Part VI – Data Quality Engineering

Part VI develops Data Quality Engineering as the practice of designing, evaluating, and improving trustworthy evidence about data as it moves through representations, transformations, storage, pipelines, interfaces, and business decisions.

Chapters

1. Chapter 1 — Data Quality Engineering: Evidence, Meaning, and Risk

   100 minutes, plus the practical exercise · Status: Draft · Version: 0.1.0

   Prerequisites: Parts I–V, or equivalent experience in quality risk, testing evidence, programming, APIs, and automation

2. Chapter 2 — Data Representations, Models, and Contextual Quality Dimensions

   110 minutes, plus the practical exercise · Status: Draft · Version: 0.1.0

   Prerequisites: Chapter 1; Parts I–V, or equivalent experience in quality risk, testing evidence, programming, APIs, and automation

3. Chapter 3 — Query-Based Data Evidence, Integrity, and Relationships

   120 minutes, plus the practical exercise · Status: Draft · Version: 0.1.0

   Prerequisites: Chapters 1–2; Parts I–V, or equivalent experience in quality risk, testing evidence, programming, APIs, and automation

4. Chapter 4 — Transformation Quality and Business Rules

   115 minutes, plus the practical exercise · Status: Draft · Version: 0.1.0

   Prerequisites: Chapters 1–3; Parts I–V, or equivalent experience

5. Chapter 5 — Pipeline Quality: Ingestion, Processing, Storage, and Consumers

   115 minutes, plus the practical exercise · Status: Draft · Version: 0.1.0

   Prerequisites: Chapters 1–4; Parts I–V, or equivalent experience

6. Chapter 6 — Reconciliation and Cross-System Consistency

   120 minutes, plus the practical exercise · Status: Draft · Version: 0.1.0

   Prerequisites: Chapters 1–5; Parts I–V, or equivalent experience

7. Chapter 7 — Batch, Streaming, and Temporal Data Quality

   115 minutes, plus the practical exercise · Status: Draft · Version: 0.1.0

   Prerequisites: Chapters 1–6; Parts I–V, or equivalent experience

8. Chapter 8 — Data Contracts, Lineage, Provenance, and Ownership

   110 minutes, plus the practical exercise · Status: Draft · Version: 0.1.0

   Prerequisites: Chapters 1–7; Parts I–V, or equivalent experience

9. Chapter 9 — Analytics, Metrics, and Reporting Integrity

   115 minutes, plus the practical exercise · Status: Draft · Version: 0.1.0

   Prerequisites: Chapters 1–8; Parts I–V, or equivalent experience

10. Chapter 10 — Production Data Learning, Change, and Sustainability

    110 minutes, plus the practical exercise · Status: Draft · Version: 0.1.0

    Prerequisites: Chapters 1–9; Parts I–V, or equivalent experience

11. Chapter 11 — Capstone: Data Quality Strategy and Evidence Portfolio

    180 minutes, plus the capstone exercise · Status: Draft · Version: 0.1.0

    Prerequisites: Chapters 1–10; Parts I–V, or equivalent experience