About this Book
How to Read & Terminologies
Introducing Chapters
Part 1: Intro
1.
Introduction to the Field of Data Engineering
❱
1.1.
The History and State of Data Engineering
1.2.
Challenges in Data Engineering
2.
Introduction to Data Engineering Design Patterns (DEDP)
❱
2.1.
Understanding Convergent Evolution
3.
Convergent Evolution and its Patterns
❱
3.1.
Business Intelligence, Semantic Layer, Modern OLAP, Data Virtualization
3.2.
Materialized Views vs. One Big Table (OBT) vs. dbt tables vs. Traditional OLAP vs. DWA
3.3.
Bash-Script vs. Stored Procedure vs. Traditional ETL Tools vs. Python-Script
3.4.
Data Warehouses vs. Master Data Management vs. Data Lakes vs. Reverse-ETL vs. CDP
3.5.
Schema Evolution vs. Data Contracts vs. NoSQL
3.6.
More to come..
Part 2: Mastering the DEDP
4.
Data Engineering Patterns (DEP)
❱
4.1.
Cache
4.2.
Data-Asset Reusability
4.3.
More to come..
5.
Data Engineering Design Patterns (DEDP)
❱
5.1.
More to come..
Part 3: Navigating DEDP
Changelog
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Ayu
📖 Data Engineering Design Patterns (DEDP)
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