**Revolutions**, and kindly contributed to R-bloggers)

It was quite the media frenzy for Revolution and R last week. In conjunction with our relaunch as Revolution Analytics, we spoke to more than a dozen journalists and analysts to explain why we think R is at the center of a perfect storm for predictive analytics: with routine collection of large data sets, data analysis is now a commercial imperative; statistical training is now prevalent, and mainly done with R; and compared to expensive, legacy tools R is the best environment for implementing the analytics that modern companies need to compete. There was quite a bit of coverage of the story, and I’ve listed the highlights below. And is often the case with journalists who have to create a multi-page article based only on a short conversation, there are a couple of clarifications to make, too.

Quentin Hardy wrote an extensive profile of Revolution CEO Norman Nie for *Forbes* magazine. It gives a history of commercial statistical software starting with SPSS, and charts the transition to open-source with several examples of R applications. I did cringe, though, at the description of R as "a freebie invented in 1993" – due credit goes to Ross Ihaka and Robert Gentleman for founding R, and also to the many other contributors for making R the most successful open-source statistical software project of all time. The article is online now, and will also be in the May 24 print issue of *Forbes*.

Timothy Prickett Morgan for The Register focussed more on R and Revolution’s open-core strategy for commercialization of R, and the background of Revolution as a business and its employees. (I was gratified to learn that Timothy had a copy of *An Introduction to R*, but he overstated my involvement with it — I only write the original version of the graphics chapters. Bill Venables was the main author.)

Steve Miller continues his interview with Norman Nie at the Information Management blog, sharing some of his own experiences getting started with R and asking Norman about the future of R in the commercial world with Revolution R.

Finally, Chris Kanaracus wrote in PC World about Revolution’s plans for Revolution R to be an alternative to SAS and SPSS, and analysts that took a look at Revolution’s plan and the place of R in predictive analytics included James Taylor and BeyeNetwork.

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