Readiness and architecture
Map workloads, skills, tenancy, security, networking and lifecycle needs into an evidence-backed target design.
Microsoft Fabric consulting
Choose the Fabric architecture before the platform chooses it for you.
We help teams assess readiness, select the right data patterns and implement Microsoft Fabric with capacity, governance and ownership designed in from the start.
Architecture firstPatterns follow workloads and team capability.
Power BI connectedSemantic models are part of the platform plan.
Capacity visibleAssumptions and monitoring are documented.
Operable handoverOwnership and release paths are explicit.
Fabric scope
One platform, with deliberate boundaries.
Fabric can simplify a stack, but only when storage, compute, transformation, semantic and governance decisions are made together.
Data products and pipelines
Implement ingestion, transformation, lakehouse or warehouse structures and semantic models with traceable ownership.
Capacity and governance
Define workspace strategy, access, deployment, monitoring, cost controls and support responsibilities.
Implementation path
Prove the pattern before scaling the estate.
A representative workload exposes architecture and operating gaps earlier than a broad platform rollout.
Assess
Inventory current workloads, constraints, volumes, refresh windows, skills and governance requirements.
Design
Define target patterns, workspace boundaries, capacity assumptions, security and deployment flow.
Pilot
Deliver one representative data product end to end and measure performance and operability.
Scale
Harden reusable patterns, migrate prioritised workloads and transfer ownership to the platform team.
Qualification
Fabric is a platform decision, not a licence decision.
The strongest starting point is a real workload plus owners who can decide architecture and governance.
Good fit
- You have named workloads and consumers to prioritise.
- Platform, security and business owners can join discovery.
- You need a governed path from data to Power BI.
- You want a pilot before broader migration.
Probably not yet
- Fabric has been selected without a workload or owner.
- No one can decide access and workspace boundaries.
- Capacity is expected to solve inefficient models automatically.
- The rollout must move everything in one untested step.
FAQ
Fabric architecture questions.
Should we use a lakehouse or warehouse?
It depends on workloads, data shape, engineering skills, SQL requirements and operating model. The readiness assessment compares those factors before selecting a pattern.
Can you migrate existing Power BI workloads?
Yes. Datasets, dataflows, refresh paths, gateways and workspaces can be inventoried and moved in controlled stages.
How do you approach capacity planning?
We model workloads, concurrency, refresh windows and growth assumptions, then compare the plan with observed usage after release.
Does implementation include governance?
Yes. Workspace boundaries, naming, access, deployment, lineage, ownership and operating responsibilities are part of the design.
Start with one workload
Tell us what you want Fabric to replace or enable.
Share the current platform, priority workload, volumes and constraints. We’ll tell you what a readiness assessment should cover.
Prefer email? info@datagrape.ai