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.
For this healthcare organization, ICF and Snowflake delivered a scalable, secure and cloud-native data environment. This change helped reduce ETL processing time by more than 75%, cut monthly data platform costs by 80% and better positioned the team to leverage advanced analytics, including using AI-driven insights.*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.
