Establishing Enterprise Data Governance at a Global Scale
About
A global leader in the food and beverage industry, headquartered in Europe, embarked on a comprehensive data transformation journey to fuel business innovation and operational efficiency through data and AI. The organization partnered with HCLTech to establish a mature, enterprise-wide data governance framework that improves data quality, ensures regulatory compliance, and empowers teams with accessible, trusted data products across the enterprise.
Overview
Discover how a global food and beverage leader transformed its fragmented data landscape into a unified, enterprise-wide governance framework with HCLTech. By operationalizing data governance through automation, AI, and a FAIR-compliant architecture, the company improved data quality by up to 80%, accelerated time-to-insight, and empowered teams with trusted, discoverable data. This end-to-end initiative drove global alignment, compliance, and smarter decision-making across the business.
The Challenge
Enabling cohesive data governance for smarter enterprise decision-making
A global consumer goods enterprise with a vast international footprint needed to transform its fragmented and siloed data ecosystem into a unified, insight-ready architecture. The company’s decentralized data practices led to duplicated efforts, inconsistent data quality and poor visibility into business-critical assets—hindering efficiency and slowing innovation.
With data spread across platforms such as SAP BW, Snowflake and Azure, the organization required a strategic approach to align data strategy across functions, improve literacy and enforce consistent governance standards.
Key challenges included:
- Siloed and fragmented data sources
Created confusion and duplication, limiting the organization’s ability to leverage insights effectively - Inconsistent data quality
Reduced trust in analytics and decision-making across global teams - Limited discoverability
Difficulties in accessing the right data at the right time hindered productivity - Lack of unified governance
Led to inefficiencies, compliance risks, and misaligned processes across business units - Low data literacy
Made it challenging for teams to self-serve and fully adopt data-driven decision-making practices
The Solution
Enterprise-scale data governance powered by automation and AI
The client partnered with HCLTech to execute a strategic data governance initiative aligned with its broader vision for data and AI transformation. Designed to address gaps across metadata, quality and access, the program focused on building a scalable framework to unify practices and improve trust in enterprise data.
Given HCLTech’s deep domain expertise and focus on operationalizing governance through modern platforms, the client was able to drive consistency, transparency and cultural adoption at a global scale.
The key features and characteristics of our solution included:
- Governance-aligned framework
Structured around metadata enrichment (MDE) and data quality (DQ), ensuring complete lifecycle control - Live data quality dashboard
Enabled real-time anomaly monitoring and transparency across critical data sources - Operationalized data factory
Streamlined discovery, onboarding and curation of global data assets across business units - 80%+ curation rate
Achieved on key platforms like SAP BW and Snowflake, boosting discoverability and reuse - FAIR-compliant architecture
Applied the principles of findable, accessible, interoperable and reusable to foster trusted data usage - Cultural enablement and literacy
Conducted training and mentoring to embed data stewardship practices and drive self-service adoption
The Impact
Enterprise-wide data governance transformation
The implementation of a unified data governance program delivered tangible business outcomes, including but not limited to:
- Significant improvement in data quality
Resulting in a 70%–80% reduction in anomalies across third-party and unstructured data sources - Streamlined data onboarding
Enhanced the availability and accessibility of trusted master data across operational and analytical environments - Improved visibility and control
Enabled faster, insight-driven decisions with better access to dashboards, reports and queries - Faster time to insight
Standardized processes and quality checks accelerated access to reliable data for business functions - Global data alignment
Ensured consistent governance practices and strategic data alignment across business units and geographies
