Dimensional modeling: Difference between revisions

Revision as of 10:36, 29 May 2022

Revision as of 20:21, 13 March 2023

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==Description==

Dimensional modeling always uses the concepts of facts (measures), and dimensions (context). Facts are typically (but not always) numeric values that can be aggregated, and dimensions are groups of hierarchies and descriptors that define the facts. For example, sales amount is a fact; timestamp, product, register#, store#, etc. are elements of dimensions. Dimensional models are built by business process area, e.g. store sales, inventory, claims, etc. Because the different [[business process areas]] share some but not all dimensions, efficiency in design, operation, and consistency, is achieved using [[Dimension (data warehouse)#Types|conformed dimensions]], i.e. using one copy of the shared dimension across subject areas.{{cn|date=July 2018}}

Dimensional modeling does not necessarily involve a relational database. The same modeling approach, at the logical level, can be used for any physical form, such as multidimensional database or even flat files. It is oriented around understandability and performance.{{cn|date=July 2018}}