Data Unification for a Leading Provider of Community-Based Specialty Healthcare

Summary

A leading healthcare provider serving seniors and children was struggling to create trusted, timely reports due to inconsistent data formats across multiple sources. This challenge impacted their ability to forecast expenses, resource effort, and other key metrics. Saxon AI addressed this by implementing a robust data unification solution backed by ETL Quality Assurance, resulting in faster, more reliable reporting.

The Business Challenge

The client’s operations relied on pulling data from various systems across departments and partner organizations. These data sets came in incompatible formats, making it difficult to consolidate insights for Forecast vs. Actual reports. Key challenges included:

• Data in different file types and structures
• No standardized schema
• Difficulty mapping and comparing time, effort, and financial metrics
• Significant time spent cleaning and aligning data
• Delays in decision-making and reporting cycles

Saxon AI’s solution

We implemented a data unification framework that standardized data from all sources into a single, reliable schema. Key components of our approach included:

• ETL pipeline design with built-in validation layers
• Data profiling and transformation using quality rules
• Automated matching and mapping for schema alignment
• Deployment of a centralized data hub
• Continuous ETL Quality Assurance for long-term scalability

This solution allowed the client’s leadership to view consistent, real-time insights in the Forecast vs. Actual reports — improving confidence and reducing reporting time.

Business Outcomes

• 40% reduction in reporting cycle time
• Unified view of key metrics across departments
• Improved trust in data from leadership and analysts
• Faster and more confident decision-making

For more details on the technical approach and outcomes.