ClickUp + Bruin

Source

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

Before you start

ClickUp API key from account settings

Step 1

Add your ClickUp connection

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

Parameters

api_keyAPI key for ClickUp authentication

connections:
  clickup:
    type: clickup
    uri: "clickup://?api_key=<api_key>"

Step 2

Create your pipeline

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

Available tables

workspacesspacesprojectsliststasksmembersgoals

name: raw.clickup_workspaces
type: ingestr

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

Step 3

Add quality checks

Add column-level and custom SQL checks to your ClickUp 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.clickup_workspaces

Step 4

Run it

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

$ bruin run .

Running pipeline...

  clickup_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

Other Productivity integrations

Airtable

Asana

Bitbucket

Calendly

Canny

Confluence

Ready to connect ClickUp?

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