Elastic Data Warehousing: Adapting To Fluctuating Workloads With Cloud-Native Technologies


  • Sina Ahmadi Independent Researcher Author




Artificial Intelligence, Data Warehousing, Data Integration, Automation, Cloud Native


This research focuses on the development of elastic data warehousing while adapting to changing workloads with the help of cloud-based technologies. The traditional methods of data warehousing need innovative and creative strategies in order to improve their efficiency. Thus, this research focuses on analyzing innovative methods which can improve the future of data warehousing, such as machine learning, encryption, artificial intelligence, etc. Moreover, the study also focuses on specific industries that require customized solutions to data warehousing. These include the manufacturing, finance, and healthcare industries. The study uses qualitative data gained through a comprehensive review of literature. The findings reveal a great level of significance of modern data warehousing techniques that assist in improving the overall efficiency of traditional methods


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How to Cite

Ahmadi, S. (2023). Elastic Data Warehousing: Adapting To Fluctuating Workloads With Cloud-Native Technologies. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 2(3), 282-301. https://doi.org/10.60087/jklst.vol2.n3.p301