Big Data Platforms and Applications - Case Studies, Methods, Techniques, and Performance Evaluation (Hardcover, 1st ed. 2021)

This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation. The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge. The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are needed for real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Computer Communications and Networks
Release date:	September 2021
First published:	2021
Editors:	Florin Pop • Gabriel Neagu
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	290
Edition:	1st ed. 2021
ISBN-13:	978-3-03-038835-5
Categories:	Books > Computing & IT > Internet > Network computers Books > Business & Economics > Business & management > Business mathematics & systems > General Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems
LSN:	3-03-038835-2
Barcode:	9783030388355

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