Data Deduplication Approaches: Concepts, Strategies, and Challenges

Data deduplication is a major challenge in data science, and Data Deduplication Approaches: Concepts, Strategies, and Challenges provides an overview of methods to eliminate duplicate data. It covers concepts, strategies, and real-world applications, focusing on reduced storage, backup, recovery, and reliability.

Format: Paperback / softback
Length: 404 pages
Publication date: 27 November 2020
Publisher: Elsevier Science Publishing Co Inc

In the realm of data science, the exponential growth of data poses a significant concern across a wide range of computing operations and data storage applications. One of the primary challenges in this field is the presence of duplicated data or redundant data, which can hinder the effectiveness and efficiency of data processing. Data Deduplication Approaches: Concepts, Strategies, and Challenges serves as a valuable resource for readers seeking to understand and address this issue. This book provides an in-depth exploration of various methods and techniques used to eliminate multiple copies of the same files, as well as duplicated segments or chunks of data within associated files.

The significance of data deduplication has grown exponentially in recent years, particularly in storage environments, particularly persistent data storage. Data Deduplication Approaches offers readers a comprehensive overview of the concepts and background of data deduplication approaches. It then delves into technical details, showcasing strategies and challenges involved in real-time implementations of handling large datasets, data science, data backup, and recovery.

Furthermore, the book includes future research directions, case studies, and real-world applications of data deduplication, with a particular emphasis on reducing storage requirements, improving backup and recovery times, and enhancing reliability. By presenting a comprehensive and practical approach to data deduplication, this book empowers readers to optimize their data management practices and achieve greater efficiency and effectiveness in their computing operations.

Weight: 806g
Dimension: 190 x 230 x 23 (mm)
ISBN-13: 9780128233955