Monitoring area
Data quality
Establish identities, expected observations, missingness and delivery clocks before interpreting a metric.
Data qualityData qualityData qualityData quality
Define the observations a monitoring report expects
Make completeness a comparison against a declared period set, with explicit identity and withholding rules.
Keep missing values separate from zero and invalid data
Trace nulls through quality, drift and outcome calculations without silently imputing information.
Measure delivery freshness without inventing a live heartbeat
Separate report time, declared last update and observation period when reviewing stale data.
Resolve duplicate and unexpected periods before monitoring
Use period identity to detect double counting, window changes and ambiguous return histories.