SAS versus R? And, why you should be clear on this!


If you are already into data science basics, you will be torn between picking and leaning a programming language. 3 out of 5 data analysts would recommend you to learn R programming. The other two could offer advises on Python and SAS course. In this article, we will do a masterful dissection of R versus SAS programming. Data science using SAS may not find many takers initially but it’s certainly worth taking a shot at learning on this platform.

What to do: Data Science Using SAS or R?



Let’s make a clear distinction.

For beginners, R is an open source programming platform that keeps evolving every hour, thanks to the contribution from the community of researchers, programmers, professors and scientists. On the other hand, SAS is a proprietary tool provided by SAS, a leader in Analytics for many years. SAS already employs 12000+ employees who are mostly data scientist and programmers from all spheres of the industry.

Some fast facts on SAS:


  • ·      Number of Countries Installed: SAS has customers in 146 countries.

  • ·      Total Worldwide Customer Sites: SAS software is installed at more than 83,000       business, government and university sites.

  • ·      Fortune Global 500® Customers: 96 of the top 100 companies on the 2017 Fortune  Global 500® are SAS customers.

In its current form, R is extensively used for statistical analysis, graphical representations, and data reporting.

SAS versus R is just a myth. Both work well!

SAS is not just another programming language applied to validate data from the spreadsheets and databases? The output from SAS is projected in the form of statistical analysis in tables and graphs and as RTF, HTML, and PDF docs. SAS certified data analysts are considered at the pinnacle of the data science industry. You can manage Big Data, Visual Data Analytics and Forecasting techniques at the push of a button. On top of it, you will be designing your own customized dashboards for your own Business Analytics teams.

Why R Programming for Data Science?

Compared to R and other programming languages, SAS offers a wide range of benefits to learners and customers. The biggest advantage of learning SAS is its industry-relevance and contemporary analytics that can be learned from the dashboards.

On the other hand, R is an open source programming language which means this is way better at handling Big Data queries in a structured manner compared to SAS!
In data science, it’s the ability of the platform to present data in a visually interactive manner that wins. SAS and R do just that.
Both SAS and R are great at handling graphical capabilities that can be integrated with other visualization and business intelligence tools.
R has a seamless integration to Big Data communities such as Hadoop, it’s the industry application of the open source language that is most preferred here. By learning R with Python applications, Data analysts could have a direct access to most products and services offered from the company’s stable.
These include:


  • ·         Machine learning and AI
  • ·         Customer Intelligence
  • ·         Visual Statistics
  • ·         Advanced Analytics
  • ·         Cloud and Risk management
  • ·         Internet of Things

If you go by industry trends, R is definitely easier to learn, but learning about SAS is also worth the effort. In an online R Course, it will pay off the dividends quicker with the existing cool job roles available in the Data Science industry already.

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