Apply SCD2 to Build Dynamic Data Models

Overview

Did you know that without historical data tracking, over 40% of business insights can become inaccurate or misleading? Implementing Slowly Changing Dimension (SCD) Type 2 ensures every change in your data tells the full story over time. This Short Course was created to help professionals in this field implement robust historical data tracking systems that maintain complete audit trails and support accurate trend analysis in enterprise data warehouses. By completing this course, you will be able to apply SCD Type 2 logic to build dynamic data models that capture historical changes, enabling reliable reporting, timebased analysis, and improved business intelligence accuracy. By the end of this 3hour long course, you will be able to: Apply slowlychanging dimension (SCD) Type 2 logic to build data models that track historical changes. This course is unique because it connects data modeling theory with practical warehouse implementation, giving you the skills to design scalable, auditready models that preserve data integrity across time. To be successful in this project, you should have: Basic SQL knowledge Understanding of data modeling concepts Familiarity with dbt fundamentals Data warehouse basics

Syllabus

Module 1: SCD2 Historical Tracking Fundamentals

Learners will understand the fundamental concepts of SCD2 logic and begin applying these principles to create data models that preserve historical context in enterprise data warehouses.

Module 2: dbt SCD2 Model Implementation

Learners will implement productionready SCD2 models using dbt, creating automated historical tracking systems with proper change detection, validity periods, and current status management.