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Data

Redefining your purpose, aligning your organisation, prioritising your projects: transformations are multiplying, yet often struggle to materialise. Willing translates your strategic directions into operational roadmaps to secure the achievement of your objectives.

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Our approach

Our teams specializing in data, architecture, and applied AI support organizations in their transformation with a pragmatic, industry-focused approach that is firmly centered on creating value.

Composed of professionals with diverse technical and industry-specific expertise, our teams combine an understanding of business challenges, mastery of modern architectures, and the ability to accelerate adoption. We work to structure data, standardize its use, and turn data into a driver of trust and sustainable performance. We believe that well-governed, well-structured, and well-utilized data is the foundation of a high-performing and resilient organization.
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Your challenges

Making Decisions

based on a proven value chain

Gaining maturity

to accelerate value creation

Accelerate the implementation
of use cases

as well as their adoption

Facilitate access
to data

and their use on a self-service basis by all teams

Increase autonomy

from your data and business teams

Anticipating a Critical Outage

to ensure the continuity of data services

Ensure safety

and the traceability of your data at scale

Ensuring Regulatory Compliance

(GDPR, AI Act, DORA)

Our expertise

To help our clients maximize the value of their data assets, we have structured our offerings around eight complementary areas of expertise, designed to build robust, agile, and value-generating data solutions.

Data Strategy and Governance

We help organizations establish a data governance framework tailored to their specific challenges, by enhancing the transparency, consistency, and effectiveness of their systems

Data Risk Management System

Mapping and managing data risks to ensure the reliability, security, and traceability of information assets: Our assessments are based on a multidimensional approach grounded in industry best practices and operational realities.

Diagnostic Data

Assess the maturity of the data infrastructure (architecture, regulations, governance, security), formulate targeted recommendations, map risks, evaluate them consistently, and oversee action plans to strengthen the resilience of the information assets:

Regulatory Compliance

Developing agile, proportionate, and sustainable solutions to meet legal obligations while securing their data assets. We support our clients in compliance analysis and operational implementation.

Data Management

Organizing, refining, and standardizing data are essential prerequisites for accelerating value creation and meeting stakeholder expectations. We help design or strengthen data management systems.

Training, Acculturation, and Awareness-Raising

Develop a data culture at all levels of the organization to firmly establish data practices and accelerate the adoption of a true data culture.

Architecture data

Design and deploy a modern, scalable data architecture aligned with business needs to maximize the value of data. We help our clients define and deploy architectures tailored to their technical and strategic requirements.

Data Preparation & Data Visualization

Organize, prepare, and leverage data through dashboards and actionable visualizations aligned with business priorities.

Our areas of expertise

  • Diagnostic Data on the IT System or Application
  • Selecting and Implementing a Target Operating Model
  • Data Platform Design
  • Implementation of BI and AI (ML, DL, generative) use cases

Our experts

Complementary areas of expertise

Business Intelligence

Architecture d'entreprise
& Stratégie IT

Cybersecurity

You have a project?

Our team is here to help.

Contact

Data Strategy and Governance

  • Data & AI Roadmap Aligned with the Organization’s Goals
  • Target Operating Model et plan de communication Data
  • Review and optimization of governance (roles, responsibilities, committees, reporting)
  • Development and updating of data policies, guidelines, and procedures
  • Maturity analysis and benchmarking of existing frameworks
  • Integrating ESG and non-financial considerations into data governance
  • Alignment with international standards (DAMA, ISO 8000)
  • Defining lines of responsibility between data, IT and business functions

Data Risk Management System

  • Assessment across various areas: architecture, regulation, governance, platformisation, security, processes
  • Identifying areas of vulnerability and opportunities for optimisation
  • Prioritised recommendations and corrective actions
  • Benchmarking practices against industry norms and standards
  • Support with the implementation of action plans
  • Optimising risk coverage through existing mechanisms
  • Assessment of data quality and the maturity of AI applications
  • Support for the professionalisation of data teams (training, governance)

Diagnostic Data

  • Data risk mapping (security, quality, compliance, availability)
  • Methodological approach and definition of evaluation methods
  • Treatment action plans tailored to the organisation’s priorities
  • Prioritising risks and identifying key areas for mitigation
  • Implementation of dashboards for monitoring data risks
  • Alignment with international standards (ISO 27001, ISO 31000)
  • Integrating data risk management into strategic cycles
  • Support for teams in developing a professional approach to data risk culture

Regulatory Compliance

  • Assessment of the level of compliance with current regulations (AI Act, GDPR, DORA, etc.)
  • Data classification and mapping of regulatory obligations
  • Conducting compliance diagnostics and identifying gaps
  • Design and implementation of tailored compliance programmes
  • Design of policies, procedures and regulatory control mechanisms
  • Implementing steering and monitoring frameworks for regulatory requirements
  • Support in dealings with the regulatory authorities
  • Regulatory monitoring and continuous adaptation of frameworks

Data Management

  • Data organisation and classification of information assets
  • Reference and master data: MDM (Master Data Management)
  • Data quality: standards, rules, checks and remediation
  • Data modelling and the data lifecycle
  • Metadata management (technical, business, operational)
  • Facilitating scoping and review workshops with stakeholders
  • Implementation of dashboards for monitoring data quality
  • Integrating data management into strategic planning cycles

Training, Acculturation, and Awareness-Raising

  • Training programmes tailored to specific audiences (governance, AI applications, self-service tools)
  • Design of bespoke learning programmes (face-to-face, distance learning, e-learning)
  • Delivering training courses on the fundamentals of data, business intelligence and applied AI
  • Sessions focusing on major emerging issues (generative AI, data ethics, etc.)
  • Serious games, role-play scenarios and collaborative workshops
  • Training in data management tools (mapping, quality, governance)
  • Advanced modules for senior managers, data owners and key roles
  • Measures to assess the impact and uptake of training

Architecture data

  • Data modelling using an appropriate model: dimensional, normalised, Data Vault, ASD (S-Series)
  • Design and implementation of modern data platforms (lakehouse, data mesh, etc.)
  • State of the art in market tools and guidance on technology selection
  • Platformisation and definition of a data marketplace
  • Integration of architectures into existing information systems
  • Selection and implementation of a data Target Operating Model
  • Implementation of BI and AI (ML, DL, generative) use cases
  • Support for the migration and evolution of existing architectures

Data Preparation & Data Visualization

  • Data preparation processes aligned with business and technical requirements
  • Data preparation: formatting, cleaning, consolidation and enrichment
  • Design and deployment of BI dashboards (Power BI, Tableau, Qlik, etc.)
  • Support and implementation of actionable visualisations
  • Definition of key indicators and reporting templates
  • Automation of data preparation and updating workflows
  • Training teams in the use of data visualisation tools
  • Optimising the performance and user experience of dashboards