Big Data-Driven Computer Science: Application Paradigms and Development Paths

Abstract

This article reviews recent advancements in the application of computer science and technology to big data. Through an analysis of key processes—including data collection, cleaning, preprocessing, storage, and management—it identifies core technologies for large-scale data processing. The discussion extends to algorithm optimization and machine learning techniques, underscoring their role in extracting value from data and improving decision-making. Additionally, the article addresses security and privacy challenges in big data, proposing relevant technical solutions. It aims to serve as a reference for further research in computer science within the big data domain.