An industry that is not data-driven is one that does not exist. But what do we really mean by data-driven? It means basing every business and operational decision on insights found from data. This is a harder and more complicated process than it sounds then again it already sounds a bit complicated. What we are talking about is data science. If data is the crude oil then data science is the very refinery that makes fuel out of it. This statement demands a suitable instance.
Data science in practice
Suppose A is a logistics firm. They dispatch and receive tons of cargo on a daily basis and work on a very tight schedule. Any delays due to vehicular breakdown lead to a significant loss of money. A vehicle is checked and all the parameters are noted before the journey. However, there are instances of breakdown due to various reasons. And the firm is worried.
Data science can arrive as the hero in this story. A data science professional can process the data regarding the vehicle’s condition as well as the breakdown information. Correlate the both and build a predictive model. This model will correlate certain vehicular conditions with probable breakdown, thus reducing the risk of a breakdown. And the management of A knows the value of data science and they want to hire a team of data science professionals to improve their business.
Its application in industries like healthcare, IT, entertainment, retail, manufacturing, digital-commerce, and artificial intelligence is indispensable in one word.
A multidisciplinary field
Now that we know that it is important we must also know that it is difficult. Like every exciting job being a data, scientist has its difficulties coupled with its excitement. It demands expertise in fields like mathematics, statistics, analytics tools, computer science, and programming languages. Mastery of one and working proficiency in a few others is what you should look for.
Though data science is truly a multidisciplinary field, it is foolhardy to try and master all the skills at the very beginning. It does not work like that. There are data science teams the members of which are usually experts in different disciplines. The collaborative effort is what creates the best results.
How to get in?
Train, practice, experience, fail, rectify, repeat: This will be your cycle of work as a data science professional. If it already excites you, then you should enroll for the first step. There are a lot of institutes that are teaching data science as a course in India. You can, of course, opt to take a university course on data science. But that will probably not train you for the industry. Professional training can be gotten from the many analytics institutes around the country. You can even opt for data science online course. The online courses come handy in all respects and one can opt to learn with it according to one’s own convenience of time. Hence, depending on one’s background and aim, the right set of courses can work wonders for one’s career.
The field of data science has expanded smoothly in the last few years. It is hard to find an industry that does not get helped by data science. However, there is a serious skill gap in this domain. It is high time, therefore, that talented candidates come forward and build great careers in data science.
