Analysing Critical AI Errors in Text-to-SQL Systems

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This lecture explores AI-generated SQL queries from a data scientist's perspective, discussing common pitfalls and error patterns. Topics include syntax, function, semantic, and logical errors, as well as aggregation and ordering mistakes. Using real-world examples, attendees will learn to identify unbalanced brackets, misuse of reserved keywords, inconsistent sub-query scopes, and issues in aggregation logic. The presentation underscores the implications for job security, detailing how these...