Scenario Lab — Scenarios 19–24
Scenario 19 — Trace sensitive field
Stem: Privacy asks where SSN originates, how it is transformed, and which downstream reports receive it.
Leading KA: Metadata Management.
Primary problem: provenance/movement.
Supporting: Security/Privacy, Integration, Governance.
Roles: Privacy, Metadata/lineage team, system owners.
Best: Data Lineage.
Weaker: Impact Analysis—the question is current path, not consequences of a proposed change.
Changed fact: ask what is affected if SSN is removed → Impact Analysis.
Source: pp. 418–419.
Scenario 20 — Column rename planning
Stem: team plans to rename a source field and needs affected ETL jobs, targets, reports, applications.
Leading KA: Metadata Management.
Primary problem: change consequence/dependency analysis.
Supporting: Integration, Architecture, Change Management.
Roles: developers, architects, change manager, Metadata team.
Best: Impact Analysis using integrated Metadata/lineage dependencies.
Weaker: document current lineage only without evaluating dependents.
Changed fact: only need to explain existing path → lineage is sufficient.
Source: pp. 418–419.
Scenario 21 — 95% documented, no users
Stem: program reports excellent critical-element coverage but almost nobody searches the repository.
Leading KA: Metadata Management.
Primary problem: usage/adoption.
Supporting: Socialization, Access, usability, value communication.
Roles: Metadata program/product owner, Governance, consumers.
Best: measure and improve Metadata usage/adoption.
Weaker: celebrate completeness; completeness and use answer different questions.
Changed fact: active use is high but many critical elements undocumented → completeness becomes primary.
Source: p. 423.
Scenario 22 — Many entries, conflicting definitions
Stem: nearly every planned element is documented, but duplicates and contradictory descriptions are common.
Leading KA: Metadata Management.
Primary problem: documentation quality.
Supporting: Standards, Stewardship, Governance, Quality.
Roles: Stewards, Governance, Metadata program team.
Best: prioritize Metadata documentation quality and conflict resolution.
Weaker: focus on coverage—it is already high.
Changed fact: definitions clean but Steward roles missing → Steward representation becomes leading gap.
Source: p. 423.
Scenario 23 — No accountable Stewards
Stem: glossary content exists, ownership fields are blank, and definition disputes remain unresolved for months.
Leading KA: Metadata Management.
Primary problem: stewardship/accountability.
Supporting: Governance, Business Glossary.
Roles: Governance, Data Owners, Data Stewards, Metadata lead.
Best: assign Stewards, define responsibilities/workflow, monitor role coverage and resolution.
Weaker: treat content existence as sufficient.
Changed fact: Stewards assigned but users never access glossary → glossary activity/usage becomes primary.
Source: pp. 421–423.
Scenario 24 — Local repositories everywhere
Stem: modeling, ETL, BI, DQ, CMDB, and database tools each contain Metadata, but there is no enterprise view, shared search, cross-tool lineage, or common standards.
Leading KA: Metadata Management.
Primary problem: fragmented enterprise Metadata knowledge.
Supporting: Governance, Architecture, Integration, Quality.
Roles: sponsor, Metadata lead/architect, Governance, source owners, Stewards.
Best: enterprise Metadata Strategy + Requirements + Architecture/integration program: assess sources, define future pattern, metamodel/standards, integrate priority Metadata, deliver usable access, measure coverage/quality/use.
Weaker: pick one local repository and declare it enterprise-wide.
Changed fact: integration exists but content is stale because refresh jobs fail → Manage Metadata Stores becomes primary.
Source: pp. 403–417.