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Data Incident Post-Mortem
Structured root-cause analysis of data quality incidents to prevent recurrence and improve data pipelines.
Updated June 2026
The prompt
Incident: {{incident_title}}. Date: {{incident_date}}. Severity: {{severity_level}}. Detection: {{detection_method}}. Duration: {{duration}}. Impact: {{impact_description}}. Conduct post-mortem: 1. Timeline: trace exact sequence of events 2. Root cause analysis: {{primary_cause}} → {{secondary_causes}} 3. Why wasn't this caught? (monitoring, alerting, testing gaps) 4. Downstream impact: which {{metric_impacted}} were affected, by how much? 5. Corrective actions (immediate vs. long-term) 6. Monitoring additions to prevent recurrence 7. Communication plan: who needs to know, what message?
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Author
AI Khazna
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Security
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