Data modeling is the process of creating a data model by applying formal data model descriptions using data modeling techniques.
Conceptual, logical and physical schemes :
- Conceptual schema: This consists of entity classes, representing kinds of things of significance in the domain, and relationships assertions about associations between pairs of entity classes. A conceptual schema specifies the kinds of facts or propositions that can be expressed using the model.
- Logical schema: This consists of descriptions of tables and columns, object oriented classes, and XML tags, among other things.
- Physical schema: describes the physical means by which data are stored. This is concerned with partitions, CPUs, table spaces, and the like.
Modeling methodologies :
Data models represent information areas of interest. While there are many ways to create data models, But only two modeling methodologies standard top-down and bottom-up are used in real time environment :
- Bottom-up models : are often the result of a reengineering effort. They usually start with existing data structures forms, fields on application screens, or reports. These models are usually physical, application-specific, and incomplete from an enterprise perspective. They may not promote data sharing, especially if they are built without reference to other parts of the organization.
- Top-down logical data models, on the other hand, are created in an abstract way by getting information from people who know the subject area. A system may not implement all the entities in a logical model, but the model serves as a reference point or template.