Using R in production: industry experts share their experiences

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I had a great time yesterday moderating the “R in Action” panel discussion at the DataWeek conference in San Francisco. Each of the panelists represented a company that is actively using R and/or Revolution R Enterprise. Here (from memory, since I couldn't take notes) are some the things they shared:

  • Jesse Bridgewater from eBay talked about how R is used within eBay's operations to analyze massive volumes of data. 
  • Anthony Goldbloom from Kaggle confirmed that more Kaggle competition winners use R than any other software package. Random Forests is a particularly popular predictive modeling technique in the competiitions.
  • Jim Porzak from Minted espoused the benefits of using R: the flexibility of the language, the data visualization capabilities, and the extensive user community and CRAN pacakages.
  • Hsiu-Khuern Tang from Intuit described how R is used in the creation of the Intuit Small Business Index, and some of the advanced modeling packages (such as gbm and the Rmetrics suite) used in the forecasting process.
  • John Wallace from Upstream Software talked about dealing with Big Data in R, and using the modeling routines in Revolution R Enterprise to fit regression models for use in production.
  • Damien Weldon from Corelogic contrasted using (previously) SAS and (now) R for financial data analysis.

Other topics of conversation included building data science teams to work in modern analytical environments, the strengths and weaknesses of R, and the technology stack and other applications working with R. All in all, it was a lively and entertaining discussion — my sincere thanks go to all of the panelists for sharing their insights and expertise.

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