📖 DMBOK Chapter Library — Chapters 1–17
Choose the chapter by exam importance, then jump directly to the study tool you need. Every chapter keeps the same pattern: Learn → Compare → Apply → Test → Recall → Source.
All 17 current Drive chapter packages have been freshly converted into GitHub-readable study pages, and every chapter contains its original DMBOK source PDF locally in the private repository. Artifact 08 remains performance-driven.
🔥 Highest-weight Fundamentals — study deepest and revisit most often
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🔥 Chapter 3 — Data Governance · 11%
Authority, decision rights, stewardship, policy/standards, operating models, issue escalation, and sustained governance.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🔥 Chapter 5 — Data Modeling & Design · 11%
Conceptual → logical → physical modeling, keys, relationships, dimensional modeling, normalization, traceability, and change.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🔥 Chapter 12 — Metadata Management · 11%
Meaning, structure, runtime evidence, lineage, impact, architecture, integration, governance, and reusable organizational knowledge about data.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🔥 Chapter 13 — Data Quality Management · 11%
Fit for purpose, critical data, dimensions, rules, metrics, thresholds, profiling, root cause, operations, monitoring, and improvement.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🔥 Chapter 10 — Reference & Master Data · 10%
Shared classifications, persistent entity identity, authority, golden records, matching, identifiers, architecture, stewardship, and sharing.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🔥 Chapter 11 — Data Warehousing & BI · 10%
Analytical architecture, history/grain/latency, staging/ODS/DW/marts, dimensional structures, CDC, BI delivery, lineage, and product operations.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
🟦 Mid-weight Fundamentals — 6% each
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🟦 Chapter 4 — Data Architecture · 6%
Enterprise blueprints, flows, target states, transition roadmaps, standards, governance, and strategy alignment.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🟦 Chapter 6 — Data Storage & Operations · 6%
Availability, integrity, DBMS support, operations, backup/recovery, retention, replication, performance, environments, and continuity.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🟦 Chapter 7 — Data Security · 6%
Classification, entitlements, policy/standards, risk, controls, monitoring, evidence, audit, and legitimate business access.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🟦 Chapter 8 — Data Integration & Interoperability · 6%
Requirements, discovery, mapping, orchestration, ETL/ELT, services, movement, latency, lineage, reliability, and governed exchange.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🟦 Chapter 9 — Document & Content Management · 6%
Documents, records, classification, version/control, retention, legal hold, disposition, search, publication, e-discovery, and defensibility.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
🟨 Foundation / recognition-weight chapters
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🟨 Chapter 1 — Data Management · 2%
Orientation to Data Management, strategy, lifecycle, major DAMA frameworks, Knowledge Areas, and the profession as a whole.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🟨 Chapter 2 — Data Handling Ethics · 2%
Ethical principles, recurring unethical-practice patterns, privacy-management principles, culture, controls, and responsible action.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🟨 Chapter 14 — Big Data & Data Science · 2%
Big Data characteristics, analytics horizon, sources, ingestion, architecture, mining/ML, model evidence, deployment, governance, and value.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
🟪 Supporting / specialist chapters
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🟪 Chapter 15 — Data Management Maturity Assessment
Evidence-supported baselines, maturity levels, current vs target state, business-prioritized gaps, roadmaps, improvement, and reassessment.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🟪 Chapter 16 — Data Management Organization & Roles
Operating-model fit, accountability, committees, stakeholder engagement, DMO/CDO/DG/DQ/EA interfaces, roles, adoption, and evolution.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
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🟪 Chapter 17 — Organizational Change Management
Bridges, Kotter, Gleicher, Rogers, communication planning, sponsorship, coalitions, adoption, resistance, sustainment, and behavior change.
📘 Overview · 🧠 Learn · ⚔️ Battle · 🧩 Scenarios · ❓ Questions · 🔁 Recall · 📕 PDF · 🗃️ Originals
📎 Source access
Every chapter has two source paths:
- 📕 PDF — the original DMBOK chapter stored locally in this private GitHub repository at
source/original-dmbok-chapter.pdf. - 🗃️ Formatted Originals — the chapter Source panel linking the current Google Drive Guided Learning, Exam Map, Visual Atlas, Battle Cards, Scenario Lab, Question Bank, Teach-Back, and Drive source copy.
Open any chapter Overview and use its standard Quick Study Navigation to reach both.
⚔️ When chapter-pure work is no longer enough
📕 Confusion Book · ⚔️ Battle Rounds · 🧩 Mixed Scenarios · 🏢 Cross-Domain Case Studies · ⏱️ Exam Conditioning
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