How AnalyticsCreator Automates SCD Type 2 Historization for Dimensional Models

SCD Type 2 is essential for historical reporting but notoriously complex to implement manually. AnalyticsCreator automates historization through metadata—generating schema changes, ETL logic, and pipelines for Microsoft Fabric SQL and SQL Server with full governance.

Managing Change in Dimensional Models

Tracking changes from ERP and CRM systems is central to accurate analytics. Businesses need to understand not just the current state of an entity, but how that state evolved over time. This is where Slowly Changing Dimensions (especially Type 2) come in.

Why Historization Matters

Historization allows BI teams to answer questions such as:

• What was the customer’s status last quarter?
• How did the product price change over time?
• Who managed this customer before the last territory update?

Without SCD Type 2, reports only show the current record—producing misleading insights and limiting compliance reporting.

Challenges with Manual SCD Implementation

Traditionally, SCD Type 2 requires custom SQL, change detection logic, timestamp management, surrogate key handling, and careful orchestration. This is slow, error-prone, and difficult to scale across many dimensions.

How AnalyticsCreator Simplifies Historization

AnalyticsCreator eliminates manual coding by using a metadata-driven approach. You define historization rules once, and the platform automatically generates:

• Schema changes (valid-from / valid-to, surrogate keys)
• Delta logic for detecting attribute changes
• Insert/update logic for new and old versions
• ETL pipelines for ADF, SSIS, or Fabric SQL

Architecture Overview

The historization architecture spans ingestion, modeling, and warehouse storage:

• Azure Data Factory loads data into Fabric SQL.
• AnalyticsCreator models dimensions, facts, and historized attributes.
• Fabric SQL hosts the metadata repository and data warehouse.
• OneLake Delta enables fast consumption for analytics.

Step-by-Step: How Historization Works in AnalyticsCreator

1. Define SCD Settings in Metadata

Select a dimension (e.g., DIM_Orders) and enable SCD Type 2. AnalyticsCreator automatically applies the required columns such as:

• DAT_VON — Valid-from timestamp
• DAT_BIS — Valid-to timestamp
• SATZ_ID — Surrogate key

2. Automatic Generation of SCD Logic

AnalyticsCreator detects changes between incoming and stored values. When a change occurs:

• The old version is closed with an end date.
• A new version is inserted with the updated values.

3. Execute and Validate

After deployment, querying the historized table shows multiple versions of a record, ensuring full time-travel visibility.

Manual SCD vs AnalyticsCreator

Use Case: Northwind Orders

Using the Northwind dataset, SCD Type 2 was enabled on the Orders dimension. After modifying source records and reloading, AnalyticsCreator detected changes and generated new record versions—no custom SQL required.

Final Takeaway

SCD Type 2 historization is essential but doesn’t need to be complicated. AnalyticsCreator automates all aspects of historization through metadata, ensuring consistent, accurate, and governable historical tracking across SQL Server and Microsoft Fabric.