Case study

A Fabric foundation for a retailer’s finance and sales

Retail

A mid-size retailer that needed a reporting foundation finance and sales could share. It now runs on a Fabric lakehouse, one KPI layer and 3 executive report templates.

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Period
6 months
Company
50–250 people
Focus
Finance and sales
A schematic: the separate reports this engagement started from, the one consolidated reporting layer that replaced them, and the technologies underneath.

From lakehouse to executive report, in one chain

The retailer needed reporting that finance and sales could both trust, built on Microsoft Fabric. We built the chain from lakehouse to report, put one KPI layer in the middle and gave the executives 3 templates designed for speed and clear drill paths.

layers from the lakehouse to the report
4
KPI domains on one layer
2
executive report templates
3
governance basics handed over
4

Anonymised by sector and size, because the confidentiality that protects this client would protect you too. Sector and outcomes are real; identifying detail is not.

Before and after

Before and after the engagement

Per report

  • Measures written per reportThe same period read two ways
  • Reporting straight off raw extractsShaped again for every model that needed it
  • Conventions left unwrittenThe client’s team had to guess the rules

One KPI layer

  • One KPI layer for finance and salesComparable periods, variance and running totals, defined once
  • A curated model in betweenData shaped once, so the semantic model stays lean
  • 3 executive templatesPerformance and drill paths designed once and reused
From measures written wherever they were needed to one KPI layer both domains read, with time intelligence, variance and YTD and MTD logic decided once.

The engagement in full

Client
A mid-size retailer of 50 to 250 people.
Situation
There was no chain from the data to the report: measures were written where they were needed, so the same period could be read two ways depending on which report you opened, and nothing written down told the client’s own team how to extend it.
Mandate
Build a Fabric analytics foundation, a finance and sales KPI layer on it, and the executive reports that read from it, with the governance to hand it over.

One KPI layer for finance and sales

One set of time intelligence, variance and YTD and MTD logic serves both domains. Finance KPIs, receivables and cash flow among them, and sales performance KPIs read the same comparable periods, the same actual against a baseline and the same running totals.

Executive report templates

Three templates, each built for fast rendering and a clear drill path from summary to detail: an overview, a receivables and cash flow view with current, 30, 60 and 90-plus day buckets, and sales performance.

The architecture, layer by layer

Lakehouse: Data landed in Fabric. Curated model: Shaped once for reporting. Semantic model: The finance and sales KPI layer. Power BI: Executive report templates
Each layer is built on the one before it, so the semantic model reads shaped data rather than raw extracts.

Architecture decisions

DecisionRejected alternativeWhy
A curated model between lakehouse and semantic modelA semantic model on raw extractsData is shaped once, so the semantic model stays lean and quick to query.
One KPI layer for both domainsMeasures written per reportFinance and sales see the same figure for the same period.
Templates for the executive reportsEach report built from scratchPerformance and drill paths are designed once and reused.
Governance packaged at handoverConventions left unwrittenThe client’s team can extend the platform without guessing the rules.

What the client has today

  • A Fabric foundation running from lakehouse through curated and semantic model to Power BI.
  • One finance and sales KPI layer with consistent time intelligence, variance and YTD and MTD logic.
  • 3 executive templates, built for performance and with clear drill paths.
  • Naming and documentation standards across models, measures and reports.
  • A governance package: workspace structure, row-level security patterns, dataset conventions and a handover checklist.
Where it left them
Finance and sales report from one KPI layer, and the executives open templates that were built to be fast and to drill down the same way.
Stack
  • Microsoft Fabric
  • OneLake
  • Power BI
  • DAX
  • SQL
  • Dataflows Gen2
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