The way we talk about data science and focus so much on methods, we actually incentivize working with *bad* data, rather than spending the time to collect good data and then use easy methods with it
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I want us to have a conference solely focused on how people collect data, and all the politics / product negotiations / etc that go along with that
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One small thing I am doing at Stitch Fix -- for the datasets we use, I'm referencing them as e.g. "the data that Cindy, Ping and Francesca created" rather than "the stylecard data".
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I don’t know how I managed to not see you except for the hour you were on stage!
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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I can already imagine the contortions required when you do a blameless post mortem.
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From a business perspective, there may also be some interesting issues here with how people financially account for the costs of data acquisition that I’ve been learning a bit about lately. How we view the cost can impact how we invest...
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Data quality is 100% my jam. Deciding what to collect and who to trust as an authority are just the tip of the iceberg, and since we can't have perfect data we have to decide what to sacrifice. Timeliness, completeness, accuracy? Such fun challengs.
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Čini se da učitavanje traje već neko vrijeme.
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