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'''Dimensional modeling''' (DM) is a methodology including a set of techniques and concepts developed by [[Ralph Kimball]] for use in [[data warehouse]] design.<ref name="MoodyKokink-1">{{cite web|url=http://neumann.hec.ca/sites/cours/6-060-00/MK_entreprise.pdf|title=From Enterprise Models to Dimensional Models: A Methodology for Data Warehouse and Data Mart Design|id=Dimensional Modelling|access-date=3 July 2018|first1=Daniel L.|last1=Moody|first2=Mark A.R.|last2=Kortink|dead-url=no|archive-url=https://web.archive.org/web/20170517164505/http://neumann.hec.ca/sites/cours/6-060-00/MK_entreprise.pdf|archive-date=17 May 2017|df=dmy-all}}</ref> It is considered to be different from [[entity-relationship model]]ing (ER). 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.
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.
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