The CEO's revenue dashboard showed wrong numbers for two days before anyone noticed. How do you fix this and prevent it from happening again?

What the interviewer wants to hear

• Immediate fix, backfill and clear communication
• Root cause analysis without blame
• Add tests on business logic and reconciliation with source
• Anomaly detection on key metrics and freshness
• Ownership, SLAs and alert routing
• Circuit breakers so bad data does not publish

Model answer

First I would fix the data: find the bug, correct it, backfill the two days, and tell stakeholders clearly what was wrong, which numbers were affected and when it was fixed. Then a blameless post-mortem to find the root cause, for example a source change that doubled refunds, and why our checks missed it. Prevention has several layers. Add tests on business logic, not just schemas, such as revenue matching the payment system within 0.5% each day. Add anomaly detection on key metrics and row counts, plus freshness SLAs. Make critical models a circuit breaker: if tests fail, the dashboard keeps showing yesterday's data with a warning instead of wrong numbers. Assign clear owners to critical tables, with alerts routed to on-call rather than a channel nobody reads. Finally, agree on a data contract with the source team so schema or meaning changes are announced.

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