This project involves analyzing the IMDb Top 1000 movies dataset using SQL to uncover trends, insights, and patterns in film data. The dataset includes information such as movie titles, release years, genres, ratings, directors, and runtime. Key objectives of the project include: Extracting and filtering top-rated movies by genre, decade, or director. Identifying trends in movie ratings over time. Analyzing the most frequent genres and prolific directors in the top 1000. Comparing average ratings across different genres and time periods. Using aggregate functions, joins, and subqueries to derive meaningful insights. This project demonstrates strong data querying, filtering, and analytical skills using SQL, with an emphasis on data-driven storytelling and clean, efficient query design.

Sample Superstore Analysis