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Validate and Track Data History Confidently

This course is part of multiple programs.

Instructor: Hurix Digital

Included with

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2 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Automated checksum validation strengthens data pipelines and detects errors early before they move downstream to impact business decisions.
Reusable SCD2 architecture lowers maintenance and ensures consistent historical tracking across data warehouses for reliable analytics.
Parameterized transforms support scalable engineering and adapt to changing needs without duplicating code or increasing technical debt.
Structured data reconciliation is vital for compliance, audit trails, and maintaining trust in analytics across all organizational levels.

Skills you'll gain

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Build your subject-matter expertise

This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 2 modules in this course

Transform your data engineering expertise with advanced validation and historization techniques that ensure bulletproof data integrity. This course equips you with the critical skills to programmatically verify transformation accuracy through automated checksum validation and build enterprise-grade reusable logic for tracking historical changes in dimensional data.

This Short Course was created to help data management and engineering professionals accomplish reliable, auditable data transformations that maintain complete historical accuracy. By completing this course, you'll be able to implement automated data validation workflows that catch discrepancies before they impact downstream systems, and architect modular SCD2 logic that can be deployed across multiple dimensional tables with confidence. By the end of this course, you will be able to: Evaluate data transformation accuracy by comparing aggregate checksums and flagging discrepancies Create reusable transformation logic to track historical changes in dimensional data This course is unique because it combines practical validation techniques with enterprise-scalable historical tracking patterns, focusing on real-world implementation challenges that data engineers face daily. To be successful in this project, you should have a background in advanced SQL, data warehousing concepts, ETL/ELT processes, and experience with dimensional modeling.

Module details

Learners will master automated checksum validation techniques to systematically verify data transformation accuracy and flag discrepancies before they impact downstream systems.

What's included

4 videos1 reading1 assignment

4 videosTotal 39 minutes

Why Data Validation Saves Careers and Companies 3 minutes
Fundamentals of Checksum-Based Data Validation 8 minutes
SQL Checksum Implementation Walkthrough 11 minutes
Building Automated Validation Workflows Step-by-Step17 minutes

1 readingTotal 10 minutes

Advanced Checksum Techniques for Enterprise Data Validation10 minutes

1 assignmentTotal 3 minutes

Data Validation Fundamentals Knowledge Check3 minutes

Learners will architect modular SCD2 (Slowly Changing Dimension Type 2) logic that can be deployed across multiple dimensional tables to systematically track historical changes with enterprise-grade reliability.