Datawarehouse Concepts... What is Slowly Changing Dimensions?

Slowly Changing Dimensions (SCD)

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.

Below i am explaining different types of SCD which i have learnt and have got definitions from net. To understand them with easy examples follow this link

SCD examples

Type 1 Dimension mapping.
It loads a slowly changing dimension table by inserting new dimensions and overwriting existing dimensions. Use this mapping when you do not want a history of previous dimension data.

Type 2 Dimension/Version Data mapping.
It loads a slowly changing dimension table by inserting new and changed dimensions using a version number and incremented primary key to track changes. Use this mapping when you want to keep a full history of dimension data and to track the progression of changes.

Type 2 Dimension/Flag Current mapping.
It loads a slowly changing dimension table by inserting new and changed dimensions using a flag to mark current dimension data and an incremented primary key to track changes. Use this mapping when you want to keep a full history of dimension data, tracking the progression of changes while flagging only the current dimension.

Type 2 Dimension/Effective Date Range mapping.
It loads a slowly changing dimension table by inserting new and changed dimensions using a date range to define current dimension data. Use this mapping when you want to keep a full history of dimension data, tracking changes with an exact effective date range.

Type 3 Dimension mapping.
It loads a slowly changing dimension table by inserting new dimensions and updating values in existing dimensions. Use this mapping when you want to keep the current and previous dimension values in your dimension table.

The Type 3 Dimension mapping filters source rows based on user-defined comparisons and inserts only those found to be new dimensions to the target. Rows containing changes to existing dimensions are updated in the target. When updating an existing dimension, the Informatica Server saves existing data in different columns of the same row and replaces the existing data with the updates.

To know more about datwarehousing concepts please check
http://www.learndatamodeling.com/

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