Microsoft Fabric consolidates ingestion, storage, transformation, warehousing, real time analytics and Power BI into a single platform with one capacity model and one permission model. For organisations running a mix of on premises SQL Server, Azure Synapse, standalone Power BI and a scattering of departmental databases, that consolidation is genuinely valuable. It is also where most of the risk sits, because collapsing an estate into one platform means the decisions you make early are expensive to reverse.
We deliver Fabric for government agencies and regulated businesses, where the reporting has to be defensible as well as fast.
Where Fabric engagements go wrong
Three failure modes account for most of it.
- The architecture is drawn before the questions are known. A reference architecture appears in week one and use cases are retrofitted to it. What follows is an expensive platform nobody queries.
- Data quality is treated as someone else's problem. The build is rarely the hard part. Discovering that three systems hold three different versions of the same entity, and that nobody owns the reconciliation, is the hard part.
- Capacity is guessed. Fabric capacity is a reserved commitment. Oversize it and you burn budget on idle compute. Undersize it and queries throttle at month end when every report runs at once.
How we scope an engagement
We start with the decisions your organisation currently makes slowly or badly because the data is not available. That produces a shortlist of concrete outputs, and the architecture follows from those outputs rather than the other way round.
From there we profile the source data before building any pipelines, name a business owner for each domain, and build one representative workload end to end. That first workload is what tells us how much capacity you actually need, which is the only reliable way to size it.
Sovereignty and data residency
For Australian government workloads we confirm early which Fabric services are generally available in Australian regions and which are not, because that gap moves. We confirm where Copilot and other AI features process data, and we map the design against your classification framework before anything is built. Establishing this at the start costs a workshop. Discovering it after a build costs a rebuild.
Delivery is ISO/IEC 27001 certified and we can provide security-cleared personnel where the environment requires it.
Fabric, Databricks or Snowflake
We are partners with Databricks and Snowflake as well as Microsoft, so we do not need to force every estate onto one platform.
- Microsoft Fabric suits organisations already standardised on Microsoft 365 and Power BI that want one capacity and permission model.
- Databricks suits heavier data engineering and machine learning workloads, and organisations working across more than one cloud.
- Snowflake suits teams that want a fully managed SQL warehouse and need to share data securely between agencies or business units.
Many estates end up using more than one. Fabric and Power BI can work directly with data held in Databricks and Snowflake, so the decision is about where each workload runs best rather than one bet for the whole organisation.
What you own at the end
The measure of a good Fabric engagement is whether your team can extend the platform six months later without calling us. That means your engineers build alongside ours rather than watching, naming conventions and patterns are documented as they are set rather than at the end, and the operating model is agreed before go live.
Where an agency prefers us to stay, we do that through Seers Care managed services rather than an open-ended project. Capability transfer is the point of the engagement, not a phase at the end of it.