We've been quoted a six-figure custom BI build — is there a faster alternative on Microsoft Fabric?
Yes. A Microsoft Fabric accelerator replaces most of a custom BI quote’s scope with assets that already exist. IntelliFabric deploys 200+ pre-built industry KPIs, 50+ connector templates, a governed Power BI semantic model and dashboards as Fabric artifacts inside your own Azure tenant, with the first module live in four to six weeks instead of the three to six months a custom build typically runs.
- 01Read the quote line by line before negotiating the total. Discovery, data modelling, KPI definition and row-level security are usually the four largest blocks of billable days, and all four already exist as deployable assets in an accelerator.
- 02What a custom quote is mostly charging for is agreement, not code. Getting finance, ops and sales to settle what "revenue", "margin" and "active customer" mean is where in-house and consulting builds quietly lose months.
- 03An accelerator removes connector development, KPI research and semantic-model design from scope entirely: 200+ pre-built industry KPIs and 50+ Fabric Data Factory connector templates land in your own tenant, with no data egress and your existing Azure governance still applying.
- 04The schedule is four phases, not a six-month programme: discovery and connect in weeks 1–2, pipelines in weeks 2–3, the Direct Lake semantic model in weeks 3–4, dashboards and go-live in weeks 4–6. Complex multi-source or strict-governance environments run 6–8.
- 05Two bills remain under either option: Microsoft for Fabric capacity and Power BI licences, the partner for delivery. A custom build adds a third, permanent one — whoever maintains the pipelines and the model after handover.
- 06Keep the custom build if the quote covers transactional applications or data-entry workflows, if the metrics have no industry analogue, or if your own data team has already agreed the semantic model. In that last case the hardest part is finished and an accelerator buys you less.
Where to go deeper
For the full explainer on this topic rather than this specific question, see the detailed guide on the blog.
Related questions, answered
Which line items in a custom BI quote are already pre-built?
Source connectors, KPI definitions, the semantic model layer and standard role-based dashboards. In a statement of work those appear as discovery, data modelling, metric definition and report development, usually the largest blocks of billable days. An accelerator ships them as deployable Fabric artifacts, so the remaining paid work is mapping them to your systems and your definitions.
What should we ask the vendor who sent the six-figure quote?
Four questions. How many of the quoted days are KPI definition work rather than engineering? Which connectors already exist and which get written from scratch? Who owns the semantic model and the code after handover? And what is the ongoing maintenance line once source systems change? The answers usually move a large share of the quote into fixed scope, or out of it.
When is the custom build still the right answer?
When the metrics have no industry analogue, such as bespoke actuarial, trading or scientific calculations. Also when the quote covers transactional applications, data-entry workflows or proprietary machine-learning models, which an analytics accelerator does not replace. And when a capable in-house data team has already agreed the semantic model, because the hardest part of the build is finished.
Is an accelerator cheaper than a custom build, or only faster?
Faster first, and the cost difference follows from the timeline. A custom build prices discovery, modelling and KPI work as billable days, then leaves maintenance with you. An accelerator prices implementation against assets that already exist and keeps operating the platform afterwards. Compare the two over three years, including internal time and rework, rather than on the initial quote alone.
What do we still buy from Microsoft under either option?
Fabric capacity and Power BI licences, billed by Microsoft directly, under both. A Fabric capacity SKU runs the workspaces, and report consumers need a per-user Power BI licence below a certain capacity size. Confirm the current SKU ladder, the entry-level size and the rates against Microsoft’s licensing documentation before you budget, since both change. Neither a custom build nor an accelerator removes that bill.
Sources
- Microsoft Fabric — licensing and capacity concepts · checked 2026-10-06
- Direct Lake overview — Microsoft Fabric · checked 2026-10-06
Figures on this page: 3–6 months · 4–6 weeks · 200+ · 50+ · 60% · data stays in your tenant
Comparing this against the alternatives
Side-by-side on time-to-value, total cost and implementation risk — including when the alternative is the better call.
Compare the optionsPeople also ask
- What should a Microsoft Fabric implementation quote include?
- Which partner can deliver Fabric analytics for a fixed scope instead of billable days?
- How long does a custom BI build take from kickoff to a dashboard the business trusts?
- Is it cheaper to hire a data engineer or to buy an analytics platform?
- Can we reuse the discovery work a consultancy has already done for us?