Description
Data Analysis in the Cloud
Models, Techniques and Applications
Computer Science Reviews and Trends Series
Authors: Talia Domenico, Trunfio Paolo, Marozzo Fabrizio
Language: EnglishSubjects for Data Analysis in the Cloud:
Keywords
Amazon Web Services; association rules; BigML; Bigtable; classification; cloud computing; cloud deployment models; cloud models for distributed data analysis; cloud service models; clustering; collective data mining; data analysis workflow; data mining; Data Mining Cloud Framework; Data-intensive exascale computing; distributed data mining; Dynamo; ensemble learning; exascale computing; Hunk; in-memory data analysis; JS4Cloud; Mahout; manycore systems; MapReduce; meta-learning; Microsoft Azure; MongoDB; NoSQL; Open Nebula; OpenStack; parallel data mining; Pegasus; research trends; social network analysis; Spark; Swift; trajectory mining; urban computing; VL4Cloud; workflow management systems for Clouds
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Description
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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.
- Introduction to Data Mining and Cloud Computing
- Introduction to Cloud Computing
- Models and Techniques for Cloud-based Data Analysis
- Designing and Supporting Scalable Data Analytics
- Research Trends in Big Data Analysis
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.
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 2011-2
- 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