Adoption of Big Data Is Becoming Mainstream
Added 25th Nov 2011Ninety percent of the enterprise data in the world has been generated in the past two years. To manage this huge volume of data, termed worldwide as Big Data, IBM has invested in InfoSphere BigInsights and InfoSphere Streams, two platforms which are uniquely placed to help clients in data exploration and utilization. Pradeep Nair, director, Software Group, IBM India/ South Asia shares his insights about Big Data as an emerging technology and what it entails.
What is your definition of Big Data?
Information management has been an age old problem among enterprises. In order to understand how you make sense of all the data generated in such large volumes in organizations, the term Big Data contributes to the unstructured data that can be captured, communicated, aggregated, stored, and analyzed.
What are the three stages of implementation of Big Data for CIOs adopting the technology?
We rarely look at it from that point of view. It is impossible to break it down into stages.
It’s about finding the use case; what is the problem we are trying to solve. We don’t need big data for everything. For enterprises which are trying to find their brand reputation, Big Data comes handy.
For example, hospitals which aim at improving better health care via ECG (Electrocardiogram), a million data points are generated for every customer. And when captured, all these parameters can give hospitals a view of increasing their business value and fasten decision making.
What kind of verticals can benefit from Big Data capabilities?
Telecom, banking and healthcare are the three main verticals which can make use of Big Data capabilities. The core of Big Data is to manage the 3 Vs: Volume, velocity and variability. For example, for most of these sectors, brand interaction is online via web.
If you are a stock-broking firm which conducts high velocity exchange trading, all the metrics from different channels such as price of the stock, price of oil, environment variables can be captured by Big Data tools to facilitate ‘in the moment’ analytics.
A call-center can make use of Big Data analytics and improve customer service and respond to queries in real time thereby escalating a call to a supervisor in case the data points captured predict that the customer is unhappy with the level of service.
What is your take on the legal and data policy issues associated with Big Data?
The industry needs to regulate itself. It is not a Big Data problem. It’s an evolving area and many of our laws haven’t dealt with such use cases. So there is a need to develop data governance frameworks with clear guidelines for regulated information management.
How do you see adoption of Big Data in India?
Big Data analytics is at an early adopter stage. It is now what cloud was three years ago. The underlying technology isn’t that unique, but enterprises in India push the envelope for what’s possible. So it is reassuring to see mainstream companies’ investing in Big Data. In short, it is ready for primetime.
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