Cloud-Based Big Data Analytics: Frameworks, Challenges, and Future Trends
DOI:
https://doi.org/10.63282/3050-9262.IJAIBDCMS-V4I1P104Keywords:
Cloud computing, Big data analytics, Hadoop, Apache Spark, Serverless computing, Artificial intelligence, Machine learning, Edge computing, Federated learning, Hybrid cloud, ScalabilityAbstract
A large amount of efficient data has been generated recently due to the increasing technological enhancements. Cloud based big data analytics have become an influential model applying flexibility, scalability, and affordability of the cloud environment for processing unmanageable amounts of data. In this paper, the author discusses the basic tenets of cloud-centered big data analytics, including Hadoop, Apache Spark, and the new serverless architecture. It looks at certain issues, including security, privacy, timeliness, and resource availability, which measure the success of cloud analytics. It also covers new directions through future possibilities that include implementing AI and ML technologies, a growing focus on the edge computing concept, and federated learning for data evaluation. The paper also outlines the trends in the future of big data analytics connected to these developments of native cloud systems and hybrid cloud arrangements. If the current threats are managed and new opportunities capitalized, cloud-based big data analytics shall transform healthcare, finance, smart cities, and IoT industries
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