R – not the epic fail we thought
[This article was first published on Realizations in Biostatistics, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
I usually like AnnMaria’s witty insight. I can relate to a lot of what she is saying. After all SAS and family life are large parts of my life, too. But you can imagine the reaction she provoked in saying the following:Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
I know that R is free and I am actually a Unix fan and think Open Source software is a great idea. However, for me personally and for most users, both individual and organizational, the much greater cost of software is the time it takes to install it, maintain it, learn it and document it. On that, R is an epic fail.With the exception of the last sentence, I am in full agreement. Especially in the industry I work in, qualification and documentation is hugely important, and a strength of SAS is a gigantic support department who has worked through these issues. Having some maverick install and use R, as I do, simply does not work for the more formal work that we do. (I use R for consulting and other things that do not necessarily fulfill a predicate rule.)
However, another company, REvolution Computing, has recognized this need as well. With R catching on at the FDA, larger companies in our industry have taken a huge interest in R, partly because of the flexibility in statistical calculations (and, frankly, the S language beats SAS/IML hands down for the fancier methods), and mostly to save millions of dollars in license fees. Compare REvolution’s few hundred dollars a year for install and operation qualification on an infinite-seat license to SAS’s license model, and it’s not hard to see how.
And SAS, to their credit, has made it easier to interact with R.
Epic win for everybody.
To leave a comment for the author, please follow the link and comment on their blog: Realizations in Biostatistics.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.