How to Be Successful in the Age of Data Science?

It has been half a decade since Harvard Business review had pointed towards the emerging skill shortage in data science; and three years since the same organization proclaimed data scientist to be the “sexiest job” on earth. All these theories were supported by numbers and facts. To the surprise of the whole world, the market has not yet found a remedy for the shortage. Can we attribute this failure completely to lack of awareness among the young generation? I do not think that is the fact. The problem with data science is that it shows results only if used skilfully. While there are a large number of institutes that are providing training for upcoming data scientists, the effort is falling short somehow. The data science is business is anything but simple and it takes one a great deal of perseverance to succeed in this world.

LinkedIn has recently released its list of top skills and statistical analysis, data mining and data presentation hold positions among the top ten. All these skills fall under the banner of data science. It should tell you enough about the current importance of data science skills in the global job scenario. The term data science has found existence through the merger of statistics and computer science. Both these subjects carry some considerable weight, hence the reputation of data science of being one of the hardest subjects to master. Enough with the intimidation! Let us move towards the solutions.

First thing’s SAS

If you have noticed the top data science skills – statistical analysis and data mining – they point all fingers towards SAS (Statistical Analysis System). SAS has been the pioneer and the most reliable software suit in these disciplines. SAS had enjoyed monopoly for several years until the arrival of R and Python as potent, open source competitors. It is true that the growth curve of SAS would have been steeper without the presence of Python and R. Never the less  SAS skills still have an astounding demand around the world. SAS online training should be your first step towards the world of data science. SAS training is readily available in both online and offline mediums. It is not too hard to learn the basics; you can take your time to learn all the intricacies of this widely functional piece of technology. What matters the most is the fact that being a certified SAS operator opens up the cream of the jobs for you while developing a steady foundation to work on and build a career.

Don’t worry, there are too many empty seats

I have already written about the ever widening skill gap in data science. In the USA alone, a shortage of 200,000 data scientists by 2020 is predicted. Although the demand in data science is not so much in India mostly because the market is not yet prepared to invest heavily on advanced analytics, it is just a matter of time. The global demand for data scientists grew by 57% between 2014 and 2015 while the searches for the same increased by 73%. The trend is pretty clear. Apart from the problem of shortage of certified data science personnel there is also a matter of efficiency. It is a great investment for a company to hire a data science expert and to try and run advanced analytics. They can only retain someone who shows results. A lot of data science ventures are going astray because of the lack of results. This problem leads us to the next point –

Consider choosing a course as a job itself

Nothing can help you survive unless you have great preparation. Experience counts for a lot but in order to make it count, first you need training. This is why choosing the right institute and the suitable course demands great importance. Before investing your time and money on a certain course, make sure the curriculum satisfies your needs. The material needs to be well targeted and in line with the contemporary industry scenario.

Let us summarize the whole thing in a few points –

  • Start with SAS online training
  • Use every opportunity to learn new technologies and tools
  • Take your time to choose the suitable courses

Data Science demands a multidisciplinary skill set. You should be able to merge  applied mathematics and statistics with computer science to find answers to the questions that you yourself have found.  Data science clearly belongs to the upper order of data oriented jobs – no wonder it would be demanding, and have no doubts that your efforts will be rewarded.

2 thoughts on “How to Be Successful in the Age of Data Science?

  1. Earlier, when it was very difficult to handle large datasheets using a single data base, Hadoop erased this problem. Now massive storage can be done putting the data in the Hadoop software and form a common source from where limitless jobs can be handled at the same time.

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