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- Chapter 1: Introduction to Data Mining
- 1.1. Data mining concepts
- 1.2. Parallel and distributed data mining
- 1.3. Summary
- Chapter 2: Introduction to Cloud Computing
- 2.1. Cloud computing: definition, models, and architectures
- 2.2. Cloud computing systems for data-intensive applications
- 2.3. Summary
- Chapter 3: Models and Techniques for Cloud-Based Data Analysis
- 3.1. MapReduce for data analysis
- 3.2. Data analysis workflows
- 3.3. NoSQL models for data analytics
- 3.4. Summary
- Chapter 4: Designing and Supporting Scalable Data Analytics
- 4.1. Data analysis systems for clouds
- 4.2. How to design a scalable data analysis framework in clouds
- 4.3. Programming workflow-based data analysis
- 4.4. Data analysis case studies
- 4.5. Summary
- Chapter 5: Research Trends in Big Data Analysis
- 5.1. Data-intensive exascale computing
- 5.2. Massive social network analysis
- 5.3. Key research areas
- 5.4. Summary
Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud.
Coverage includes scalable data mining and knowledge discovery techniques together with cloud computing concepts, models, and systems. Specific sections focus on map-reduce and NoSQL models. The book also includes techniques for conducting high-performance distributed analysis of large data on clouds. Finally, the book examines research trends such as Big Data pervasive computing, data-intensive exascale computing, and massive social network analysis.
- Introduces data analysis techniques and cloud computing concepts
- Describes cloud-based models and systems for Big Data analytics
- Provides examples of the state-of-the-art in cloud data analysis
- Explains how to develop large-scale data mining applications on clouds
- Outlines the main research trends in the area of scalable Big Data analysis
Researchers, graduate students, and professionals in the field of scalable data analysis, Cloud computing and knowledge discovery
- No. of pages:
- © Elsevier 2016
- 25th September 2015
- Paperback ISBN:
- eBook ISBN:
Domenico Talia is a professor of computer engineering at University of Calabria and partner of two startups: DtoK Lab and Exeura. His research interests include parallel and distributed data mining algorithms, cloud computing, social data analysis, distributed knowledge discovery, mobile computing, green computing systems, peer-to-peer systems, and parallel programming. He is the author of several books including Service-Oriented Distributed Knowledge Discovery (CRC 2012) and Grid Middleware and Services: Challenges and Solutions (Springer 2010), and more than 300 papers in archival journals such as CACM, IEEE TKDE, ACM Computing Surveys, FGCS, Parallel Computing, IEEE Internet Computing and international conference proceedings. He is a member of the editorial boards of many journals including IEEE Transactions on Cloud Computing, the Future Generation Computer Systems journal, Journal of Cloud Computing, and The International Journal on Web and Grid Services.
Professor of Computer Engineering, University of Calabria, Rende, Italy
Paolo Trunfio is an associate professor of computer engineering at University of Calabria, Italy. He has been a visiting researcher at the Swedish Institute of Computer Science (SICS) in Stockholm and a research collaborator at the Institute of Systems and Computer Science of the Italian National Research Council (ISI-CNR). His current research focuses on cloud computing, distributed data mining, service-oriented architectures, social data analysis, energy-efficiency in distributed systems, and peer-to-peer networks. He published three books, Data Analysis in the Cloud (Elsevier 2015), Service-Oriented Distributed Knowledge Discovery (CRC 2012) and The Internet of Things Based on Smart Objects (Springer 2014), and many scientific papers in conference proceedings, edited books and international journals.
Associate professor of computer engineering, University of Calabria, Italy
Fabrizio Marozzo received a Laurea degree in computer engineering and a Ph.D. in systems and computer engineering from University of Calabria, where he currently works as a Research Technician. In 2011-2012 he visited the Barcelona SuperComputing Center (BSC) for a research internship. His research interests include distributed systems, software engineering, cloud computing, data mining, social data analysis, and peer-to-peer networks. He co-authored several papers in conference proceedings, edited books and international journals. He has been a member of the program committee of several scientific conferences and reviewer for international journals. He was the recipient of two Italian awards for best master thesis in the ICT area: Javaday award 2010 and AICA/Confindustria thesis award 2010.
Department of Electronics, Computer Science and System Sciences (DIMES), University of Calabria, Rende, Italy