Asana + Bruin

Source

Ingest Asana 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
Asana data in your warehouse means analytics that Asana's built-in reporting can't provide. Cross-tool, cross-team, custom.
Cross-tool project views
Combine Asana 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 Asana data — automatically updated.
No manual data pulling
Asana 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 Asana records. No full reloads, no wasted compute.
YAML-defined, Git-versioned
Your Asana pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert.
Schema change handling
Bruin detects Asana schema changes automatically. No manual intervention when fields get added or renamed.
Cross-tool joins
Combine Asana data with other tools in SQL transforms. Bruin resolves dependencies across sources automatically.

Before you start

Personal access token from Asana developer console

Step 1

Add your Asana connection

Connect using workspace ID and personal access token. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.

Parameters

workspace_idThe gid of the workspace
access_tokenPersonal access token from Asana developer console

connections:
  asana:
    type: asana
    uri: "asana://<workspace_id>?access_token=<access_token>"

Step 2

Create your pipeline

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

Available tables

workspacesprojectssectionstagstasksstoriesteamsusers

name: raw.asana_workspaces
type: ingestr

parameters:
  source_connection: asana
  source_table: 'workspaces'
  destination: bigquery

Step 3

Add quality checks

Add column-level and custom SQL checks to your Asana 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.asana_workspaces

Step 4

Run it

One command. Bruin connects to Asana, 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 Asana to your dashboards

$ bruin run .

Running pipeline...

  asana_workspaces
    ✓ 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

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Ready to connect Asana?

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