Snowflake, ICF Modernize Federal Health Data

Snowflake and ICF modernized a federal health program's data infrastructure, cutting costs by 80% and improving data processing speeds.

5 min read
Abstract image representing interconnected data streams and cloud technology.
Modernizing public sector data infrastructure with cloud-native solutions.· Snowflake
Visual TL;DR
Legacy SystemsDriver
outdated platform caused operational bottlenecks and escalating costs for federal health program
From the articleFederal health programs are critically dependent on data, yet many are hampered by legacy systems that impede real-time decision-making.
Slow Data ProcessingDriver
prolonged ETL processes and redundant data pipelines hindered timely insights
From the article 2 mentionsThe initiative reduced ETL processing time by more than 75% and cut monthly data platform costs by 80%, enhancing the program's ability to leverage advanced analytics.
Snowflake + ICFCore
From the article 9 mentionsThe organization turned to ICF and Snowflake to overhaul its data foundation without disrupting ongoing business functions.
Cloud-Native DataContext
From the article 9+ mentionsThis partnership delivered a scalable, secure, cloud-native data environment.
80% Cost ReductionOutcome
cut monthly data platform costs by 80% for the federal health program
From the article 5 mentionsKey achievements include a drop in ETL processing time from over 12 hours to approximately three hours, and a reduction in monthly data platform costs from roughly $30,000 to $6,000.
Faster ETLOutcome
reduced ETL processing time by more than 75% for critical data
From the article 7 mentionsThe modernized data foundation provides faster access to trusted data, enabling better public health outcomes.
Advanced AnalyticsEffect
enhanced program's ability to leverage advanced analytics for better decisions
From the articleThe initiative reduced ETL processing time by more than 75% and cut monthly data platform costs by 80%, enhancing the program's ability to leverage advanced analytics.
Future-ProofingEffect
preparing for AI and data readiness to ensure long-term adaptability
Contents(4)

Federal health programs are critically dependent on data, yet many are hampered by legacy systems that impede real-time decision-making. One large federal health program faced operational bottlenecks, escalating costs from its outdated platform, and strategic misalignment with its parent agency.

The organization turned to ICF and Snowflake to overhaul its data foundation without disrupting ongoing business functions. This partnership delivered a scalable, secure, cloud-native data environment. The initiative reduced ETL processing time by more than 75% and cut monthly data platform costs by 80%, enhancing the program's ability to leverage advanced analytics.

Legacy Systems Stall Mission Outcomes

Program leaders grappled with delivering timely insights while adhering to strict security and compliance mandates and managing costs. Their existing architecture, a replica of the parent agency’s integrated data repository, led to prolonged ETL processes and redundant data pipelines, introducing complexity and risk. Crucially, this setup was misaligned with the parent agency's standardization on Snowflake, impacting the overall organizational strategy.

Partner-Led Modernization on Snowflake

To address these challenges and align with enterprise strategy, ICF and the program stakeholders executed a phased, zero-downtime migration from Redshift to Snowflake. This approach ensured mission-critical reporting continued uninterrupted. The solution integrated direct access to enterprise data within Snowflake, implemented Snowflake-native security features for federal compliance, enabled enterprise-scale data sharing, and built an AI-ready platform.

By combining Snowflake’s architecture with ICF’s federal data solution expertise, the migration maintained data integrity, performance, and user continuity. This initiative represents a significant step in data modernization in the public sector, echoing trends seen in other government initiatives like the US Gov Taps Snowflake for AI Push.

Tangible Results: Speed, Savings, Alignment

The modernized data foundation provides faster access to trusted data, enabling better public health outcomes. Key achievements include a drop in ETL processing time from over 12 hours to approximately three hours, and a reduction in monthly data platform costs from roughly $30,000 to $6,000. User reporting workflows remained unaffected throughout the migration, and Snowflake’s native controls bolstered security and compliance.

The reduction in ETL processing time reduction is a critical enabler for future innovation.

Future-Proofing with AI and Data Readiness

This modernization effort has established a robust platform for future innovation. With reduced ETL bottlenecks and readily accessible enterprise data, the program is now better positioned to adopt machine learning and AI-driven capabilities. This shift underscores how partner-led, cloud-native data modernization can deliver substantial value and drive AI adoption within federal health organizations.

ICF and Snowflake collaborate to offer organizations confidence in their modernization journeys. Their combined strengths in Snowflake's AI Data Cloud and ICF’s domain expertise enable faster progress, reduced risk, and the transformation of data into actionable outcomes.

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