Imperfect data leads to imperfect analysis

I’m a big believer in looking at data even when it’s imperfect to see if you can gain insights as some data is better than nothing, but it’s important to be realistic and think of it as an indicator to test rather than a TRUTH to build on. I thought this article did a good job of pointing out several potential flaws that I’ve seen occur in my career. http://www.newyorker.com/tech/elements/how-to-call-bullshit-on-big-data-a-practical-guide

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