Hii, It depends on the business requirement u have. We use this SCD's to maintain history(changes/updates) in the dimensions. Each SCD type has it's own way of storing/updating/maintaining the history. For example, A customer dimension is a SCD, because the customer can change his/her address,contact,name or anything. These types of changes in dimensions are know a SCD's. And we use the 3 different SCD TYPES to handle these changes and historyu.byeMayee
Sridhar.B
Jul 11th, 2006
The "Slowly Changing Dimension" problem is a common one particular to data warehousing. In a nutshell, this applies to cases where the attribute for a record varies over time. We give an example below: Christina is a customer with ABC Inc. She first lived in Chicago, Illinois. So, the original entry in the customer lookup table has the following record: Customer Key Name State 1001 Christina IllinoisAt a later date, she moved to Los Angeles, California on January, 2003. How should ABC Inc. now modify its customer table to reflect this change? This is the "Slowly Changing Dimension" problem. There are in general three ways to solve this type of problem, and they are categorized as follows: In Type 1 Slowly Changing Dimension, the new information simply overwrites the original information. In other words, no history is kept. In our example, recall we originally have the following table: Customer Key Name State 1001 Christina IllinoisAfter Christina moved from Illinois to California, the new information replaces the new record, and we have the following table: Customer Key Name State 1001 Christina CaliforniaAdvantages: - This is the easiest way to handle the Slowly Changing Dimension problem, since there is no need to keep track of the old information. Disadvantages: - All history is lost. By applying this methodology, it is not possible to trace back in history. For example, in this case, the company would not be able to know that Christina lived in Illinois before. Usage: About 50% of the time. When to use Type 1: Type 1 slowly changing dimension should be used when it is not necessary for the data warehouse to keep track of historical changes. In Type 2 Slowly Changing Dimension, a new record is added to the table to represent the new information. Therefore, both the original and the new record will be present. The new record gets its own primary key. In our example, recall we originally have the following table: Customer Key Name State 1001 Christina IllinoisAfter Christina moved from Illinois to California, we add the new information as a new row into the table: Customer Key Name State 1001 Christina Illinois 1005 Christina CaliforniaAdvantages: - This allows us to accurately keep all historical information. Disadvantages: - This will cause the size of the table to grow fast. In cases where the number of rows for the table is very high to start with, storage and performance can become a concern. - This necessarily complicates the ETL process. Usage: About 50% of the time. When to use Type 2: Type 2 slowly changing dimension should be used when it is necessary for the data warehouse to track historical changes. In Type 3 Slowly Changing Dimension, there will be two columns to indicate the particular attribute of interest, one indicating the original value, and one indicating the current value. There will also be a column that indicates when the current value becomes active. In our example, recall we originally have the following table: Customer Key Name State1001 Christina IllinoisTo accomodate Type 3 Slowly Changing Dimension, we will now have the following columns: ? Customer Key ? Name ? Original State ? Current State ? Effective Date After Christina moved from Illinois to California, the original information gets updated, and we have the following table (assuming the effective date of change is January 15, 2003): Customer Key Name Original State Current State Effective Date 1001 Christina Illinois California 15-JAN-2003Advantages: - This does not increase the size of the table, since new information is updated. - This allows us to keep some part of history. Disadvantages: - Type 3 will not be able to keep all history where an attribute is changed more than once. For example, if Christina later moves to Texas on December 15, 2003, the California information will be lost. Usage: Type 3 is rarely used in actual practice. When to use Type 3: Type III slowly changing dimension should only be used when it is necessary for the data warehouse to track historical changes, and when such changes will only occur for a finite number of time.
Can u tell me how to go for SCD's and its types.Where do we use them mostly