Individual applications each carry their own schema. An enterprise data model rises above them to define shared entities once, so "customer" or "product" is structured consistently across finance, operations, and analytics.
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It differs from an ontology in emphasis. A data model focuses on how data is structured and stored; an ontology focuses on the meaning and reasoning between concepts. In practice they complement each other, and a strong data model is a natural foundation for a semantic layer above it.