R has been featured in a couple of recent articles in the tech press. Last month, Data Informed's feature article 5 Key Considerations When Choosing Open Source Statistics Software suggested R for its analytics capabilities:
Certainly, the statistical language R, for instance, is these days hugely popular—not least because it’s free, rather than requiring users to pay SAS’s and SPSS’s annually renewable hefty license fees, where prices in the thousands of dollars are the norm.
Meanwhile, according to today's edition of TechRepublic, The R programming language could challenge SAS for big data queries. I was interviewed for the article, where I talked about how the Hadoop movement for big data is a natural fit for R and big analytics:
Smith says the steady movement away from legacy relational databases that languages like SAS operate on to parallel processing with Hadoop is why companies need to take a fresh look at how they are going to develop analytics programs that can process and produce results from big data. Because R is a non-procedural language developed expressly for big data that is being parallel processed, he believes that more companies will adopt R as part of their big data strategy.
You can find more news articles mentioning R in the Rmedia section of this blog.
"R is a non-procedural language developed expressly for big data that is being parallel processed"
Really?
Posted by: Duncan Murdoch | September 06, 2013 at 15:41
Duncan, I had a similar reaction to that line. I suspect it came from me talking to the reporter about SAS as a procedural language unlike R, which I guess is where the "non-procedural" part came from. And I talked about big data and parallel processing in the context of Revolution R Enterprise (which wasn't mentioned in the article). Sadly I didn't have the opportunity to review the article before it was published.
Posted by: David Smith | September 06, 2013 at 16:21