https://github.com/nagar2nd/amazon-sales-analysis-mysql

This project analyzes sales data from Amazon to extract insights related to product pricing and reviews. It utilizes SQL for querying data and Google Drive for dataset and video storage.
https://github.com/nagar2nd/amazon-sales-analysis-mysql

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This project analyzes sales data from Amazon to extract insights related to product pricing and reviews. It utilizes SQL for querying data and Google Drive for dataset and video storage.

• Host: GitHub
• URL: https://github.com/nagar2nd/amazon-sales-analysis-mysql
• Owner: Nagar2nd
• Created: 2024-09-11T10:40:19.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-10-22T06:46:09.000Z (3 months ago)
• Last Synced: 2024-10-23T09:41:49.518Z (3 months ago)
• Topics: sql
• Homepage:
• Size: 2.61 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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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."**

*For the complete SQL queries, please refer to the attached PDF document in the project repository.*

## Technologies Used

- SQL for data querying and analysis

- Google Drive for dataset and video storage

- GitHub for version control and collaboration

## Installation

To run the SQL queries locally, follow these steps:

1. Download the dataset from the provided link.

2. Import the dataset into your SQL database management system.

3. Execute the SQL queries to perform the analysis.