Semantic Layers & Enterprise Ontology
A consistent business vocabulary connects analytics, applications, and AI agents to the same trusted enterprise meaning.
Beyond the technology.
One definition, many consumers
A metric such as net revenue should mean the same thing in a dashboard, SQL query, application, or AI answer. Shared definitions reduce reconciliation work.
Connect meaning to reality
The enterprise is a network of customers, products, locations, events, policies, and relationships. Semantic models and ontologies make parts of that context explicit.
Treat meaning as testable
Validate joins, grain, business calculations, access control, and cross-consumer consistency. Trust is built through repeatable checks, not just documentation.
Explore related thinking in my selected essays ↗.
Enterprise AI Architecture ↗
Building trustworthy enterprise AI requires business context, evaluation, governance, and workflows that connect answers to decisions.
Modern Data Architecture ↗
Open and governed data foundations should help organizations adapt to new workloads while improving how people work with data.