patterns and effectiveness of different media campaigns. So it ranges anywhere from life sciences to finance to Internet to telecom.