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I guess the usefulness would be from client software like plsql or any other, implement a natural language processing powered by chatgpt, since the client already has access to the structure then it can include it in the prompt, the user would only write something vague like i want all the clients who bought with more than 500$ this year.


For everyday stuff like that it's easier to put the NLP in a BI tool, and some of them already did that.

If you're doing more involved stuff then writing a good prompt will probably need as much analytical and domain knowledge as writing SQL.


This is a great thread! As you might imagine I put in a lot of thought about whether Chat GPT made learning this stuff obsolete. Conclusion I came to is that those tools make this all more accessible (in terms of helping people to avoid things like frustrating single character mistakes) but that kind of makes knowing some SQL MORE valuable because it makes it much easier to know what direction to move in, and helps a person more easily debug confidently incorrect suggestions.

A big problem with SQL is that sometimes the answers can LOOK right if a person doesn't know the pitfalls of, say, table joins, but can in fact be quite off the rails. I also think that there's still space for highly skilled experts doing the REALLY advanced stuff but for the average user - just knowing the basics probably helps them get even more out of LLM helpers




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