Snowflake and ICF: Unlocking Data Value for the Public Sector

Federal health programs run on data. But many organizations continue to rely on legacy systems that are costly and inhibit real-time decision-making. 

When one large federal health program faced operational bottlenecks, the rising cost of its legacy platform and misalignment with its parent agency’s data strategy, it needed to make a change. The challenge was that the organization needed business functions and operations to continue during a transition, so it turned to ICF and Snowflake to effectively modernize its data foundation.

Overcoming challenge: Legacy data systems slow mission outcomes

Program leaders in this federal healthcare organization were facing increased pressure to deliver timely insights while maintaining security and compliance standards and controlling costs. 

Prior to shifting to ICF and Snowflake, the program was using a replica of its parent agency’s integrated data repository as its data architecture. This caused issues, including lengthy extract, transform, load (ETL) processing which delayed access to insights and duplicative data pipelines which created unnecessary complexity and operational risk. The parent agency had also already standardized on Snowflake, so this program was misaligned with the organization’s overall strategy. 

The solution: Partner-led data modernization with Snowflake

The organization needed to modernize to reduce risk and align with the enterprise’s broader data strategy, all without interrupting mission-critical reporting. To do so, ICF partnered with program stakeholders to create a phased, zero-downtime migration from Redshift to Snowflake, aligning the program with the parent agency’s strategy.

Key elements of the solution included direct access to enterprise data in Snowflake, Snowflake-native security and role-based access controls to meet federal compliance requirements, enterprise-scale data sharing to support collaboration across agencies, and an AI-ready data platform to support advanced analytics and automation.

By leveraging Snowflake’s architecture and ICF’s expertise delivering data solutions in highly regulated federal environments, the team supported data integrity, performance and user continuity throughout the migration.  

The results: Faster insights, lower cost, stronger alignment

With a modernized data foundation in Snowflake, the organization now has faster access to trusted data, supporting better, timelier decisions that directly impact public health outcomes.

Achievements realized include: 

• ETL processing time dropped from 12+ hours to approximately three hours
• Monthly data platform costs fell from ~$30,000 to ~$6,000, cutting spend by roughly 80%
• End users experienced no disruption to reporting workflows during the migration
• Snowflake-native controls improved security and compliance

Building an AI- and data-ready future

Beyond performance improvements, this modernization effort laid the groundwork for the next phase of innovation. With ETL bottlenecks reduced and enterprise data readily available, the program is now better positioned to adopt advanced analytics, machine learning and AI-driven capabilities all on a trusted, governed data platform.

For federal health organizations, this shift demonstrates how partner-led, cloud-native data modernization can deliver real value and adoption of AI-powered solutions. 

Partnering for outcomes

ICF and Snowflake work together to help organizations modernize with confidence. By combining Snowflake's AI Data Cloud with ICF’s domain expertise and delivery experience, customers can move faster, reduce risk and turn data into meaningful outcomes.

Learn more about how ICF and Snowflake can help move your data strategy forward. 

Discover product quickstarts, industry specific use-cases, administration best practices and reference architectures from Snowflake experts and partners.

_{*Results based on one customer's production environment; actual outcomes may vary.}