4 ms·
A basic problem with de-indentification of data is useful uniqueness. The sensitive data that needs de-identified tends to be the data that provides the uniquen
by beat 12y ago
A basic problem with de-indentification of data is useful uniqueness. The sensitive data that needs de-identified tends to be the data that provides the uniqueness needed to make the data useful. Sufficiently scrubbed data often doesn't work well for actual testing.
After years in banking and health care, I've seen businesses tilting at that windmill too often. Hire outside consultants to help if you need to do it.
- bcg1 12y agoThe problem that I've noticed is that we DO hire outside consultants... but too often that provides a security blanket for the decision makers, and they think that just because they outsourced the work, that they have nothing to worry about anymore. I think the author's approach is pragmatic. I think more decision makers need to realize that data sets can just as easily be a liability as they can be an asset. I work in healthcare and I see slow motion trainwrecks waiting to happen all around me.