The document discusses rules for data normalization and practical considerations when applying them to real-world databases. It acknowledges that perfectly normalized models are not always possible or desirable due to performance needs, incomplete information, and complex business rules. Instead, pragmatic solutions like de-normalization, manual processes, and flags/text fields are sometimes needed to balance theoretical ideals with practical constraints.

1. Crack-Smoking Data Models Data Models Theory Meets Reality