Project 9: Netflix SQL Analysis

Technology: SQL, Relational Database Concepts, Analytical Querying

In the vast digital arena of streaming giants, one platform reigns supreme — Netflix. But behind the red curtain of binge-worthy series and blockbuster films lies a goldmine of structured data. What if we could decode the entertainment DNA? That’s exactly what this project set out to do.

This SQL-powered project dives deep into Netflix’s catalog, slicing through thousands of titles to reveal what drives the world’s top streaming service. Is there a pattern to content ratings? Do certain years dominate Netflix's releases? Is the global reach truly global? These are not just questions — they are business triggers.

💡 Objectives & Key Questions

• Analyze the distribution of content types — Movies vs TV Shows.
• Identify the most common ratings for various age groups.
• Segment content by release years, countries, and durations.
• Extract and categorize based on keywords and hidden insights.

🚀 Impact & Business Relevance

This project demonstrates how data isn't just rows and columns — it's business intelligence. The insights derived here help streaming platforms:

• Tailor content strategies to audience demand.
• Understand genre saturation and underrepresented categories.
• Optimize release schedules and regional content investments.

So if you’ve ever wondered how Netflix keeps you hooked — this project reveals the analytical engine behind the scenes.

View Project on GitHub