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Many-to-Many Dimensions

In SSAS, data structures do not always conform to the snowflake or star schema model where one fact is associated with a single dimension member.  For example, consider the example of financial...

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Degenerate Dimensions

Degenerate dimensions, also called fact dimensions, are standard dimensions that are constructed from attribute columns in fact tables instead of from attribute columns in dimension tables.  This is...

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Reference Dimensions

A reference dimension occurs when the key column for the dimension is joined indirectly to the fact table through a key in another dimension table.  This results in a snowflake schema design. The...

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Conformed dimensions

A conformed dimension is a dimension that has the same meaning to every fact with which it relates.  Conformed dimensions allow facts and measures to be categorized and described in the same way across...

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Role-playing Dimensions

Dimensions are often recycled for multiple purposes within the same database.  For instance, a “Date” dimension can be used for “Date of Sale”, as well as “Date of Delivery”, or “Date of Hire”.  This...

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Junk dimensions

Junk dimensions are dimensions that contain miscellaneous data such as flags and indicators.  When designing a data warehouse, you might come across a source system that has a bunch of yes/no indicator...

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Slowly Changing Dimensions

When designing a data warehouse, how you handle changes to dimensional data over time is the most important decision to make.  It is rare that a dimension will remain static over time.  For example, a...

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