Google Drive + Bruin

Source

Ingest Google Drive 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

Operational analytics
Google Drive data in your warehouse means analytics that Google Drive's built-in reporting can't provide. Cross-tool, cross-team, custom.
Cross-tool project views
Combine Google Drive with Jira, GitHub, Slack, and other tools. One dashboard that shows the real state of projects.
Team workload insights
Understand collaboration patterns, bottlenecks, and workload distribution from Google Drive data — automatically updated.
No manual data pulling
Google Drive data syncs on schedule. Managers and leads get fresh data without asking anyone.

For data & engineering teams

How it works

Incremental sync
Only sync new and changed Google Drive records. No full reloads, no wasted compute.
YAML-defined, Git-versioned
Your Google Drive pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert.
Schema change handling
Bruin detects Google Drive schema changes automatically. No manual intervention when fields get added or renamed.
Cross-tool joins
Combine Google Drive data with other tools in SQL transforms. Bruin resolves dependencies across sources automatically.

Before you start

Google Cloud project with Drive API enabled

OAuth2 credentials with appropriate Drive scopes

Step 1

Add your Google Drive connection

Connect using Google OAuth2 credentials. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.

Parameters

client_idGoogle OAuth2 client ID from Cloud Console
client_secretGoogle OAuth2 client secret
refresh_tokenGoogle OAuth2 refresh token with Drive API scopes

connections:
  google_drive:
    type: google-drive
    uri: "google-drive://?client_id=<your-client-id>&client_secret=<your-client-secret>&refresh_token=<your-refresh-token>"

Step 2

Create your pipeline

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

Available tables

filesfolderspermissionsrevisionscomments

name: raw.google_drive_files
type: ingestr

parameters:
  source_connection: google_drive
  source_table: 'files'
  destination: bigquery

Step 3

Add quality checks

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

Validate workspace data synced completely

Ensure record IDs are unique and titles are present

Catch missing or null fields on every sync

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

custom_checks:
  - name: workspace sync is complete
    query: |
      SELECT COUNT(*) > 0
      FROM raw.google_drive_files

Step 4

Run it

One command. Bruin connects to Google Drive, 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 Google Drive to your dashboards

$ bruin run .

Running pipeline...

  google_drive_files
    ✓ 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 Productivity integrations

Airtable

Asana

Bitbucket

Calendly

Canny

ClickUp

Ready to connect Google Drive?

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