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.

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