**Logical data architecture** is the intermediate level of abstraction within [[Data architecture|data architecture]], defining the structure and relationships of an organization's data in precise, technology-agnostic terms. Situated between the high-level business view of [[Conceptual data architecture|conceptual data architecture]] and the implementation-specific detail of [[Physical data model|physical data architecture]], the logical layer specifies how data entities are composed, how they relate to one another, and what rules govern their integrity — without reference to any particular [[Database management system|database management system]], storage platform, or deployment environment. A logical data architecture typically elaborates the major entities identified at the conceptual level into fully defined structures, specifying [[Attribute (computing)|attributes]], [[Data type|data types]], [[Primary key|primary keys]], [[Foreign key|foreign keys]], and [[Cardinality (data modeling)|cardinalities]]. [[Normalization (database)|Normalization]] is commonly applied at this stage to reduce [[Data redundancy|data redundancy]] and enforce [[Data integrity|data integrity]]. Relationships between entities are expressed through formal [[Entity–relationship model|entity–relationship diagrams]] or equivalent notations, providing a precise blueprint that can be translated into multiple physical implementations across different platforms or systems. The logical layer serves as a stable, platform-independent contract between business requirements and technical implementation. It is central to [[Data governance|data governance]] efforts, providing the authoritative reference for [[Data dictionary|data dictionaries]], [[Business glossary|business glossaries]], and [[Metadata management|metadata]] standards. In enterprise settings, a well-maintained logical data architecture supports [[Data integration|data integration]], [[Master data management|master data management]], and [[Interoperability|interoperability]] across heterogeneous systems by establishing common definitions and structures that transcend any single technology stack.