Data: It takes a village, but the buck has to stop somewhere

I’ve said many times: too often, an existing function implicitly assumes data responsibilities in organizations that struggle with data management (for example, in this post here). Usually, this is either the technology function or the analytics function, which only reluctantly takes it on. I mean “organization” rather loosely. At the fundamental level, this applies even to the entire information services profession; the idea is still the same. Also, as usual, I mean “analytics” broadly to include applied statistics, data science, business intelligence, machine learning, AI, business analytics, etc. So, exactly how does this misalignment of responsibilities happen? Scenario 1: The…...