The problem

“Our BI deployments are manual and risky.”

Deliverables

  • CI/CD pipelines on GitHub Actions or Azure DevOps
  • DEV, UAT and PRD environments with controlled promotion
  • Automated quality gates: best practices, DAX tests, refresh validation
  • Automated workspace provisioning
  • AI-assisted development (PBIR, TMDL)
  • Training for your developers and documented standards

How it works

  1. Audit

    Your current release process, your environments and your teams.

  2. Set up the framework

    TMDL and PBIR versioning, pipelines, quality gates, central configuration.

  3. Pilot on one scope

    A first model delivered end to end through the new pipeline.

  4. Scale and train

    Every team trained, standards documented.

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

Contact

Are your releases still manual?

Let's look at how to automate your Power BI and Fabric releases.