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Power BI Semantic Model Design

The semantic model is where Power BI succeeds or fails. We design star-schema models with clean DAX architecture, calculation groups, row-level security, and the right storage mode, built to be shared, certified, and maintained.

What You Get

StarProper dimensional design, always
SharedOne model serving many reports
FastStorage mode matched to workload
DocumentedMeasures and lineage explained
What's Included

Power BI Semantic Model Design: the full scope

Dimensional modeling
Star schemas with conformed dimensions, replacing single-table sprawl.
DAX architecture
Measure organization, calculation groups, and patterns that stay debuggable.
Storage strategy
Import, DirectQuery, Direct Lake, or composite, chosen per workload with evidence.
Row-level security
RLS and OLS design tested per role, including dynamic patterns.
Performance engineering
Aggregations, incremental refresh, and query tuning.
Model consolidation
Rationalizing dozens of overlapping datasets into governed shared models.
How We Work

Structured delivery, every engagement

The same disciplined framework behind our enterprise migrations: documented, validated, and led by senior expertise from start to finish.

1

Assess

Inventory every report, data source, and dependency. Usage analysis identifies what actually matters.

2

Rationalize

Retire duplicates and unused reports. Typically 30 to 50 percent never need migrating.

3

Modernize

Rebuild on Power BI and Fabric with governed semantic models and validated outputs.

4

Govern

Workspaces, row-level security, certified datasets, and documented standards.

5

Enable

Training and handover so your team owns the platform, not a vendor.

Talk to a specialist

A free 30-minute discovery call: bring your questions about power bi semantic model design, leave with a clear next step and an honest read on effort and cost.

Book a Discovery Call →
Common Questions

Power BI Semantic Model Design FAQ

Why do our reports disagree with each other?

Almost always: each report carries its own dataset with its own logic. Consolidating onto shared, certified semantic models with governed measures is the structural fix.

Import, DirectQuery, or Direct Lake?

It depends on volume, latency, and infrastructure. We benchmark your actual workload against the options and document the tradeoffs rather than defaulting.

Can you fix a slow model without a rebuild?

Often yes: DAX rewrites, relationship fixes, aggregations, and refresh strategy recover most performance. Where rebuild is genuinely cheaper, we say so with evidence.

Do you document as you build?

Every model ships with measure definitions, lineage, and design rationale, so the next developer (internal or external) is not starting from archaeology.

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Tell us what you are working with. A senior specialist will respond within one business day.

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Location
Vancouver, BC. Serving BC, Alberta, and Washington.
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