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Our project explores the Anime 2023 Dataset, a comprehensive collection of data related to anime, including details on genres, ratings, popularity, release years, studios, and more. This project aims to analyze trends in the anime industry, uncover hidden patterns, and provide insights through data visualization and predictive modeling.
This repository comprises the design, implementation, and analysis of a near real-time data warehouse prototype for an electronics business chain, utilising a multi-threaded Extract, Transform, Load (ETL) pipeline leveraging the efficient HYBRIDJOIN algorithm implemented with Java and MySQL on customer sales data.