Netflix SQL Data Analysis Project

Overview

This project focuses on analyzing Netflix Movies and TV Shows dataset using PostgreSQL and SQL.
The goal of this project is to solve real-world business problems, perform data analysis, and extract meaningful insights from Netflix content data.

The project demonstrates practical implementation of SQL concepts including:

• Window Functions
• CTEs
• Aggregate Functions
• String Functions
• Date Functions
• CASE Statements
• Pattern Matching
• PostgreSQL-specific functions

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Objectives

• Analyze Movies vs TV Shows distribution
• Identify the most common ratings
• Explore country-wise content trends
• Analyze genres, actors, and directors
• Perform year-wise Netflix content analysis
• Categorize content based on keywords
• Practice advanced SQL querying techniques

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Dataset Information

The dataset contains:

• Show ID
• Type
• Title
• Director
• Cast
• Country
• Date Added
• Release Year
• Rating
• Duration
• Genres
• Description

Dataset Source: Netflix Titles Dataset

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Database Schema

DROP TABLE IF EXISTS netflix;

CREATE TABLE netflix
(
    show_id VARCHAR(10),
    type VARCHAR(15),
    title VARCHAR(200),
    director VARCHAR(210),
    casts VARCHAR(2000),
    country VARCHAR(200),
    date_added VARCHAR(50),
    release_year INT,
    rating VARCHAR(10),
    duration VARCHAR(15),
    listed_in VARCHAR(250),
    description VARCHAR(300)
);

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SQL Concepts Used

• SELECT Statements
• WHERE Clause
• GROUP BY
• ORDER BY
• Aggregate Functions
• Window Functions
• CTEs
• CASE Statements
• Pattern Matching (LIKE & ILIKE)
• String Functions
• Date Functions
• Type Casting
• PostgreSQL Functions

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PostgreSQL Functions Used

RANK()
UNNEST()
STRING_TO_ARRAY()
SPLIT_PART()
TO_DATE()
EXTRACT()
CASE WHEN
ILIKE

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Business Problems Solved

1. Count Movies vs TV Shows

2. Find Most Common Rating for Movies & TV Shows

3. List Movies Released in 2020

4. Top 5 Countries with Most Netflix Content

5. Identify the Longest Movie

6. Find Content Added in Last 5 Years

7. Find Content by Director 'Rajiv Chilaka'

8. TV Shows with More Than 5 Seasons

9. Count Content Items by Genre

10. Year-wise Average Content Release in India

11. List Documentary Movies

12. Find Content Without Director

13. Salman Khan Movies in Last 10 Years

14. Top 10 Actors in Indian Netflix Content

15. Categorize Content as Good or A-Rated

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Key Insights

• Movies dominate Netflix content compared to TV Shows
• India is among the top contributors to Netflix content
• Drama and International Movies are highly common genres
• TV-MA is one of the most frequent ratings
• Netflix content significantly increased after 2015

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Tools & Technologies

• PostgreSQL
• SQL
• pgAdmin 4
• Kaggle Dataset

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Project Structure

Netflix_SQL_Data_Analysis/
│
├── netflix_sql_project.sql
├── README.md
├── logo.png
└── dataset/
    └── netflix_titles.csv

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Future Improvements

• Create Power BI Dashboard
• Add Tableau Visualizations
• Optimize Queries
• Create SQL Views
• Add Stored Procedures
• Build Recommendation Analysis

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About Me

Sanskar Pandey

Aspiring Data Analyst passionate about:

• SQL
• Power BI
• Python
• Data Analytics
• Machine Learning

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Project Outcome

This project helped strengthen:

• SQL Query Writing
• Business Problem Solving
• Data Cleaning & Transformation
• PostgreSQL Query Optimization
• Analytical Thinking