Data Foundations & Governance Pack
Structure and improve the reliability of critical business data to support sound decisions, improve reporting quality and prepare future Data & AI applications. For French-speaking Africa, the approach prioritises pragmatic implementation, controlled costs, local delivery and quickly observable results.
- Data
Identify critical data, risks and Data & AI opportunities.
Make data reliable
Data is scattered, unreliable or insufficiently governed, producing contradictory reporting, weakening decisions and slowing Data and AI initiatives.

Pain points
Data is scattered, unreliable or insufficiently governed, producing contradictory reporting, weakening decisions and slowing Data and AI initiatives.

Promise
Quickly identify critical data, assess reliability and define a pragmatic roadmap to improve quality, make reporting dependable and prepare Data & AI applications.

Outcome
A clear view of data assets, remediation priorities, a suitable governance framework and a pragmatic roadmap to improve reporting reliability and prepare Data & AI initiatives.
Recommended entry service
A short assessment to objectively map the situation, identify the major gaps and prepare a prioritised action plan.

Essential services
These services form the offer's foundation and contribute to the expected deliverables within the agreed scope.
Data Readiness Assessment
Data maturity assessment measuring availability, quality, governance, architecture, use cases and AI readiness.
Reliable, high-performance data foundations
Data foundation structuring service: architecture, integration, quality, models, security, performance and operations.
Data Governance Starter
Data governance starter package: roles, ownership, quality rules, dictionary, reference data and initial indicators.
Services to go further
Activate complementary services according to priorities, constraints and capabilities already in place.
Data Platform Blueprint
Data target architecture scoping product: source mapping, target architecture, flows, security, governance, backlog and implementation roadmap.
Unified data and analytics platform
Design and deployment of an integrated data platform: ingestion, storage, transformation, models, security and operations.

Talk to an RFC expert
Describe your priorities, constraints and projects to prepare a discussion with the relevant teams.

Technology stack
Data, automation and AI platforms used according to applications and integration needs.
Data and steering
Connect reliable data, governed models and business decisions.
(Step 01)
Define data usages
Specify the decisions to inform, the indicators and the users of the scope.
Deliverable
Indicator dictionary and priority usages.


Projects to inform your choices
Explore related engagements to understand the contexts, scopes and challenges covered by RFC.
2023
Unify HR and payroll data
ETL flows consolidate HR and payroll data from 28 entities.
Tracked Indicators
Quality, completeness, availability

Explore the domain's other capabilities
Find complementary offers and areas of expertise to extend your approach according to your organisation's needs.
Power BI decision-support cockpit
Turn scattered data and reporting into a reliable decision-support cockpit enabling leaders to manage the business using shared, consolidated and actionable indicators. For French-speaking Africa, the approach prioritises pragmatic implementation, controlled costs, local delivery and quickly observable results.
AI-ready Data Foundation
Structure the data, content and technology foundations needed to deploy reliable, secure and scalable Data, AI and RAG applications. For French-speaking Africa, the approach prioritises pragmatic implementation, controlled costs, local delivery and quickly observable results.
Talk to an RFC expert
Share your context, priorities and constraints. Our experts help you structure an IT journey aligned with your transformation goals.
Tell us about your challenges
Share your priorities to prepare for a focused discussion.








