CASE STUDY

Healthcare Data Warehouse

CLIENT’s Challenge

• 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

OUR APPROACH

• 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 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

skills & tech leveraged

Microsoft Suite – SQL Server 2016, SSIS, T SQL, 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