Representative Retail Analytics Team

The retail analytics function was producing reports from multiple sources — some from Power BI connected to a central data warehouse, others from ad-hoc Excel extracts, and a growing number from Power BI Embedded on commerce platforms. There was no shared semantic model, no consistent naming convention, and no clear handover process between the team that built the data pipelines and the analysts who created reports on top of them.

Business stakeholders were receiving inconsistent numbers from different reports on the same metrics. Trust in analytics outputs was declining. The lead analyst estimated that 30–40% of reporting time was being spent on validation and reconciliation rather than insight delivery.

The engagement focused on three areas in sequence: data modeling foundations, report governance standards, and deployment workflow clarity. A three-week enablement series combined structured sessions with working group reviews of live reports and data models already in production.

The data modeling sessions introduced star schema design, composite model considerations, and semantic layer principles — with examples pulled directly from the team's existing Power BI workspace. Governance standards covered report certification workflow, naming conventions, and the distinction between certified datasets and working drafts. The final sessions helped engineering and analytics teams agree on a shared handover process, a documentation template, and a lightweight review checklist before reports moved into production.