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7 Ways The U.S. Dept. Of Veterans Affairs Tackled Its Big Data Big Challenges

The U.S.' second-biggest federal agency is undergoing a major data quality initiative to whip its more than 11 petabytes of data into tip-top shape. Here's a glimpse inside that project, and the key lessons learned along the way.

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Big Data, Big Headache?

The U.S. Department of Veterans Affairs (VA) had a big problem with big data.

Just ask Dat Tran, deputy assistant secretary for data governance and analysis at the VA, and the keynote speaker at the Massachusetts Institute of Technology's seventh annual Information Quality Symposium, taking place this week in Cambridge, Mass. As the second-biggest federal agency in the country, the VA has a lot of data -- over 11 petabytes of it, to be exact. But the problem, according to Tran, was the quality of that data. There were repetitive data entries, a lack of interoperability between systems and no "authoritative source" when it came to customer records.

But Tran and his team recently set out to change all that, launching a massive data quality initiative across the VA. Here, according to Tran, are the department's top lessons learned along the way.

 
 

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