I am including a link to my tableau workbook, which has all of my visualizations, for your better understanding. https://prod-useast-b.online.tableau.com/#/site/msis670fall2023/workbooks/1064564
This is a Data Visualization project using IMDB data performed by using Tableau tool. The primary goal of my project is to use a sizable dataset from IMDb to fully study and comprehend the world of movies. I'm concentrating on English-language films and TV shows that were released between 2010 and 2022. My objective is to unearth fascinating information regarding various facets of these films. In order to determine any patterns or changes in the industry throughout time, I would need to know the number of films that were released annually during this time frame. I also want to know what categories of films, or genres, are typically nominated for and winning major Oscars like Best Picture. This, in my opinion, may tell me a lot about the kinds of films that are well-liked in the business. Comprehending the ways in which audiences interact with these films is equally crucial. I'm examining IMDb ratings, which can tell me how much or how little people thought of a particular film. In order to observe the variety of content, I'm also looking into the age ratings assigned to these films. In addition, I'm looking into how production businesses perform as well as the parts that actors and actresses play in movie casts. This will enable me to recognize prosperous businesses and comprehend the parts that various actors play in films. My objective is to compile all of this data, do a thorough analysis, and then display it in an understandable manner. By doing this, I intend to offer insightful information that will help streaming services, production businesses, filmmakers, and anybody else who wants to learn more about the movie industry. In the end, I want to provide a thorough overview of the film world over these years, illuminating global cinematic trends, industry norms, and audience preferences.
BRIEF SUMMARY OF MY PROJECT JOURNEY:
Data Collection: The research project started by obtaining a large dataset from IMDb that included English-language films and television shows that were released between 2010 and 2022. I was able to acquire this dataset, which included a wealth of movie-related data, such as titles, genres, ratings, cast bios, production firms, and more.
Analyses and Project Schedule: Different levels of analysis were considered when creating the project schedule. I started with exploratory analysis, looking at annual trends in the release of movies, looking into prizes based on genre, closely reviewing measures related to audience involvement such as IMDb ratings and age rating distributions, and evaluating the work of production businesses. Every stage of the research was methodically planned in order to derive valuable conclusions from the data.
Highlights and obstacles: During the project, I had a number of obstacles, major among them being managing substantial amounts of data and guaranteeing data integrity during the cleaning and preparation stages. It was crucial to make sure the dataset was accurate and consistent. Nonetheless, these difficulties helped me hone my problem-solving and data-handling skills.
Highlights of the project included identifying patterns in the release of movies over time, learning unique insights into audience participation through IMDb ratings, and finding fascinating relationships between genre preferences and award nominations. These discoveries greatly influenced the project's storyline and offered insightful information about the film industry.