Microsoft Fabric Consulting for UK Organisations

Fabric is a platform decision, not a product install

Most organisations arrive at Fabric from one of three directions. Power BI Premium capacity has been retired and the F-SKU question has landed on your desk. An ageing SQL Server estate needs a modern analytical destination. Or the board has asked what the AI strategy is, and the honest answer starts with getting the data estate in order.

In each case the expensive mistakes happen early: capacity sized on guesswork, a lakehouse structure that mirrors the old warehouse instead of the workloads, governance bolted on after the first oversharing incident, and a delivery partner whose junior team learned Fabric on your project. Those mistakes are cheaper to avoid than to unwind.

If you held Power BI Premium, the clock is already running

Microsoft retired Power BI Premium capacities and moved the workload model to Fabric F-SKUs. For organisations that held P-SKUs, this is not an optional evaluation: the renewal conversation is a Fabric conversation whether you planned one or not. The trap is treating it as a like-for-like licensing swap. F-SKU capacity behaves differently under load, smoothing and throttling work differently, and the capacity now carries workloads Premium never did: lakehouses, pipelines, notebooks, real-time intelligence. Renew at the equivalent SKU without baselining and you either overpay for headroom you never use or discover throttling the first month a data engineering workload lands on the reporting capacity.

The right sequence is short: baseline the current consumption from the capacity metrics app, model the workloads you intend to add over the licence term, then size. One recent engagement, capacity optimisation for an insurer running F512, paid for itself in the reservation decision alone. That is the shape of work an afternoon of licensing advice from a reseller does not cover, because the reseller's incentive is the larger SKU.

What the consulting covers

Area	What gets decided	What you keep
Architecture and workspace design	Lakehouse versus warehouse per workload, medallion structure, workspace and domain layout, source control	A documented target architecture your team can extend
Capacity planning and cost	F-SKU sizing against real workloads, capacity metrics baselining, reservation versus pay-as-you-go, chargeback model	A sizing model with the workings shown, not a licence quote
Migration	Which SQL Server, Synapse and Power BI Premium workloads move, in what order, and which should not	A phased migration plan you can deliver with or without us
Governance and security	Tenant settings, Purview integration, sensitivity labels, sharing controls, certification workflow	A governance baseline configured, documented and owned in-house
Team capability	Skills gaps against the target architecture, training plan, DP-600 pathway where certification matters	A team that runs the platform without a support retainer

Published pricing

No Fabric consultancy ranking for this work in the UK publishes a price. Here is ours.

Day rates are exclusive of VAT. Remote delivery as standard, on-site across the UK by arrangement.

Fabric is the unglamorous half of your AI strategy

Every AI ambition an organisation holds, Copilot grounded in company data, agents acting on business systems, models trained on operational history, rests on the same prerequisite: a governed, consolidated, well-modelled data estate. That is what Fabric is for. OneLake gives AI workloads one place to find the data; the semantic models give them meaning; the governance layer decides what they are allowed to see. Skip that layer and the AI programme discovers it the hard way, usually as a Copilot answer built on an overshared spreadsheet.

This is why the Fabric conversation and the AI conversation belong together, and why this practice runs both: Fabric consulting for the platform, and an AI enablement programme for what the organisation does on top of it. Boards asking "what is our AI strategy" are usually asking, without knowing it, "is our data estate ready", and the assessment answers that question with evidence rather than sentiment.

Why a named expert rather than a delivery team

Large consultancies sell Fabric through a partner badge and deliver it through whoever is on the bench. You meet the principal at the pitch and the graduates at the kick-off. The commercial model also rewards long engagements, so the incentive is to stay, not to hand over.

This engagement works the other way. The person on the call is the person doing the work: a Microsoft Data Platform MVP, a Microsoft Certified Trainer, and a consultant who has administered SQL Server estates for over twenty years and now designs and delivers Fabric platforms for insurers, local authorities and fintechs. Because training is half the practice, knowledge transfer is not a closing slide. It is the delivery method. The measure of a good engagement is that you do not need the next one.

The mistakes we get called in to fix

A pattern has emerged in the Fabric estates we inherit rather than design, and it is worth naming because every item on the list is avoidable at the design stage for a fraction of the remediation cost.

The most common is the warehouse rebuilt as a warehouse: the old dimensional model lifted into Fabric table for table, complete with the ETL logic that existed to work around constraints Fabric does not have. The second is capacity contention, where reporting, refresh and engineering workloads share one capacity with no surge protection, so month-end reporting slows every time a notebook runs. The third is governance by default: tenant settings never reviewed, everyone a workspace admin, sensitive data discoverable through OneLake search because nobody configured the boundaries. The fourth is the semantic model sprawl Premium estates carried for years, imported wholesale instead of consolidated on the way in.

None of these is a tooling failure. All of them are decisions that were never consciously made. The value of the assessment stage is that the decisions get made once, on purpose, with the reasoning written down.

Recent Fabric delivery

The proof for this kind of work is delivery, not certification badges. Recent and current engagements include Fabric and Power BI capacity optimisation for a UK insurer on F512, producing significant cost savings on the capacity commitment; design and architecture of a Fabric deployment for a large local authority; a data engineering build for risk reporting with a fintech in the insurance broker space; and bespoke Fabric training for public sector teams operating the platforms afterwards. Client references are available on request, and several are quoted on the team page.

How an engagement runs

Every engagement is scoped in writing against one of three shapes. A short assessment produces a decision and a plan. A delivery engagement builds the platform alongside your team in agreed project days. An advisory arrangement provides ongoing architecture and governance review at a defined monthly cadence. In all three, artefacts are documented as they are produced, decisions are recorded with their reasoning, and your team is in the room, not copied in afterwards.

Where the gap is skills rather than delivery capacity, the training practice takes over: DP-600 Fabric Analytics Engineer for certification, Power BI and Fabric governance training for administrators, and bespoke team programmes built around your own estate.

Frequently asked questions