SQL Project Repository

Project Overview

This repository contains SQL scripts and data for various analytical and database management tasks. The project is designed to demonstrate SQL capabilities in handling complex queries, data analysis, and database design. It includes datasets related to e-commerce and streaming services, with a focus on real-world scenarios and use cases.

Objectives

• Database Design: Create and manage relational databases using SQL.
• Data Analysis: Perform complex queries to extract meaningful insights from the data.
• Case Study Analysis: Solve practical business problems using SQL queries.
• Visualization: Use SQL data to support data visualization and reporting tasks.

Datasets

The repository includes datasets for the following domains:

1. E-Commerce Data

• Tables: Customers, Orders, OrderDetails, Products, InventoryDetails
• Features: Analyze customer behavior, order trends, and product performance.

2. Netflix Movies and Shows

• Tables: titles, Credits
• Features: Explore content distribution, ratings, and geographical diversity.

SQL Scripts

The project includes SQL scripts for various analyses:

E-Commerce Data

1. Top Spending Customers: Identify customers with the highest total spending.
2. Sales by Category: Calculate total sales for each product category.
3. Inactive Customers: List customers who have not placed an order recently.
4. Product Reorder Point: Determine the reorder point for each product.
5. Orders with Diverse Products: Find orders including products from multiple categories.

Netflix Movies and Shows

1. Genre Distribution: Determine the most common genres.
2. Top Rated Titles: Find titles with the highest IMDb scores.
3. Content by Country: Examine the number of titles produced in different countries.
4. Release Trends: Analyze the trend of content releases over the years.
5. Ratings Correlation: Assess the correlation between IMDb scores and TMDb popularity.

How to Use

1. Database Setup:

   • E-Commerce Data: Create a database and run the provided SQL scripts to set up the schema and populate the tables.
   • Netflix Data: Similarly, create a database and import the SQL scripts for the Netflix dataset.

2. Run Queries: Use SQL clients such as MySQL Workbench, pgAdmin, or any SQL IDE to execute the queries and analyze the results.

3. Analyze Results: Review the results to gain insights into customer behavior, product performance, content trends, and more.

Prerequisites

• SQL Database (MySQL, PostgreSQL, etc.)
• SQL Client (MySQL Workbench, pgAdmin, etc.)

Conclusion

This repository provides a comprehensive set of SQL scripts and data for analyzing various business and content-related scenarios. It serves as a practical resource for learning and applying SQL in real-world contexts.

Acknowledgements

• Dataset Providers (if applicable)
• SQL Documentation (for SQL client usage)