In a new article for FastCoLabs, journalist Tina Amirtha has published a follow-up article to last month's piece on R's impact on open science. In her latest article, the focus is on how R is used at companies and displacing legacy statistics software like SAS:
SAS is no match for the open-source language that pioneering data scientists use in academia, which is simply known as R.
Tina interviews R users from companies Facebook and DataSong (as well as me and data scientist Casey Herron from Revolution Analytics) and discovers some cool applications of how R is used:
Facebook, for example, uses a technique called power analysis in order to figure out whether it has collected enough relevant data when it studies how users interact with new features on the site. It is all thanks to research data scientists who have developed the appropriate statistical tools in R and made them available to everyone.
The article points out the obvious reasons why R is good for business: it's open-source, it's great for data visualization, and because new research in statistics is done in R, it has far more capabilities (especially new and powerful algorithms) compared to proprietary tools. I wanted to point out one often-overlooked but, I believe, extremely important reason why R is good for businesses: people.
“I think the number one value to businesses [in using R] is access to talent,” says Smith. “So many businesses now are doing much more with data, especially with the big data revolution and doing much more with analytics. And because they’re hiring people coming out of school. They know R already.”
The data science talent shortage is a real problem for data driven businesses, but those companies that have adopted R as their platform have a supply of ready-trained R users graduating from academia (and who likely already know other cutting-edge open-source technologies to boot).