Название: Big Data Management and Analytics Автор: Brij B Gupta and Mamta Издательство: World Scientific Publishing Год: 2024 Страниц: 288 Язык: английский Формат: pdf (true) Размер: 19.6 MB
With the proliferation of information, Big Data management and analysis have become an indispensable part of any system to handle such amounts of data. The amount of data generated by the multitude of interconnected devices increases exponentially, making the storage and processing of these data a real challenge. Big Data management and analytics have gained momentum in almost every industry, ranging from finance or healthcare. Big Data can reveal key insights if handled and analyzed properly; it has great application potential to improve the working of any industry. This book covers the spectrum aspects of Big Data; from the preliminary level to specific case studies. It will help readers gain knowledge of the Big Data landscape.Highlights of the topics covered include description of the Big Data ecosystem; real-world instances of Big Data issues; how the Vs of Big Data (volume, velocity, variety, veracity, valence, and value) affect data collection, monitoring, storage, analysis, and reporting; structural process to get value out of Big Data and recognize the differences between a standard database management system and a Big Data management system. Readers will gain insights into choice of data models, data extraction, data integration to solve large data problems, data modelling using Machine Learning techniques, Spark's scalable Machine Learning techniques, modeling a Big Data problem into a graph database and performing scalable analytical operations over the graph and different tools and techniques for processing Big Data and its applications including in healthcare and finance.
The subsequent chapters of this research work delve into a comprehensive examination of Big Data Management and Modelling, Big Data Processing, Big Data Analytics and Machine Learning, and Big Data Analytics Through Visualization. The aforementioned chapters not only explicate the theoretical concepts but also offer valuable practical perspectives on effectively tackling the challenges that manifest within these specific domains.
The chapter titled “Taming Big Data with Spark 2.0” provides an indepth exploration of Apache Spark, emphasizing its architectural design and constituent elements. This study aims to provide a comprehensive understanding of the significance of Resilient Distributed Datasets (RDDs) and their utilization in the processing and analysis of large-scale datasets, commonly referred to as Big Data. The acquisition of this knowledge is of utmost significance in contemporary society where the utilization of real-time analytics and processing holds great prominence.
Within the domain of Big Data, characterized by an overwhelming abundance of information in terms of volume, velocity, and variety, this literary work emerges as a beacon of guidance, catering to a wide-ranging audience. This work is expected to provide significant benefits to a wide range of individuals, including students, data analysts, data scientists, and IT professionals. What is particularly noteworthy about this is that it operates under the assumption that the user possesses no prior understanding or expertise in the field of big data management and analytics. As a result, it is designed to be easily understood and utilized by individuals at all levels of proficiency, including those who are new to the subject matter as well as those who have extensive experience in the field.
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