olist dashbord

**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