Author: Jaysee Sunapho 

Managing the evolution of data through time is critical in relation to data warehousing and data analytics. Slowly Changing Dimensions (SCDs) are a collection of approaches for dealing with data changes in a systematic and consistent manner. This blog thoroughly explains SCDs, their different kinds, and real-world examples of how they may be used to address dynamic data problems.

Understanding Slowly Changing Dimensions

Definition of Slowly Changing Dimensions.  

Slowly Changing Dimensions (SCDs) are data warehouse attributes that have varying values over time but are not often updated. These dimension

Importance of SCDs.  

Historical records are essential for analytical and decision-making processes. SCDs aid in the recording of entity changes while keeping the context of each change, allowing analysts and organisations to understand trends and patterns over time.

Types of Slowly Changing Dimensions 

Type 1 SCD – Overwrite.  

The past modifications are not retained in Type 1 SCD, and the current attribute values are simply replaced with the new data. This method is ideal when keeping previous data is unnecessary and only the most recent information is required. Updating a customer’s phone number in a CRM system is one example.

Concept View

Type 2 SCD – Add New Version

Type 2 SCDs keep historical data by establishing a new record if something changes. This approach keeps track of prior and current attribute values, making historical analysis easier. A product catalogue, for example, is a Type 2 SCD implementation since each product version is documented with its characteristics and timestamps.

Concept View

Type 3 SCD – Add New Attribute

Concept View

Application and Examples of Slowly Changing Dimensions

Retail Industry – Product Price Changes

Product pricing is critical for a retail organisation since it might change over time due to promotions, inflation, or other market conditions. Implementing a Type 2 SCD allows the organisation to keep track of each product’s pricing history. When a price changes, a new record is produced with the new price and an effective date. This allows the company to monitor how pricing changes affect sales, consumer behaviour, and profitability over time.

Healthcare – Patient Records

Patient records in the healthcare area are constantly susceptible to updates and alterations, such as address changes or changes in medical conditions. Implementing a Type 1 SCD for non-critical attributes (for example, phone number) and a Type 2 SCD for critical attributes (for example, medical condition) allows healthcare providers to keep up-to-date patient information while also preserving historical medical records for analysis, research, and treatment comparisons.

Human Resources – Employee Profiles

Employee data in a human resources department is vulnerable to changes such as promotions, department transfers, and wage modifications. These problems can be properly handled by combining Type 1 and Type 2 SCDs. Type 1 SCDs can be utilised for regularly updated features such as contact information, but Type 2 SCDs can capture historical changes in job titles, department assignments, and compensation levels.

Financial Services – Customer Addresses

Financial organisations deal with consumer data that may change from time to time, such as address updates or name changes due to marriage. Using a Type 1 SCD for most characteristics and a Type 2 SCD for the address field helps the bank to keep accurate contact information while also recording past address changes for compliance and fraud detection.


Slowly Changing Dimensions (SCDs) play an important role in data warehousing and business intelligence. SCDs maintain data accuracy, allow historical analysis, and improve decision-making processes by categorising and managing data changes consistently. The use of numerous SCD types in real-world applications such as retail, healthcare, human resources, and financial services demonstrates the adaptability and relevance of SCDs in efficiently handling dynamic and developing data. Understanding and adopting SCDs enables firms to use the power of historical data and get significant insights for long-term growth and success.

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