Innovative Approaches to Scalable Data Storage and Retrieval: Trends and Challenges in Data Management
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Abstract
As the digital landscape continues to witness an exponential growth in data, the scalability of storage and efficient retrieval mechanisms become paramount in ensuring optimal data management. This research explores innovative approaches to tackle the evolving challenges associated with scalable data storage and retrieval. We examine current trends in storage technologies, including distributed file systems, cloud-based solutions, and emerging storage architectures. The study also addresses challenges such as data security, latency, and the impact of diverse data types on storage infrastructures. Furthermore, the research investigates the integration of machine learning techniques for predictive storage management and explores the potential of edge computing in enhancing data retrieval speed. By providing a comprehensive overview of contemporary trends and challenges, this study aims to guide organizations in adopting forward-looking strategies for scalable and efficient data management.
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