Best Practices in Management of Data Science/Analysis

Just a quick question: what are the best practices in managing data science/analysis? I'm especially interested in different industries.

Who approves? What questions are asked? What documents should be kept?

For context, most of my exposure to DS has been in banking, where there are standard governance requirements (White papers, official approvers, related decisioning, etc). Obviously, this doesn't make sense for every area, but... in a domain where it's easy for practitioners to fool themselves with their statistical practices(p-hacking, etc), …

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