This project is an end-to-end Amazon E-Commerce Sales Analysis Dashboard built using Power BI, based on thousands of order records from the Amazon Sale Report dataset.
The dashboard visually represents business KPIs, sales patterns, geographic performance, and operational insights for decision-making.
The dataset contains detailed information about Amazon orders, including:
- Order ID
- Date
- Status (Delivered, Shipped, Returned, Cancelled)
- Sales Channel
- Fulfilled By (Amazon or Merchant)
- Style
- SKU
- Size
- ASIN
- Category
- Ship City
- Ship State
- Ship Postal Code
- Ship Country
- Qty (Quantity Ordered)
- Amount (Revenue)
- Currency (INR)
- Shipping Service Level
- Promotion IDs
This rich dataset helps analyze sales, fulfillment efficiency, and customer location-based performance.
- Analyze overall Amazon sales performance
- Identify top-performing states and cities
- Visualize trends in daily, monthly, and quarterly sales
- Track how many orders were delivered, returned, or cancelled
- Compare demand across regions using treemaps and bar charts
- Help businesses understand customer behavior and revenue patterns
The dashboard highlights the most important business metrics:
| KPI | Description |
|---|---|
| Current Month Sales | ₹23.43M |
| Sales in Selected Period | ₹3.22M |
| Total Quantity Sold | 4814 units |
| Orders Delivered | 1195 orders |
These KPIs give a quick snapshot of performance.
Shows the highest revenue-generating ship-cities:
- Bengaluru
- Hyderabad
- New Delhi
- Chennai
- Others
Breakdown of:
- Delivered Orders
- Shipped Orders
- Returned Orders
- Cancelled Orders
Useful for evaluating operational performance.
Highlights states with maximum order volume:
- Maharashtra
- Tamil Nadu
- Telangana
- Uttar Pradesh
- Karnataka
- Delhi
- Kerala
- West Bengal
Two separate charts show trends from April 2022 – June 2022:
- Daily Quantity Sold
- Daily Sales Amount
Includes filters for:
- Day
- Month
- Year
- Power BI Desktop
- Power Query for data cleaning & transformations
- DAX (Data Analysis Expressions) for KPI calculations
- Data Modeling for relationships
- CSV Data Source (Amazon Sale Report)
- Visualization Techniques (bar, treemap, donut, line charts)
- Removed null values
- Corrected inconsistent date formats
- Standardized product size & category fields
- Fixed blank ship-city/ship-state entries
- Created star schema
- Fact table: Orders
- Dimension tables: City, State, Date, Product
Some example DAX measures used:
- Total Sales
- Total Quantity
- Delivered Orders
- Sales Selected Period
- Monthly Sales Trend
- Order Status Count
| File | Description |
|---|---|
Amazon Sales Dashboard.pbix |
The complete Power BI dashboard |
Amazon Sale Report.csv |
The raw dataset used for analysis |
README.md |
Project documentation |
- Download the
.pbixfile - Open it in Power BI Desktop
- Load or refresh the dataset
- Use slicers (Date, Order Status, Region) to explore sales insights
- Bengaluru and Hyderabad are major sales hubs
- Maharashtra is the top-performing state
- Significant difference between delivered vs returned orders
- Sales peak between April–June 2022
- Clear patterns in city-level customer activity
This project demonstrates:
- Strong Power BI skills
- Proficiency in data modeling, DAX, and visual analytics
- Ability to convert raw datasets into meaningful business insights
- Expertise in dashboard design and storytelling with data
It is an excellent example of real-world analytics applied to e-commerce data.
Feel free to reach out for improvements, collaboration, or dashboard enhancements!