Project Context

As part of its ERP renewal, a major European pharmaceutical laboratory faced critical issues in data quality and structure.

Errors and inefficiencies caused by uncontrolled data represented a significant cost to the organization, directly impacting processes and performance.

Objectives

The main objective was to implement a robust data governance framework to:

• Secure the quality of data used in Data & AI projects
• Structure and document datasets to facilitate exploration and reuse
• Ensure regulatory compliance and reliability of business analyses

Mission Duration

A long-term assignment with a dedicated technical consultant to support the group’s ongoing Data maturity improvement.

Implementation

Agaetis deployed a progressive and pragmatic approach:

• Analysis and identification: Mapping article data and identifying quality gaps
• Challenge and structuring: Controlling data transformation flows and clarifying processes
• Documentation: Creation of data catalogs and traceability for datasets
• Annotation & labeling: Integration of labeling processes to improve the performance of future AI models
• Continuous support: Knowledge transfer and awareness sessions for business teams

Results Achieved

• Improved data quality
• Cost optimization
• Sustainable structuring: Strong foundations established for future Data & AI projects
• Guaranteed compliance: Better control of data in line with pharmaceutical regulatory requirements

Key Success Factors

• Expertise in Data Governance applied to the pharmaceutical sector
• Pragmatic approach focused on measurable results and cost efficiency
• Tailored support with a dedicated technical consultant
• Close collaboration with business teams to ensure adoption

And You?

Are you wondering about:

• Bringing your data under control to strengthen your Data & AI projects?
• Improving the quality of your critical datasets?
• Integrating governance processes to meet regulatory requirements?

👉 Contact our experts to turn your data into a true strategic asset.