AI-Driven Cloud Solutions for Robust Data Engineering: Addressing Challenges and Opportunities
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Cloud computing has developed at a very fast pace and has transformed data engineering for organizationsto handle big data. But limitations including reliability of data, the ability to expand the cloud based systems,and security become major issues. This paper discusses the use of artificial intelligence (AI) in solving thesechallenges with techniques to improve the reliability of the cloud data engineering. Through the integrationof AI algorithms such as predictive analysis, anomaly detection, and automated optimization, the findings ofthis research highlight how data reliability increases and how the scalability and security compliance of thesystem enhance. Altogether, the research compares AI with the existing literature study, experiments it oncloud platforms, and benchmarks it with traditional approaches to demonstrate how AI can improve dataworkflows, minimize operating expenses, and support better decision making. The results evidence thecapabilities of AI in combination with cloud solutions in establishing effective and progressive dataengineering structures that can advance further as a field.
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