Our mission at Revolution Analytics is to make R the statistical analysis tool of choice in the workplace. But even though R is pervasive in academia and rising in popularity generally, we still sometimes get blank faces when we demonstrate R to potential new clients. Sure, most people have heard of R -- it's been hard to miss in the news lately -- but some haven't yet heard how leading-edge companies are using R today to improve their data analysis processes and how they communicate the results.
That's why we started a project to document how R is Hot. We interviewed a dozen R users, mostly from industry but also from the R user community generally, to try and understand what makes R different, and how you can do things with R that just can't be done in other statistical software. The result is a story, told in 8 pages, of how a statistical programming language Invented in New Zealand became a global sensation. The article tells how R is more than just a programming language: its power and elegance are helping companies build their business around modern data analysis practices. The fact that there's no need to reinvent the wheel (every statistical analysis you might ever need is already there) and that R makes high-quality data visualization easy, has given R critical mass and seen it go viral, being widely used around the world. But R isn't standing still: as a vibrant, open-source project it is changing, transforming and evolving to keep up with the latest advances in data analysis.
Starting tomorrow and over the next five weeks, we'll be serializing the article here on the blog each Thursday, and you'll be able to find new posts in the R is Hot section. If you want to get the scoop early, you can download the full article now from the Revolution Analytics website at www.revolutionanalytics.com/R-is-Hot (in exchange for your email address and the opportunity to sign up for our monthly newsletter). We've released the content under a Creative Commons license, so please feel free to share these stories about R with others.
I'd like to give thanks to everyone who participated in interviews for this project, including:
- Peter Aldhous, San Francisco Bureau Chief, New Scientist magazine.
- Amanda Cox, Graphics Editor, New York Times.
- Abhijit Dasgupta, consulting biostatistician, National Institutes of Health.
- Zubin Dowlaty, VP / Head of Innovation & Development, Mu Sigma.
- Michael Elashoff, Director of Biostatistics, CardioDX.
- Mike King, Quantitative Analyst, Bank of America.
- John Lucker, Consulting Principal - Advanced Analytics and Modeling, Deloitte Consulting LLP.
- Robert A. Muenchen, author, R for SAS and SPSS Users.
- Glenn Meyers, Vice President of Research, ISO Innovative Analytics.
- Norman Nie, CEO, Revolution Analytics.
- Robert Sudol, Sr. Development Manager in Fixed Income Technology, AllianceBernstein.
- Hadley Wickham, author, ggplot2: Elegant Graphics for Data Analysis.
I'd also like to give a special thanks to Mike Barlow who conducted the interviews and was instrumental in putting this article together.
We hope you enjoy the article, and let us know what you think in the comments.
Revolution Analytics: R is Hot