Design the architecture before building
Lakehouse architecture for your data landscape, workspace and capacity planning, a governance and security model, and integration with the Azure and Power BI estate you already run.
Build
Fabric platform build
The build is scoped around what happens after go-live: a platform your team can operate, that fits the systems you already have and grows with the organisation.
- Duration
- 8 to 12 weeks
- Engagement
- Fixed scope and deliverables, agreed in a written proposal after a first call
- You leave with
- A production platform, a trained team, and the documentation to run it
What is included
Build it to production standard
Workspace setup and configuration, pipelines in Data Factory and Dataflows, a medallion lakehouse, semantic models for self-service, and report templates with design standards.
Hand it over to a team that can run it
Training, documentation of every architecture decision, a governance playbook, knowledge transfer with your technical team, and four to six weeks of support after go-live.
How the build runs
Discovery and planning
Stakeholder workshops, a current-state view of your data landscape, and success criteria agreed before anything is designed.
Foundation
Workspaces and capacity set up, governance and security configured, source systems connected, and the first pipelines running.
Build and integrate
Lakehouse layers implemented, pipelines built out and orchestrated, semantic models developed, reports created, then tested with the people who will use them.
Go live and hand over
Training sessions, the decision log and governance playbook handed across, go-live support, and a post-implementation review a few weeks in.
Who this is for
Organisations ready to move to one platform: several data sources to bring together, self-service analytics to enable across teams, governance needed from day one, and the capacity to give time to workshops and knowledge transfer.
If you're still deciding whether Fabric is right at all, start with a POC and assessment. If you only need report and model work, Power BI transformation is the better fit.
What moves it from eight weeks to twelve
- Number of data sources and how they connect
- Existing infrastructure and technical debt
- Team availability for workshops and reviews
- Governance and approval requirements
What a client said
Prathy made an exceptional impact from the moment she joined, leading the build of a complete Microsoft Fabric environment and delivering a wide range of high quality reports. Her technical expertise was matched by her ability to explain complex concepts in a clear, approachable way, ensuring the wider team understood not just what was being built, but why it mattered and how it worked.
Plan the build
Book a call and tell me about your data landscape. I'll say what the build would involve, then follow up with a written proposal.