Proactive Approaches to Data Access Reliability and Loss Mitigation in Big Data Cloud Platforms

Abstract

As the adoption of Big Data cloud platforms increases, ensuring data access reliability and effective loss mitigation has become critical for businesses. Traditional reactive methods of addressing data issues often fall short in modern cloud environments, necessitating proactive strategies. This paper explores advanced approaches to maintaining data reliability and preventing data loss in Big Data cloud platforms. By employing predictive analytics, automated monitoring, and redundancy mechanisms, organizations can anticipate potential disruptions and safeguard against data loss. Additionally, we examine strategies such as multi-layered backups, AI-driven fault detection, and the integration of blockchain technology to bolster data security and resilience. These proactive approaches represent a shift towards more reliable and secure data management in cloud infrastructures.