# 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