Answer Posted / manoj
When developing a dimensional model, we often encounter miscellaneous flags and indicators. These flags do not logically belong to the core dimension tables.
A junk dimension is grouping of low cardinality flags and indicators. This junk dimension helps in avoiding cluttered design of data warehouse. Provides an easy way to access the dimensions from a single point of entry and improves the performance of sql queries.
Example: For example, assume that there are two dimension tables (gender and marital status). The data of these two tables are shown below:
Code:
Table: Gender
Id Gender_status
----------------
1 Male
2 Female
Table: Marital Status
Id Marital_Status
----------------
1 Single
2 Married
Here both the dimensions have low cardinality flags. This will cause maintenance of two tables and decrease performance of sql queries.
We can combine these two dimensions into a single table by cross joining and can maintain a single dimension table. The result of cross join is shown below:
Code:
id gender mrg_status
--------------------
1 Male Single
2 Male Married
3 Female Single
4 Female Married
This new dimension table is called a junk dimension. This will improve the manageability and improves the sql queries performance.
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