A data quality score that stopped flattering the data
The problem
Most completeness metrics count a field as filled as soon as something is in it. Here that included N/A,
- Choose - and — in one case — today's date, entered as a placeholder regardless of when the event actually ran.
The field looked 98% complete and meant almost nothing.
What I built
- A completeness score for 18 mandatory fields across 464 events, per field, per manager and per business unit.
- Placeholders counted as missing, not as filled — the part where most completeness metrics quietly lie.
- Rankings by owner, so every gap has a name next to it while it can still be fixed.
Field completeness, March to September 2026
Share of records where the field holds a real value.
Result
Market unit completeness went from 25% to 86% in six months — the field was not mandated or chased. It became visible next to someone's name, and it filled itself.
Event start date dropped from 98% to 83% once placeholder dates stopped counting. The metric got worse and the reporting got honest: you cannot plan around a date that just says today.
Relevant if your role mentions
Data qualityData governanceData validation Master dataAccountability reportingDo you trust your completeness numbers? Tell me which fields matter most — two lines are enough.
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