data model

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data model

The product of the database design process which aims to identify and organize the required data logically and physically.

A data model says what information is to be contained in a database, how the information will be used, and how the items in the database will be related to each other.

For example, a data model might specify that a customer is represented by a customer name and credit card number and a product as a product code and price, and that there is a one-to-many relation between a customer and a product.

It can be difficult to change a database layout once code has been written and data inserted. A well thought-out data model reduces the need for such changes. Data modelling enhances application maintainability and future systems may re-use parts of existing models, which should lower development costs.

A data modelling language is a mathematical formalism with a notation for describing data structures and a set of operations used to manipulate and validate that data.

One of the most widely used methods for developing data models is the entity-relationship model. The relational model is the most widely used type of data model. Another example is NIAM.

["Principles of Database and Knowledge-Base Systems", J.D. Ullman, Volume I, Computer Science Press, 1988, p. 32].

data model

A description of the organization of a database. It is often created as an entity relationship diagram. Today's modeling tools allow the attributes and tables (fields and records) to be graphically created. The SQL code that defines the data structure (schema) in the database is automatically created from the visual representation. See entity relationship model.

Building an Entity Relationship Model
The Erwin modeling program from Logic Works, Princeton, NJ, stands for Entity Relationship for Windows. In this order processing example, the tables for customers and orders are drawn graphically, and Erwin turns the graph into the appropriate SQL code for the target database. (Example courtesy of Logic Works, Inc.)
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The following five data models will be presented in this paper:
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The presentation will explore how adaptive enterprise data warehousing can improve the quality of data models within IT systems to realize dramatic business benefits.