Fabric puts ingestion, the lakehouse, the warehouse, orchestration and Power BI behind a single billing model and a single security boundary. For a business already committed to Microsoft, that removes most of the integration work a data platform usually demands — and introduces a set of choices about capacity and workspace design that are expensive to get wrong.
Overview
OneLake, and what it changes
Fabric's shortcut model means data can be queried where it lives instead of being copied into each engine that needs it. That is the single biggest saving available in a Microsoft data estate, and it is also the part most implementations miss — they lift and shift their existing copy-everywhere pipelines into Fabric and pay for the same duplication on a newer bill.
What we deliver
Where the money is actually spent
Fabric bills by capacity, not by query, which changes how you design. Workloads that were fine on a per-query platform can saturate a capacity unit and throttle everything sharing it. We size capacity against real workload profiles and separate workspaces so that a heavy refresh cannot take reporting down with it.
- Lakehouse and warehouse design, with a clear rule for which to use when
- OneLake shortcuts instead of duplicate copies
- Direct Lake semantic models for Power BI, avoiding import refresh windows
- Capacity sizing, monitoring and workspace separation
- Migration from existing Synapse, Data Factory or Power BI estates
Why it matters
Why Fabric, and when not
Fabric is the right answer when the organisation is already on Microsoft 365 and Power BI, and wants one security model across the estate. It is the wrong answer when the workload is a single large warehouse with heavy concurrent SQL, where a dedicated warehouse still wins. We will tell you which case you are in.
Workflow
How we work in it.
- 01
Assessment
- Current estate: Synapse, Data Factory, Power BI, on-premises sources
- Workload profile and concurrency requirements
- Capacity sizing model and cost forecast
- Security and tenancy boundaries
- 02
Platform Design
- Workspace and domain structure
- Lakehouse and warehouse split
- OneLake shortcut strategy
- Semantic model approach: Direct Lake or import
- 03
Build & Migration
- Pipelines and dataflows
- Medallion layering with tested transformations
- Report migration and rewiring
- Parallel running against the existing estate
- 04
Operate
- Capacity monitoring and throttling alerts
- Refresh scheduling that respects the capacity
- Governance, lineage and endorsement
- Handover and training
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