Help deciding

Should you move to Fabric? In most cases, not yet.

We are asked this every week, and the honest answer often displeases integrators. Here are the three signals that genuinely justify the move, and what it costs.

signals that justify the move. One is enough.

Below that, Power BI on its own does the job

3
Signals are enough to know whether to move: 1
One of them is enough to raise the question: 3-10 d
A standard Power BI project, with no platform: 30-150 d
A complete Fabric platform

The tipping point

The three signals, and one is enough

The three signals that justify moving to Microsoft Fabric
Signal	What you observe	Why Power BI alone no longer suffices
Divergence	Two departments announce different figures for the same question.	Each report has recoded its own definition. As long as the rule lives inside the reports, it will keep diverging.
Asynchrony	Nobody knows how old the figures on screen are, nor whether the dataflow and the model are current together.	Dataflows and models refresh separately, within a limit of eight times a day on a Pro licence.
Opacity	When a report breaks, finding the faulty link takes hours.	There is neither end-to-end lineage nor supervision: diagnosis rests on one person’s experience.

The comparison

What each architecture brings, and what it costs

Power BI on its own compared with a Fabric platform
Criterion	Power BI alone	With Microsoft Fabric
Setup	3 to 10 days for a focused scope.	30 to 150 days depending on the number of sources.
Licences	One Pro licence per user who reads.	Dedicated capacity: readers no longer need an individual licence, but the capacity is billed.
Consistency of the figures	Rests on discipline: one shared model, as long as everyone sticks to it.	Structural: the rules live upstream, so they cannot diverge any more.
Multiple sources	Workable up to a few similar sources.	Designed for it, that is what it is for.
Governance	Drift is likely once dataflows and datasets multiply.	Git versioning, deployment pipelines, explicit ownership.
Reversibility	The semantic model stays reusable under Fabric.	Storage in the open Delta format, readable by other tools.

The sequence

Starting with Power BI is often the right call

It is often the right sequence, too. A well-built semantic model in Power BI is reused under Fabric: the modelling work is not lost, it simply changes level.

What is lost are the business rules recoded in every report. Hence the one piece of advice that holds, whether you move to Fabric or not: centralise your rules from the very first report. A measure defined once and reused everywhere will gain you more than any platform.

Frequently asked

What people ask about this trade-off

Should we move to Microsoft Fabric?

In most cases, no, not yet. Power BI on its own is enough as long as your sources are few, stable and clean, and the calculation rules stay simple. Fabric becomes relevant when several departments produce different figures for the same question, when refreshes no longer keep up, or when nobody can diagnose a chain that breaks.

Can we start with Power BI and move to Fabric later?

Yes, and that is often the right sequence. A well-built semantic model in Power BI is reused under Fabric: the modelling work is not lost. What is lost are business rules recoded in every report, which is why centralising them from the start is worth it, even without Fabric.

Does Fabric replace Power BI?

No. Power BI is the serving layer of Fabric: the reports your teams use remain Power BI reports. Fabric adds what sits upstream, ingestion, storage, transformation and orchestration, under one platform and one bill.

What does moving to Fabric cost?

Two separate lines. The Microsoft capacity, billed by Microsoft: on shared capacity every reader needs a Power BI Pro licence, on dedicated capacity readers no longer need one but the capacity is billed monthly. And the build, 30 to 150 days depending on the number of sources. We cost both scenarios during the scoping workshop.

The gap

What a shared layer changes

With no platform, every report pulls its own extract and recodes its rules, hence three figures for the same question. With a shared layer, the rule is written once and every report agrees.

The same report, two architectures underneath

On the left, every report redoes the work. On the right, it is done once and for all.

The move changes nothing of what the user sees: it changes what sits behind, and therefore whether two departments get the same figure.

Two hours to decide, on your own data.

Eleven expert consultantsSaint-Priest, near Lyon, France

A scoping workshop with a consultant, free and without commitment. We look at your sources and your business rules, and we tell you straight which side you are on, including when the answer is to stay on Power BI.

Request a scoping workshop

Scoping workshop · 2 hours · free