Modern ETL Testing with AI
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 Learn
Understand ETL architecture and data flow from source systems to data warehouses
Master SQL fundamentals for ETL testing, including:
Learn Python for ETL testing:
Explore Data Warehouse concepts:
Perform common ETL validations:
Discover how AI can assist ETL testers:
Understand modern Cloud ETL architecture and industry trends
Build confidence with two real-world projects:
Who Should Read This Book?
This book is ideal for:
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:
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - Modern ETL Testing with AISQL, Python & AI for Real-World Data ValidationModern ETL Testing Series - Volume 1Are 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 warehousesMaster 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 techniquesLearn Python for ETL testing: - pandas basics- Database connectivity- Automated validation scripts- PASS/FAIL reportingExplore 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 reconciliationDiscover how AI can assist ETL testers: - Generate SQL queries- Create Python scripts- Write test cases- Analyze validation failures- Use ChatGPT, Claude, and Gemini effectivelyUnderstand modern Cloud ETL architecture and industry trendsBuild confidence with two real-world projects: - Banking ETL Testing Project- Insurance ETL Testing ProjectWhy This Book Is Different- 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 pathWho 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 testingModern ETL Testing SeriesThis 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. Artikel-Nr. 9798181826137
Anzahl: 2 verfügbar