ankitsharma071/brazilian-e-commerce-analytics-powerbi-sql

This repository is a business analytics portfolio project built around a public dataset of over 100,000 real orders from Olist, a Brazilian online marketplace. It combines MySQL for data analysis with Power BI for building interactive dashboards, turning raw order and customer records into a set of readable business reports. The project centers on two dashboards. An executive dashboard reports overall numbers such as total revenue, total orders, average order value, total customers, and average review score. A customer analytics dashboard digs deeper into behavior, tracking active customers, how many customers come back to buy again, average spend per customer, and how recently customers have purchased. Alongside these, the project applies RFM segmentation, a common marketing technique that groups customers by how Recently, Frequently, and how much Money they have spent, sorting them into labels like Champions, Loyal, New, Regular, and At-Risk. The SQL work behind the dashboards covers several areas: sales trends by month, state, and product category, customer lifetime and repeat purchase patterns, freight cost and delivery time analysis by product category, and seller performance including revenue and ratings. To build these, the author uses joins, common table expressions, SQL views, case statements, window functions, and ranking functions like NTILE and DENSE_RANK. Some of the specific findings reported are that only 3.12 percent of customers are repeat buyers, that logistics heavy product categories carry noticeably higher freight costs, and that the top 544 sellers generate 80 percent of total marketplace revenue, following the well known 80/20 pattern seen in many businesses. The repository is organized into a dashboard folder holding the Power BI file, an images folder with dashboard screenshots, and a SQL files folder containing separate scripts for sales, RFM, product, seller, and customer analysis. It is presented by the author, a mechanical engineering undergraduate, as a portfolio piece demonstrating SQL and business intelligence skills rather than a tool meant to be installed or run as software.