Big Data is expected to be a market worth $1 billion in India by 2015, growing at a CAGR of 83 per cent since 2012, according to a Nasscom report. At the Techcircle Big Data Forum 2014, eminent panellists discussed how they have monetised, implemented and scaled Big Data.
The panel was moderated by Varsha Tagare, director, Qualcomm Ventures, and saw participation from N Vishwanathan, head Big Data, cloud & legacy transformation, L&T Infotech; Tarun Krishnamurthy, senior director - engineering, McAfee Software India; and Sunil Gupta, president and COO, Netmagic Solutions. Here are some of the forward-looking observations made by the panellists:
N Vishwanathan, head Big Data, cloud & legacy transformation, L&T Infotech
Most large enterprises have multidimensional data coming from multiple sources and they are getting predictions and granular detail on one single screen to make it intuitive for the user to consume. This is valuable as it improves business efficiency. To do this, we need a mix of tools and products as either of these will not solve all the problems. Creating disruptive solutions requires synergies with three kinds of people including domain SME, tech, and data scientists to make it easy for the end user to consume data.
Tarun Krishnamurthy, senior director - engineering, McAfee Software India
We created a startup within our big firm, hired some interns, and told them about business problems, and in the process were able to identify some really easy-to-use tools. Many companies have been engaged in identifying attacks before they occur. But the competition is about who puts out the signature first solution and prevents the attacks.
Sunil Gupta, president and COO, Netmagic Solutions
In last four years, the pattern of data consumption has changed dramatically, moving everything to cloud as opposed to using a service provider's instruments. An enabler for Big Data for our customers is putting the core business & analytics, as well as storage on the cloud. Internet enabled businesses and e-commerce firms in particular are creating a lot of data that can be analysed.
Most of the analytics is happening in real-time or the data is collected throughout the month and then put into an analytic engine to derive some intelligence out of it. In all this, the data pattern is very busty.
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