Big Data Could Save Feds $500 Billion

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Forget sequestration. According to a recent poll of 150 federal IT executives, federal agencies could potentially save almost six times as much — or nearly $500 billion — by tapping into big data technologies.

Such savings would amount to 14 percent of agency budgets across the federal government on an annual basis. But while almost one out of four of the executives surveyed report that they are already involved in at least one big data project, less than one-third of them believe that their agencies have a strategy in place to deliver on big data’s full potential.

The findings come from a survey conducted by MeriTalk, a Web-based community and resource center for government IT, and sponsored by EMC Corp. The results are summarized in an infographic developed by MeriTalk to popularize the outcomes.

Those surveyed expect the federal government to spend 16 percent of its annual IT budget, or nearly $13 billion, on big data projects over the next five years, and these will become critical to fulfilling agency objectives, according to 70 percent of the respondents. Those goals include improving processes and efficiencies, enhancing security and predicting trends.

For federal agencies to succeed with big data, "The big component will be getting their hands around metadata and properly tagging it," said Rich Campbell, federal chief technologist at EMC, during a webinar held in conjunction with the release of the findings.

According to the survey, currently 26 percent of government data has been tagged and 23 percent has been analyzed, but the respondents believe their agencies should redouble their data management efforts, aiming for 46 percent for tagged data and 45 percent for analyzed data.

The federal initiatives that are expected to benefit the most from big data analysis include military operations and intelligence, surveillance and reconnaissance missions; combating fraud, waste and abuse; and managing the transportation infrastructure.

"It varies agency by agency," Campbell observed, but "the time frame for big data projects is six to nine months for most agencies, and 18 to 36 months for larger projects."

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