Types of Dimension Tables in a Data Warehouse

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  • Post last modified:March 15, 2018
  • Post category:Data Warehouse
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A dimension is something that qualifies the quantity or measures. Dimensions store the textual descriptions of the business. With help of dimension you can easily identify the measures.The different types of dimension tables are available as below:

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types of fact tables Types of dimension tables-in-a-data-warehouse

Types of Dimension Tables in a Data Warehouse

Below are the commonly used dimension tables in data warehouse:

Conformed Dimension

A conformed dimension is the dimension that is shared across multiple data mart or subject area. Company may use the same dimension table across different projects without making any changes to the dimension tables.

Conformed dimension example would be Customer dimension, i.e. both marketing and sales department can use Customer dimension for their reporting purpose.

Junk Dimension

A junk dimension is a grouping of typically low cardinality attributes, so you can remove them from main dimension.

You can use Junk dimensions to implement the rapidly changing dimension where you can use it to stores the attribute that changes rapidly.

For example, attributes such as flags, weights, BMI (body mass index) etc

Degenerated Dimension

A degenerated dimension is a dimension that is derived from fact table and does not have its own dimension table.

For example, receipt number does not have dimension table associated with it. Such details are just for information purpose.

Role Playing Dimension

Dimensions which are often used for multiple purposes within the same database are called role-playing dimensions.

For example,  you can use a date dimension for “date of sale”, as well as “date of delivery”, or “date of hire”.

Based on the frequency of data change below are the types of Dimension Tables:

Unchanging or static dimension (UCD)

Dimensions values are static and will not change

Slowly changing dimension (SCD)

Attribute values changes slowly over time. Based on the frequency of data change and history preservation, there are various slowly changing dimensions available.

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Rapidly changing Dimension (RCD)

Attribute values changes rapidly