Enhancing Cloud Migration Efficiency with Automated Data Pipelines and AI-Driven Insights
Year: 2025
Type: article
Abstract: The rapid adoption of cloud computing has made efficient migration strategies a critical need for enterprises. Traditional migration processes often encounter challenges, such as data inconsistencies, prolonged downtimes, and resource inefficiencies. This paper explores how automated data pipelines, coupled with AI-driven insights, can enhance cloud migration efficiency by streamlining data transfer, minimizing human intervention, and ensuring real-time data validation. Automated pipelines facilitate seamless data integration across heterogeneous environments, reducing manual errors and accelerating migration timelines. AI-driven insights further optimize the process by enabling predictive analytics, anomaly detection, and resource optimization during migration. Through case studies and practical examples, the paper demonstrates how combining automation and AI can significantly reduce operational costs, enhance data quality, and ensure a robust, scalable cloud infrastructure post-migration. These advancements establish a foundation for organizations to innovate and remain competitive in a rapidly evolving digital landscape.
Authors: Siddharth Choudhary Rajesh, Dr. Vishwadeepak Singh Baghela
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893110474