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What is SAS?

The full form of the acronym SAS is Statistical Analysis System, and it is a software suite developed by the SAS Institute. The software is applied to advanced analytics, business intelligence and data management, besides a host of other tasks. It is used by data scientists to seamlessly mine, retrieve, manage, and alter data from numerous and varied sources to carry out statistical analysis for insight on making strategic and operational business decisions.

The capabilities that the SAS software brings to the analytics arena make it an indispensible component of data science. The financial industry recognizes the importance of SAS and banks heavily on its ability to generate accurate and complex analytics while handling extremely large data quantities. Many consider SAS to be the backbone of the Big Data initiatives in their companies.

4 Big Benefits of Using SAS

Google and eBay were among the first companies to apply Big Data analytics and showcased its positive results. SAS is a tool that enables Big Data to be analysed accurately and quickly. There are a lot of benefits that it enables, but the 4 big ones are:

  • Promotes the use of Big Data: Till SAS showed the way, organizations had no idea what to do with the huge amount of data they collated. Now they have a way to use that data and more companies are becoming proponents of Big Data analytics.
  • Reduce Cost: The analysis provides companies with insight to improve productivity and efficiencies that lead to reduction in cost and improves profitability to the company and price benefits for the customer.
  • Enhances Decision-making: Using SAS enables companies to make faster and better decisions because the inputs they receive are comprehensive and allows for better strategies to be devised.
  • Align with Customer Expectations: Analyzing customer data always gives a company an in-depth view into the customer’s needs and desires. This makes it easier for companies to develop products and services that are specifically aligned to customer expectations.

Reasons to be trained on SAS

SAS is like the backbone of Big Data analytics going forward. Having SAS skills is in demand in all kinds of industries. This requirement will only grow. As a SAS expert, here are my top 6 reasons for you to learn SAS:

  1. Jobs: Like I just mentioned, there is no dearth of opportunities for SAS skilled programmers, and the salaries are also good.
  2. Reading Data: Data files created with various statistical packages, such as Minitab, Stata, Excel, Systat and more can be read by SAS and converted to SAS format for seamless analysis and delivery of results.
  3. Data Formats: Formats of data for softwares like DB2 and Oracle are also useful and can be applied in transferring data to a SAS format for analysis.
  4. Analysis: It is extremely versatile and flexible for inferential, descriptive and forecasting requirements from statistical analyses.
  5. Network: There is a global community of SAS users that are available for sharing and assistance with their in-depth knowledge of SAS.
  6. Open & Scalable: SAS solutions are built on an open and scalable architecture that allows for seamless platform and process integration.

Who should train on SAS?

Getting trained on SAS is not specific to any one as there are no prerequisites for learning SAS. Though it is a statistical analysis tool it does not require any previous knowledge or experience in statistics.

However, the following can be the key contenders for learning SAS:

  • Software professionals with an interest in analytics
  • Data Science experts that desire to understand exploiting analytics with SAS
  • Professionals wanting to incorporate analytics in business
  • Newbies wanting to build a career in data science and analytics

The demand for analytical talent is very high and you can take advantage of it by getting trained in SAS. Become an expert who can not just talk about data science, but can actually do it.

[rating itemreviewed=”Data Science with SAS Certification Information” rating=”7.9″ reviewer=”ProQuotient” dtreviewed=”2016-11-24″ best=”10″ worst=”0″][/rating]