Olist E-Commerce Data Analysis

**Olist E-Commerce Data Analysis Project** In this project, I performed an end-to-end data analysis on the Olist Brazilian E-commerce dataset to extract actionable business insights and evaluate sales performance, customer behavior, and operational efficiency. I started with **data cleaning and transformation** using SQL and Power BI, where I handled missing values, standardized data types, and built a well-structured data model by defining relationships between orders, customers, products, payments, and reviews tables. I created several **key performance measures** such as: * Total Revenue * Total Orders * Average Order Value * Delivery Time Analysis * Customer Distribution by State * Top Product Categories by Revenue * Sales Trends by Month and Year : Using Power BI, I designed an interactive dashboard that allows users to * Track overall sales performance * Identify the best-selling product categories * Analyze order status and delivery performance * Monitor customer geographic distribution * Compare revenue across time periods I also applied DAX calculations to measure shipping delays, average delivery time, and order approval duration, which helped highlight operational bottlenecks in the order fulfillment process The final dashboard provides a clear business view that can support decision-making in areas such as inventory planning, logistics optimization, and marketing strategy. This project strengthened my skills in ( data modeling, DAX, SQL querying, and data storytelling ), and demonstrated my ability to transform raw transactional data into meaningful business insights