This handbook offers comprehensive coverage of recent advancements in Big Data technologies and related paradigms. Chapters are authored by international leading experts in the field, and have been reviewed and revised for maximum reader value. The volume consists of twenty-five chapters organized into four main parts. Part one covers the fundamental concepts of Big Data technologies including data curation mechanisms, data models, storage models, programming models and programming platforms. It also dives into the details of implementing Big SQL query engines and big stream processing systems. Part Two focuses on the semantic aspects of Big Data management including data integration and exploratory ad hoc analysis in addition to structured querying and pattern matching techniques. Part Three presents a comprehensive overview of large scale graph processing. It covers the most recent research in large scale graph processing platforms, introducing several scalablegraph querying and mining mechanisms in domains such as social networks. Part Four details novel applications that have been made possible by the rapid emergence of Big Data technologies such as Internet-of-Things (IOT), Cognitive Computing and SCADA Systems. All parts of the book discuss open research problems, including potential opportunities, that have arisen from the rapid progress of Big Data technologies and the associated increasing requirements of application domains.
Designed for researchers, IT professionals and graduate students, this book is a timely contribution to the growing Big Data field. Big Data has been recognized as one of leading emerging technologies that will have a major contribution and impact on the various fields of science and varies aspect of the human society over the coming decades. Therefore, the content in this book will be an essential tool to help readers understand the development and future of the field.
Table des matières
Big Data Storage Models.- Big Data Programming Models.- Programming Platforms for Big Data Analysis.- Big Data Analysis on Clouds.- Data Organization and Curation in Big Data.- Big Data Query Engines.- Unbounded Data Processing.- Semantic Data Integration.- Linked Data Management.- Non-native RDF Storage Engines.- Exploratory Ad-hoc Analysis for Big Data.- Pattern Matching over Linked Data Streams.- Searching the Big Data Practices and Experiences in Efficiently Querying Knowledge Bases.- Management and Analysis of Big Graph Data.- Similarity Search in Large-Scale Graph Databases.- Big Graphs Querying, Mining, and Beyond.- Link and Graph Mining in the Big Data Era.- Granular Social Network Model and Applications.- Big Data, Io T and Semantics.- SCADA Systems in the Cloud.- Quantitative Data Analysis in Finance.- Emerging Cost Effective Big Data Architectures.- Bringing High Performance Computing to Big Data.- Cognitive Computing where Big Data is Driving.- Privacy-Preserving Record Linkage for Big Data.
A propos de l’auteur
Albert Zomaya is the Chair Professor of High Performance Computing & Networking in the School of Information Technologies, University of Sydney. Dr. Zomaya published more than 500 scientific papers and articles and is author, co-author or editor of more than 20 books. He served as the Editor in Chief of the IEEE Transactions on Computers (2011-2014) and was elected recently as a Founding Editor in Chief for the newly established IEEE Transactions on Sustainable Computing. Dr. Zomaya also serves as an associate editor for more than 20 leading journals. He is Fellow of AAAS, IEEE, and IET.
Sherif Sakr is currently a professor of computer and information science in the Health Informatics department at King Saud bin Abdulaziz University for Health Sciences. He is also affiliated with the University of New South Wales and DATA61/CSIRO. He received his Ph D degree in Computer and Information Science from Konstanz University, Germany in 2007. Dr. Sakr held visiting appointments in several academic and research institutes including Microsoft Research (2011), Alcatel-Lucent Bell Labs (2012), University of Zurich (2016) and TU Dresden (2016). His current research is revolved around advanced big data management and processing technologies. In addition to his dozens of peer-reviewed articles in reputable conferences and journals, he is the author and editor of several valuable books in this domain.
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