Modernizing Business Intelligence: Seamless Migration to Microsoft Fabric

A global pharmaceutical manufacturer that delivers medicines to millions of patients worldwide, with operations spanning R&D, production, and logistics across dozens of facilities

The company relied on a legacy Qlik-based BI system that handled millions of records and supported dozens of daily users—from analysts to plant managers—creating reports and accessing real-time insights into the pharmaceutical manufacturing process. Over time, performance began to lag, reporting logic became increasingly difficult to maintain, and the platform struggled to keep up with growing business needs. Migrating to Microsoft Fabric was a strategic decision to modernize the analytics stack, but doing so required preserving complex business logic, maintaining seamless user access, and boosting performance without disrupting critical operations.

Brimit designed and executed a custom migration strategy focused on stability, transparency, and speed. Working closely with business teams, we rebuilt the core analytics engine around a semantic model and implemented end-to-end DevOps workflows.

Solution highlights:

• Translated Qlik’s implicit logic into explicit semantic models in Power BI
• Introduced data load limiting functionality for local, memory-efficient development
• Optimized queries and migrated data processing to Databricks for faster performance
• Reduced full data load time from 4–6 hours to 16 minutes
• Built Git-based deployment pipelines to provide version control and collaboration functionality
• Worked directly with gold-tier data, ensuring reliability and accuracy

• 96% faster processing of large datasets with 5M+ records loaded in just 1 minute
• Shorter time to insight for reports with local, memory-light environments that allow teams to build and test reports independently
• Zero downtime and uninterrupted access to critical reports during migration
• Reduced maintenance costs with CI/CD workflows that streamline updates and reduce manual overhead