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16.9 Troubleshooting & Reconciliation Labs

Lab 1 — CDS view not visible​

Investigate:

  • source release,
  • extraction enablement,
  • connection type,
  • source authorizations,
  • supported object type,
  • required SAP Notes.

Do not immediately recreate the connection.

Lab 2 — Initial load succeeds, totals differ​

Check:

  1. grain,
  2. filters,
  3. deleted records,
  4. currency,
  5. unit,
  6. time zone,
  7. source selection logic,
  8. transformation.

A successful load is not evidence of correct data.

Lab 3 — Delta stopped​

Determine:

  • source delta state,
  • last successful package,
  • subscriber state,
  • target commit,
  • source changes during outage,
  • recovery or reinitialization requirement.

Lab 4 — Duplicate target rows​

Investigate:

  • source key,
  • target key,
  • duplicate source records,
  • incorrect key configuration,
  • parallel processing,
  • replay behavior.

Lab 5 — S/4HANA performance degradation​

A replication flow becomes slow after increasing parallelism.

Investigate:

  • source CPU,
  • database workload,
  • network,
  • thread settings,
  • competing workloads,
  • target throughput.

Architect answer:

More parallelism is a hypothesis, not a guarantee.

Lab 6 — Delete not reflected​

Determine whether the selected extraction mechanism supports the required delete semantics.

If not, redesign the contract rather than inventing a target-side workaround.

Lab 7 — Source schema changed​

Classify:

  • compatible metadata change,
  • breaking semantic change,
  • key change,
  • type change,
  • removed field.

Then determine supported Datasphere behavior and required consumer testing.

Lab 8 — Wrong CDS view​

A team selected a technically accessible CDS view with the wrong grain.

Fix the design by returning to:

business object -> supported view -> grain -> extraction -> target.

Lab 9 — Production readiness review​

Review:

  • source prerequisites,
  • security,
  • delta,
  • performance,
  • reconciliation,
  • monitoring,
  • recovery,
  • ownership.

Lab 10 — Architect scenario​

S/4HANA Finance feeds Datasphere, BW/4HANA, SAC, and a data science platform.

Design:

  • source contracts,
  • acquisition patterns,
  • persistence,
  • semantic layer,
  • governance,
  • security,
  • operational ownership.

For each choice, state one rejected alternative and why.