Historical Dimension Tracking & SCD Pipeline Implementation Using PySpark and PostgreSQL
Group: Capstone Project
|Product Category: Cloud & Data Engineering
|Sub Category: Data Modeling & Dimensional Modeling
About this Product
Historical Dimension Tracking & SCD Pipeline Implementation Using PySpark and PostgreSQL is a practical implementation guide that teaches you how to build a production-ready Slowly Changing Dimension (SCD) pipeline using PySpark and PostgreSQL.
This guide demonstrates how to implement SCD Type 1, Type 2, and Type 3 across dimension tables while preserving historical data accuracy for analytics and reporting. You'll build a complete SCD pipeline with row-hash-based change detection, surrogate key resolution, temporal joins, data quality validation, idempotent processing, audit logging, and point-in-time reporting using production-ready engineering practices.
Product Highlights
- Implement SCD Type 1, Type 2, and Type 3 using PySpark.
- Build row-hash-based change detection for historical versioning.
- Resolve surrogate keys using temporal joins.
- Implement idempotent processing, audit logging, and data quality checks.
- Validate point-in-time reporting with historical accuracy.
- Learn scalable and production-ready dimensional data engineering practices.
By completing this guide, you will:
- Build enterprise-ready SCD pipelines using PySpark and PostgreSQL.
- Implement historical versioning and temporal data modeling.
- Apply row-hash change detection and surrogate key resolution.
- Validate historical reporting with data quality and audit checks.
- Develop reusable SCD frameworks for dimensional data warehouses.
Why this project matters
Historical accuracy is essential for reliable business reporting and analytics. This guide teaches industry-standard techniques for implementing Slowly Changing Dimensions that preserve historical records, maintain point-in-time correctness, and prevent data changes from rewriting business history—skills expected in modern Data Engineering and Data Warehousing roles.
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