A Systematic Literature Review on inhibitors and challenges in Cloud Computing as a Platform for Big Data Storage and Analysis

Abstract

The ability to handle large volumes of data at the same time, allowing a flexible, reliable, and a more secure access to this data, has proved that cloud computing is appropriate even more in Big Data analysis. Effective and efficient organization of large-scale data analysis illustrates a critical challenge. Lately, cloud computing has played a significant role in the storage and processing of large data sets. This systematic literature review (SLR) aims to review the existing research studies on cloud computing as a platform for Big Data analysis. The search was done through IEEExplore, Springer, Science Direct, Arxiv, ACM, Tandfonline, DAOJ, Emerald insight and hindawi databases in order to sprout out any article related either directly or indirectly to cloud computing. This SLR examined the research studies published between 2020 and 2025 within the popular digital libraries. About one hundred and fifty (150) articles were identified but twenty (20) papers were selected after a meticulous screening of published works to answer the proposed research questions. This systematic literature review presents the key issues of cloud computing in big data processing, including elements of platforms, cloud architecture, cloud database and data storage scheme. Finally, it discusses the open issues and challenges, and deeply explores the research directions in the future on big data analysis in cloud computing platforms.