In the world of data warehousing, handling changes to dimensions over time is a critical challenge. As organizations grow and evolve, so does their data. Slowly Changing Dimensions (SCD) is a concept used in data warehouses to track and manage historical changes to dimension data. In this blog, we will explore what SCD is, the various types of SCD, and how they are implemented.
What are Slowly Changing Dimensions (SCD)?
Slowly Changing Dimensions (SCD) refer to the method used to manage and track changes in the dimension tables of a data warehouse. Dimension tables contain descriptive attributes (dimensions) that define facts in a fact table. Unlike fact tables, which are updated frequently, dimensions change less often. However, when changes occur, it is important to decide how to manage these changes without losing historical context.
For example, consider a retail store’s customer dimension. A customer may move to a new address or change their name, and we need to capture this change in a way that preserves the customer’s history.
Types of Slowly Changing Dimensions
There are three main types of SCD, each handling changes differently:
SCD Type 0: Retaining Original Values
SCD Type 0 is used when the original value of a dimension attribute is critical and should not be changed. This type is often used for attributes that are not expected to change frequently or where historical accuracy is essential.
Example:
If a product is assigned a unique identifier (SKU) that should never change, SCD Type 0 would ensure that the SKU remains constant in the dimension table, even if other attributes of the product change.
Advantages:
Disadvantages:
SQL Implementation Example:
SELECT * FROM product_dimension
WHERE product_id = 1;
SCD Type 1: Overwriting the Existing Data
In Type 1 SCD, when there is a change in dimension data, the old data is simply overwritten with the new data. There is no history of the previous values. This approach is suitable when tracking historical changes is not important.
Example:
If a customer changes their address, the old address is replaced with the new one in the table. The old address is no longer available.
Advantages:
Disadvantages:
SQL Implementation Example:
UPDATE customer_dimension
SET address = ‘New Address’
WHERE customer_id = 1;
SCD Type 2: Creating a New Record
SCD Type 2 maintains full historical data by creating a new record each time a change occurs. It adds a new row with the updated information while preserving the original row. To differentiate between the historical and current data, additional columns like StartDate, EndDate, or a flag (IsCurrent) are often added.
Example:
If a customer changes their address, a new row is inserted with the updated address, while the old row remains with an EndDate marking when the change occurred.
Advantages:
Disadvantages:
SQL Implementation Example:
UPDATE customer_dimension
SET EndDate = GETDATE(), IsCurrent = 0
WHERE customer_id = 1 AND IsCurrent = 1;
INSERT INTO customer_dimension (customer_id, name, address, StartDate, IsCurrent)
VALUES (1, ‘John Doe’, ‘New Address’, GETDATE(), 1);
SCD Type 3: Adding a New Column
SCD Type 3 handles changes by adding new columns to store both the old and the new values of the changed attribute. This approach is useful when only the previous version of data is needed, but not the entire history.
Example:
If a customer changes their address, a new column PreviousAddress is created to store the old value, while the Address column stores the new value.
Advantages:
Disadvantages:
SQL Implementation Example:
UPDATE customer_dimension
SET PreviousAddress = Address, Address = ‘New Address’
WHERE customer_id = 1;
Other Types of SCD
In addition to the main types, there are some advanced SCD types:
Choosing the Right SCD Type
Selecting the appropriate SCD type depends on your business requirements. Here are a few factors to consider:
Best Practices for Implementing SCD
Conclusion
Slowly Changing Dimensions (SCD) play a crucial role in data warehousing by helping to track changes over time in dimension tables. The choice of SCD type depends on your organization’s needs for retaining historical data and managing changes. Whether you opt for the simplicity of Type 1, the comprehensive history tracking of Type 2, or the limited history of Type 3, understanding the pros and cons of each type will help you build a robust and efficient data warehouse.
That’s all from this blog until next time.. keep learning..
Lochan R