Data Modeling Overview

Information Modelers, Data Modelers and Architects are responsible for creating models of an organization’s information that span multiple levels of abstraction, from conceptual through to logical and physical. The conceptual models are technology independent and can be used for discussions with business people and domain experts, allowing the basic concepts in the domain to be represented, discussed and agreed upon. The logical model elaborates the conceptual model, adding more detail and precision but is still typically technology neutral, allowing Information Analysts to discuss and agree on logical structures. The physical model applies technology specific data to the models and allows engineers to discuss and agree on technology decisions in preparation for generation to a target environment, such as a database management system.

Enterprise Architect provides a number of features to assist in this process, including the ability to develop conceptual, logical and physical models and to be able to trace the underlying concepts between the models. The physical models can be developed for a wide range of database systems, and forward and reverse engineering allows these models to be synchronized with live databases.

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.

Entity Relationship Diagrams (ERDs) Conceptual Data Model

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 Entity-Relationship or 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.

Entity-relationship modeling is an abstract and conceptual database modeling method, used to produce a schema or semantic data model of, for example, a relational database and its requirements, visualized in Entity-Relationship Diagrams (ERDs).

ERDs assist you in building conceptual data models through to generating Data Definition Language (DDL) for the target DBMS.

A Logical model can be transformed to a Physical data model using a DDL Transformation.

Entity Relationship Diagrams (ERDs) Logical Data Model DDL Transformation

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 columns, keys, constraints, indexes, triggers, referential integrity and other relational database features.

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

Physical Data Model Database Engineering