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Autor(en): 
  • Masud Mondal
  • Modern ETL Testing with AI: SQL, Python & AI for Real-World Data Validation 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Juni 2026  
    Genre:  EDV / Informatik 
     
    COMPUTERS / Data Processing / COMPUTERS / Programming Languages / Python / COMPUTERS / Software Development & Engineering / Quality Assurance & Testing
    ISBN:  9798181826137 
    EAN-Code: 
    9798181826137 
    Verlag:  Independently Published 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 229 mm / B 152 mm / D 8 mm 
    Gewicht:  199 gr 
    Seiten:  140 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Modern ETL Testing with AISQL, Python & AI for Real-World Data Validation

    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:

    • 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
    Why 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 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
    Modern ETL Testing Series

    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

      
     Empfehlungen... 
     MODERN ETL TESTING WITH AI: Cloud Data Platforms, - (Buch)
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