Data Completeness

The degree to which required records, fields, and time periods are present in a dataset.

Why it matters

Data Completeness helps data teams design systems that are reliable, understandable, governable, and efficient at scale.

Design considerations

• Define ownership, contracts, and expected consumers.
• Make failure, replay, compatibility, and observability behavior explicit.
• Measure quality, freshness, cost, and operational burden rather than optimizing only throughput.