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dedp ingestion plan

2026-04-04·plan·status: active

DEDP Book Ingestion Plan

Source: Patterns of Data Engineering by the DEDP author. Book is published incrementally — not all chapters are live yet. Current inventory: 20 content chapters across 2 parts (Part 3 not yet published).

Full Table of Contents

Front Matter

# Title URL
FM-1 About This Book https://www.dedp.online/about-this-book.html
FM-2 Introduction https://www.dedp.online/introduction.html
FM-3 Terminologies https://www.dedp.online/terminologies.html

Part 1 — Foundations (History, State, and Design Pattern Concepts)

Chapter 1: Introduction to Data Engineering

# Title URL
1.1 Introduction to the Field of Data Engineering https://www.dedp.online/part-1/1-introduction/_intro-data-engineering.html
1.2 The History and State of Data Engineering https://www.dedp.online/part-1/1-introduction/history-and-state-of-data-engineering.html
1.3 Challenges in Data Engineering https://www.dedp.online/part-1/1-introduction/challenges-in-data-engineering.html

Chapter 2: Overview of DEDP

# Title URL
2.1 Introduction to Data Engineering Design Patterns https://www.dedp.online/part-1/2-overview-dedp/_intro-dedp.html
2.2 Understanding Convergent Evolution https://www.dedp.online/part-1/2-overview-dedp/understanding-convergent-evolution.html

Part 2 — Mastering the Patterns

Chapter 4: Convergent Evolution Examples

# Title URL
4.1 Convergent Evolution and its Patterns (Intro) https://www.dedp.online/part-2/4-ce/_example-of-convergent-evolution.html
4.2 Bash-Script vs. Stored Procedure vs. Traditional ETL vs. Python-Script https://www.dedp.online/part-2/4-ce/bash-stored-procedure-etl-python-script.html
4.3 Data Contracts, Schema Evolution, NoSQL https://www.dedp.online/part-2/4-ce/data-contracts-schema-evolution-nosql.html
4.4 DWH, MDM, Data Lake, Reverse ETL, CDP https://www.dedp.online/part-2/4-ce/dwh-mdm-data-lake-reverse-etl-cdp.html
4.5 Materialized View vs. OBT vs. dbt Table vs. OLAP Cube vs. DWA https://www.dedp.online/part-2/4-ce/mv-obt-dbt-table-traditional-olap-dwa.html
4.6 Business Intelligence, Semantic Layer, Modern OLAP, Data Virtualization https://www.dedp.online/part-2/4-ce/semantic-layer-business-intelligence.html

Chapter 5: Data Engineering Patterns (DEP)

# Title URL
5.1 Data Engineering Patterns (Intro) https://www.dedp.online/part-2/5-dep/_data-engineering-patterns.html
5.2 Cache Pattern https://www.dedp.online/part-2/5-dep/cache-pattern.html
5.3 Data-Asset Reusability Pattern https://www.dedp.online/part-2/5-dep/data-asset-reusability-pattern.html
5.4 Data Engineering Workspace Packaging Pattern https://www.dedp.online/part-2/5-dep/de-workspace-packaging-pattern.html

Chapter 6: Data Engineering Design Patterns (DEDP)

# Title URL
6.1 Data Engineering Design Patterns (Intro) https://www.dedp.online/part-2/6-dedp/_data-engineering-design-patterns.html
6.2 Dynamic Query Design Pattern https://www.dedp.online/part-2/6-dedp/dynamic-queries.html

Appendix

# Title URL
A-1 Changelog https://www.dedp.online/appendix/changelog.html
A-2 Author https://www.dedp.online/appendix/author.html
A-3 Feedback https://www.dedp.online/appendix/feedback.html
A-4 Sponsors https://www.dedp.online/appendix/sponsors.html

Not ingested (utility pages)

Suggested Processing Order

Priority based on relevance to active projects (phData consulting, data marketplace, newsletter content).

Batch 1 — Highest priority (architecture & modeling patterns) ✅ Complete (2026-04-04)

Direct fuel for phData consulting engagements and newsletter thought pieces.

  1. ✅ 4.4 — DWH, MDM, Data Lake, Reverse ETL, CDP → [[06-reference/2026-04-04-dedp-dwh-mdm-datalake-reverse-etl-cdp]]
  2. ✅ 4.5 — Materialized View vs. OBT vs. dbt Table vs. OLAP Cube vs. DWA → [[06-reference/2026-04-04-dedp-mv-obt-dbt-olap-dwa]]
  3. ✅ 4.6 — Semantic Layer, BI, Modern OLAP, Data Virtualization → [[06-reference/2026-04-04-dedp-semantic-layer-bi-olap-virtualization]]
  4. ✅ 5.3 — Data-Asset Reusability Pattern → [[06-reference/2026-04-04-dedp-data-asset-reusability-pattern]]

Batch 2 — Design patterns and evolution examples ✅ Complete (2026-04-04)

Core pattern thinking that differentiates our consulting and newsletter POV.

  1. ✅ 6.1 — Data Engineering Design Patterns (Intro) → [[06-reference/2026-04-04-dedp-design-patterns-intro]]
  2. ✅ 6.2 — Dynamic Query Design Pattern → [[06-reference/2026-04-04-dedp-dynamic-queries]]
  3. ✅ 4.2 — Bash vs. Stored Proc vs. ETL vs. Python → [[06-reference/2026-04-04-dedp-etl-tool-comparisons]]
  4. ✅ 4.3 — Data Contracts, Schema Evolution, NoSQL → [[06-reference/2026-04-04-dedp-data-contracts-schema-evolution]]
  5. ✅ 5.2 — Cache Pattern → [[06-reference/2026-04-04-dedp-cache-pattern]]

Batch 3 — Foundations and frameworks ✅ Complete (2026-04-04)

Important for grounding but less immediately actionable.

  1. ✅ 2.1 — Intro to DEDP → [[06-reference/2026-04-04-dedp-intro-dedp]]
  2. ✅ 2.2 — Understanding Convergent Evolution → [[06-reference/2026-04-04-dedp-convergent-evolution]]
  3. ✅ 4.1 — Convergent Evolution and its Patterns (Intro) → [[06-reference/2026-04-04-dedp-ce-intro]]
  4. ✅ 5.1 — Data Engineering Patterns (Intro) → [[06-reference/2026-04-04-dedp-dep-intro]]
  5. ✅ 5.4 — DE Workspace Packaging Pattern → [[06-reference/2026-04-04-dedp-de-workspace-packaging]]

Batch 4 — History, context, and front matter ✅ Complete (2026-04-04)

Background context; ingest last.

  1. ✅ FM-1 — About This Book → [[06-reference/2026-04-04-dedp-about-this-book]]
  2. ✅ FM-2 — Introduction → [[06-reference/2026-04-04-dedp-introduction]]
  3. ✅ FM-3 — Terminologies → [[06-reference/2026-04-04-dedp-terminologies]]
  4. ✅ 1.1 — Intro to the Field of Data Engineering → [[06-reference/2026-04-04-dedp-intro-data-engineering]]
  5. ✅ 1.2 — History and State of Data Engineering → [[06-reference/2026-04-04-dedp-history-state-de]]
  6. ✅ 1.3 — Challenges in Data Engineering → [[06-reference/2026-04-04-dedp-challenges-de]]

Batch 5 — Appendix (optional)

Only if useful for attribution or context.

  1. A-1 — Changelog
  2. A-2 — Author

Batch Summary

Batch Chapters Focus
1 4 Architecture & modeling patterns
2 5 Design patterns & evolution
3 5 Foundations & frameworks
4 6 History & context
5 2 Appendix (optional)
Total 22 5 batches

Notes