transformation
Power BI Monitoring for dbt Cloud
dbt Cloud runs SQL transformations that produce the tables and views that Power BI queries. When a dbt job fails or a model produces wrong output, Power BI refreshes against bad data — often without any error. MetricSign integrates with dbt Cloud to monitor job runs, parse failed model errors, and surface them alongside the Power BI datasets that depend on those models.
What you can monitor
- Get alerted when a dbt Cloud job fails, with the exact model name and error type from the run steps
- Trace a Power BI dataset refresh failure back to the dbt model that wrote its source table
- Detect schema changes introduced by dbt that break downstream Power BI measures or relationships
- See dbt run history and Power BI refresh history in a single timeline
How MetricSign helps
01dbt Cloud job and run monitoring with step-level error detail
02Automatic manifest lineage parsing — links dbt models to Power BI source tables
03Incident creation for job_failed with the specific model and error from run steps
04Chain visualization: dbt model → database table → Power BI model → report
MetricSign vs alternatives
Existing tools like dbt Cloud native alerts, Slack notifications from dbt Cloud, Monte Carlo are built for their own domain — not for connecting dbt Cloud failures to downstream Power BI report health. MetricSign bridges that gap: you get one incident feed that covers both layers without switching between dashboards.
Alternatives
—dbt Cloud native alerts
—Slack notifications from dbt Cloud
—Monte Carlo
MetricSign
✓Covers dbt and Power BI in one view
✓Chain visualization from source to report
✓One incident feed, not multiple alert tools
✓Free to start, no credit card required