Servier is an independent international pharmaceutical company of French origin, employing more than 20,000 people worldwide and present in nearly 150 countries. The Hungarian subsidiary is one of the group's key regional centers, which, in addition to pharmaceutical distribution, actively participates in clinical research and business process development.
The company had been using a local SQL Server-based reporting system for years for business data analysis and management decision support. The system was becoming increasingly difficult to maintain, report preparation required significant manual work, and data was often available only with a delay of several days. Different departments used different Excel spreadsheets and ad-hoc queries, leading to data inconsistencies and opaque reporting processes. With growing data volumes, the local SQL Server's performance was also becoming an increasingly critical bottleneck.
During the project, we transformed the entire reporting system to a modern, cloud-based architecture. We centralized the data in Azure Data Lake, where we designed a unified data model for data arriving from various source systems (SAP, CRM, sales systems). By automating the ETL processes, we ensured daily data refreshes and consistency. For the visualization layer, we developed Power BI dashboards and reports that provide users with interactive, self-service analytics capabilities. During the migration, we paid special attention to accurately reproducing existing reports to ensure a smooth transition for end users.
As a result of the migration, report preparation processes that previously took several days became available in Power BI within minutes. Thanks to the unified data model, data inconsistencies between departments were eliminated, and management gained real-time visibility into business metrics. The cloud-based architecture allows the system to scale easily as data volumes grow, while maintenance requirements have been significantly reduced compared to the previous local solution. Thanks to self-service reporting, business users can independently create new analyses, thereby relieving the IT team.
For the solution development, we used Azure Data Lake, Power BI, Python ETL scripts, and SQL Server.
