Platform Build / Rapid Start

Snowflake and Matillion Data Platform Implementation for Healthcare Information Exchange

The Situation

A Colorado-based health information exchange serving over 4,900 users and upwards of one million patients needed to modernize its analytics stack. Their existing cloud BI platform had hit its limits, and a traditional SQL Server data warehouse approach would have required expensive hardware and struggled with the semi-structured healthcare data formats they worked with daily — including HL7, MongoDB, and Postgres sources. Key challenges included:

  • High volumes of complex, semi-structured healthcare data including variant formats that traditional tools struggled to ingest reliably
  • A small analytics team with no bandwidth for lengthy, large-scale infrastructure projects
  • A need for a budget-conscious, scalable solution that could grow with the organization
  • Existing data-capture and history-capture methods that needed to be modernized across every connected source

What We Did

Recommended a Snowflake, Matillion, and Tableau stack as an alternative to the traditional SQL Server approach, then delivered a proof of concept to validate it before full investment

  • Implemented Snowflake as the central cloud data platform, demonstrating its ability to handle Oracle, Postgres, and tSQL functions alongside JSON and XML datasets in a single environment
  • Configured Matillion for data ingestion and workflow automation, utilizing its native connectors for MongoDB, Postgres, and flat files to handle the organization's variant data sources
  • Imported the majority of data sources, built an initial data warehousing layer, and updated data-capture and history-capture methods across every connected source — all within a three-month proof of concept
  • Connected the full stack to Tableau for rapid report prototyping and stakeholder delivery

Results

  • Proof of concept delivered in three months, establishing a strong data foundation
  • All data sources loaded into Snowflake — more data ingested than had been possible under the legacy environment
  • Data-capture and history-capture methods modernized across every connected source
  • Analytics team freed from infrastructure constraints to focus on surfacing new data streams from providers, subjects, and diagnoses

What This Unlocks

For healthcare organizations managing high volumes of semi-structured or variant data formats — including health information exchanges, clinical analytics teams, or population health providers — this engagement demonstrates how Snowflake's flexibility across data types can replace a traditional warehouse approach with something more scalable, cost-transparent, and faster to implement. The proof of concept model is directly reusable for any organization that needs to validate a new stack before committing to full investment.

Team

Led by a data lead and data architect, supported by a solutions consultant handling Tableau dashboard delivery.

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