The problem

“We want AI. Is our data ready for it?”

Deliverables

  • Current state of the platform, BI, governance and costs
  • AI maturity assessment
  • Prioritized roadmap: expected gains and effort for each workstream
  • Presentation to leadership and to the teams

How it works

  1. Scope

    A kick-off meeting: goals, scope, stakeholders.

  2. Analyze

    Business and technical interviews, review of the platform, models, access and costs.

  3. Prioritize

    Workstreams ranked by value and effort, with their dependencies.

  4. Present

    A clear roadmap, presented to leadership and to the teams.

Case studies

Related case studies

  • Luxury

    Global luxury group

    Industrializing Power BI and Fabric for a global luxury group

    Context
    Several teams of Power BI developers, manual releases, and no systematic check before production.
    Outcome
    100% of Power BI developers trained3 environments, DEV to PRD, with controlled promotion
    • Power BI
    • Microsoft Fabric
    • GitHub Actions
    • CI/CD
  • Healthcare / Medtech

    Medtech group

    Moving beyond Excel: a medtech group's first BI platform

    Context
    A medtech group with no BI platform: sales, marketing, finance and leadership ran the business from large Excel files and exports reworked by hand.
    Outcome
    130+ users across sales, marketing, finance and leadership-50% manual data handling
    • Power BI
    • CRM
    • Self-service
    • Automation

Contact

Start with an assessment

Two weeks to know what to do, and in what order.