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Except that the plural of anecdotes is definitely not data, because without controlling for confounding variables and sampling biases, you will get garbage.

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Based on my limited understanding of analytics, the data set can be full of biases and anomalies, as long as you find a way to account for them in the analysis, no?

The accuracy of your analysis becomes limited to the accuracy of how well you correct for the biases. And it's difficult to measure the bias accurately without lots of good data or cross-examination.

Garbage data is still data, and data (garbage or not) is still more valuable than a single anecdote. Insights can only be distilled from data, by first applying those controls you mentioned.

Or you can apply the Bezos/Amazon anecdote about anecdotes:

At a managers meeting "user stories" about poor support but all the KPIs looked good from the call center so Jeff dials in the number from the meeting speaker phone, gets put on hold, IVR spin cycle, hold again, etc .... His take away was basically "if the data and anecdotes don't match always default to the customer stories".

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