E-Commerce Delivery & Customer Experience — Power BI

This project analyzes the Brazilian Olist e-commerce dataset to understand sales performance, delivery efficiency, and customer satisfaction.

I cleaned and transformed the data using Power Query, addressing missing values and preparing orders, products, payments, customers, sellers, and reviews for analysis. I built a relational data model and created DAX measures to calculate revenue, order volume, freight charges, average delivery time, late-delivery percentage, and customer review scores.

I designed an interactive Power BI dashboard with filters for date, product, seller, and payment type. The dashboard allows users to explore revenue by category and geography, compare delivery performance, and examine how delivery delays relate to customer satisfaction.

Key findings included approximately $14 million in revenue across 99,000 orders, an average delivery time of 12.5 days, and a late-delivery rate of 6.8%. Late deliveries were associated with lower customer review scores.

The project demonstrates how sales and delivery data can help businesses identify strong-performing categories, investigate delivery issues, and prioritize improvements to the customer experience.

Tools and skills: Power BI, Power Query, DAX, data cleaning, data modeling, KPI reporting, and data visualization.