So, while there's a bunch of good points in this article, the biggest point is missed.

Data isn't the problem. The way you misunderstand or misuse data is the problem.

"Don't be data driven" is terrible advice.

That's like telling a child not to walk because they're bad at walking.

Get better at making data-driven decisions. That's what this article really proposes and should conclude to.

Just because you don't have every piece of data doesn't mean the data you have is wrong. It means you, as a data-driven person, should recognize when the data you have is sufficient, or insufficient.

If you do much data analysis at all, you should have been presented with the simple concept of correlation and causation.

A good data scientist will never conclude causation. They will only conclude correlation. Data on its own is not misleading or meaningless - it is simply observation.

Take the observation for what it is. Don't throw it out simply because you don't have the means to see the whole picture.

instead of looking for the answers the data provides, look for the questions it generates.

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