Unifying Enterprise Data to Accelerate AI Governance

A global pharmaceutical leader faced a fragmented data landscape siloed across business units with inconsistent metadata and no authoritative definitions. Myridius implemented a Collibra-powered enterprise data catalog with metadata remediation and change management, establishing a single source of truth and a compliant governance foundation for enterprise-wide AI readiness.

Key Outcomes

• A single, consistent view of enterprise data assets.
• An AI-ready foundation reducing compliance and ethical risk.
• Institutionalized data literacy and stewardship.

Overview

A global pharmaceutical leader managing complex operations across supply chain, manufacturing, finance, legal, and regulatory functions faced a deeply fragmented data landscape, siloed across business units with inconsistent metadata quality, redundancies, and no authoritative definitions. As AI and machine learning initiatives scaled, the absence of a governed, unified data foundation became a critical barrier to confident, compliant AI deployment. Myridius combined Collibra platform implementation with metadata remediation and organizational change management, deploying Collibra as the authoritative hub for enterprise data definitions, building ontologies and taxonomies, and digitizing data lake workflows with structured training. As a result, decision-makers gained a single, consistent view of enterprise data, AI and ML teams gained governed, contextually rich data that reduced compliance and ethical risk, and data literacy became an institutionalized capability.

Client Context

The client is a global pharmaceutical leader operating across supply chain, manufacturing, finance, legal, and regulatory functions.

A governed, unified data foundation mattered here because data was siloed across business units with inconsistent metadata and no authoritative definitions, which became a critical barrier as AI and ML initiatives scaled. What was at stake was the ability to deploy AI confidently and compliantly at enterprise scale, which depends on trustworthy, well-governed data.

The Challenge

The pharmaceutical leader faced a deeply fragmented data landscape, siloed across business units with inconsistent metadata quality, redundancies, and no authoritative definitions. As AI and ML initiatives scaled, the absence of a governed, unified data foundation became a critical barrier to confident, compliant AI deployment. The desired state was an authoritative catalog and a compliant governance framework.

Consider an AI team needing trustworthy data. Definitions varied across business units, metadata was inconsistent, and there was no single source of truth, making confident, compliant AI deployment difficult. The enterprise needed governed, contextually rich data before it could scale AI responsibly.

Transformation Goals

The engagement focused on north stars that connected an authoritative data foundation to unified persona visibility and AI governance enablement.

• Authoritative Data Foundation: Establish a Collibra-powered enterprise data catalog as the single source of truth for data definitions, types, and rules across all business units and systems.

• Unified Persona Visibility: Deliver tailored, role-based data views for Business Stewards, Technical Stewards, and Business Analysts to drive cross-functional data literacy and accountability.

• AI Governance Enablement: Build a compliant governance framework enabling AI and ML teams to deploy solutions with ethical and regulatory confidence at enterprise scale.

The Solution

The engagement combined Collibra platform implementation with metadata remediation and organizational change management to build a governed, AI-ready data foundation. Myridius orchestrated the data catalog foundation, embedded high-quality metadata and ontologies into the enterprise, and reimagined governance as an institutionalized capability. The progression moved from deploying Collibra as the authoritative hub, to embedding metadata remediation and ontologies, to reimagining governance through digitized workflows and data literacy.

• Orchestrated the foundation: Deployed Collibra as the authoritative hub for enterprise data definitions, integrated with the existing business glossary and enterprise data lake.

• Embedded intelligence into the journey: Eliminated redundancies, corrected inaccuracies, and built ontologies and taxonomies to ensure consistent, high-quality metadata across all business units.

• Reimagined the operating model: Digitized data lake workflows and delivered structured training to embed data literacy and upfront governance enterprise-wide.

Governance and Trust

Because this engagement was fundamentally about governance for a regulated pharmaceutical enterprise, trust and compliance were the core of the work. Deploying Collibra as the authoritative hub established a single source of truth for data definitions, types, and rules, while metadata remediation eliminated redundancies and inaccuracies to ensure consistent, high-quality metadata across business units.

Role-based views for Business Stewards, Technical Stewards, and Business Analysts embedded accountability across personas, while a compliant governance framework enabled AI and ML teams to deploy with ethical and regulatory confidence. Digitized workflows and structured training institutionalized data literacy and upfront governance, making stewardship a sustained operational capability rather than a one-time effort.

Results

The engagement transformed fragmented, untrustworthy data into a governed, AI-ready single source of truth. The result was unified intelligence, an AI-ready foundation, and lasting data maturity.

The result:

• Gave decision-makers a single, consistent view of enterprise data assets, eliminating silos and enabling reliable cross-functional insight at scale.

• Provided AI and ML teams access to governed, contextually rich data, accelerating development velocity and reducing compliance and ethical risk.

• Elevated metadata stewardship into a sustained, institutionalized capability through enterprise-wide data literacy and digitized governance workflows.

Technology Stack

Core Platform

Collibra
Provides the authoritative enterprise data catalog

Data and Integration

Business glossary integration, enterprise data lake, digitized workflows
Connect the catalog to enterprise data assets

Security and Governance

Ontologies, taxonomies, metadata remediation, governance framework
Ensure consistent, compliant, high-quality data

Engineering and Delivery

Role-based persona views, structured training programs
Embed accountability and data literacy enterprise-wide

For a pharmaceutical enterprise scaling AI, fragmented data is the single biggest barrier to confident, compliant deployment. This case shows how a governed data foundation turns data into an AI advantage. This was not a cataloging project. It was a governed, AI-ready data foundation with institutionalized stewardship.