🍿📊 Netflix-Database-MySQL

Welcome to the Netflix-Database-MySQL project! This project simulates Netflix's business operations using MySQL, including managing content production, user subscriptions, and activities.

📜 Overview

In this project, we designed and implemented a relational database 🗄️ for Netflix using SQL. It covers entities such as users 👤, content 🎥, genres 🎭, and more, enabling comprehensive data queries to uncover insights about user behavior and content trends.

🛠️ Features:

• 🎞️ Content Management: Manage movies, TV shows, and new arrivals.
• 🧑‍🤝‍🧑 User Management: Store details on user profiles, subscriptions, and payments 💳.
• 📊 User Interaction: Track user activity, recommendations 💡, and reports 📝.
• 🛠️ Issue Reporting: Manage user-submitted reports regarding technical and content issues.
• 💡 SQL Queries: A collection of useful SQL queries to analyze Netflix's business operations.

📂 Files

1. 🗄️ Netflix_Database.sql: SQL file containing the schema, data, and queries.
2. 📑 Netflix_Report.pdf: A detailed project report, including the database design, schema, and queries.
3. 🎥 Video Presentation: https://drive.google.com/file/d/1qCuAfws9GqqBofEmEoVVy1XN3l7xgIif/view?usp=sharing

🎯 Project Goals

• 🏗️ Build a relational database to simulate Netflix operations.
• 🔍 Develop SQL queries for retrieving valuable business insights.
• 📊 Analyze relationships between users, content, and reports to optimize Netflix’s workflow.

💻 Setup Instructions

1. Download or clone the repository.
2. Import the Netflix_Database.sql file into your MySQL database.
3. Start running the SQL queries 🖥️ to interact with the Netflix database.

📊 SQL Queries

Basic Queries:

• 👤 Retrieve user details like name, email, and subscription data.
• 🎬 Display all content 🎥 from specific genres or regions.
• 🌍 Rank the top regions 🌟 with the most popular content.

Advanced Queries:

• 📅 Show the most recently added content in the catalog.
• 🎙️ Display the voice actors and cast for a particular show.
• ⚙️ List all user reports categorized by problem type (e.g., technical 🛠️, content issues 🎭).

📈 Analytics and Insights

Use the provided SQL queries to analyze:

• 📊 User Engagement: Identify trends in user preferences and activity.
• 🎬 Content Popularity: Rank the most-watched or liked content by region.
• 📝 Issue Tracking: Analyze the reports submitted by users and their resolutions.

🌟 Highlights

• Entity-Relationship Diagram (ERD): Represents the database structure for better organization 🎨.
• Data Dictionary: A well-documented guide to the tables and fields used in the database 📖.
• Complex SQL Queries: Utilize advanced joins and subqueries for deeper insights 🔎.

📚 References

• 📘 Netflix Business Model Canvas
• 📖 Netflix History