Late-Arriving Data

Events or records that reach a processing system after their expected event-time window or reporting period.

Why it matters

Late-Arriving Data 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.