Logical Data Model
A conceptual representation of data structures, relationships, and business rules independent of physical storage details.
Logical Data Model is a structured blueprint that defines data elements, entities, and the logical relationships between them. It translates complex conceptual business processes into structured database designs without committing to specific database technologies or physical configurations.
How it Works
A logical data model maps out structural entities using standardized relational methodologies. It defines primary and foreign keys, attribute data types, and cardinality relationships, providing a clean abstraction that engineers use to structure physical storage.
- Entity-Relationship Definitions: Diagrams tables and the logical links between them, such as one-to-many or many-to-many mappings.
- Technology Abstraction: Omits physical details like file partitioning, indexing strategies, or directory structures to focus on logical consistency.
Lakehouse & Agentic Relevance
Within a data lakehouse, the logical data model serves as the structural foundation of the semantic layer, mapping how raw parquet files correlate to logical business concepts. AI agents rely on logical data models to navigate database schemas during text-to-SQL generation. Providing the logical model as context allows agents to understand table relationships and write correct joins. Dremio supports logical modeling by allowing architects to build nested virtual datasets that represent logical entities without duplicating physical data.