DEDP — How to Read & Terminologies
Reading guide and core abbreviations used throughout the book.
Core Philosophy
The book departs from traditional IT reference formats. It is structured as a narrative journey building toward design patterns — skipping sections risks missing foundational concepts. Uses a bottom-up methodology: examining standard data engineering terminology developed over two decades, then identifying recurring patterns across convergent evolution.
Key Abbreviations
| Abbreviation | Definition |
|---|---|
| DE | Data Engineering |
| CE | [[2026-04-04-dedp-convergent-evolution |
| DEP | [[2026-04-04-dedp-dep-intro |
| DEDP | [[2026-04-04-dedp-design-patterns-intro |
| MDS | Modern Data Stack |
| ODS | Open Data Stack |
Navigation Features
- Search function (press 's') for full-text lookup
- Interactive graph at chapter ends showing connections to related content
- Link styling: full-color underlines = internal references; subtle underlines = external sources
- Admonitions (Note, Info, Example, Idea) for supplementary content
Design Note
The author references the Data Engineering Vault for rapidly-evolving definitions, keeping the book focused on stable patterns with longer lifecycles. This is the right call — separating volatile terminology from durable patterns.
Mental Models
- Bottom-up pattern discovery — start with terminology, observe convergence, extract patterns. The reverse of top-down framework imposition.
- MDS vs ODS distinction — Modern Data Stack (commercial/SaaS-heavy) vs Open Data Stack (open-source/open-standards). This framing shows up repeatedly in the pattern chapters.
Related
- [[2026-04-04-dedp-about-this-book|About This Book]] — motivation and audience
- [[2026-04-04-dedp-introduction|Introduction]] — book structure
- [[2026-04-04-dedp-intro-data-engineering|Intro to the Field of Data Engineering]] — Chapter 1.1