Fast changing dimensions are those dimensions if one or more of its attributes changes frequently and in many rows. A fast changing dimension can grow very large if we use the Type-2 approach to track numerous changes. These dimensions some time called rapidly changing dimensions.
Examples of fast changing dimensions are
Age
Income
Test score
Rating
Credit history score
Customer account
status
Weight
How to solve fast changing dimensions
After identifying the fast changing dimensions attributes, you have to create a mini dimension table with these attributes joined directly to fact table and not snowflaking.
Examples of fast changing dimensions are
Age
Income
Test score
Rating
Credit history score
Customer account
status
Weight
How to solve fast changing dimensions
After identifying the fast changing dimensions attributes, you have to create a mini dimension table with these attributes joined directly to fact table and not snowflaking.
A mini-dimension is a dimension that usually contains fast changing attributes of a larger dimension table. This is to improve accessibility to data in the fact table.
Before creating a mini dimension table, you have to convert these identified attributes individually into band ranges. The concept behind this method is to take limited discreet values as shown below.
Rows in mini-dimensions will be fewer than rows in large dimension tables because it restricts the rows in mini-dimensions by using the band range value method.
Rows in mini-dimensions will be fewer than rows in large dimension tables because it restricts the rows in mini-dimensions by using the band range value method.
After identifying the fast changing attributes of the primary customer dimension, and determining the band ranges for these attributes, a new mini-dimension is formed called Cust_Mini_Dim as shown below.
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