How do I use a headless BI workflow?
Metrics and queries are defined in code and served through an API instead of a fixed visual interface. Applications and scheduled jobs request the numbers directly, so the same definitions drive charts, alerts, and exports. Bruin does this in one platform: ingestion, SQL and Python pipelines, quality checks, lineage, and an AI data analyst that answers in Slack, Microsoft Teams, Google Chat, WhatsApp, Discord, Telegram, email and the browser.
Command
bruin runDefined in
YAML + SQL
Works with
Bruin + your warehouse
What you get
How it works in code
query:
metric: active_users
time_dimension: event_date
grain: day
filters:
- plan = 'pro'
order_by: event_dateRun bruin run and any client can request the metric over the API.
Related use cases
Define a dashboard as code
How do I define a dashboard as code?
Dashboards as codeBuild a metrics layer so metrics stay consistent
How do I build a metrics layer so metrics stay consistent?
Dashboards as codeBuild dashboards directly from dbt models
How do I build dashboards directly from dbt models?
Dashboards that live in git
Bruin CLI and ingestr are on GitHub.
A demo walks through your own data.