Get a Strong Footing in Data Science with SAS

It is a well known fact that a large chunk of the technological jobs in India currently lies in the domain of data analytics and data science. A whole lot of the IT crowd is eagerly up-skilling in order to get an entrance into this domain. If you are a fresh graduate and looking for a break you must have already noticed that there is an increasing demand for data oriented skills. You have probably run into some companies that are looking for personnel skilled in analytics. If you are willing to up skill in the domain of data analytics but in need of some direction, this is for you.

This article is designed keeping a fresher in mind, but can help anyone who is starting it off with new technologies. This should help you take the first few steps after which you will be able to map the whole thing out.

Language first

Yes, you got to learn to talk first don’t you? There are specific languages that work best for data science programming. You might have had a great hand at JAVA or C++ but in here you need to understand what the employers are looking for. It often occurs that graduates come to Bangalore for a job and find themselves one language short from the break they wanted. They are forced to get trained in a new technology. Why not start early? So, what is working right now? The answer is easy and anyone will tell you – ‘go for Python, it’s the coolest stuff.’ Well, so it seems and you should listen to it. But don not forget the other two. Of course SAS and R. Yes, you need to learn one more if not both and if it is one than go for SAS.

Reasons you should learn SAS

It is true that SAS is has been out of the buzz for some time and for good reasons. The buzz always carries the new and the surprising. Well, the job market does not really follow the buzz. SAS has been and is a reliable name for hundreds of companies around the world. Each year there are more than two thousand new jobs created solely in the domain of SAS in India. SAS programmers have always been in demand and they still are. The best part is if a company is using SAS and hiring you, they are probably going to pay you real well.

  1. It has been there since 1970s and is relied upon more than any platform for advanced analytics.
  2. SAS professionals are way low in number in respect to the demand.
  3. It is usually a gateway to the corporate houses.
  4. It gets you a better salary.

If that is not reason enough then try some more facts.

  • SAS is used by the biggest players in predictive analysis and data mining. Both of these have places in the list of top ten advanced analytics skills. 43% companies that use predictive analysis use SAS.
  • Here is some deduction for you to do – The two industrial sectors that use the maximum use of advanced analytics are Financial Services and Marketing Services. These two are also the sectors that make maximum use of SAS tools. What does it explain?

The point I wish to make is if you are entering the domain of data science do not skip SAS. It might come handy at any point in your career. SAS online training is pretty easily available and the learning curve is not too hard. The certification exams however test your analytical skills to an elevated level. Once you come out with a SAS certificate employers start to revere your analytical skills. It gives you a kind of acceptability.

SAS is an easily accessible fourth generation language that lets you manage and analyse data created by SPSS, Excel, Minitab and other sources. These features should surely mean something to you if you are analytics savvy.

A skill set combining SAS, Python and R skills can really take you places. If not all three at least two should help you get to a vantage point from where you can actually pick and choose your options when it comes to the jobs.

However you need to be very careful while choosing your course. Whether it is online or off line, do make sure that the curriculum is for you and the faculty is actively involved in the industry. It is important to be industry ready at the end of the training.

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