Data Modeling

Coverage

Design logical and physical data structures from a validated conceptual model. Covers entities as stored records, identifiers, primary keys, foreign keys, uniqueness, cardinality enforcement, normalization, denormalization, derived data, materialized views, provenance, retention, indexing implications, and schema-change risk.

Philosophy

Data models are long-lived promises. Application code changes quickly; stored data and integrations remember mistakes. A good data model preserves business meaning, supports expected queries, and prevents invalid states without overfitting to today's UI.

Do not jump from concept to migration. First decide what must be stored, what can be derived, what must be constrained, and what must remain queryable.

Method