Challenge
A leading UK nonprofit faced fragmented data silos across SQL databases, APIs, SharePoint lists and Shopify. While beginning to adopt Databricks, they still relied on a traditional SQL warehouse, lacked a unified ingestion framework and struggled with inconsistent customer address data.
They needed geospatial processing to integrate ArcGIS location intelligence and wanted near–real-time visibility into Shopify orders—all without a scalable, maintainable solution in place.
Solution
Our four-engineer team delivered an end-to-end data platform on Azure and Databricks, driven by SnapLogic pipelines:
- Multi-Source Ingestion: Configurable SnapLogic–Databricks pipelines load data from SQL, APIs, SharePoint and Shopify into bronze/silver lakehouse layers, with support for full or incremental loads, schema change handling and centralized logging.
- Geospatial Integration: Python/PySpark routines map coordinates to polygonal regions, handle point-in-polygon computations and exchange data with ArcGIS Online.
- Shopify Data Quality: An address‐validation process leverages the Postcode Address File (PAF) to detect, correct and standardize misfielded components.
- Real-Time Orders: Shopify webhooks feed Azure Functions and Service Bus into SnapLogic, enabling sub-second updates to downstream systems.
Business Value
This solution transformed the nonprofit’s data ecosystem by automating 100+ pipelines, delivering unified, near-real-time insights and improving data quality across operations. Stakeholders gained faster decision-making, higher operational efficiency and more accurate CRM data.
Download the full case study to explore our technical approach, and detailed results.
