SaratChandra

• May 27th, 2005

 

Dimensions that change over time are called Slowly Changing Dimensions. For instance, a product price changes over time; People change their names for some reason; Country and State names may change over time. These are a few examples of Slowly Changing Dimensions since some changes are happening to them over a period of time

senkumar79

 Profile Answers by senkumar79 Questions by senkumar79

• Oct 4th, 2005

 

If the data  in the dimension table happen to change very rarely,then it is called as slowly changing dimension.

ex: changing the name and address of a person,which happens rerely.

yugandhar.bo

 Profile Answers by yugandhar.bo 

• May 15th, 2006

 

WHAT ARE THE STEPS WE NEED TO TAKE CARE OF THE SLOWLY CHNAGING DIMENSIONS IN THE DATA WAREHOUSE DESIGNING

Minal Sarmokadam

• Jul 5th, 2006

 

While handling Slowly changing Dimension, Dimesion schema might required to change. It depends on Business Requirement.

E.g Dimension Table Product has Product ID and Price. If Price changes , if we update the Price in the Dimension we might end up in loosing History Data. In this case we can Add One Column as Dateof Change. So if Price Changes for the given date, 1 Record gets added in to Dimension while keeping the history intact.

chandrarekha

• May 7th, 2007

 

SCD explains the changed data captures(CDC)in the target data base

1292033

• Aug 2nd, 2007

 

The definition of slowly changing dimension is in its name only. The dimension which  changes slowly with time. A customer dimension table represents customer. When creating a customer, normal assumption is it is independent of time. But what if address of customer changes or name of customer changes?

This change can be implemented in three ways...

Type I: Replace the old record with a new record with updated data, there by we lose the history. But data warehouse has a responsibility to track the history effectively, where Type I implementation fails.

Type II: Create a new additional dimension table record with new value. By this way we can keep the history. We can determine which dimension is current by adding a current record flag or by time stamp on the dimensional row.

Type III: In this type of implementation we create a new field in the dimension table, which stores the old value of the dimension. When an attribute of the dimension changes then, we push the updated value to the current field and old value to the old field.

swathirao_829

 Profile Answers by swathirao_829 

• Dec 6th, 2008

 

A Slowly Chaging dimension explains changed data captures over the period of time. There r three types of slowly changing dimensions(SCD).
1)Type 1 SCD: It keeps most recent updated values in the target. It does not maintain the history.
2) Type 2 SCD: It keeps full history in the target. For every update in the source it inserts a new record in the target.
3) Type 3 SCD: It maintain current & previous information in the target.