https://github.com/keshab5300/amazon-sales-analysis-mysql
This repository contains SQL queries and analysis tools for examining Amazon sales data. It helps uncover insights on pricing, discounts, product performance, and customer reviews. The project is designed to optimize sales strategies and evaluate key metrics for better decision-making.
https://github.com/keshab5300/amazon-sales-analysis-mysql
mysql sql
Last synced: 3 months ago
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This repository contains SQL queries and analysis tools for examining Amazon sales data. It helps uncover insights on pricing, discounts, product performance, and customer reviews. The project is designed to optimize sales strategies and evaluate key metrics for better decision-making.
- Host: GitHub
- URL: https://github.com/keshab5300/amazon-sales-analysis-mysql
- Owner: Keshab5300
- License: mit
- Created: 2025-02-24T10:24:06.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-02-24T10:30:43.000Z (3 months ago)
- Last Synced: 2025-02-24T11:35:37.412Z (3 months ago)
- Topics: mysql, sql
- Homepage:
- Size: 3.73 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Amazon Sales Data Analysis Project
## Overview
This project involves analyzing sales data from Amazon to derive insights and answer specific queries related to product discounts, reviews, and pricing. The analysis aims to facilitate data-driven decision-making by identifying trends and patterns in the sales data.
## Dataset
Dataset Link : https://drive.google.com/file/d/1hJOXNpOUXOpyjsrBt1O8MyIJHfWgzakS/view
The dataset includes information about various products, including their actual price, discounted price, category, and customer reviews.
## Queries
The analysis involves executing the following SQL queries:
1. List all products with a discounted price below ₹500.
2. Find products with a discount percentage of 50% or more.
3. Retrieve all products where the name contains the word "Cable."
4. Display the difference between the average of the actual price and the discounted price for each product.
5. Query reviews that mention "fast charging" in their content.
6. Identify products with a discount percentage between 20% and 40%.
7. Find products that have an actual price above ₹1,000 and are rated 4 stars or above.
8. Find products where the discounted price ends with a 9.
9. Display review contents that contain words like worst, waste, poor, or not good.
10. List all products where the category includes "Accessories."
11. For the complete SQL queries, please refer to the attached PDF document in the project repository.
## Usage
- **Set Up Your Database:** Ensure your database includes the relevant tables with the necessary columns.
- **Run Queries:** Execute these queries(refer project.sql) in your SQL environment to analyze your data. Adjust table and column names as needed to match your database schema.
- **Review Results:** Use the results from these queries to gain insights into product pricing, discounts, and review content.
## Contribution
Feel free to fork this repository and submit pull requests with any improvements or additional queries.