Getting started with Power BI (without overbuilding)
Most mid-market teams do not need a data platform program on day one. They need one dashboard leadership trusts—built on a semantic model that can grow. Here is a practical path from spreadsheets and ERP exports to credible Power BI.
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Start with one decision, not every report
Pick the question that hurts most this quarter: margin by customer, backlog risk, pipeline vs. bookings, or fill rate. Scope the first dashboard to answer that question end-to-end. Everything else waits.
Model before visuals
Resist the urge to connect everything at once. Land a small star schema: a fact table at the grain finance expects, conformed dimensions for customer, product, date, and region, and centralized measures in DAX. When ops and finance disagree, the fix belongs in the model—not in another Excel tab.
Use your ERP as system of record
Power BI should not replace your ERP. Curate extracts, SQL views, or a replica into a reporting layer. Document lineage so IT and auditors can follow the path from source to dashboard.
Keep refresh boring
A dashboard nobody refreshes is worse than a spreadsheet everyone distrusts. Define a schedule you can operate (nightly is common), monitor failures, and name an owner. Start with import mode if it meets latency needs; move to DirectQuery or a lakehouse only when volume or freshness demands it.
Govern lightly, but early
Before you invite the whole company to self-service, agree on KPI definitions, workspace permissions, and who can publish changes. Our BI governance checklist is a good starter.
Plan for phase two
Once the first dashboard is trusted, extend dimensions, add operational drill-through, and connect CRM or warehouse data. Microsoft Fabric, Databricks, and AI features pay off when the semantic model is already solid—see Fabric readiness when you are ready.
Next step
Bring one report you do not trust and one question you wish you could answer on Monday morning—we will outline a realistic first sprint.