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https://github.com/rakumar99/netflix-analysis-using-tableau

This repository contains Netflix Analysis Dashboard Using Tableau where it will help in analyzing total revenue and total subscribers over a period of time based on data provided.
https://github.com/rakumar99/netflix-analysis-using-tableau

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This repository contains Netflix Analysis Dashboard Using Tableau where it will help in analyzing total revenue and total subscribers over a period of time based on data provided.

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# Netflix Analysis Dashboard



## Project Description:



This Tableau Desktop project provides an in-depth analysis of Netflix's performance and content trends between 2018 and 2020. The dashboard focuses on key metrics such as revenue, subscribers, top-rated genres, production by country, and content release trends. The aim of the project is to give a comprehensive view of Netflix’s growth, popular genres, and the geographical distribution of content production.



### Key Insights:



Total Revenue and Subscribers (2018–2020):



Visualizes Netflix’s total revenue growth and subscriber count over the three-year period.

Identifies trends and highlights Netflix’s rapid expansion during this timeframe.



### Top 10 Rated Genres (IMDb Ratings):



Displays the top 10 highest-rated genres based on IMDb ratings.

Helps users understand which genres resonate most with Netflix viewers.



### Total Shows and Movies Released by Year:



Analyzes the total number of shows and movies released each year.

Highlights content growth, showing how Netflix’s original productions have expanded year-over-year.



### Country Productions:



Breaks down Netflix content production by country, offering insights into which countries contribute the most to Netflix's content library.

Identifies top-producing countries and their impact on Netflix’s global content strategy.



### Popular TV Shows:



Lists popular TV shows based on viewership or IMDb ratings.

Offers insights into which shows drive Netflix’s global viewership and popularity.



### Data Overview:



The project uses Netflix data spanning from 2018 to 2020, covering the following aspects:



Total Revenue and Subscribers: Includes detailed information on revenue growth and subscriber numbers, segmented by year.



IMDb Ratings: Data on genre ratings based on viewer feedback on IMDb, focusing on the top 10 rated genres.



Content Releases: A breakdown of the total number of shows and movies released by Netflix each year.



Country Productions: Data on content production by country, identifying the top regions contributing to Netflix’s original content.



Popular TV Shows: A list of high-performing TV shows based on either ratings or viewership.



### Dashboard Features:



Revenue and Subscriber Growth: A line graph showing the increase in Netflix’s revenue and subscriber base from 2018 to 2020.



Top Genres by IMDb Ratings: A bar chart highlighting the top 10 genres rated on IMDb, helping users identify viewer preferences.



Yearly Content Release: A timeline visualization that tracks the number of new shows and movies released by Netflix each year.



Country Production: A map showing the distribution of Netflix’s original content production by country, offering a global view of content creation.



Popular TV Shows: A list of top TV shows, with additional filtering options to explore different genres, ratings, or regions.



### Technologies Used:



Tableau Desktop: For creating interactive visualizations and dashboards.



IMDb Data: For gathering ratings and genre information.



Netflix Subscriber Data: For analyzing subscriber growth and revenue trends.



### How to Use:



Clone the repository and open the Tableau Workbook file.



Explore the various dashboards and visualizations to gain insights into Netflix’s growth, top genres, and production trends.



Interact with the filters to customize the visualizations based on specific countries, years, or genres.



### Future Enhancements:



Integrate more data on user engagement metrics such as total watch hours.



Add machine learning models to predict future subscriber growth based on historical trends.



Expand the analysis to include comparisons with competitors like Disney+ and Hulu.