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

Visual TL;DR
outdated platform caused operational bottlenecks and escalating costs for federal health program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.
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.
From the article 9 mentionsThe organization turned to ICF and Snowflake to overhaul its data foundation without disrupting ongoing business functions.
From the article 9+ mentionsThis partnership delivered a scalable, secure, cloud-native data environment.
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.
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.
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.
preparing for AI and data readiness to ensure long-term adaptability
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