Elena Malykhina at InformationWeek reports that Federal IT professionals have estimated that the U.S. government agencies can save $500 billion dollars or 14% of their budgets by analyzing big data. However, only 31% of these federal IT managers believe their big data strategies are sufficient to achieve this, and only a quarter of them have launched a big data project. They also predict that they will spend 16% of their annual IT budgets, about $13 billion on big data in five years.
The numbers come from a report sponsored by EMC, produced by government IT networking group MeriTalk entitled “Smarter Uncle Sam: The Big Data Forecast.”
Among the findings 51% of those surveyed said big data could enable agencies to improve processes and efficiency, 44% said it would enhance security, and 31% said it could predict trends. 70% believed that in five years successfully leveraging big data would be critical to accomplishing their objectives, and 69% said big data would make the government work better.
NASA chief technology officer Dr. Sasi Pillay, said the agency stores vast amounts of climate and weather data at the Center for Climate Simulation, which provides supercomputing resources to NASA scientists and engineers. Big data would allow them to reduce the number of tests and rely instead on more computational modeling. “It’s a way for the agency to save time and billions of dollars. NASA is in the business of collecting information and looking at how we can make it useful. We engage citizen scientists to share that data through Data.gov. We’re working on making it available in digital formats,” she said.
54% of the survey respondents said big data analytics is expected to improve military/intelligence, surveillance and reconnaissance, 48% said it would help to combat waster, fraud and abuse, and 27% said it would improve the management of the transportation infrastructure. Currently, 26% of government data has been tagged and 23% has been analyzed, according to the survey, and respondents believe the government should double its data management, aiming for objectives of 46% for tagged data and 45% for analyzed data.
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