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Automation plays a huge role in getting real-time Big Data analysis. However, automation is often related with job cut rumours. Sunil Jose, Managing Director, Teradata India clarifies that automation in Big Data is for good and there is clearly an increasing demand of data scientists. Read the detailed interview with TechGig.com here…

What are the challenges in getting real-time data analytics and putting it to use in real business case scenario?

As an organisation, it is our job to help companies drive their data strategy.  Data is in pockets and silos. It is probably all over the enterprise. Nine out of 10 times, people who own the data don’t know where it is. People need to have a strategic outlook on where data is possibly residing. Then it is easy to clean it, impart it a structure and  put it in a form which makes it easy to analyse data.

Real-time is probably far ahead from the starting point of data analysis. In today’s world, businesses are looking to add value from the data that they have. Traditional data like ERP, CRM and all have been in use for a while now. Today, people have started looking at social analytics whether it’s Facebook, Twitter, WhatsApp, crawlers, mobile apps, et al. These channels are producing a lot of data and people are now looking at combining these data points from different sources and patching them together to make sense. This is exactly where real-time data analytics is really playing a larger role in the organisations.

Does India have enough talent for real time data analysis and related jobs?

It is less to do with people and more about the organisations who want to delve into this realm. There are enough data scientists in India and more being produced within the country.  Organisations have started looking at tools and technology to marry with the data scientists. Do large organisations deploy many data scientists?  The answer is both  yes and no.  You have new age organisations doing it in-house. You have traditional organisations outsourcing it.

What should a CXO or a CIO keep in mind while framing his organisation’s data strategy?

There are two things to be considered. First, he should see the short term and long term aspects of his business. He has to think of both these scenarios hand in hand.  Sometimes organisations jump into a situation where they lookfor quick wins out of a particular data, for which they buy tools and technology and employ people for it but three or six months later they realise that the value coming  out of it is not up to the mark.

Second, the CIO or the CXO has to look at where his organisation wants to be in the digital arena.  They have to evaluate whether they want to be a digital immigrant or a digital native. Today the consumer age group they are servicing is probably 40 to 60, but going forwardthey may be servicing an age group between 20 to 40 years. Servicing these people would need a very different thinking. Hence the data strategy has to be relevant for both present and future customers.

How do you see Big Data evolving in 2016?

We will witness the ability of technology to look at all available data streams and take decisions on the fly. A lot of work is happening in this sphere and customers are now starting to see the importance of real time analytics. We will see a lot of automation coming in.

Big Data is getting automated, does that mean job cuts?

No.  Automation has nothing got to do with job cuts.  The idea of automation is more to do with faster decision making and real-time analysis. Automation leads to better accuracy in predicting the trends.

This article was originally published on www.gizmodo.com and can be viewed in full

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