The question posed was simple enough. As innocuous as it was, I didn’t think such a firestorm would result. Here’s the original post from August 2011 with the subject “SAS versus R”:

Did anyone have to justify to a prospect/customer why R is better than SAS? What arguments did you provide? Did your prospect/customer agree with them? Why do you think, despite being free and having a lot of packages, R is still not a favorite in Data Mining/Predictive Analytics in the corporate world?”

The inquiry was posted on the discussion forum for the LinkedIn group – Advanced Business Analytics, Data Mining, and Predictive Modeling. As of today I found a whopping 900+ comments/replies, many of which posted in the last couple of months. By any standard, the question generated a lot of interest and I think I know why. Data science and big data are currently at an important inflection point – companies are trying to decide whether the traditional license fee model of analytics software is still viable or open source is destined to reign in the coming years.

To provide a bit of perspective for how I see this issue, in a previous life I ran a company that was a long-time Microsoft Certified Partner firm. I lived and breathed Microsoft. I was an evangelist and generated a lot of revenue for the company over the years based on my product recommendations. It took an unfortunate policy change by Microsoft, to shed themselves of all smaller partners, to open my eyes and make me see the light. I now see Microsoft’s license model, as well as that of SAS, as a dinosaur of an age gone by. This is why I eagerly left the Microsoft BI solution-set behind in favor of R and other open source technologies. I won’t be going back. And this is the essence of the LinkedIn discussion where both factions argue strenuously for their position. I’ll give you a small sample of the highlights from the discussion here:

R has some very good extensions for larger data sets. The fact that R is a programming language gives you a lot more freedom in analytics when using R, but for data management I do want to use a more database-like tool, which SAS certainly is.

As a long time/advanced SAS user who is in the process of transitioning into being more R oriented the thing I miss most are my beloved Macros. I’m hoping I can use R functions the same way I used SAS Macros…fingers crossed.

I have avoided SAS except where professionally necessary. I find the macro oriented language extremely unpleasant and the generally prepackaged nature is also contrary to my needs. I don’t normally comment on that publicly since I figure different folks would like different strokes (posted by a software architect at MapR).

We can endlessly argue about when exactly R catches up with SAS (in 1 year or 3 years), but this won’t have much benefit for this discussion. Potential SAS or R users are more interested in trends, I believe.

Even if R was used by more people than SAS it would not mean that R is better than SAS. I believe more people drive Suzuki than Mercedes, but that does not mean that Suzuki is better then Mercedes.

The reason I think the R job growth trend will continue is: it’s free, it’s easy to use in conjunction with SAS and many other tools, and it’s growth in capability is very high. R is now adding more functions in one year than SAS has in total.

I work in analytics every day and own a small consulting firm. I do not observe the same increase in R requirements being stated here. In fact, I see an increase in demand for SAS and services for SAS. I also see Python and other products infringing on R’s territory.

I attended (and spoke at) the American Statistical Association’s Conference on Statistical Practice last week. I must say I was surprised to find the degree to which SAS dominated that particular group. R was there, of course – prominently. Yet, SAS appeared to be the tool of choice for this group.

What if SAS is cheaper in future, or even free, would people change their mind and switch from R? Probably, an interesting assumption it is when debating SAS vs. R, purely from functionality perspective.

I’ve just posted some findings on jobs in analytics, including SAS and R. Based just on job trends, R should catch SAS in between 1.87 and 3.35 years.

Based on the last highlight above, here is the poster’s original research article: “Forecast Update: Will 2014 be the Beginning of the End for SAS and SPSS?” and his recent update: “Job trends in the Analytics Market.” Here is a trend plot from the article that seems to show R slowly approaching SAS from a jobs perspective:

I enjoy monitoring this kind of emotion-charged debate on technology issues because I take it to mean that industry participants truly care about what they’re doing and how they do it. Since this particular LinkedIn discussion thread seems to have some longevity, I’ll continue checking it out in order to keep a pulse on this important issue.

Daniel — Managing Editor, insideBIGDATA

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