Enterprise semantics
The shared business meaning behind entities, metrics, relationships, ownership, quality, and context.
Concepts
Business meaning, explained for enterprise teams
Semantics as Code is intentionally not a runtime. It is an authoring and generation specification for portable meaning.
Semantics versus metadata
Metadata describes data assets. Semantics defines what business concepts mean and how they should be interpreted.
Semantics versus a semantic layer
A semantic layer may execute queries. Semantics as Code is a portable authoring specification and generation layer, not a runtime.
Semantics versus ontology
Ontologies formalize concepts and relationships. Semantics as Code can generate graph-ready context while staying approachable in YAML.
Semantics versus glossary
A glossary defines terms. Semantics as Code connects glossary terms to entities, metrics, quality, governance, and platform outputs.
Entities
Canonical business objects such as Customer, Product, Order, Supplier, Store, or Region.
Metrics
Governed calculations with formula, grain, dimensions, filters, owner, steward, and quality context.
Domains
Business ownership boundaries for organizing semantic definitions.
Relationships
Typed connections that explain how semantic objects relate.
Business keys
Stable identifiers used to recognize business objects across systems.
Quality expectations
Business-readable requirements attached to semantic objects.
Governance metadata
Ownership, stewardship, lifecycle, classification, PII, tags, and source metadata.
AI context
Plain-language guidance for retrieval systems, copilots, and AI agents.
Knowledge graph mappings
Graph-oriented representations generated from semantic objects and relationships.