Production Data Monitoring & Quality Assurance

[levelslip]

• Description: Setup monitoring for production data quality
• Activities:
  • Design data quality monitoring:
    • Define quality metrics to track
    • Define alert thresholds
    • Design monitoring dashboards
  • Implement data validation:
    • Create validation rules for incoming data
    • Implement range checks (e.g., wait time < 1000 minutes)
    • Implement consistency checks
    • Implement completeness checks
  • Setup monitoring alerts:
    • Alert if data quality drops below threshold
    • Alert if data volume is unusual
    • Alert if data distribution changes (data drift)
  • Create data health dashboard:
    • Monitor data quality metrics
    • Track data freshness
    • Track data volume trends
  • Document monitoring procedures:
    • Document what is monitored
    • Document alert thresholds
    • Document response procedures
  • Setup data anomaly detection:
    • Detect unusual patterns in data
    • Alert on suspicious data
    • Create anomaly investigation procedures
• Deliverables: Monitoring system, data quality dashboard, procedures documentation