1. About this Book
  2. How to Read & Terminologies
  3. Introducing Chapters
  6. Part 1: Intro
  7. Introduction to the Field of Data Engineering
    ❱
    1. The History and State of Data Engineering
    2. Challenges in Data Engineering
  8. Introduction to Data Engineering Design Patterns (DEDP)
    ❱
    1. Understanding Convergent Evolution
  9. Convergent Evolution and its Patterns
    ❱
    1. Business Intelligence, Semantic Layer, Modern OLAP, Data Virtualization
    2. Materialized Views vs. One Big Table (OBT) vs. dbt tables vs. Traditional OLAP vs. DWA
    3. Bash-Script vs. Stored Procedure vs. Traditional ETL Tools vs. Python-Script
    4. Data Warehouses vs. Master Data Management vs. Data Lakes vs. Reverse-ETL vs. CDP
    5. Schema Evolution vs. Data Contracts vs. NoSQL
    6. More to come..
  11. Part 2: Mastering the DEDP
  12. Data Engineering Patterns (DEP)
    ❱
    1. Cache
    2. Data-Asset Reusability
    3. Workspace Packaging
    4. (more to explore during writing)
  13. Data Engineering Design Patterns (DEDP)
    ❱
    1. Dynamic Querying
  15. Part 3: What's Next?
  20. Changelog
  21. Feedback
  22. Author & Support
  23. Sponsors
  24. Copyright & Legal Notice
  25. Privacy Policy
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