logical-data-modeling

To create a normalized logical data model, describe your domain concepts and target normalization level. The model maps business requirements to entities, attributes, and relationships, enforcing 1NF through 3NF with defined primary keys, foreign keys, and constraints.

Generating an ER diagram with referential integrity involves defining relationship cardinalities and cascade rules like CASCADE or SET NULL. The output includes a Mermaid ERD visual and a detailed report documenting referential actions and per-entity normalization verification.

Mapping domain concepts to technology-agnostic database entities requires a logical data model that avoids vendor-specific types. This approach preserves conceptual clarity and serves as a bridge to guide physical database design input across any platform.

You need junction tables for many-to-many relationships in data modeling when mapping complex domain concepts. The logical model resolves M:N relationships via junctions, defining appropriate foreign keys and referential actions to maintain data integrity.

Logical data modeling supports both natural and surrogate keys when defining entity attributes. The model explicitly declares primary keys, foreign keys, and constraints like NOT NULL and UNIQUE, verifying normalization compliance for each entity.

A logical data model report for physical database design includes scope, entities, relationships, and normalization verification. It provides structured documentation of constraints, referential integrity decisions, and a Mermaid ERD to guide physical implementation.