Case Study

Healthcare Data Warehouse


  • Expensive, slow and ineffectual analytics capability: Updates to high numbers of disparate data sets produced unreliable numbers, required heavy manual coding and support by IT, and resulted in lengthy query run times
  •  No ability to scale for continuous delivery: Lack of modern data architecture impeded the ability to scale the workload to keep pace with new health plans and new lines of business being introduced
  •  No central management of enterprise data: Limited enterprise stakeholder engagement in the development and management of a centralized, integrated data set to be used by the organization


  • Based on the previously delivered multi-year Data Strategy & Roadmap, designed, architected, and engineered the foundation for the new Enterprise Data Ecosystem
  • Applied an iterative, data-driven approach to data modeling and continuous deployment. Automated the Extract, Transform, and Load processes and to enable continuous deployment.
  • Leveraged the Data Vault 2.0 methodology to combine provider, member, and claims data from transactional and historical data sources into the new ecosystem
  • Used agile sprints to engage Business stakeholders to prioritize the data to be migrated into the new warehouse


Microsoft Suite – SQL Server 2016, SSIS, TSQL, Stored Procedures; Embarcadero – Data Model, Data Lineage, Metadata, Team Foundation Server; Tableau; Jira

The Results

  • Implemented easy-to-query data structures, eliminating the heavy reliance on DBA interaction
  • Improved daily run times for data processing from hours to minutes
  • Enabled parallel processing aligned to the data vault methodology to allow easy scalability
  • Leveraged the new platform to provide integrated enterprise provider data to support provider directory and claims processing
  • Established a platform to support continuous development by using agile sprints