Hi all,

We’ve been improving our data quality monitoring for several pipelines, but we keep running into the same problem — too many alerts, most of which aren’t actionable. Over time, it becomes harder to trust them.

Right now, we’re doing:

• Freshness checks

• Volume anomaly detection

• Schema change alerts

• Some data lineage tracking

Recently, we started using Sifflet to automate checks and add context, which has already reduced alert fatigue quite a bit. But I’d love to hear what others are doing to strike the right balance between coverage and noise.

How do you configure your checks so alerts are both accurate and actionable?