Data professionals spend 40% of their time on quality tasks, with freshness violations causing nearly a third of all data downtime. Engineers end up running constant fire drills instead of building new pipelines.
The freshness problem shifts wildly by context. Fraud detection algorithms need sub-second latency. Marketing dashboards can wait a week. The same extraction system serves both, each with its own decay curve and operational burden.
What gets logged as "successful extraction" often hides the real work: validating timestamps, flagging stale records, managing refresh schedules across dozens of sources that age at different rates.