Power BI + Bruin

Source

Ingest Power BI data into your warehouse with incremental loading, quality checks, and full lineage. Defined in YAML, version-controlled in Git.

For business teams

What you get

Dashboards powered by clean data
Feed Power BI from Bruin pipelines with built-in quality checks. No more stale or incorrect dashboards.
End-to-end lineage to ${pn}
Trace data from raw sources through every transformation to Power BI. Find the root cause of wrong numbers in seconds.
Scheduled data refresh
Bruin pipelines refresh Power BI data on a cron. Dependencies resolve automatically — Power BI only sees complete data.
Multi-source, one destination
Combine 100+ sources into clean models that power Power BI. Bruin handles the pipeline, Power BI handles the visuals.

For data & engineering teams

How it works

Dependency-aware scheduling
Bruin ensures upstream transforms complete before Power BI gets new data. No more stale or partial dashboards.
YAML-defined, Git-versioned
Every pipeline feeding Power BI is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert.
Quality gates before visualization
Quality checks run before data reaches Power BI. If checks fail, Power BI keeps showing the last known good data.
End-to-end lineage
Trace data from raw sources through transforms to Power BI dashboards. Find root causes in seconds, not hours.

Before you start

Power BI Pro or Premium workspace

Azure AD app with Power BI API permissions

Admin consent for Power BI Service

Step 1

Add your Power BI connection

Connect using Azure AD service principal. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.

Parameters

client_idAzure AD application client ID
client_secretAzure AD application client secret
tenant_idAzure AD tenant identifier

connections:
  powerbi:
    type: powerbi
    uri: "powerbi://client_id:client_secret@tenant_id"

Step 2

Create your pipeline

Define a YAML asset that tells Bruin what to pull from Power BI and where to land it. This file lives in your Git repo — reviewable, version-controlled, and deployable with CI/CD.

Available tables

datasetsreportsdashboardsworkspacesdataflowsrefresh_history

name: raw.powerbi_datasets
type: ingestr

parameters:
  source_connection: powerbi
  source_table: 'datasets'
  destination: bigquery

Step 3

Add quality checks

Add column-level and custom SQL checks to your Power BI data. If a check fails, the pipeline stops — bad data never reaches downstream models or dashboards.

Validate data freshness before it reaches dashboards

Ensure IDs are unique across syncs

Block stale data from appearing in visualizations

columns:
  - name: id
    checks:
      - name: not_null
      - name: unique

custom_checks:
  - name: data is fresh
    query: |
      SELECT MAX(updated_at) >
        TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 24 HOUR)
      FROM raw.powerbi_datasets

Step 4

Run it

One command. Bruin connects to Power BI, pulls data incrementally, runs your quality checks, and lands clean data in your warehouse. If a check fails, the pipeline stops — bad data never reaches downstream.

Backfill historical data with --start-date

Schedule with cron or trigger from CI/CD

Full lineage from Power BI to your dashboards

$ bruin run .

Running pipeline...

  powerbi_datasets
    ✓ Fetched 2,847 new records
    ✓ Quality: campaign_id not_null     PASSED
    ✓ Quality: spend not_null           PASSED
    ✓ Quality: no negative ad spend     PASSED
    ✓ Loaded into bigquery

  Completed in 12s

Other Data Analytics Platform integrations

Looker

Metabase

Tableau

Ready to connect Power BI?

Start for free, or book a demo to see how Bruin handles ingestion, quality, lineage, and scheduling for your entire data stack.

Book a demo Read the docs