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Chapter 12 — Metadata Management

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CDMP Fundamentals weight: 11% — major domain
Source boundary: DAMA-DMBOK2 Revised, Chapter 12, pp. 395–423.

Metadata Management is not merely “data about data.” In Chapter 12 it is the discipline that makes organizational knowledge about data reusable: meaning, structures, systems, rules, ownership, quality, security, lineage, operations, and relationships.

Chapter mental model

WHAT DOES IT MEAN? → WHERE IS IT? → WHERE DID IT COME FROM? → WHAT HAPPENS TO IT? → WHO OWNS/USES IT? → CAN I TRUST IT? → WHAT BREAKS IF IT CHANGES?

That sequence explains why Metadata connects almost every other DMBOK knowledge area. A field can exist physically while still being difficult to use if nobody knows its definition, owner, source, transformations, quality state, security classification, or downstream dependencies.

Current-source study system

  1. Guided Learning — 10 teaching lessons built from the current Drive guide.
  2. Exam Map & High-Yield Targets — 17 Tier-1 targets plus changed-fact discrimination.
  3. Visual Memory Map / Framework Atlas — 12 redraw-ready maps.
  4. Comparison & Battle Cards — 36 rapid + 12 deep cards.
  5. Scenario Lab — 24 scenarios + integrated capstone.
  6. Question Bank — 68 questions with separate diagnostics.
  7. Teach-Back & Blank-Page Recall — 80 recalls, 12 rebuilds, 20 classifications, 3 compression drills.

The seven ideas to keep connected

  • Types: Business = meaning/governance; Technical = implementation/movement; Operational = runtime evidence.
  • Sources: enterprise Metadata already exists across glossaries, dictionaries, catalogs, models, integration tools, databases, BI, DQ, CMDBs, services, and other repositories.
  • Architecture: Centralized, Distributed, Hybrid, and Bi-Directional differ mainly by persistence and update flow.
  • Lifecycle: Strategy → Requirements → Architecture → Create/Maintain → Query/Report/Analyze.
  • Integration: harvest, stage, standardize, map, resolve conflict, merge, audit, deliver.
  • Dependencies: As Designed vs As Implemented lineage; Lineage vs Impact Analysis.
  • Evidence: completeness, quality, stewardship, usage, glossary activity, maturity, and service reuse answer different questions.

Exam warning

A Metadata question often contains several true statements. The best answer normally turns on one deciding clue: meaning vs structure vs runtime; persistent copy vs live retrieval; selected persistence vs write-back; intended design vs actual code; trace path vs predict consequence; coverage vs quality vs adoption.

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