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Modern ETL Testing with AI: SQL, Python & AI for Real-World Data Validation
Paperback
Series: Qa Testing, Book 1
Publisher: Independently Published
Published: Jun 16 2026
Pages: 140
Weight: 0.43
Height: 0.30 Width: 6.00 Depth: 9.00
Language: English
Modern ETL Testing Series - Volume 1
Are you looking to start a career in ETL Testing or upgrade your skills with SQL, Python, and AI?
Do you find traditional ETL books too theoretical and difficult to follow?
Modern ETL Testing with AI - Volume 1 is a beginner-friendly, practical guide designed to help you learn ETL testing step by step using simple language, real-world examples, and hands-on projects.
Instead of overwhelming you with theory, this book focuses on what ETL testers actually do in real projects-validating data, writing SQL queries, automating checks with Python, and using AI tools to work faster and smarter.
What You'll LearnUnderstand ETL architecture and data flow from source systems to data warehouses
Master SQL fundamentals for ETL testing, including:
- SELECT, WHERE, GROUP BY, ORDER BY
- INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN
- Aggregations and reconciliation queries
- Practical data validation techniques
Learn Python for ETL testing:
- pandas basics
- Database connectivity
- Automated validation scripts
- PASS/FAIL reporting
Explore Data Warehouse concepts:
- Fact and Dimension tables
- Star Schema
- Slowly Changing Dimensions (SCD)
Perform common ETL validations:
- Row count validation
- Null value validation
- Duplicate record checks
- Aggregate validation
- Source-to-target reconciliation
Discover how AI can assist ETL testers:
- Generate SQL queries
- Create Python scripts
- Write test cases
- Analyze validation failures
- Use ChatGPT, Claude, and Gemini effectively
Understand modern Cloud ETL architecture and industry trends
Build confidence with two real-world projects:
- Banking ETL Testing Project
- Insurance ETL Testing Project
- Unlike many ETL books that focus heavily on concepts, this book emphasizes:
- Simple explanations with minimal jargon
- Practical SQL and Python examples
- AI-assisted testing techniques
- Real enterprise scenarios
- Interview-oriented insights
- Beginner to intermediate learning path
Who Should Read This Book?
This book is ideal for:
- Beginners starting their ETL Testing journey
- QA Engineers transitioning to Data Testing
- Manual Testers learning automation
- Automation Testers exploring ETL and Data Quality
- Freshers preparing for ETL Testing interviews
- Professionals interested in AI-powered testing
This book is Volume 1 of the Modern ETL Testing Series, a practical series that teaches ETL testing using modern technologies and real-world examples.
Upcoming volumes cover:
- Advanced ETL Testing with AI
- Cloud ETL Testing with AI
- Python Automation for ETL Testing
- CDC, SCD & Incremental Load Testing
- Snowflake, Databricks & Modern Data Pipelines
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