📊 Netflix Content Analysis Project
This project is a complete end-to-end data analysis of Netflix’s content catalog using Python, MySQL, andPower BI. The goal was to uncover patterns in the type, release year, rating, duration, and origin of content available on Netflix, and visualize the insights using interactive dashboards.
🧠 Key Highlights 🔍 Data Cleaning & Preprocessing using Python (pandas)
🗃️ SQL-based Data Analysis with 14+ custom queries
📈 Power BI Dashboard for visual storytelling
🔧 Created custom fields like duration_int and duration_unit for better filtering
📁 Organized project structure for clarity and reproducibility
🛠 Tools & Technologies Python (Pandas, Jupyter Notebook)
MySQL
Power BI
SQLAlchemy (for DB connection)
Excel/CSV
📌 Topics Analyzed TV Shows vs Movies distribution
Most frequent genres, ratings, and countries
Content trends over time
Top directors and content contributors
Interactive breakdowns by type, year, and category
📂 Project Structure bash Copy Edit Netflix-Content-Analysis/ ├── data/ # Raw and cleaned dataset ├── notebooks/ # Jupyter notebook for preprocessing ├── sql/ # SQL analysis queries ├── powerbi/ # Power BI dashboard (.pbix) ├── report/ # Project summary report └── README.md # Project overview (this file)
📌 How to Use Clone the repo
Run the Python notebook to clean the data
Import cleaned data into MySQL
Use SQL queries from sql/ folder for analysis
Open the Power BI dashboard to explore visual insights
✅ Outcome By the end of this project, we built a solid analytics pipeline to extract meaningful business and content insights from the Netflix catalog, turning raw data into a visually engaging story.