Data Lifecycle Management: Optimizing Storage, Retrieval, and Deletion Processes for Enhanced Efficiency
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Abstract
Efficient data lifecycle management is imperative in the contemporary data landscape. This research investigates innovative strategies and practices for optimizing the entire data lifecycle, encompassing storage, retrieval, and deletion processes. We explore trends and advancements in data storage technologies, emphasizing the importance of scalable and adaptive solutions. The study delves into retrieval mechanisms, including real-time analytics and machine learning applications for predictive data retrieval. Additionally, the research addresses the often-overlooked aspect of data deletion, proposing secure and compliant methods to manage data end-of-life. By providing insights into comprehensive data lifecycle management, this study aims to guide organizations in enhancing operational efficiency, minimizing storage costs, and ensuring compliance with data privacy regulations.
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