IMDB Movie Industry Correlation Analysis

A deep dive into the world of cinema, this project explores an IMDb dataset spanning four decades, from 1980 to 2020. Using SQL Server, the dataset was skillfully imported from Excel and analyzed to uncover intriguing insights about movies and their attributes. Key factors such as ratings, scores, budgets, gross revenues, and votes were examined through exploratory data analysis.

Feature engineering brought the data to life, introducing new metrics like profit and converting categorical data into numeric formats for deeper analysis. Advanced techniques revealed fascinating trends over time, relationships between key attributes, and identified top contributors to box office success.

Dynamic visualizations illuminated data distributions and trends, providing a clear picture of the factors driving movie popularity and profitability. The project culminated in identifying genres with the highest average gross revenue and total votes, offering valuable insights into what makes a movie truly successful.