SAS is one of the computer programming languages that is extensively used for statistical analysis. The language originated in the North Carolina State University in United States. It has the ability to read data from all types of databases as well as spreadsheets and to provide output and results based on statistical analysis. Results are displayed in the form of tables, graphs as well as RTF, HTML or as PDF documents.
Basic Advantages of Using SAS Language in Data Science
1. It is Easy to Learn: SAS is not only easy to learn, but it also offers easy options for people having the knowledge of SQL. The programming language comes with a stable Graphic User Interface. Learners can benefit from the tutorials available on the website of various universities and can also have certification from the SAStraining institutes.
2. Excellent Data Handling: SAS has an excellent capability for data handling. It can compute everything that is stored in the RAM and can also carry out parallel computation easily.
3. Functional Graphical Capabilities: SAS has substantial functional graphical capabilities. With a little application of mind, designers are also able to customize the functionalities. Understanding the intricacies of Graph package offered by SAS is also not very difficult with tutorials available in plenty.
4. SAS Offers Advancement in Tools: SAS has all the tools and functions for data processing based on latest technologies. It also updates its functionalities as and when the new versions roll out. Development of new techniques is also fast because it is used in most academies.
5. Global Leader in Job Market: Due to its extensive use, SAS is still the leader in the global corporate job market. Most leading commercial enterprises work on SAS. This is because SAS supports end to end infrastructure like visual analytics, data quality, data warehouse, and reporting and analytics.
With numerous other advantages, SAS is a widely preferred language for data science.