Wrong but useful. Working @Twitter, tweeting about data science and people management.
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One of our unique strengths as DSes is getting data into a shape where the signal is differentiable from the noise, so maybe we should direct our energy towards creating environments where data is widely accessible and hard to use wrong
That's the promise of self-serve analytics, I suppose. But IMO such initiatives focus too much on making it possible for everyone to be a data scientist, when in actuality they should make data scientists unnecessary in as many situations as possible
And don't get me wrong, data scientists still have tremendous influence in a world like that. You make what you measure, so designing the datasets, metrics, procedures, dashboards, etc. that other teams use gives a DS tremendous influence over where the company puts its focus
Stepping up as owner of these things, really taking responsibility for their quality, reliability and improvement over time--it gives you way more leverage than a dropping few Insights every quarter, even if the Insights are Actionable®
How is this different on balance from saying that what most companies need is old school business intelligence rather than data science?
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