Wrong but useful. Working @Twitter, tweeting about data science and people management.
"Wait, it's all her views?" 
"Always has been"
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This might feel like giving in, but it's actually making you part of the existing knowledge creation process. If you do your job well, more people will understand where you're coming from and what you do, and you'll be able to play a bigger role in knowledge creation over time
If you must deliver Insights, treat them like modular pieces of context that can be plugged into your company's shared understanding of how things work. Treat them like tools for figuring out what's going on and what to do next.
Tools may fall out of favor or become obsolete, but they've still got more longevity than a science fair trifold
i think about this as DS teams needing understand how stakeholders make decisions (what tools, processes, and data) and use "Insights" to build data products that are core to decision-making process (i.e. metrics on dashboards or literal recommendations on how to act next).
I completely agree! Knowing how decisions are made makes it a lot easier to plug into those processes in the right way
Would be awesome to hear what you’d consider to be a best-in-class example of this
Sure. Cohorting users (or whatever your unit of analysis is) is a pretty classic example. Good segmentation turns one ill-defined problem into several smaller more tractable problems, and it gives you a basis for asking deeper questions.
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