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In your machine learning projects, once a model is deployed, how often do you revisit and adjust the feature engineering process to address issues caused by data drift?What indicators or monitoring strategies help you decide when updates are needed?

I am planning to learn data analytics and i got overwhelmed by all the information at the internet so I am asking here how much statistics do you need and what are those you actually have to master to become a data analyst? Also need some advice or mentorship if any want to help.