R or SAS? Most Used Tool in Analytics IndustriesJuly 21, 2016
With the boom of the digitalization era and the advent of Big Data, firms and companies started taking notice of the amount of data that was created. It is known that, if one could burn all the data onto CD drives and stack them, the pile would reach the moon twice. Easy access to technology has led to the number of users and thereby, the amount of data generated on a daily basis. As this data cannot be stored in traditional storage systems, there are new systems devised specially for it. What we can infer from this is if one wants to interpret this data, they have to possess a certain set of skills. These people with a specific set of skills are popularly known as Data Scientists.
Data Science is the field, where big data is studied, interpreted and analyzed to draw insights and then take relevant business decisions. There are a lot of professionals in the field of data science, who make use of various tools to help them in data analytics. SAS programming, R Programming, Python, Pig and so on are some of the tools used for data analytics. Interestingly enough, a lot more professionals use SAS programming than R.
The reason is some of the fundamental differences between the two, which will be elaborated in this article.
SAS or Statistical Analysis System is a very old programming software which has been used by almost all the professionals including Data Scientists. It has been on the scene for a much longer time than R programming and is the default software in a lot of firms.
Another fundamental difference is that, R programming is open source software while SAS is licensed software. The major reason for R programming getting a lot of popularity is the fact that it can be downloaded and used free of cost, while SAS programming is considerably expensive.
R programming is primarily coding/programming software, where someone with a background in the field of IT works well. Whereas there have been so many people who have been using the SAS software for everything but statistical use. The SAS programming software is more of a graphical user interface, where the coding part is rarely needed.
Being an open source, R Programming also has its downsides, as it does not have any accountability because; it is out there for everyone to change and use as they go. In addition to that, it is not tested at all as there is no central authority providing this software. With being free, comes no support in fixing of any issues as well, which then leads the user to take help of Google for solving the issues.
Contrary to that, as SAS is licensed it provides high level technical support and comes with great accountability. Although it is expensive, it is very reliable as there are a number of timely upgrades to this software. While R programming is a software that is not tested at the same time, SAS is a thoroughly tested programming language.
Although it may seem that there are stark differences in both the programming language tools, it is evident that R programming is of utmost use in research institutes and for people who want to practice learns it. SAS on the other hand, cannot be used just for learning due to its highly expensive nature.
While it may seem that one of the two programming languages is important and the other is not, it is not the case. For a data scientist, it becomes imperative to have knowledge of how to use every tool there is. One can achieve the same either on their own, or by taking a course on any tool.
Imarticus learning is an institute that offers both short term and long term courses on data analytics, R programming, SAS programming, Python and more.