Students must combine other skills with big data: Dean Ramayya Krishnan, Carnegie Mellon University

Big data scientists are in great demand. To get business value from big data, companies are looking for multi-skilled experts who understand programming, large-scale mathematics, statistics and business, and universities are introducing specialised programmes to meet this demand.

Dean Ramayya Krishnan of Carnegie Mellon University, is the professor of Management Science and Information System. He spoke to Varuni Khosla on the new role of data scientists in both public and private sectors to understand policy, information sciences, and how the two intersect in order to create-forward thinking organisations. Edited excerpts:

What is the volume of big data being produced?

It’s not just the volume of data that has gone up but also the variety, like video, sounds and so on. Something as simple as using maps on phones generates a stream of data.

What kind of industries need to study big data?

Consulting companies like the Big Four and the poster children for big data — companies like Google, Amazon etc. But you don’t have to be a Google or an Amazon to find value in big data. Sectors like finance and governance require evidence-based decision making.

Do students need to specialise in this field?

Students studying big data can choose whether they want to be in technology creation or technology implementation. The global demand for these students is quite high and going forward it will be a horizontal skill.

Students who are just data scientists won’t be the only requirement; they will need to combine it with marketing, human resources or operations skills.

At our college for instance, we offer courses in technology innovations. So you could do a masters in data science or data research — and we include both decision as well as data analytics. Decision analytics is equally important.

This area has a lot of global interest and the supply of scientists is less than demand. Masters’ students who have studied data analytics have a median salary (with an engineering degree before they came to us and two years of work experience) of $1,10,000 per annum.

What is the background requirement to study big data?

Amajority of students getting into this field hold a masters degree in some field with a background in quantitative engineering because it needs strength in math, problem solving and information technology to be able to do these jobs.