Questions to Ask a Microsoft Fabric Consulting Partner Before You Sign

Microsoft Fabric is Microsoft's unified analytics platform — Data Engineering, Data Factory, Data Science, Real-Time Intelligence, Power BI and AI in one SaaS environment. But a successful Fabric rollout is rarely a licensing decision. It is a partner decision.

Plenty of organisations move fast on the platform and find out months later that costs overran, performance is poor, governance was never planned, the old Power BI reports do not perform, security does not meet compliance, or the data migration was far harder than anyone scoped. The wrong consulting partner costs a great deal more than the right one — usually in rework nobody budgeted for.

This guide sets out the questions worth asking before you sign, what a good answer sounds like, and the red flags that should give you pause.

Fabric touches the whole data estate — ERP, CRM, manufacturing systems, warehouses, Power BI, AI, data lakes, streaming, governance and security. A poorly designed implementation is expensive to maintain and hard to scale, and the cost of that shows up long after go-live.

A partner who genuinely knows the platform is what gives you:

• Faster deployment
• Lower running cost
• Governance built in from the start
• Higher user adoption
• An architecture that scales

Are you a Microsoft Fabric specialist, or a general BI firm? Many firms now advertise Fabric. Push for specifics: how many Fabric projects have you delivered, how many Fabric-certified consultants do you have, and what share of your work is actually Fabric? A genuine specialist is fluent in the parts that matter:

• Lakehouse architecture and OneLake
• Direct Lake and semantic models
• Data Factory pipelines
• Real-Time Intelligence
• Fabric warehouses
• Capacity optimisation

What industries have you worked in? Every sector has its own data — MES and OEE in manufacturing, HIPAA and clinical reporting in healthcare, forecasting and inventory in retail, fleet and route data in logistics, regulatory and risk reporting in finance. Ask for examples in yours; sector experience takes real risk out of the build.

Can you show real Fabric work, not slides? Ask for a demonstration — a lakehouse, a pipeline, live Power BI reports, capacity monitoring, a governance setup — rather than a deck. A real partner is comfortable showing prior work within the bounds of client confidentiality.

How will you handle our existing Power BI reports? Most organisations already run Power BI. Ask whether reports need rebuilding, whether semantic models can be reused, whether Direct Lake will improve performance, how paginated reports are handled, and whether Row-Level Security carries over. Migrating well can save hundreds of development hours.

How will you design our architecture — and why? Architecture decisions set your scalability for years. Ask for a proposed design covering OneLake structure, lakehouses, warehouses, pipelines, Dataflows Gen2, notebooks, semantic models, Power BI, security and workspace strategy. A good partner explains why they recommend a shape, not just what they will build.

What is your data migration strategy? Migration is usually the hardest part. Ask how they move from SQL Server, Azure Synapse, Snowflake, Databricks, Oracle, SAP or on-premises databases — and, just as important, how data quality is validated, whether historical data comes across, and what the rollback plan is if a cutover goes wrong.

How will you keep capacity costs under control? Fabric runs on a consumption-priced capacity, and the bill climbs quickly without discipline. Ask which SKU they recommend and why, how workloads are scheduled, how idle capacity is minimised, whether auto-scale is used, and how utilisation is monitored through the Capacity Metrics App.

How will security and governance be handled? Governance belongs in the initial design, not bolted on later. Ask how they implement Microsoft Purview, data lineage and classification, role-based access control, Row-Level Security, workspace governance, sensitivity labels and compliance monitoring.

Do you deliver AI and Copilot properly? Ask whether they can implement Fabric AI features, Copilot, Azure AI, predictive models and natural-language querying — and, more tellingly, whether they will tell you where AI adds measurable value and where it does not. Copilot on an ungoverned model answers confidently and wrongly.

What is included after go-live? Many engagements end the day the platform ships. Clarify hypercare, performance monitoring, user training, documentation, knowledge transfer, SLA commitments, ongoing optimisation and capacity tuning. Post-implementation support is often as important as the build.

Can you show a detailed project plan? Ask for a phased roadmap with clear deliverables at each step:

What does success look like? Agree measurable success criteria before the work starts — faster refresh times, lower infrastructure cost, better query performance, higher adoption, less data duplication, stronger governance. If nobody defines success up front, nobody can hold the project to it.

Be cautious of a partner who:

• Talks only about Power BI and cannot go deep on Fabric
• Cannot explain OneLake architecture
• Has no experience with Fabric capacity management
• Gives vague timelines or pricing
• Skips past governance and security
• Cannot provide references or case studies
• Proposes a single architecture for every client
• Has no clear plan for after go-live

A quick scorecard for any Fabric consulting firm — you want a clear yes to each:

• Fabric-certified consultants on the team
• Industry-specific experience
• Proven Fabric implementations you can see
• Real data-migration expertise
• A capacity optimisation strategy
• A governance and security framework
• AI and Copilot capability
• Post-go-live support included
• A transparent pricing model
• A documented delivery methodology

We are a Microsoft-first practice — Fabric, Power BI, Azure and Power Platform — working with manufacturers, FMCG, logistics, EPC and financial-services operations. The questions above are the ones we expect buyers to ask us, and the ones we answer plainly:

• Fabric readiness assessment and a costed roadmap
• End-to-end implementation and legacy-platform modernisation
• Power BI migration and optimisation on Direct Lake
• OneLake architecture and data-engineering pipelines
• Capacity planning and cost control
• Governance and security from day one
• AI and Copilot where it earns its place
• Managed support and continuous optimisation after go-live

And the honest part: we will tell you where Fabric is not the right answer, and where a smaller scope gets you further than a big programme. First working output in six weeks — not a 50-slide roadmap.