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Held on 3 March 2022

How Not To Use Your Data Team


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Far too many data science teams I see are labouring in an ivory tower: disconnected from developers and business needs, running at an academic not an urgent pace, and generating results that have huge potential value but are miles away from commercial validation or live release. Whether you have data scientists now or want to hire them, join me and my expert guest to learn how to avoid the most common mistakes in structuring and evaluating your data team, including:

  • keeping product managers "out of the data team's hair"
  • accepting progress reports and incomplete results instead of demoable, live results
  • producing models and schemas without mechanisms for testing, evaluation, and release to production