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SAS versus R

There is a big argument going on the pros and cons of SAS and R technologies for statistical computing now-a-days. Entrepreneurs are in search of the right answer to find which one is more cost effective for statistical modeling. They want to know, “Will R be able to replace SAS in near future or not?” Here is a brief contrast between SAS and R which will help you to understand the importance and worth of these two software languages.

SAS or Statistical Analysis System is an integrated system of business analytics software utilities. It encompasses various modules which aid large scale organizations and corporations in managing their sophisticated data effectively to take important organizational decisions. Driven by advanced algorithms, the software works on systematic procedure of performing operations on user data saved in the form of tables. Whereas R is a language and environment employed in statistical computing and graphics. The methodology permits its users to add multiple additional functionalities. This is done by defining new functions which are called packages. R already contains user-contributed packages, called statistical routines. They are publicly shared works installed under the rules set by Free Software Foundation's GNU project.

There is no discrepancy related to data set size limitation with any of these software. In both of them, the size of data sets are limited only by the physical machine. But the differentiation between these two is highlighted by the way they handle the data.

In SAS the size of analyzed data sets are compressed by the size of hard disk. On the other side, in R, this analyzed data set size is decided as per the size of RAM. With technological developments, we see that 64-bit operating systems have come up to support more RAM. So, the concluding difference it makes is that R can be customized to carry any size data set as compared to SAS.

Another advantage with R is that it is an open-source whereas SAS is copyrighted and closed. It is designed in a unique way that one can dig entirely into the source code, giving an additional advantage to the user to know what steps have been taken by R. It will help to know whether the analysis is useful for you or not. On the other hand, you cannot access the codes with SAS as it is copyrighted software.

There is buzz that R is just for academics whereas SAS is for the corporates but if you go with the Data Analytics Outsourcing surveys, you will find that it is a false data or information. At present for their day to day operations, some of the top-notch companies like Google, Facebook, and Pfizer opt for R over SAS. Besides that, there are some other renowned firms which are in the process of Switching from SAS to R.

Both of the software are designated for use in statistical computing, but due to the search for cost effective solution, mass has been led towards R. Moreover, because of the burgeoning emphasis on statistical computing plus its additional features, R is gaining an upper hand on SAS. If we glance over on the latest user survey, it reveals that almost 50% of SAS users have switched away from SAS, and more than 33% are heading towards R.

So, definitely R will be able to replace SAS in near future, or we should deduce it has already taken its place.


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