From enterprise models to dimensional models: a methodology for data warehouse and data mart design

This paper describes a method for developing dimensional models from traditional Entity Relationship models. This can be used to design data warehouses and data marts based on enterprise data models. The first step of the method involves classifying entities in the data model into a number of categories. The second step involves identifying hierarchies that exist in the model. The final step involves collapsing these hierarchies and aggregating transaction data to form dimensional models. A number of design alternatives are presented, including a flat schema, a terraced schema, a star schema and a snowflake schema. We also define a new type of schema called a star cluster schema. This is a restricted form of snowflake schema, which minimises the number of tables while avoiding overlap between different dimensional hierarchies. Individual schemas can be collected together to form constellations or galaxies. We illustrate the method using a simple example.

• Type: Conference
• Year: 2000
• Where: DMDW
• Authors: Daniel L. Moody, Mark A. R. Kortink
• Keywords: Data Model, Dimensional Models, DMDW 2000, DMDW 2001, Snowflake Schema