Saw a Reddit thread of people complaining about running hypothesis tests right in SQL. Which made wonder who on this green earth decided this was the way to go, and wonder if this is actually prevalent. In your experience, is it? I worked at one of the world's largest RDBMS vendors, and even then my team never once felt the need to do this.

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As long as they are just basic hypothesis testing and exploring data, its probably fine provided that they know what they are doing. Most databases have the tools necessary to do this. If they are trying to train a model, I agree that that would not make sense. Some databases such as Redshift can create functions to call models trained in Sagemaker, which can simplify testing for bias against features that weren’t included in the original training data.

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Google has been adding this functionality to Bigquery. Like you can straight up train a model and store parameters/results in a table, all using their SQL syntax. I guess their thinking is that it’s still SQL so it’s more approachable for the analyst type level, but I agree I don’t think it’s a great idea.

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What in gods green earth…..

Dear God why would they do this

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