Top 8 Reasons to Learn SAS


SAS software has proved itself as the market leader in providing a new generation of business intelligence software and services that creates true enterprise intelligence. The SAS Institute is the world’s largest privately held software company. It is also the only vendor that completely integrates leading data warehousing, analytics and traditional BI applications, to create intelligence from massive amounts of data. Isn’t that impressive!

SAS has a large part to play in the future of analytics and big data. Today everyone in the business world must be aware of the benefits of having SAS skills and understand why these skills are in demand in current and future markets. As someone with SAS expertise, here are my top reasons why you should learn SAS. After you go through them I am sure you will agree with me.


1. You will be impressed if you try to search for “SAS Jobs” online. Your search is sure to turn up many current job listings that require a variety of SAS expertise. Since, SAS emerges as a key research data analysis tool, it is in demand in the market. Every company is looking for SAS resources.



2. The big advantage of learning SAS is that it is a fourth generation language. It is fun learning SAS. It provides GUI and an easy way to access multiple applications. It relies on user-written scripts or “programs” that are processed when requested to know what to do. Because it is a script-based application, the key to being successful using SAS is learning the rules and tricks of writing scripts. It works with large data and generate graphs and report.



3.  SAS can read data files created by other statistical packages. SAS allows data files created by SPSS, Excel, Minitab, Stata, Systat, and others to be incorporated into a SAS program directly or through file conversion software. Thus, to experienced users of these statistical packages, SAS presents no threat at all because it is possible to convert data files created by these packages into a SAS file format.



4. Learning SAS will not make you abandon data formats you previously mastered or managed. These formats include those generated and supported by database software such as Oracle, DB2.



5. SAS is versatile and powerful enough to meet your needs in data analyses. SAS is flexible, with a variety of input and output formats. It has numerous procedures for descriptive, inferential, and forecasting types of statistical analyses. Because the SAS System is an integrated system with similar architecture shared by modules or products, once you master one module, you can easily transfer the knowledge to other modules.



6. There is a worldwide electronic network of SAS users which are easy to access. Free SAS resources are available at your fingertips, and you can easily connect with many SAS experts who deliberately and willingly share their SAS knowledge online.



7. SAS solutions are built on a proven intelligence architecture that is open & scalable, allowing seamless integration of processes & platforms. It relies on user-written scripts or “programs” that are processed when requested to know what to do. Because it is a script-based application, the key to being successful using SAS is learning the rule and tricks of writing scripts. It works with large data and generates graphs and report.


8. SAS keeps itself updated with the latest technology. It can easily be integrated and this enhances its usability and flexibility as it can easily interlink with many technologies.

Do you have any more to add to this list? We would love to hear from you.

If you are convinced that learning SAS is the way to grow you career, take a look at an article by Jigsaw Faculty Neha Shitut titled The Easiest Way to Get Your Foot Into the Analytics Industry- Get Some Language of SAS Training.

Interested in learning about other Analytics and Big Data tools and techniques? Click on our course links and explore more.
Jigsaw’s Data Science with SAS Course – click here.
Jigsaw’s Data Science with R Course – click here.
Jigsaw’s Big Data Course – click here.

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