Building Scalable and Secure Data Ecosystems for Multi-Cloud Architectures
Abstract
The proliferation of cloud computing has led to the adoption of multi-cloud architectures by organizations seeking to optimize performance, reduce costs, and mitigate vendor lock-in risks. However, building scalable and secure data ecosystems across multiple cloud platforms presents significant challenges. This research paper explores the key considerations, best practices, and emerging technologies for developing robust multi-cloud data ecosystems. We analyze the architectural patterns, data governance strategies, and security measures essential for maintaining data integrity, availability, and confidentiality in distributed environments. Through a comprehensive literature review, case studies, and experimental evaluations, we propose a novel framework for designing and implementing scalable and secure multi-cloud data ecosystems. Our findings provide valuable insights for organizations navigating the complexities of multi-cloud data management and offer a roadmap for future research in this rapidly evolving field.
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