Data Unification for a Leading Provider of Community-Based Specialty Healthcare
Improving Forecast Accuracy and Reporting Speed with Saxon AI’s Data Integration Expertise
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.
