Rapid Recall Key 41–80

1. Centralized = one persistent enterprise repository stores copies harvested from source tools.
2. Strengths: common consistency/global search/standard presentation/manual enrichment. Challenges: extraction, synchronization, adapters, maintenance/currency.
3. Distributed = one common access point queries source Metadata in real time and keeps no persistent central repository.
4. That no-persistence feature distinguishes it from Centralized/Hybrid; Metadata remains source-held.
5. Benefits include source-held current values; challenges include source availability/quality dependency, no central manual content, harder standardized presentation and persistent global analysis.
6. Hybrid = selected critical/standard/manual/enriched Metadata persists centrally while other source details are retrieved live.
7. Useful for rapidly changing operational Metadata, need for enterprise consistency, and increasing Metadata/source volume.
8. Bi-Directional = controlled Metadata changes can flow both toward the enterprise environment and back to originating sources.
9. Synchronization/version/conflict risk; the environment must coordinate authority and latest state carefully.
10. Define Metadata Strategy → Understand Metadata Requirements → Define Metadata Architecture → Create and Maintain Metadata → Query, Report, and Analyze Metadata.
11. Create Metamodel; Apply Metadata Standards; Manage Metadata Stores.
12. Integrate Metadata; Distribute and Deliver Metadata.
13. Charter/scope/objectives/stakeholders/communications; interviews; current source assessment; future architecture including Governance/security/delivery; phased plan.
14. Architecture and product decisions must follow what business/technical consumers actually need and at what detail.
15. Maintenance/change/approval; roles; quality; volatility/currency; search/access/integration; history/versioning; security and other functional/non-functional needs.
16. Metadata can expose existence, location, structure, ownership, movement, or security context of protected data even when values are hidden.
17. Metamodel = data model for the Metadata repository/environment—Metadata entities, attributes, relationships.
18. Data Model describes business/data structures; Metamodel describes Metadata structures/relationships.
19. The metamodel must reflect agreed Metadata content and relationships required by strategy/consumers, not arbitrary tool structures.
20. Establish/enforce internal/external conventions such as naming, custom attributes, security/visibility, and exchange standards.
21. Repository movement/updates, warnings/job logs, interface issues, administrative controls, metrics, training/operations, Governance oversight.
22. Plan and control Metadata creation/change, source accountability, standards, integration, stewardship, quality, delivery, and feedback.
23. Staging supports controlled integration, rollback/recovery, and an interim audit trail for source/quality investigation.
24. Extract/harvest → stage → standardize → map equivalent concepts → resolve conflict/overlap → merge/load managed Metadata.
25. Portal/intranet; reports/glossaries/documents; DW/data marts/BI; application layers; flat/XML/JSON files; web services/APIs.
26. Metadata creates organizational value only when consumers/systems can access and use it.
27. Discover/understand assets, query definitions, support BI/operations, troubleshoot, govern, trace lineage, analyze impact, and measure Metadata itself.
28. As Designed = mapping/specification/intended flow; As Implemented = actual code/implemented processing.
29. Lineage traces origin/movement/transformation; Impact identifies dependencies affected by a proposed change.
30. Lineage only covers systems/processes for which the Metadata environment has sufficient source coverage/visibility.
31. Capture preserves context while it is known; waiting risks hard-to-find, hard-to-govern objects.
32. Roles/responsibilities, ownership/stewardship, standards/compliance, quality/currency/completeness, security/access, change/approval/maintenance, issues/feedback, repository oversight.
33. Implementation status; source/target stores; schedules; retention/versioning; content; quality warnings; SOR/source status/history/retirement; tools/architectures/people; sensitive-information masking/removal.
34. Repository completeness; Metadata Management maturity; Steward representation; Metadata usage; Business Glossary activity; Master Data service data compliance; Metadata documentation quality.
35. Completeness = how much in-scope Metadata exists; Usage = whether consumers actually access/use it.
36. Steward representation = whether accountable Stewards/roles are assigned; documentation quality = correctness/consistency/fitness of Metadata content.
37. Overall organizational capability/maturity in managing Metadata.
38. Glossary use, updates, definition resolution, and coverage/activity.
39. Metadata helps developers discover/reuse Master Data services; the metric reflects service reuse/compliance.
40. Business need → Strategy → Requirements → Architecture → Metamodel/Standards → Harvest/Integrate → Quality/Security/Governance → Deliver/Use → Lineage/Impact → Metrics/Improvement.

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