🧱 Data Foundation Program

Since 2023, Gerflor has launched an ambitious Data Foundation program aimed at structuring, governing, and leveraging the group's data. This initiative is built around six strategic objectives:

🎯 Key Objectives

1. Reference Data Governance
   Ensure centralized, reliable, and shared management of business reference data across the group.

2. Industrialization of Key Indicators
   Standardize and automate strategic KPIs while regaining control over the group’s data visualization tools.

3. Validated Data : Acquired and Made Available
   Facilitate access to high-quality, validated data shared across business units.

4. Data Valorization
   Unlock the value of data through analysis, prediction, and business optimization.

5. Design of a Reliable and Adaptable Business Information System
   Build a robust and scalable information system aligned with business needs.

6. Methodological Support and Project Framework
   Provide structured guidance and best practices for data-related projects.

🧠 Cross-Functional Focus Areas

To meet these goals, several cross-cutting initiatives have been identified:

• Data Analytics
  Develop advanced analytical capabilities for business teams.

• Data Cataloging & Lineage
  Implement a data catalog and ensure traceability of data flows.

• Data Hub / MDM
  Centralize and govern master and reference data.

• Data Governance & Quality Management
  Establish rules, processes, and tools to ensure data quality and compliance.

• Data Architecture & Technology Choices
  Define a target architecture and select appropriate solutions.

🏗️ Key Architecture Components

The program is built on a modern, modular architecture that includes the following components:

• Data Lake: Large-scale storage for raw, structured or unstructured data.
• Master Data Management (MDM): Centralized management of reference data.
• Data Hub: Platform for data exchange and distribution.
• Data Warehouse: Structured storage for business intelligence and reporting.
• Data Science & Big Data: Exploration, predictive modeling, and processing of large data volumes.
• Integration Middleware: Orchestration and transformation of data flows between systems.