Hypothesis. Lack of domain expert input is the largest flaw in analytics.

Most analysts don't bother to do basic KD interviews, not to mention incorporating expert knowledge in probabilistic models. This spans everything from heuristics defining sales ops to advanced ML black boxes running $B projects. Worse, this is the standard in exec decisions; financiers pitch and invest, but often can't even explain what a company does beyond the industry it's in.

Your own observations?

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It’s a cultural thing with data scientists (which I am)- they get offended if you suggest the business can help them improve their models; it’s absolutely mind blowing.

There’s this view that if the statistics can’t discern it from the data it’s not worth knowing, even though we work with data sets with hundreds of millions or billions of rows and hundreds or thousands of features where it would be impossible to methodically check more than a tiny fraction of relationships.

#1 problem with the data science industry today.

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This is absolutely true. I specialize in retail and the nonsense that data scientists propose and send me shows a clear lack of understanding of the business and the value of what they focus on

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As a data quality person, I look at things this way - if the business can’t understand it and act on it, it’s bad data.

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