Microsoft Fabric ./

Enterprise semantic models, dimensional design, and BI architecture brought into Microsoft's unified data platform for data-intensive and regulated environments.
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Microsoft Fabric data estate, semantic model, and analytics architecture

What Matters

One platform means fewer handoffs and higher stakes

Bringing ingestion, transformation, semantic models, and reporting into one platform reduces handoffs between teams. It also puts more weight on the core decisions: how the estate is structured, who owns metrics, how pipelines run, and how governance is applied.

Fabric works best when metrics are defined once, owned clearly, and used consistently across reports and teams. The semantic layer is where analytical confidence is either established or quietly lost, so model design, ownership, and versioning need to be treated as part of the platform, not as reporting afterthoughts.

What We Do

The core layers of a governed Fabric estate

Fabric architecture decisions shape the platform long after go-live: workspace structure, OneLake boundaries, lakehouse and warehouse usage, and the overall design of the estate. Those decisions need to reflect the data itself, the reporting needs, the access model, and the team that will maintain the platform.

How We Work

A controlled path from estate review to operational handover

Fabric delivery needs architecture, governance, and platform controls to move together from the start.

1

Assessment

We start with the actual state of the data estate: sources, existing models and pipelines, quality problems, governance gaps, and the business requirements the platform needs to serve. For greenfield engagements, this is a requirements and architecture discovery. For existing platforms, it is a structured diagnostic. We assess before we propose.

2

Architecture design

Data estate structure, semantic model design, dimensional model, pipeline architecture, governance model, and security design are documented before implementation begins. Decisions and their rationale are recorded so the platform is maintainable and the reasoning survives personnel change.

3

Implementation

Semantic model build, pipeline development, report layer, security configuration, and deployment pipeline setup are built to the architectural design. No undocumented shortcuts that become the next team's legacy problem.

4

Governance and operationalisation

Deployment pipelines, source control, refresh automation, monitoring and alerting, and access review processes keep the platform operating as a managed artefact rather than a file someone maintains in isolation.

5

Handover and knowledge transfer

Documentation, training where required, and a transition designed so the client team understands what they have and can maintain it. Not a handoff, but an operational handover with readiness confirmed before we step back.

What the Market Says

What Fabric estates actually run into

Real pain points from analytics, data, and IT leaders working through model sprawl, refresh failures, and rising cost.

“We have thirty-something Power BI reports. Every team has their own version of revenue. We've been trying to agree a single definition for two years. We haven't.”

— Head of Analytics, Professional Services

Proven Track Record

Built on deep BI architecture experience

Enterprise BI architecture, semantic models, dimensional design, and performance optimisation across twenty-five years of delivery in data-intensive and regulated environments.

Years

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Delivering technology solutions across 15 countries

Clients

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Across financial services, insurance, healthcare, telecoms and retail

Projects

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Delivered worldwide

NPS

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Client satisfaction score (H1)

Microsoft Fabric

Talk to us about your Microsoft Fabric programme.

Whether you are defining the target estate, rebuilding the semantic layer, or stabilising inherited pipelines, we can help.

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