Checks from pipelines

CatalystData runs checks on a schedule, from the app. A data pipeline fits in by timing: schedule the checks that depend on a load to run once that load is expected to be complete, and let an alert rule tell the team when something is wrong.

Schedule checks to run after the pipeline

The most common pattern: schedule the check to run a few minutes after your pipeline's known completion time — for example, if a nightly dbt run finishes by 2:00 AM, schedule the checks that depend on it for 2:15 AM. Combine this with an alert rule so your team is notified the moment a scheduled check fails, rather than needing to poll the Results screen.

This is the right fit for most "did last night's load look right" needs, and does not require the pipeline itself to know anything about CatalystData.

Group the checks that cover one pipeline

Put the checks that cover one pipeline's output into a single schedule on the Scans screen. They run together after that pipeline, show up together in Results, and can share one alert rule — so a failing load produces one notification with everything that broke, rather than one per check.

Failing the pipeline itself on a check failure

Some teams want the pipeline run to fail synchronously when a check fails — a quality gate before a promotion, or before dbt build is considered successful. That's not available today: it would require calling CatalystData directly to trigger a run and read back the result, and that isn't offered yet. If your pipeline needs a synchronous quality gate rather than a scheduled check with an alert, talk to your CatalystData contact — it's useful to know there's demand for it.