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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2016/07/burtch-survey.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="http://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p>by Joseph Rickert</p>
<p>Last week in a webinar, Burtch Works, an Illinois based executive recruiting firm that specializes in finding analytic talent, released the <a target="_blank" href="http://www.burtchworks.com/2016/07/13/sas-r-python-survey-2016-tool-analytics-pros-prefer/">results of their third annual survey of &quot;quantitative business professionals&quot;</a>. Other than having attended this webinar, I have no knowledge of Burtch Works, but I am willing to take their survey at face value as a good faith, objective effort to answer a question that must be of some importance to a firm in the business of recruiting data scientists and other quantitative professionals.</p>
<p><iframe height="360" allowfullscreen="" width="450" src="https://www.youtube.com/embed/DS8P8url03o?rel=0"></iframe> </p>
<p>This year they asked just one question: <em>Which do you prefer to use: SAS, R, or Python?</em> – Not the question I would have thought to ask: I would not have boldly asked people to pick a winner without providing some context. There is no nuance here. Nevertheless, it is a practical, straightforward question that has provided some interesting results. The simple tally from over 1,000 responses came down like this.</p>
<p>  <a target="_blank" href="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01b7c87d74b3970b-pi"><img title="Burtch_Ring" alt="Burtch_Ring" src="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01b7c87d74b3970b-800wi" border="0"></a></p>
<p>Open source tools dominate overall. SAS did well with professionals with over 16 years of experience while those with less than 5 years of experience preferred R. R was also the dominant choice of analytics professionals with Ph.D's and Master's Degrees. </p>
<p>In an original, and I think revealing attempt to distinguish job function, the Burtch team distinguishes between Data Scientists and Predictive Analytics professionals. This unusual dichotomy led to the following chart.</p>
<p><a target="_blank" href="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01b8d2074946970c-pi"><img title="Burtch_pie" alt="Burtch_pie" src="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01b8d2074946970c-800wi" border="0"></a></p>
<p>I interpret the left side to say that programming professionals doing data wrangling overwhelmingly prefer the opensource languages. It seems reasonable that the Python could have the edge here over R, and that very little of the pie goes to SAS. On the right, it is clear that R and SAS are the tools preferred by people building statistical models. These charts make good sense, and it is very nice to see R doing well in both categories.</p>
<p>The Burtch folks also slice their data by region and industry. You can review all of their findings by watching the short video above, or by examining the report posted on the Burtch <a target="_blank" href="http://www.burtchworks.com/2016/07/13/sas-r-python-survey-2016-tool-analytics-pros-prefer/">website</a>. The report concludes with a few by cherry picked comments from the survey responders. My favorite is: <strong><em>R –</em></strong> <em><strong>Anytime, Anywhere, Anything.</strong></em></p>
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