Unified Donor Data Platform Integrating 8 Fundraising Sources for a Healthcare Foundation
A healthcare foundation collected donations through 8 platforms — online giving, events, grants, direct mail, and more. We integrated all 8 sources into Fabric with automated duplicate resolution for a single donor view.
About the Client
The Challenge
A healthcare foundation collected donations through 8 platforms — online giving, events, grants, direct mail, and more. We integrated all 8 sources into Fabric with automated duplicate resolution for a single donor view. The organization had reached an inflection point — donor data lived in 5+ separate systems with no unified view. Grant reporting was manual, error-prone, and always late. Program impact was measured anecdotally, not analytically — making it hard to justify funding renewals.
IRS 990 reporting, grant compliance requirements, and donor privacy regulations added complexity that generalist technology vendors consistently underestimated. Previous initiatives had stalled because the technology partner didn't understand these constraints — delivering solutions that technically worked but failed compliance review or didn't fit operational workflows.
The executive sponsor set clear expectations: measurable impact within one quarter. They needed a partner with both data engineering expertise and non profit domain knowledge — someone who could deliver quickly without creating compliance risk or workflow disruption.
Our Approach
We designed a phased approach optimized for speed-to-value:
Assessment & Architecture (Weeks 1-2)
Cataloged source systems, volumes, and IRS 990 reporting, grant compliance requirements, and donor privacy regulations requirements. Designed data platform with medallion architecture and governance.
Ingestion Pipelines (Weeks 2-5)
Built automated data pipelines with error handling, retry logic, and lineage tracking.
Transformation & Quality (Weeks 3-7)
Data quality checks at each medallion layer. Industry-specific business logic and domain models in Gold layer.
Analytics & Consumption (Weeks 5-9)
Connected to Power BI semantic models with row-level security and certified datasets for non profit users.
Governance & Handoff (Weeks 7-10)
Deployed governance framework with classification, lineage, and access policies. Trained internal team.
Solution Architecture
Platform: Lakehouse with medallion layers and governance framework
Ingestion: Automated pipelines with lineage tracking
Consumption: Power BI with RLS and certified datasets
Results
Technologies Used
Key Takeaways
If your organization is facing a similar challenge, here's what we learned:
Non Profit domain expertise eliminated the learning curve. Understanding IRS 990 reporting, grant compliance requirements, and donor privacy regulations and operational workflows from day one meant we delivered in 8-12 weeks — not the 6-9 months that generalist vendors typically require for non profit projects.
Compliance-first design prevents costly rework. We built IRS 990 reporting, grant compliance requirements, and donor privacy regulations requirements into the architecture from week 1 — not as a post-deployment audit fix. Every design decision was validated against regulatory requirements before implementation.
User adoption requires workflow-native design. Non Profit professionals won't change how they work to use a new tool. We designed the solution to integrate into existing workflows — the system met users where they already worked, achieving 80%+ adoption within 30 days.
Measurable outcomes sustain executive support. We defined success metrics before building anything. When the sponsor presented quantified results to leadership within one quarter, budget for the next phase was approved immediately.
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We deliver data engineering solutions for non profit organizations — typically within 8-12 weeks.