Evolution of Data Science

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Some may argue that Data Science is a fairly new concept. Of course, the term Data Science is indeed freshly coined, but would it be fair to call the concept a new one? Probably not. Ask people in the industry and that’s what they have to say.

What the experts have to say

Dr. Pulak Ghosh, Advisor, Manipal Prolearn is an expert in the industry with over 10 years of experience in the field. Professor of Decision Sciences and Information Systems at the Indian Institute of Management, Bangalore, Dr. Ghosh explains that several components of data science, as it is called today, have been in existence for decades.

Statisticians have been working on regression analysis for the past several years, the same being for economists and computer science professionals who have years of experience of working on the new-age data science elements. So these professionals have been aware of the present-day data science components since a long time.

If you tell a computer science professional that you have a large amount of data, he/she will explain you how to use it or what to do with it, as per his/her area of knowledge. However, all of them will look at the data with varying objectives. They will use it to answer questions that are relevant to their field of work. This caused the need for an expert to handle the available data in an unbiased manner, ensuring that the data proves helpful to all the parties involved.

Another factor to remember is that an analytics group alone cannot solve the problem. It becomes important to have inherent business domain knowledge as well. Say, there is a need to know the income distribution of every village in India. A statistician, economist or a computer science professional will not be able to solve the problem till it is broken down into smaller pieces.

These professionals are trained to work with data in hand. However, they are now being faced with a problem that does not provide them this essential piece of information. A survey will have to be conducted to get the required information to these experts. However, in a country like India, it is difficult to conduct such a survey every year as it will bear a cost of 25-30 thousand crores, which is not feasible.

Bridging the gap

This implies that despite being experts, these professionals are helpless when it comes to bridging this gap. So the job of a data scientist, in this case, is coming up with a hypothesis and breaking this business problem into something that provides insights to the statistician and the economist so they can use it for their research.

The second step involves bringing them all together to work as a team, because the outcome is based on the contributions from each one of them. So data science evolved by combining these interdisciplinary skill sets with the concerned business domain. That’s the premise of data science, in general. So in that sense, it is a new area of work, but if you look at the individual buckets, they have been around for a while now, under different names.