IA & Data Management
Our expertise
IA & Data management
We support your teams across the entire data value chain, from AI to governance, to turn your data into reliable decisions and measurable gains. Our work is structured around three areas:
- Creating value:
- AI roadmap: use cases, benefits, deployment
- Business AI agents (closings, reporting, sustainability) under human supervision
- Value-driven management, from business need to industrialization
- Leveraging data:
- Data science, from experimentation to industrialization
- Support for your Machine Learning projects, predictive and prescriptive analytics, LLMs
- Dashboards and data visualization
- Design of real-time dashboards to visualize your KPIs and act quickly
- Transformation of your complex data into impactful visuals, supporting decision-making and team alignment
- Making data reliable:
- Maturity and governance model
- Policies and processes
- Data mapping and data quality
- Data roles and functions
Our approach is focused on:
- Reducing costs
- Increasing revenue
- Improving customer satisfaction
Your benefits
AI at the service of your business functions
AI under control
Value-driven management
Mastery of data & AI tools
Our services
Data Visualization
Process automation & AI agents
Data Governance
Change Management
Our commitments
- Proven expertise in infrastructure, agentic AI, Business Intelligence and Data Visualization
- Tailored solutions adapted to each client's unique needs
- Concrete, measurable results that directly impact performance
- A collaborative approach with your teams to ensure smooth implementation and adoption
business case
- The delegated management division’s desire to optimize the monitoring of management flows through reporting tools,
- Multiple data sources and high data volumes,
- The need to explore and validate data in order to define robust business rules and calculate key indicators,
- The need to industrialize reporting data pipelines in order to reduce manual interventions and errors.
- Exploration and analysis of data from multiple sources,
- Requirements gathering from business teams,
- Documentation and formalization of business rules,
- Development of a set of Power BI reports, with varying levels of detail tailored to the needs of top management, team leaders and operational teams,
- Implementation of secure report sharing via AD groups and Power BI applications.
Improved reliability of key figures, strengthening management’s confidence in strategic decisions,
Significant time savings through process industrialization (reduction of manual files and errors).
business case
The executive committee’s drive to improve the company’s operational and financial performance through a data-driven solution.
- Modeling and design of the enterprise data warehouse solution using Data Vault architecture and Oracle technologies,
- Optimization of existing data flow management processes,
- Implementation of data integration and data warehouse feeding pipelines,
- Creation of dedicated business reporting solutions (Marketing, Sales, Procurement & HR),
- Implementation of operational performance dashboards.
Significant gains in business process and activity optimization: marketing campaign performance, procurement management, HR monitoring and financial reporting,
Major reduction in consolidated reporting production time, down from one week to just 2 hours.
business case
- Critical need for a tool to centralize and provide access to a comprehensive list of the group’s contracts, segmented by market type,
- The need to ensure the quality and compliance of data integrated into the reference framework,
- The importance of rigorous organization and monitoring for data updates and contract lifecycle management,
- A desire to equip processes with the right tools to facilitate coordination and communication between stakeholders,
- Multiple data sources and high data volumes.
- Scoping and formalization of requirements in collaboration with the various business teams,
- Implementation of a data governance committee,
- Identification of data sources and definition of business rules to be implemented,
- Design and deployment of quality controls to ensure data reliability,
- Writing and prioritization of the product backlog for tool development,
- Facilitating business workshops to share progress, gather feedback and adjust functionalities based on evolving needs,
- Supporting business teams in the use and exploitation of data.
Optimized use of segmentation, enhancing the effectiveness of analyses and decision-making,
Strengthened control, governance and quality of contractual data across the group.