Overview
- Provides cutting-edge research in large-scale data analytics from diverse scientific areas
- Surveys varied subject areas and reports on individual results of research in the field
- Shares many tips and insights into large-scale data analytics from authors and editors with long-term experience and specialization in the field
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (8 chapters)
-
Front Matter
-
Back Matter
Keywords
About this book
This edited book collects state-of-the-art research related to large-scale data analytics that has been accomplished over the last few years. This is among the first books devoted to this important area based on contributions from diverse scientific areas such as databases, data mining, supercomputing, hardware architecture, data visualization, statistics, and privacy.
There is increasing need for new approaches and technologies that can analyze and synthesize very large amounts of data, in the order of petabytes, that are generated by massively distributed data sources. This requires new distributed architectures for data analysis. Additionally, the heterogeneity of such sources imposes significant challenges for the efficient analysis of the data under numerous constraints, including consistent data integration, data homogenization and scaling, privacy and security preservation. The authors also broaden reader understanding of emerging real-world applications in domains such as customer behavior modeling, graph mining, telecommunications, cyber-security, and social network analysis, all of which impose extra requirements for large-scale data analysis.
Large-Scale Data Analytics is organized in 8 chapters, each providing a survey of an important direction of large-scale data analytics or individual results of the emerging research in the field. The book presents key recent research that will help shape the future of large-scale data analytics, leading the way to the design of new approaches and technologies that can analyze and synthesize very large amounts of heterogeneous data. Students, researchers, professionals and practitioners will find this book an authoritative and comprehensive resource.
Editors and Affiliations
Bibliographic Information
Book Title: Large-Scale Data Analytics
Editors: Aris Gkoulalas-Divanis, Abderrahim Labbi
DOI: https://doi.org/10.1007/978-1-4614-9242-9
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Science+Business Media New York 2014
Hardcover ISBN: 978-1-4614-9241-2
Softcover ISBN: 978-1-4939-4225-1
eBook ISBN: 978-1-4614-9242-9
Edition Number: 1
Number of Pages: XXIII, 257
Number of Illustrations: 83 b/w illustrations
Topics: Database Management, Information Systems and Communication Service, IT in Business, Data Mining and Knowledge Discovery, Systems and Data Security