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Data is among today's most valuable assets, yet enabling smooth analysis, monitoring, and reporting remains challenging.
Based on the report, only 18% of data analytics experts are satisfied with their data landscape's comprehensibility, while 26% of business managers lack the flexibility to extend data requirements.
We present a case study on Professional Billing, Inc.'s (PBI) new data warehouse solution, which increased processing efficiency, enabled better insights, and reduced IT costs.
Professional Billing, Inc. (PBI) is a privately owned company providing tailored medical billing and technology solutions for healthcare providers, including physicians. Established more than three decades ago, the company has built its reputation on flexibility and customisation and is now one of the leading medical billing and practice management service providers in the United States.
PBI’s existing DWH solution was ineffective. Maintaining both Tableau and PostgreSQL on‑premises required significant resources, while reliance on a Progress‑based legacy system resulted in an overly complex infrastructure. The solution lacked flexibility and scalability and could not support efficient reporting or monitoring.
PBI needed a reliable, performance‑driven technology that would streamline data analysis, reporting, and delivery processes while reducing operational overhead.
Baltic Amadeus delivered the full project within one month, covering situation analysis, solution development, testing, and complete data migration. The project consisted of two main parts: an internal medical billing and management application and a DWH and reporting solution built in the Microsoft Azure cloud.
On the application side, the team used Progress OpenEdge database trigger logic to track and store database changes. The database configuration was updated to include a separate broker for SQL‑only connections. Users and permissions were created specifically for SQL access, and SQL stored procedures were implemented for processing and deleting records.
On the Azure side, the Progress OpenEdge ODBC Driver was used to connect to the Progress database. Reporting data was extracted and stored in Azure SQL Database. Azure Data Factory enabled incremental DWH updates using change‑tracking tables, while a separate process marked and deleted processed records. The final DWH solution supported fast, in‑memory performance for Power BI and other client databases.
The new DWH implementation optimised resource usage by removing obsolete code and reducing ETL processes by half, significantly lowering solution maintenance costs.
Thanks to improved flexibility, PBI can now scale resources more efficiently during peak and off‑peak periods. Power BI enables faster access to data and more convenient report generation for users.
By fully caching and partitioning data in Power BI, the solution eliminated unnecessary data management processes, improved querying speed and data quality, reduced redundant data copies, and established a single source of truth.
