Dimensions. Dimensional modeling divides the world of data into two major types: measures and descriptions of the context surrounding those measures. The measures, which are typically numeric, are stored in fact tables, and the descriptions of the context, which are typically textual things describing entities like customer, product, location and time, are stored in the dimension tables.
When an enterprise decides to create a set of common labels (names for similar things such as ‘customer name’, ‘account type’, etc.) across all the sources of data, then the separate data
mart teams (or, equivalently, a single centralised team) must sit down to create master dimensions that everyone will use for every data source. These master dimensions are called conformed dimensions. Data Governance then controls the single, centralised dimension authority that creates, administers, and periodically releases each conformed dimension.
Conformed dimensions. Dimensions are conformed (otherwise known as common, master, standard or reference dimensions) if both have attributes that share the same name, definitions and values. In other words, the dimension attribute values are drawn from the same data domain. Conformed dimensions are agreed to by an interdisciplinary team of data stewards representing all the interests within an organisation.
The example below (care of the Kimball organisation) shows how several business functions can be accomplished in the business intelligence application by dragging an item from a list and dropping it onto a target:
26th January 2010, 01:49 PM
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