Olist Power BI
Executive Dashboard

Leadership needs one trusted view of e-commerce performance

The Olist marketplace generates performance data across thousands of orders, dozens of product categories, and hundreds of sellers. Without a structured dashboard, leadership relies on ad-hoc reports that are slow, inconsistent, and impossible to drill into.

The core question: how do we build a single executive dashboard that tracks KPIs reliably, enables drill-down by category and time period, and surfaces the insights that matter most — without overwhelming the reader?

Star schema — 7 relationships, clean and scalable

The data model follows a proper star schema: one central fact table connected to dimension tables. This ensures DAX measures calculate correctly, filters propagate properly across the dashboard, and the model is fast to query even on large datasets.

5-page executive dashboard structure

10 DAX measures built for business decisions

What the dashboard reveals

Executive actions from the dashboard

• Build Q4 inventory and logistics capacity 6–8 weeks before the seasonal peak. The 34% Q4 spike is consistent across years — it is predictable and should be planned for, not reacted to.
• Set an internal delivery KPI target of 95% on-time delivery. The review score data shows this is the threshold where average scores remain above 4.0 — the level associated with repeat purchase behavior.
• Prioritize Health & Beauty seller acquisition in the next recruitment cycle. The category growth rate justifies dedicated category management and preferential logistics terms for new sellers.
• Create a top-seller account management program for the 50 highest-revenue sellers. The concentration analysis makes clear these accounts require proactive relationship management, not just platform access.