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An entity does not stop being a data model, because an entity and a data model are different things. An entity is something being described; a data model is the organized description of data, including the entities, their properties, and how they relate. An entity is part of a model once its intended type and relevant structure are specified—not after some universal lifecycle milestone.
Entity vs. data model: the basic distinction
The European Commission’s data-model glossary describes a data model as an abstract organization of data elements that standardizes how they relate. It defines an entity as a thing about which information may be held—such as a vessel, location, sensor, incident, event, or observation.
In short: the entity is what the model describes; the data model is the organized description. A customer can be an entity; a model can describe customer properties and how customers relate to orders. Calling the customer itself “the data model” confuses the subject with its representation.
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These related terms refer to different levels of a model. Microsoft’s Entity Data Model (EDM) concepts describe entity types, properties, and associations as central concepts. OData uses entity sets for named collections of instances.
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| Term | What it means | Customer example |
|---|---|---|
| Entity type | A template describing a class of things with shared structure. | Customer, with defined properties and possibly relationships. |
| Entity instance | One specific occurrence of an entity type. | A particular customer. In EDM, its key identifies it within an entity set. |
| Entity set | A named collection of entity instances; in OData, it can also be an entry point into the service model. | Customers, a collection of customer instances. |
| Data model | The broader organized representation of data concepts and their relationships. | A model describing customers, orders, their properties, and how they connect. |
The OData data-model overview explains how the model describes a service’s data; its metadata document communicates that model to clients. A collection, type, or individual record is therefore not interchangeable with the complete model.
When is an entity part of a data model?
A candidate noun such as “customer” is not, by itself, a complete model. It becomes represented in a model when the structure needed for the model’s purpose is made explicit. Depending on that purpose, this can include:
- Which entity type the concept represents.
- Which attributes or properties describe it.
- How it relates to other modeled concepts.
- Where relevant, how instances are identified and what constraints apply.
There is no universal minimum number of properties, required diagram, or deployment milestone that makes this happen. A model can be conceptual and independent of storage, describe an API, or be mapped into database structures. In EDM, the conceptual representation of entities and relationships is distinct from their stored form.
How to classify common examples
- “Customer” as a business concept: Usually an entity type, or a candidate entity type—not the data model.
- One customer record: An entity instance. In EDM, it has a key that identifies it within its entity set.
- A Customer type with properties and an Orders relationship: A structured part of a data model.
- A Customers collection: An entity set in OData/EDM terminology, not the type or the whole model.
- A database table: An implementation representation that may realize part of a model; it is not necessarily the whole conceptual model.
- A code class named
CustomerEntity: The name alone does not establish its role. It could be a persistence class, domain object, API object, or framework-specific representation. Identify the layer and purpose before classifying it.
How a data model differs from a schema
“Schema” often refers to an implementation-facing definition of database structures. ISO/IEC 19763-12 terminology describes a schema as a persistent, named collection of descriptors for database objects. A data model is the broader organized representation; an entity is a thing or instance represented within it. These terms can overlap in particular technologies, but they are not exact synonyms by default.
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This distinction matters when moving from business understanding to an API or database. A conceptual model may express domain concepts for stakeholders; a service model describes what an API exposes; a database schema defines structures for storage. They can be related without being identical, and an entity does not have to map one-to-one to a database table.
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