Understanding Slowly Changing Dimensions: Types and Differences

11/14/20232 min read

red and blue lights from tower steel wool photography
red and blue lights from tower steel wool photography


Slowly Changing Dimensions (SCDs) are an essential concept in data warehousing and business intelligence. They refer to the way data changes and evolves over time in a database or data warehouse. In this blog post, we will explore the different types of SCDs and discuss their differences, providing a comprehensive understanding of this crucial data management concept.

What are Slowly Changing Dimensions?

Slowly Changing Dimensions are dimensions in a data warehouse that capture and store historical data, allowing for analysis and reporting on how data changes over time. They are particularly useful when dealing with data that evolves slowly, such as customer information, product details, or employee records.

Types of Slowly Changing Dimensions

Type 1: Overwrite

In Type 1 SCD, the old data is simply overwritten with the new data. This means that historical information is lost, and only the most recent values are retained. Type 1 SCD is suitable when historical data is not critical and only the current values matter. For example, if you are tracking the current address of customers, you may choose to use Type 1 SCD.

Type 2: Add New Row

Type 2 SCD maintains a separate row for each change in data, effectively creating a new version of the record. This approach allows for historical analysis and tracking changes over time. Each row contains a valid time range, indicating when the data was active. Type 2 SCD is commonly used when preserving historical data is important, such as tracking employee positions or product pricing.

Type 3: Add New Column

Type 3 SCD adds new columns to the existing row to store the changed values. This means that only a limited history can be maintained, typically capturing only the previous and current values. Type 3 SCD is useful when tracking a small number of changes and when historical analysis requires only the most recent changes. For example, if you want to keep track of the last two addresses of customers, you can use Type 3 SCD.

Type 4: Hybrid Approach

Type 4 SCD is a hybrid approach that combines elements of both Type 1 and Type 2 SCD. It maintains a separate table to store historical data, while also overwriting the original row with the most recent changes. This approach allows for efficient querying of the current data while preserving historical records for analysis. Type 4 SCD is suitable when you need to balance performance and historical analysis.

Differences between Slowly Changing Dimensions

Each type of Slowly Changing Dimension has its own advantages and use cases. Here are the key differences between the types:

  • Type 1 SCD overwrites old data with new data, losing historical information.

  • Type 2 SCD creates a new row for each change, maintaining a complete history.

  • Type 3 SCD adds new columns to store changed values, capturing limited historical data.

  • Type 4 SCD combines a separate historical table with overwriting for efficient querying and historical analysis.


Slowly Changing Dimensions are crucial for capturing and managing historical data in data warehousing and business intelligence. By understanding the different types of SCDs and their differences, organizations can make informed decisions on how to store and analyze evolving data. Whether it's overwriting, adding new rows, columns, or a hybrid approach, the choice of SCD type depends on the specific requirements and goals of the data analysis project.

Remember, choosing the right SCD type is essential for accurate reporting, trend analysis, and gaining valuable insights from historical data.