Hot take: a reason many data science projects are unsuccessful is that they're not planned in a user-centric way, which results in them not being valuable to the stakeholder they're created forhttps://shopify.engineering/make-dashboards-using-product-thinking-approach …
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Sure, stakeholders don't always make clear requests, but end users rarely do and it's not their job to in the first place. Instead, put your analytic skills to the test and think through what problem they're really trying to solve before prescribing solutions
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They may not appreciate the subtleties of well-executed data science work work, but they'll scramble to get their hands on it if it's useful and they'll absolutely remember it if it made life easier for them
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Relatedly, your future self is likely to be a customer of the work you're doing today. Even when you're designing for someone else, it's worth keeping yourself in mind as an end user in your user-centric data science process!
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