Skip to content

Scenario Lab 13–18

13 — Dirty source values

Stem: load discovers malformed customer-state values.

  • Primary: DQ defect/root cause.
  • Supporting: Integration, Metadata, Governance, source stewardship.
  • Roles: Steward, DQ specialist, source owner, integration team.
  • Best: remediate/correct source where possible; define controlled warehouse exception handling and monitor recurrence.
  • Weaker: hide every defect via warehouse transformation; preserves upstream root cause.
  • Changed: valid values converted per business rule, e.g. currency/units → transformation.
  • Source: pp. 375–379.

14 — Unknown dimension arrives late

Stem: fact arrives before dimension; business accepts controlled provisional handling.

  • Primary: load-order exception with allowed provisional member.
  • Supporting: Dimensional modeling, population, Metadata/audit.
  • Roles: DW designer, integration engineer, Steward as needed.
  • Best: optimistic load—create provisional/unknown dimension member, load fact, reconcile correctly later.
  • Weaker: reject despite explicitly allowed temporary handling.
  • Changed: policy forbids unresolved facts → pessimistic recycle.
  • Source: pp. 377–379.

15 — Fact cannot resolve to dimension

Stem: policy forbids inventing a member.

  • Primary: referential/load exception under strict rule.
  • Best: pessimistic recycle/reject with alert, correction and later reload.
  • Weaker: random/placeholder member contrary to policy.
  • Changed: controlled provisional members allowed → optimistic may fit.
  • Source: pp. 377–379.

16 — One BI tool for everyone

Stem: executives, power users and front-line staff are forced into one interface.

  • Primary: BI portfolio/user segmentation.
  • Supporting: Requirements, support, security, cost/governance.
  • Roles: BI product owner, architects, CoE/support, user representatives.
  • Best: segment users and match capabilities/tools to needs while rationalizing portfolio.
  • Weaker: one interface solely for admin simplicity.
  • Changed: users truly share similar workflows/capabilities → common tool can be appropriate.
  • Source: pp. 379–384.

17 — Users build dashboards themselves

Stem: business users explore governed warehouse data and share dashboards.

  • Primary: self-service BI governance.
  • Supporting: Metadata, Security, DQ, Governance, support.
  • Roles: analysts, BI CoE, Stewards, security/governance.
  • Best: governed self-service on trusted reusable data, shared definitions, lineage, permissions, training/support, publication controls.
  • Weaker: assume every user-created dashboard is successful self-service.
  • Changed: no governed data/Metadata/security → unmanaged analysis; establish guardrails.
  • Source: pp. 382–386, 389–392.

18 — Where did this KPI come from?

Stem: auditor wants origin and transformation path.

  • Primary: provenance/traceability.
  • Supporting: Metadata, Governance, Integration, audit.
  • Roles: Metadata owner, Steward, integration/DW team, auditor.
  • Best: end-to-end lineage supported by source-target and transformation Metadata.
  • Weaker: provide glossary definition only; explains meaning, not provenance.
  • Changed: question is only “what does this field mean?” → dictionary/glossary first.
  • Source: pp. 363–364, 385–391.

← Scenarios 07–12 · Scenarios 19–24 →