For data engineering

Fix-first triage for BigQuery + dbt — without babysitting five alert channels.

The problem

DE owns the pipelines. Alerts arrive fragmented. Leadership still asks “is the data good?” while you dig logs and INFORMATION_SCHEMA by hand.

The outcome

Watchdog, freshness, dbt failure triage, and cost spikes in one command center — metadata only, flat pricing, built for small DE teams.

1 queue

Incidents ranked by blast radius

Artifacts

dbt run_results without row access

~15 min

Read-only BigQuery setup

Capabilities

Know what to repair before standup — stale tables, failed models, cost outliers.

Grouped root causes instead of a page per downstream model.

Expensive jobs with concrete next steps — partition filters, clustering hints.

Prove the workflow in /app before requesting credentials.

For analytics

Trust the marts behind your dashboards — and catch the explore that burns the budget.

For founders & operators

A calm reliability net when you have one data person — or none full-time.

RevOps & GTM data

Pipeline boards that are fresh before forecast meetings.

Finance analytics

Close-week freshness and cost spikes without spreadsheet archaeology.