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Scenario Lab 07–12

7 — Vendor system exposes change table

Stem: application stores inserts, updates and deletes in a dedicated log table.

  • Primary: source-supported CDC.
  • Supporting: Integration, audit/control, operations.
  • Roles: source owner, integration engineer, DW operations.
  • Best: log-table delta CDC using explicit change records.
  • Weaker: full compare despite good change evidence; unnecessary processing.
  • Changed: no usable change indicator → full comparison may become necessary.
  • Source: pp. 371–374.

8 — Five-minute mini-batches

Stem: loads fire every five minutes or after a source threshold.

  • Primary: low-latency source-side accumulation.
  • Best: trickle feed.
  • Weaker: call it streaming solely because frequent; streaming clue is target queue/buffer.
  • Changed: tiny events published to shared bus → messaging.
  • Source: pp. 372–374.

9 — Events on enterprise bus

Stem: targets subscribe independently to transaction events.

  • Primary: event-based middleware integration.
  • Roles: integration architect, message-platform team, source/target owners.
  • Best: messaging through bus/pub-sub.
  • Weaker: trickle; no source-side mini-batch clue.
  • Changed: continuous direct arrivals accumulate in target queue → streaming.
  • Source: pp. 372–374.

10 — Target queue

Stem: warehouse continuously receives events and processes them in order from its buffer.

  • Primary: target-side continuous-flow accumulation.
  • Best: streaming.
  • Weaker: messaging when no middleware bus is the accumulation/distribution point.
  • Changed: source accumulates count/time threshold before sending → trickle feed.
  • Source: pp. 372–374.

11 — Dashboard request starts the project

Stem: team immediately catalogs tables without clarifying goals/questions.

  • Primary: requirements sequence/business alignment.
  • Supporting: Architecture, BI portfolio, source assessment, Governance.
  • Roles: sponsor, analysts, DW/BI product team, architect.
  • Best: clarify goals, decisions, KPIs, users, grain/history/latency/security before committing to sources/tools.
  • Weaker: build from easiest tables; lets source availability drive business scope.
  • Changed: questions/KPIs already clear → profiling/mapping can proceed.
  • Source: pp. 374–376.

12 — Equivalent fields, different names

Stem: three billing systems label customer identifiers differently.

  • Primary: source-to-target semantic mapping.
  • Supporting: Metadata, Modeling, Integration, Governance.
  • Roles: Modeler, integration engineer, Steward/SME.
  • Best: source-to-target mapping using common logical taxonomy/enterprise semantics.
  • Weaker: automatically label different names as DQ defects; they may be valid source-specific semantics.
  • Changed: malformed/invalid values → remediation becomes primary.
  • Source: pp. 375–379.

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