Netflix‑SQL‑Project

Description

A project that uses SQL to analyse the Netflix dataset, aiming to explore various attributes of TV shows and movies such as genre, rating, director, and country. The goal is to extract insights about content popularity, release trends, and key factors influencing platform selections.

Dataset Overview

The project analyses the Netflix dataset, which includes various attributes of TV shows and movies on the platform. The dataset contains the following information: show name, director, cast, production country, release year, rating, etc. The objective is to identify trends, patterns, and key insights related to Netflix content.

Dataset Description

The dataset contains the following columns:

1. show_id: Unique identifier for each show or movie.
2. type: Content type (e.g., Movie or TV Show).
3. title: Title of the show or movie.
4. director: Director of the content.
5. cast: Main actors/actresses.
6. country: Production country of the show/movie.
7. Date Added: Date the content was added to Netflix.
8. release_year: Year the content was released.
9. rating: Content rating.
10. duration: Duration of the movie or number of seasons for a TV show.
11. listed_in: Category of the content (e.g., Comedy, Drama).
12. description: Brief description of the content.

Objectives

1. Content Distribution: Understand the distribution of movies and TV shows across countries, ratings, and genres.
2. Trend Analysis: Identify trends in release years, rating changes over time, and types of content added by Netflix.
3. Genre Insights: Explore the most common or popular genres based on the listed_in column.
4. Director and Actor Analysis: Analyze which directors and actors appear frequently in the dataset.
5. Content Addition Trends: Investigate when Netflix adds the most content to its library and any seasonal patterns.

SQL Techniques Used

1. Data Filtering: Filter content based on various attributes (e.g., rating, genre, country).
2. Aggregation: Aggregate data to analyze trends in release years, ratings, or content types.
3. Grouping: Group data by columns such as country or genre for distribution analysis.
4. Sorting and Ranking: Sort and rank data by release year or rating to identify top shows and movies.

Expected Insights

• Analyze the most popular content types on Netflix.
• Identify top‑rated movies and TV shows.
• Explore release trends over the years.
• Understand content distribution across different countries.
• Identify key directors and actors associated with popular content.