Should You Learn SAS In 2021?

Is the SAS language on its way out, or should you seriously consider picking it up?

The Data Science Industry is one that has rapidly evolved and changed over the past decade. With this rapid development has come a string of new tools, as well as some changes to the convention when it comes to programming languages. Many of the languages that used to be used more commonly for Data Science are now being phased out to some extent for this purpose.

Of course, a very noteworthy example of this is the R programming language. There was a time when R was the dominating pioneer of the statistical computing domain, but that time has come and passed. Python is the new king of machine-learning and statistical data analysis. This comes down to a few key advantages that Python has over R. If you are interested in learning more about R’s story with Python, I wrote an article around this time last year that goes into more detail on this topic that you can read here:

Another notable language in the Data Science ecosystem is SAS. The SAS programming language was created at North Carolina State University by Anthony James Barr in 1960. Given that the language was created so early on, it is easy to see why it has been such a staple in the world of statistical computing. SAS has been an industry staple for a long time now, but recently this has stopped being the case. Why is this, and is it still worth picking up in 2021?

One very important contributing factor to SAS’s demise is the language’s business model. While most of the competition is open-source, SAS remains a closed-source language. Personally, I do not like to work with closed source languages nearly as much for two reasons:

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