Data Freshness & Sync Latency

Concept

Data freshness is the elapsed time between when an event occurs in the real world and when it becomes available to query in your database or warehouse.

Layman Explanation & Analogy

Data freshness is how "up to the minute" your reports are. If a customer places an order at 2:00 PM and your sync pipeline runs once every night at midnight, your data has a 10-hour freshness lag during the afternoon.

Worked real-world example

Stripe syncs transactions via webhooks within 2 seconds (near real-time), while Google Ads Data Transfer updates warehouse tables once every 24 hours (daily batch).

What people get wrong & common traps

Mistaking scheduled pipeline delays for missing data leads to false panic. If an ad connector only syncs at 6:00 AM, reporting on today's live numbers at 10:00 AM will always show zero until the next sync cycle.

Last reviewed August 28, 2026.