-Netflix Headquarters, Los Angeles — Sunset Boulevard

🎬 NetflixAI-InsightEngine

This project analyzes Netflix movies and TV shows data using SQL to solve real business problems and extract actionable insights that support content strategy and decision-making.

📌 Project Overview

An end-to-end SQL project exploring Netflix's global content library. This project translates real business questions into analytical queries and surfaces actionable insights for content strategy and decision-making.

📊 Project Stats

Metric	Value
Total SQL Queries	15+
Records Analyzed	8,000+
Countries Covered	190+
Database	PostgreSQL

🛠️ Tech Stack

Database: PostgreSQL
Domain: Entertainment / Streaming Analytics
Dataset: Netflix Movies and TV Shows (Kaggle)

🔍 Featured Queries

Query 14 — Top 10 Actors in Indian Productions

Unnests the comma-separated cast column and ranks actors by appearance count across India-produced titles.

SELECT 
    UNNEST(STRING_TO_ARRAY(casts, ',')) AS actor,
    COUNT(*) AS appearances
FROM netflix
WHERE country = 'India'
GROUP BY actor
ORDER BY appearances DESC
LIMIT 10;

Query 15 — Content Safety Classification

Uses a CASE expression inside a subquery to label titles as Bad or Good based on keywords in the description, then aggregates counts by category.

SELECT 
    category,
    COUNT(*) AS content_count
FROM (
    SELECT 
        CASE 
            WHEN description ILIKE '%kill%' 
              OR description ILIKE '%violence%' THEN 'Bad'
            ELSE 'Good'
        END AS category
    FROM netflix
) AS categorized_content
GROUP BY category;

💡 Project Impact

This project demonstrates the ability to:

✅ Translate business questions into analytical SQL queries
✅ Work with real-world, production-scale datasets
✅ Apply advanced SQL concepts — window functions, CTEs, array unnesting
✅ Communicate insights clearly for non-technical stakeholders
✅ Think from a business decision-making perspective

This analysis provides a comprehensive view of Netflix's content library and can help inform content strategy, regional investment, and platform decision-making.

📁 Repository Structure

netflix-sql-analysis/
│
├── datasets/
│   └── netflix_titles.csv
│
├── queries/
│   ├── 01_content_type_distribution.sql
│   ├── 02_movies_vs_shows.sql
│   └── ...
│   └── 15_content_classification.sql
│
├── shre.jpg
└── README.md

👨🏻‍💻 Author

Your Name
📧 Email: [email protected]

💼 LinkedIn: linkedin.com/in/mihirr51

🐙 GitHub: github.com/mihirr00051

"Data is the new oil — and SQL is the refinery."

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