Social Media and Big Data Analytics
By Matt Sarrel
As the 2012 IBM Institute for Business Value survey indicates, big data analytics is evolving. More and more companies see the power of building big data solutions to better understand and optimize various aspects of the business. Sixty-three percent of survey respondents in 2012 report that the use of information (including big data) and analytics is creating a competitive advantage for their organizations. This represents a seventy percent increase since IBM’s 2010 New Intelligent Enterprise Global Executive Study and Research Collaboration. Executives are becoming more data driven and systems are being built to make recommendations based on data such as current market conditions, supply chain, customer sentiment, and more. Big data analytics is becoming a core component of many enterprise IT departments.
For example, Santam Insurance, South Africa’s largest short-term insurance provider uses predictive analytics to improve fraud detection and speed up claims processing. The company felt that rising fraud was compromising operational efficiency so they built an early fraud detection system that assesses each incoming claim against identified risk factors. The company saves millions by flagging claims that are likely to be fraud and also gained the operational efficiency required to lower average claim processing time dramatically, sometimes to as little as an hour.
The impact of big data analytics programs is being felt far beyond IT departments. As data capture, storage, and retrieval technologies improve, so do a lot of the tools that go with them. Now that programs have expanded to included non-IT staff, there is an understanding of the data available and the insight it holds. Ad-hoc query tools make it easy for business managers to ask (and get answers to) questions about their line of business using a GUI dashboard.
There is a plethora of social data available for inclusion in big data analytics. Monitoring social networks and the user supplied content within has proven invaluable to those who understand it and do it right. However, according to the IBM survey, only 43% of participants are actively including social media data in their formal big data programs. This represents a huge opportunity for the big data analyst with an understanding of social networking data structures (or non-structures) and APIs.
What are you doing to include social media data into your big data analytics program?
For more insight on how companies are using analytics to shape their futures, join IBM on November 7, 2012 at 1:00 p.m. ET. For a webinar: Analytics: The real-world use of big data / How innovative enterprises extract value from uncertain data.