Mastering Data Management

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Watch the webinar replay and learn why connecting the dots isn't what it used to be

I'm in the process of refinancing my home mortgage. Yesterday, the loan processor sent me a note asking why I hadn't disclosed information about property I own in Utah. The thing is, I don't own property in Utah. My father, A. Eric Eastman, does. It seems that his information was incorrectly linked.

Being the victim of inaccurate matching during a mortgage refinancing is amusing, if not frustrating. Being the victim of inaccurate matching in a national security setting could be dangerous.

Earlier this year, CBS News told the story of Mikey Hicks, an eight-year old Cub Scout who repeatedly gets stopped for secondary screening at airports because his name looks like that of someone on a watchlist. On the other hand, people with terrorist intentions sometimes get through security and are allowed to board planes.

Accuracy in entity resolution means the ability to find true matches (avoid false negatives) without making false matches (false positives). We spoke about this recently on a webinar, Connecting the Dots Isn't What it Used to Be. We also discussed how the definition of "accuracy" and "good enough" has evolved as the Intelligence Community faces new challenges.

With the proliferation of data, deterioration of data quality, and deliberate masking of identities by criminals, sophisticated and accurate entity resolution is more important than ever. Watch the webinar replay to learn more.

This webinar inspired quite a few great questions from the audience, which I answered along with my colleague, Jeff Huth. Questions included:

How long does it take for the self-learning algorithm to become valuable?

When we had the 5 people at the same address, is it explicitly stated that they are co-habiting simultaneously or might they have been sequential occupants?

We invite you to listen and ask any additional questions in the comments below.