A top global pharmaceutical organization was facing critical data management roadblocks that slowed operations, eroded trust, and increased regulatory risk. With growing data complexity across commercial, clinical, and supply chain functions, slow data processing, inconsistent reporting, and fragmented ownership made it difficult to act quickly or confidently.
To address these challenges, the company partnered with Axtria to design and implement a modern data platform and enterprise-wide governance framework, turning data into a strategic advantage.
The organization struggled with:
- Slow Data Cycles: Core data loading processes took up to a week per cycle, delaying analytics, regulatory submissions, and market insights.
- No Unified Quality Standards: Manual validation and inconsistent metrics caused widespread data errors and compliance risks.
- Weak Governance Controls: Absence of taxonomy, stewardship, and ownership made enforcing regulatory processes difficult.
- Inconsistent Reporting: Conflicting KPIs and definitions across teams led to misaligned strategies and confusion.
The goal was clear: modernize the data platform, create a robust governance model, and deliver trusted, timely, and compliant data across the enterprise.
Axtria served as a strategic partner to lead this enterprise-wide data modernization journey, bringing deep expertise in governance frameworks, platform engineering, and life sciences compliance.
- Migrated from a legacy data platform to Databricks for scalability and performance.
- Implemented Enterprise Data Catalog and Data Marketplace for discovery and reuse of governed data assets.
- Developed a standardized taxonomy and business glossary to harmonize KPIs and data definitions.
- Introduced policy-driven workflows for classification, approval, and publishing of data.
- Embedded change management and training programs for enterprise-wide adoption.
This initiative reduced data onboarding time by 50%, improved KPI accuracy, and created a governance-first culture, transforming data from a liability into a trusted, strategic asset.
With scalable frameworks, enterprise taxonomy, and role-based accountability, the organization is now ready to operationalize AI-driven insights and comply with evolving global regulations.
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