Mastering Slowly Changing Dimensions (SCD) "Type 2" with Azure Data Factory: A Step-by-Step Guide

Introduction to Slowly Changing Dimensions (SCD) Type 2

Slowly Changing Dimensions (SCD) Type 2 is a data warehousing technique used to track historical changes in dimension data over time. Unlike SCD Type 1, which overwrites old data, Type 2 preserves a complete history of changes by creating additional rows for each modification.

This approach is particularly useful for scenarios where understanding historical trends or maintaining data lineage is essential, such as in customer information, product pricing, or employee roles. Each version of the data is uniquely identified, typically with effective dates, version numbers, or status flags, enabling precise querying of historical and current states.

Step 1: Setting Up Your Azure SQL Database for SCD Type 2: Creating the emp_scdtype2 Table.

Step 2: Populating Your Table: Adding Initial Data Entries.

Step 3: Data Lake Insights: Reviewing New File Entries.

Step 4: Starting the Dataflow in Azure Data Factory: Connecting Your SQL Database

Step 5: Integrating Azure Data Lake: Adding Another Data Source.

Step 6: Joining Data Sources: Merging SQL Table and CSV File

Step 7: Selecting Relevant Data: Using Select Transformation for Efficiency

Step 8: Adding Historical Data Indicators: Creating the Active_Flag Column. Value if the flag will be 0 i.e. active_flag = 0

Step 9: Use the Alter Row Transformation in the data flow which will allow dataflow to update the row policy and dataflow would be able to update the SQL Table. Without Alter Row transformation, update is not possible. condition 1==1 will be always true so update will not fail.

Step 10: Sink 1 will be an “Update” to SCD Type 2 table. We will do this update on the basis of a Key Column ID.

Step 11: Inserting New Data Entries: Adding Rows with Active_Flag = 1

Step 12: Executing Insert Operations: Configuring Sink 2 for New Data

Step 13: As we have “2 Sink Operations“; we need to provide the default write behavior of both the sinks. Sink 1 will be “Update“and Sink 2 will be the “Insert“operation.

Step 14: Executing the Dataflow: Calling from the Pipeline

Step 15: Successful Dataflow and Pipeline Execution: Ensuring Process Completion

Step 16: Verifying SQL Database Updates: Observing Historical and Current Data Changes

Update operation has pushed all historical line items with Active_flag = 0 status and Insert operation has pushed all entries with the active_flag = 1 status in the table.

In conclusion, mastering Slowly Changing Dimensions (SCD) Type 2 using Azure Data Factory involves a series of well-defined steps that ensure data integrity and historical accuracy. By setting up an Azure SQL Database, populating it with initial data, and leveraging Azure Data Factory's data flow capabilities, you can efficiently manage and transform data. The process includes connecting data sources, performing necessary transformations, and executing update and insert operations to maintain both current and historical records. This guide provides a comprehensive approach to implementing SCD Type 2, enabling organizations to track changes over time and make informed decisions based on accurate data insights.