gopiashokan / analysis-on-amazon-prime-videos-using-tableau Goto Github PK

Amazon Prime Video, a popular streaming service with over 200 million global subscribers, offers an extensive collection of movies, TV shows, and original content. In this captivating analysis using Tableau, I delved into the realm of Amazon Prime Video to gain valuable insights into its content library, user engagement, and viewer preferences.

• Visualize data related to genres, viewership patterns, user behavior, content performance, and regional preferences.
• Discover actionable recommendations to optimize content selection, enhance user experience, and boost viewer engagement.

The analysis is based on the "Amazon Prime Movies and TV Shows" dataset sourced from Kaggle.

Explore the dynamic Tableau dashboards and intriguing visualizations of this analysis on Amazon Prime Videos: Tableau Project Dashboard Link

The analysis of Amazon Prime Video using Tableau offered valuable findings to the streaming service. By visualizing data related to genres, viewership patterns, user behavior, content performance, and regional preferences, actionable recommendations were derived to optimize content selection, enhance user experience, and boost viewer engagement.

Discover the magic of interactive exploration! With my Tableau dashboard, you can select any movie or TV show from Amazon Prime Video's vast collection of 10,000+ titles. Witness as details like type, genre, cast, description, release year, and duration update automatically, providing captivating insights at your fingertips. Immerse yourself in the world of Amazon Prime Video's rich content library and uncover the stories behind your favorite entertainment.

This enthralling odyssey into Amazon Prime Video's data landscape empowered me to provide valuable insights that can shape strategic decisions within the competitive streaming industry. Understanding viewer preferences and content trends hold the key to fostering lasting connections with audiences worldwide.

This project is licensed under the MIT License. Please review the LICENSE file for more details.

📧 Email: [email protected]

🌐 LinkedIn: linkedin.com/in/gopiashokan

For any further questions or inquiries, feel free to reach out. We are happy to assist you with any queries.