Dataobservability

Integration

Data Observability for Snowflake, Live in 15 Minutes

Monitor every Snowflake table for freshness, volume, schema, and anomalies, with metadata-first checks that barely touch your compute.

See how it works
SNOWFLAKE · PROD
247 tables |
Break a monitor:

Alerted #data-eng 0.8s ago.

Downstream impact · consumers at risk

INCIDENT #1042 OPEN · owner @you

In one paragraph

Data observability for Snowflake means continuously monitoring your Snowflake tables for freshness, volume, schema changes, and anomalies, plus mapping lineage across your warehouse. Dataobservability connects to Snowflake with read-only access, reads metadata and information-schema statistics rather than scanning full tables, and alerts your team the moment data breaks, so your Snowflake compute cost stays low.

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Why it fits

Snowflake teams on dbt who want monitoring without a six-figure contract or a big compute bill.

Metadata-first on Snowflake

We read account_usage and information_schema statistics, so monitoring barely registers on your warehouse credits.

Auto-monitors on every table

Freshness, volume, schema, and anomaly monitors generate across your Snowflake databases automatically.

Lineage across the account

Column-level lineage spans Snowflake schemas through to dbt and your BI tools.

Live in 15 minutes

Connect your warehouse and watch monitors generate across every table. Transparent pricing, no credit card.