Architecting Cloud Database Solutions with Embedded AI for Real-Time Analytics
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The quick extension of cloud computing and artificial intelligence (AI) has provoked a considerable revolution in how data is supervised and analyzed. The fusion of AI-enhanced analytics with cloud-based databases is redesigning decision-making across various sectors by offering enhanced scalability, instant processing, and anticipating abilities. This study investigates the merger of AI and cloud database systems, with a focus on how machine learning and deep learning algorithms enhance data processing and decision accuracy. Through an examination of diverse industry examples, we demonstrate how AI-powered analytics have boosted operational efficiency, risk mitigation, and long-term planning in fields such as healthcare, finance, retail, and environmental sustainability. Furthermore, we address the obstacles and prospects, including issues related to data privacy, the intricacy of AI models, and the potential incorporation of quantum computing. The findings of this research emphasize the significant influence of AI on cloud databases, providing valuable knowledge for organizations targeting to develop their decision-making capabilities and maintain power in the digital environment
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Copyright (c) 2025 Padma Rama Divya Achanta
This work is licensed under a Creative Commons Attribution 4.0 International License.
