Enterprise Data Modeling:
The development of a common consistent view and understanding of data elements and their relationships across the enterprise is referred to as Enterprise Data Modeling. This type of data modeling provides access to information scattered throughout an enterprise under the control of different divisions or departments with different databases and data models.
Enterprise Data Modeling is sometimes called as global business model and the entire information about the enterprise would be captured in the form of entities.
Data Model Highlights:
When a enterprise logical data model is transformed to a physical data model, super types and sub types may not be as is. i.e. the logical and physical structure of super types and sub types may be entirely different. A data modeler has to change that according to the physical and reporting requirement.
When a enterprise logical data model is transformed to a physical data model, length of table names, column names etc may exceed the maximum number of the characters allowed by the database. So a data modeler has to manually edit that and change the physical names according to database or organization’s standards.
One of the important things to note is the standardization of the data model. Since a same attribute may be present in several entities, the attribute names and data types should be standardized and a conformed dimension should be used to connect to the same attribute present in several tables.
Standard Abbreviation document is a must so that all data structure names would be consistent across the data model.
Consider an example of a bank that contains different line of businesses like savings, credit card, investment, loans and so on.
In example, enterprise data model contains all entities, attributes, relationships, from lines of businesses savings, credit card, investment and loans.
Example of Enterprise Data Model: