What are the different types of Dimension?

Confirmed Dimension:

• Confirmed Dimension is a dimension which is shared by different fact tables.
  
• Confirmed Dimension is a dimension table which is connected to the multiple fact tables across multiple Data Marts.
  
• Conformed Dimensions are the Dimensions which are common to two cubes.
  
• Example: 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
  
• Generally the TIME (Period, Date, etc) Dimension is a conformed Dimension.
  

 

Junk dimension:

A "junk" dimension is a collection of random transactional codes, flags and/or text attributes that are unrelated to any particular dimension. The junk dimension is simply a structure that provides a convenient place to store the junk attributes.
The fact would contain several metrics (principal amount, net amount, price per share etc.) and would be related to several dimensions (such as account, date etc.) This fact would also contain several codes and flags that were related to the transaction rather than any of the dimensions such as origin code (that indicates whether the trade was initiated with a phone call or via the Web), a reinvest flag (that indicates whether or not this trade as was the result of the reinvestment of a dividend payout) and a comment field for storing special instructions from the customer. These three attributes would normally be removed from the fact table and stored in a junk dimension. In this way, the number of indexes on the fact table would be reduced, and performance would be enhanced.

Degenerated dimension:

A column of the key section of the fact table that does not have the associated dimension table but used for reporting and analysis, such column is called degenerate dimension or line item dimension. For ex, we have a fact table with customer_id, product_id, branch_id, employee_id, bill_no, date in key section and price, quantity, amount in measure section. In this fact table, bill_no from key section is a single value, it has no associated dimension table. Instead of creating a separate dimension table for that single value, we can include it in fact table to improve performance.