FundraiseUp + Bruin

Source

Ingest FundraiseUp 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

Revenue reporting you can audit
FundraiseUp transaction data flows into your warehouse with quality checks that validate amounts, currencies, and reconciliation — every single sync.
MRR/ARR calculated right
Combine FundraiseUp with subscription data to automate MRR, ARR, and churn calculations. Finance gets numbers, not guesswork.
Catch issues before close
Quality checks flag missing transactions, amount mismatches, and anomalies. Finance finds out from Bruin, not from the CFO.
Unified financial view
Join FundraiseUp with your ERP, CRM, and other financial tools. One source of truth for revenue, not five spreadsheets.

For data & engineering teams

How it works

Idempotent incremental loads
Re-runs are safe. Bruin's merge strategy ensures FundraiseUp transactions are never duplicated, even on retry.
YAML-defined, Git-versioned
Your FundraiseUp pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert. Auditors love this.
Reconciliation checks
Custom SQL checks validate that amounts balance and currencies match. Pipeline stops if something doesn't add up.
Multi-destination support
Land FundraiseUp data in BigQuery, Snowflake, Redshift, or DuckDB. Switch destinations by changing one line.

Before you start

FundraiseUp private API key

Step 1

Add your FundraiseUp connection

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

Parameters

private_keyFundraiseUp private API key

connections:
  fundraiseup:
    type: fundraiseup
    uri: "fundraiseup://?private_key=<private_key>"

Step 2

Create your pipeline

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

Available tables

donationsdonorscampaignsrecurring_donations

name: raw.fundraiseup_donations
type: ingestr

parameters:
  source_connection: fundraiseup
  source_table: 'donations'
  destination: bigquery

Step 3

Add quality checks

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

Validate that credits and debits balance

Catch null amounts and missing currencies

Ensure transaction IDs are unique — no duplicates

columns:
  - name: transaction_id
    checks:
      - name: not_null
      - name: unique
  - name: amount
    checks:
      - name: not_null
  - name: currency
    checks:
      - name: not_null

custom_checks:
  - name: amounts balance
    query: |
      SELECT ABS(SUM(credit) - SUM(debit)) < 0.01
      FROM raw.fundraiseup_donations

Step 4

Run it

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

$ bruin run .

Running pipeline...

  fundraiseup_donations
    ✓ 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 FundraiseUp?

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