The big news from the SAS world this summer was the release, on May 28, of the SAS University Edition, which brings the effective price for a single user edition of SAS down from around $10,000 to $0. It does most of the things that statistical analysts need, is not a student edition, does not require academic status, and runs locally using a browser interface (SAS Studio). Clearly SAS is making a bid for the mindshare of the analytic community hooked on open-source software such as R.
Gregory Piatetsky-Shapiro, publisher of the KD-Nuggets data mining newsletter, published a poll yesterday (8/20) that shows a dramatic shift in program preference from 2013 among the data science community. In both 2013 and 2104 his poll asked “What programming/statistics languages you used for an analytics / data mining / data science work in 2014?” SAS has substantially increased its share of the responses (respondents can select more than one response):
SAS: From 21% (2013) to 36% (2014)
SQL: From 37% to 31%
Python: From 39% to 35%
R: From 61% to 49%
SAS users tend to be a more self-contained bunch — 58% said they used only SAS (compared to 20% for R, 14% for Python, and 5% for SQL). This is consistent with a recent poll from a Strata conference, which found two types of users – those who stuck mainly to one environment (usually SAS or Excel), and those who used multiple languages (R, Python, etc.).