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Data is one of the most valuable currencies of today’s digital world. And companies winning at the data game can secure their spots among top industry leaders. Yet, enabling smooth data analysis, monitoring, and reporting processes is a solid task.
Statistics from Precisely’s report shows that only 18% of data analytics experts are satisfied with the comprehensibility of the data landscape/architecture as a whole. Also, 26% of business managers lack the flexibility to extend data requirements.
Therefore, we are delighted to share a case study about the new Professional Billing, Inc. (PBI) data warehouse (DWH) solution, which significantly increased data processing efficiency, enabled better data insights, and cut IT-related costs.
PBI is a privately-owned company that offers tailored medical billing and technology solutions to healthcare providers, including physicians. The company was established more than three decades ago with a commitment to flexibility and customisation and has since become one of the leading providers of medical billing and practice management services in the United States.
The existing client’s DWH solution was ineffective, wherefore, maintaining both Tableau and PostgreSQL on-premises was a significant resource-intensive task. Also, due to its reliance on a Progress-based legacy system, PBI’s infrastructure was overly complicated, unable to support effective reporting and monitoring, lacking in flexibility and scalability.
PBI looked for a reliable technology that could solve mentioned performance challenges and streamline the data analysis, reporting, and delivery processes. This is where Baltic Amadeus stepped in and proposed an efficiency-driven and cost-effective solution for PBI’s reporting and DWH.
Baltic Amadeus pulled off an entire project in one month – from situation analysis to solution development, testing, and complete data migration. The project was divided into two equal parts – internal medical billing and management application as well as DWH and reporting solution created in the Microsoft Azure cloud.
On the application side, our team used Progress OpenEdge database trigger logic to track and store database changes. Then, the database configuration was adjusted to have a separate broker for SQL-only connections. In addition, users and permissions were created for SQL connections, and SQL Stored Procedures were implemented for processing and deleting records.
On the Azure side, we used Progress OpenEdge ODBC Driver to connect to the Progress Database and data required for reporting was taken from Progress Database and stored in Azure SQL Database. Our team used the Azure Data Factory to update the DWH incrementally, utilising change tracking tables. Meanwhile, processed records were marked and deleted by a separate process. Finally, the DWH was made available for fast, in-memory performance for Power BI and other client databases.
The brand-new DWH implementation optimised resource usage, removing obsolete code and reducing half of ETL processes. These improvements significantly cut solution maintenance costs.
Thanks to the solution’s flexibility, scaling resources is now easier during peak and off-work periods. Moreover, PowerBI allows users to generate reports more conveniently and access data faster.
Furthermore, the project eliminated unnecessary data management processes by fully caching and partitioning data in Power BI, resulting in improved data processing, querying, and quality. The solution also reduces unneeded data copies and provides a single point of truth.
Want to discuss potential opportunities? Pick the most suitable way to contact us.
Book a call+370 5 2 780 400
info@ba.lt
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