Skip to content

Latest commit

Β 

History

History
100 lines (63 loc) Β· 2.55 KB

File metadata and controls

100 lines (63 loc) Β· 2.55 KB

πŸ“Ί Netflix Analysis Dashboard (Power BI)

This project provides an interactive data visualization of Netflix content using Power BI. The analysis is based on the Netflix Titles dataset from Kaggle, which includes movies and TV shows available on Netflix as of 2021.


πŸ“Š Dashboard Overview

Netflix Power BI Dashboard

The Power BI dashboard provides insights into:

  • Total Titles: 8802
  • Time Coverage: From 1925 to 2021
  • Ratings & Genres: Breakdown of top genres and viewer ratings
  • Content Type: Proportion of Movies vs TV Shows
  • Top Countries: Countries with the highest number of titles
  • Trends Over Time: Titles added to Netflix by release year

πŸ“ Dataset

This dataset includes:

  • Title names
  • Cast and directors
  • Country and date added
  • Duration and rating
  • Type (Movie/TV Show)
  • Genre categories

πŸš€ Features

  • Built using Power BI Desktop
  • Interactive visuals: bar charts, pie charts, treemaps, and time series
  • Dark theme with Netflix-style color palette
  • Scrollable legends and dynamically filtered data

🧠 Key Insights

  • The U.S. leads in content volume, followed by India and Japan.
  • Most titles are movies (69%), while 31% are TV shows.
  • The most common rating is TV-MA, indicating mature audiences.
  • Content creation has surged after 2010, especially around 2018–2020.

🌐 Live Dashboard

⚠️ Currently, the report is not published online due to Power BI publishing restrictions. Once "Publish to web" is enabled, a live interactive version will be linked here.


πŸ“Œ How to Use

If you want to explore or edit the report:

  1. Download Power BI Desktop
  2. Clone this repository
  3. Open the .pbix file included in this repo

πŸ“· Screenshots

Click to expand

Netflix Dashboard


πŸ› οΈ Tools Used

  • Power BI Desktop
  • Microsoft Power Query
  • DAX (Data Analysis Expressions)
  • Kaggle Dataset

πŸ™Œ Acknowledgments

Thanks to Shivam Bansal for the dataset on Kaggle.


πŸ“¬ Contact

Feel free to reach out via GitHub Issues for questions or collaboration ideas.