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Data Models

Data Modelers and Information Architects are challenged with creating data models that span multiple levels of abstraction - from concept to physical implementation. They might also be responsible for maintaining traceability between these models. Enterprise Architect helps to meet these challenges with easy-to-use tools for building and maintaining all of the fundamental data models: Conceptual, Logical and Physical data models.




See also

Conceptual Data Models

Conceptual data models, also called Domain models, establish the basic concepts and semantics of a given domain and help to communicate these to a wide audience of stakeholders

Conceptual models also serve as a common vocabulary during the analysis stages of a project; they can be created in Enterprise Architect using Entity-Relationship or UML Class models


Logical Data Models

Logical data models add further detail to conceptual model elements and refine the structure of the domain; they can be defined using UML Class models

One benefit of a Logical data model is that it provides a foundation on which to base the Physical model and subsequent database implementation


Physical Data Models

Physical data models in Enterprise Architect help you visualize your database structure and automatically derive the corresponding database schema; you use Enterprise Architect's UML Profile for Data Modeling specifically for this purpose

The profile provides useful extensions of the UML standard that map database concepts of tables and relationships onto the UML concepts of Classes and Associations; you can also model database keys, triggers, constraints, referential integrity and other relational database features

Because Enterprise Architect lets you visualize each type of data model in the same repository, you can easily manage dependencies between each level of abstraction; this helps you maximize traceability and verify completeness of system implementation


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