This review shows how cloud technologies enhance scalability and performance in big data handling, highlighting key techniques and frameworks.
The explosive growth of data across industries has challenged traditional data processing systems, necessitating scalable, efficient, and distributed solutions. This review explores the integration of the divide and conquer paradigm with parallel computing and cloud technologies to address Big Data handling. By examining current techniques, frameworks, and challenges, the article offers a comprehensive overview of how cloud-based parallel divide and conquer strategies optimize Big Data processing in terms of performance, scalability, and cost-efficiency.
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Singh et al. (2025) studied this question.
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