Dimension

 A table in a data warehouse whose entries describe data in a fact table. Dimension tables contain the data from which dimensions are created.

Types

Slowly changing Dimension

SCD Type 1 -

 The attribute value is overwritten with the new value, obliterating the historical attribute values. For example, when the product roll-up changes for a given product, the roll-up attribute is merely updated with the current value.

SCD Type 2 -

A new record with the new attributes is added to the dimension table. Historical fact table rows continue to reference the old dimension key with the old roll-up attribute; going forward, the fact table rows will reference the new surrogate key with the new roll-up thereby perfectly partitioning history. 

SCD Type 3 -

            Attributes are added to the dimension table to support two simultaneous roll-ups - perhaps the current product roll-up as well as “current version minus one”, or current version and original.

Rapidly changing Dimension

A rapidly changing dimension is a dimension whose membership and attribute data may change with either high frequency or with widespread scope, and is typically represented as a separate dimension related to an existing regular or slowly changing dimension. The contents of an RCD are updated far more frequently (monthly, weekly, even daily for some business intelligence applications) than the dimension to which the RCD is associated.

Snowflake Dimension

            There may be a need to take out some data, to keep that in a separate table and link that table to the original table.

Junk Dimension

            While designing the fact table and dimension table from the operational database, some attributes in the original database cannot be discard. But they donot fit into the fact and dimension table.

In such case, the options are,

• To discard them, which may result in the loss of information.
• To put them in different dimension table which unnecessarily increase the number of dimension
• To use junk dimension where in a junk dimension table is created with the ‘junk’attributes. 

Conformed Dimension

Conformed Dimensions are the Dimensions, which are common to two cubes .say CUBE-1 contains F1,D1,D2,D3 and CUBE-2 contains F2,D1,D2,D4 are the Facts and Dimensions ,here D1,D2 are the Conformed Dimensions