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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Rather than focus on changing the raw data, DSes are better suited to making their data transformations more robust to variation in said raw data. This can be hard to wrap your head around if you think data should always perfectly reflect what happened in your product.
But it's also why it's called data SCIENCE. It's about finding signals in noise. It uses similar tools to SWE, but it's a fundamentally different craft. Being crisp about this distinction saves you the grief of looking like an amateurish engineer
I can’t believe this site is free. Thanks for the pointers!
@threader_app compile
Hello Abhishek, the whole thread from @imightbemary is compiled now. Read it here:https://threader.app/thread/1295045411091038209 …
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