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Building The Modern Data Team
Emily Schario and Taylor Murphy argue that data teams should be run like product teams. This model suggests that if we can think of data as a product that we deliver then the teams that help build this product can think of themselves as a product team.
There’s good advice on being user-centric, being empathetic, practicing effective communication, and perhaps more controversial advice on developing features by focusing on user stories. Pardis Noorzad made a similar argument for a Product Data Science Model, suggesting that the hybrid approach offers better accountability and speed by having the data scientists be embedded within the product teams, but reporting to a central data science management team.
The reality, however, is that even product teams can be highly dysfunctional. While I largely agree about how teams should be organized, there’s still the outstanding question of how to make these teams, however organized, effective.
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