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Dashboards people actually open.

Power BI and Microsoft Fabric work, delivered by engineers who model first and visualise second. Semantic models that scale, governance you can defend, and a capacity story that survives a CFO review.

Why most BI dies

Pretty dashboards don't beat trusted ones.

Most BI estates we inherit have the same problem: 400 reports, six versions of revenue, and an audience that quietly stopped opening them. The fix isn't another visual — it's the modelling layer beneath.

We design semantic models that tell a single truth, write DAX that's readable in six months, and deploy via a real ALM pipeline. Then — and only then — we make it look good.

What we deliver

Built for the work — not for the deck.

Modelling

Semantic model design

Star schemas done properly. Single source of truth for the metrics that matter, with calculation groups that keep DAX readable.

Fabric

Microsoft Fabric architecture

Lakehouse, warehouse, and semantic layer on Fabric — with the capacity sizing and workspace governance that stops surprise bills.

Engineering

Data pipelines

Ingest from Dataverse, SQL, SaaS, and legacy sources via Fabric pipelines or Synapse. Incremental refresh, lineage, and quality gates baked in.

Reporting

Reports & visualisation

Reports that pass a usability test on a phone, a tablet, and a 4K screen. Designed for the question, not the showcase.

Governance

Tenant governance

Workspace strategy, deployment pipelines, certification of datasets, and a Purview catalogue your stewards will maintain.

AI

Copilot for Power BI

Copilot integration for natural-language reporting and narrative summaries — with guardrails that keep it factual.

How we work

A measured, honest path from idea to production.

01

Audit

Two-week audit of your current estate. Usage telemetry, model debt, and the metrics that nobody can defend.

02

Model

Design the semantic layer first. Stakeholder workshops to lock the definitions of revenue, margin, churn — every contested metric.

03

Build

Pipelines, datasets, and reports built in source-controlled solutions. Test packs that catch broken DAX before users do.

04

Steward

Stewardship model so trust doesn't decay. Quarterly review of the model, the metrics, and the unused reports.

Where it lands

Patterns clients keep coming back for.

Finance and exec reporting

Single source of truth for revenue, margin, cash, and forecast variance — with the documented lineage your auditor wants and the agility your CFO needs.

Operations analytics

Real-time operational dashboards for ops, supply, and service — with drill-through to the underlying transactions and integrated alerts.

Customer & product analytics

Unified customer view stitching CRM, support, e-commerce, and product telemetry — the foundation for retention work and next-best-action.

Outcomes you can defend

What good looks like.

  • One definition of revenue. Defended by the team, not just by IT.
  • Capacity sized to actual workload, not pessimistic estimates.
  • Report performance you can show off, not apologise for.
  • A stewardship model that decays gracefully when people leave.
  • Documented data lineage that survives an audit.
Frequently asked

The questions clients ask first.

Should we move to Microsoft Fabric?
Sometimes. Fabric is right when you want a unified lakehouse story and you're already heavy on Power BI. It's not right when you have an established Databricks or Snowflake estate that's working. We'll tell you which is which.
Can you migrate from Tableau / Qlik / Looker?
Yes. We've done several Tableau-to-Power BI migrations. The work is mostly semantic — the visuals are the easy part.
How do you handle the contested-metric problem?
We facilitate a definitions workshop with the people who care, write the definition down, and embed it in the semantic model with calculation groups. The argument happens once.
Do you support DataOps and DevOps for analytics?
Yes — source-controlled .pbip projects, deployment pipelines via Azure DevOps or Fabric Git integration, and automated tests with Tabular Editor and DAX Studio in CI.

Let's scope a first conversation.

Tell us what you're trying to do. We'll come back with a point of view, not a sales pitch.