Why R Programming is better than SAS?

R Programming and SAS Programming have over the years, assumed the role of programming giants in the big data industry. And since the time of R programming’s inception, a debate between which tool is the best has been quite commonplace. For us to finally determine why one tool is better than the other, it would be very imperative to know what exactly the two ecosystems comprise of.
SAS by far has been the hands-down leader in the industry, mainly because of its long list of renowned clients and its time-honored existence in the industry. This tool or software environment offers its users with an enormous amount of varied statistical functions and has a great Enterprise Guide and Miner for its clients. This ensures that users learn faster with a continuous flow of technical support.
R, on the other hand, has come to be a crowd favorite, mainly because of its open-sourced nature. This means that it can be downloaded free of cost as opposed to its licensed counterpart SAS. This free mature and an overactive community, R programming have to offer quite a number of latest statistical functions and a number of solutions as well.
Related Article: R Programming in Business Analytics
It may seem that R has come to lead the race in this commercial analytics space and rightly so. Here we present, in a nutshell, a few very strong reasons which tip the scale in R Programming’s favor.

  1. The Cost

SAS programming, since its inception, has been a licensed software environment. While it has a plethora of private companies under its belt, very few individuals are able to get access to it on their own. This is the fundamental difference that gives R the cutting edge. Being free and easily available to download makes R a novice’s dream.

  1. Application

R programming wins here with quite a large margin too, mainly owing to its community. All the latest features and new abilities have already reached the users, both faster and more frequently when compared to SAS. On the other hand, SAS has a team, which upgrades its features in variation roll outs, which have major intervals of time between them.

  1. Transparency 

R happens to have the largest community available for any kind of open-sourced programming tool out there. As this proves a greater advantage for all those looking for small tricks and tips to solve any sort of bugs in their programs. Fast and free help is always appreciated by many of us in the society today. This is not quite the case with SAS though.
These three qualities unearth stark differences between the two tools. At the same time, it is also true that many professionals today don’t just work with either one of these tools. Many reasons are touted for this, it could be the amazing customer support that SAS offers, the extensive amount of statistical facilities, and the fact that SAS has only reviewed features in it and so on. But at the same time, there has been a popular trend among data science aspirants of opting for courses, which give them the benefit of the best of both worlds. Institutes like Imarticus Learning thus become their go-to places for the same.

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