Amazon Prime Insights: A Data Exploration

gavlestrangebusine
Mar 18, 2024
3 min read

Updated: Apr 9, 2024

Skills Used: Tableau, Excel, Radial Bar Chart (Advanced Tableau Calculations)

Full Project on GitHub: https://bit.ly/4aKxU3u

Tableau: https://tabsoft.co/4cJW53T

About The Data:

Data source for this project is public on Kaggle and can be found at

https://www.kaggle.com/datasets/shivamb/amazon-prime-movies-and-tv-shows

No definite date for the dataset but it was last updated 2 years ago (2022)

The data source contains 9668 rows of movies and series, with 12 columns

(Show_id, Title, Type, Director, Cast, Country, Date Added, Release Year, Rating, Duration, Genre listed, Description)

The data source has missing values, which could cause issues in in the analysis and the dataset could benefit from further transformation, with the addition of user reviews and IMDB scores.

The data source provides valuable insights into the platform's content offerings, allowing for an exploration of trends in genre, release years, and potentially user preferences.

Question:

Using the Amazon Prime video dataset, implement a informative, interactive dashboard to provide data-driven insights into Amazon's library preferences. Work with the given data , implement no transformation's nor update missing values.

Dashboard:

The dashboard is designed in two parts. The first section provides insights into Amazon Prime's collection of movies and series. Notably, Amazon Prime boasts a vast library of movies, making up 80% of the collection, with series constituting the remaining 20%. Additionally, drama reigns supreme as the most prominent genre, with 986 movies/series falling under this category. Furthermore, 4 of the top 10 genres include drama as a category or sub-category.

The dashboard is designed in the Amazon Prime blue and white with minimal headers and minimalistic design, for ease of understanding the visuals.

The second section allows users to delve deeper into individual movies and series. Leveraging a title search feature, users can explore a wealth of information about each title, including its type (movie or series), length (seasons for series or runtime for movies), year of release, cast, and a short description. The search will also display the genre(s) associated with each title, allowing users to find movies and series based on their preferences.

Conclusion:

An interactive dashboard was created to analyze potential user preferences within the Amazon Prime media library. The analysis revealed Drama as the most prominent genre, with 986 movies/series being labeled drama, closest is comedy with 531 movies/shows. Drama is also featured in 4 of the top 10 genres.

Interestingly, movies constituted the majority of the content with 80% (7750), suggesting potential user preferences for long form entertainment or Amazon's preference for movie's of shows. United States of America has produced the most content (292) with India a close second with 238, this insight is misleading as a major portion of the datasets country column has missing values.

Notably, the analysis revealed an exponential increase in recently released or Amazon produced content, suggesting a strategic shift towards original content or modern content, catering to user preferences for fresh entertainment.

While this project provides valuable insights, limitations exist:

Improvements include, to update all missing values, to provide a full in-depth analysis, as well as transforming the data to include IMDB ratings and Amazon Prime user reviews, providing a further analysis for the company to compare the platforms content. To gather further insights into how the content is perceived by the users.

Improvements for the dashboard include more in depth visuals, this improvement with the above transformation, would allow a deep analysis of each genre to user rating, specific actors and directors to IMDB rating and user ratings to provide an understanding of whom is preferred on the platform.

The removal of the second section (title search feature) for more visuals or insights to provide the company would be more beneficial.

By implementing these suggestions, my future iterations of this project can offer even more valuable insights into understanding user preferences and optimizing the Amazon Prime video platform.