This project presents an interactive Power BI dashboard built using Amazon Store Sales Data (CSV).
It provides deep insights into sales, profit, returns, shipping, and customer segments to help analyze business performance effectively.
✔ Sales by Category – Compare revenue across Office Supplies, Technology, and Furniture.
✔ Profit by Sub-Category – Identify the most profitable products (e.g., Copiers, Accessories, Phones).
✔ Sales by Segment – Distribution across Consumer, Corporate, and Home Office customers.
✔ Shipping Analysis – Count of orders by shipping mode (Standard, Second Class, First Class, Same Day).
✔ Returns Analysis – Orders returned vs. successful orders.
✔ Sales Trends – Monthly/Yearly sales visualization (2019–2020).
✔ Regional Analysis – Sales across Central, East, South, and West regions.
✔ State-Level Breakdown – Top-performing states like California, New York, and Texas.
- Source: Amazon Store Sales Data (CSV)
- Columns Include:
- Order ID, Product ID
- Category, Sub-Category
- Sales, Profit, Quantity, Discounts
- Customer Segment, Region, State
- Ship Mode, Returns, Date
- Power BI Desktop – Data cleaning, modeling & visualization
- Excel / CSV – Source dataset
- Clone this repository:
git clone https://github.com/your-username/Amazon-Sales-Dashboard.git
- Open
Amazon Store Sales.pbixin Power BI Desktop. - Explore filters, slicers, and interactive visuals.
- California contributes the highest sales (~1.57M).
- Copiers generate the most profit (~43K).
- Consumer segment is the largest (48%).
- Standard shipping dominates (58%).
- Return rate is ~5%.
Pull requests are welcome! For significant changes, please open an issue first to discuss what you’d like to improve.
This project is licensed under the MIT License.