🛒 SQL E-commerce Analysis

📌 Project Overview

This project contains beginner SQL queries used to analyze e-commerce sales, customers, and product performance using SQLite.

The project demonstrates basic SQL operations such as:

• Creating tables
• Inserting data
• Retrieving records
• Performing sales analysis

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🛠️ Tools & Technologies Used

• SQL
• SQLite Online
• Git & GitHub

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📂 Project Structure

sql-ecommerce-analysis/
│
├── datasets/
│
├── sql_queries/
│   └── basic_queries.sql
│
├── screenshots/
│   └── sql_output.png
│
├── README.md
└── insights.md

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📜 SQL Queries Used

Create Orders Table

CREATE TABLE orders (
    Order_ID INT,
    Customer_Name TEXT,
    Category TEXT,
    Sales FLOAT
);

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Insert Data into Table

INSERT INTO orders VALUES
(1, 'Navya', 'Technology', 500),
(2, 'Rahul', 'Furniture', 300),
(3, 'Anu', 'Office Supplies', 200),
(4, 'Kiran', 'Technology', 700),
(5, 'Priya', 'Furniture', 450);

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Retrieve All Records

SELECT * FROM orders;

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📸 SQL Output Screenshot

📈 Advanced SQL Query Outputs

Total Sales

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Average Sales

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Highest Sale

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Category Wise Sales

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Order By Sales

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📊 Analysis Performed

• Created SQL table
• Inserted sample e-commerce sales data
• Retrieved customer order records
• Analyzed category-wise sales data

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🎯 Skills Demonstrated

• SQL Syntax
• Table Creation
• Data Insertion
• SELECT Queries
• Database Basics
• GitHub Project Structuring

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📚 Future Improvements

• Add more advanced SQL queries
• Connect real datasets
• Perform joins between tables
• Build SQL dashboards
• Integrate with Power BI

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🚀 Outcome of Project

This project demonstrates beginner-level SQL skills and understanding of database operations using a simple e-commerce sales dataset.