Download Data Analysis in the Cloud : Models, Techniques and by Marozzo, Fabrizio; Talia, Domenico; Trunfio, Paolo PDF

By Marozzo, Fabrizio; Talia, Domenico; Trunfio, Paolo

Data research within the Cloud introduces and discusses versions, equipment, options, and structures to research the big variety of electronic facts resources on hand on the web utilizing the computing and garage amenities of the cloud.

Coverage comprises scalable facts mining and information discovery recommendations including cloud computing ideas, versions, and structures. particular sections concentrate on map-reduce and NoSQL versions. The publication additionally contains recommendations for undertaking high-performance disbursed research of enormous info on clouds. eventually, the publication examines learn developments akin to titanic info pervasive computing, data-intensive exascale computing, and big social community analysis.

  • Introduces facts research suggestions and cloud computing concepts
  • Describes cloud-based types and structures for giant info analytics
  • Provides examples of the cutting-edge in cloud information analysis
  • Explains the right way to strengthen large-scale info mining functions on clouds
  • Outlines the most examine tendencies within the region of scalable great info analysis

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Additional info for Data Analysis in the Cloud : Models, Techniques and Applications

Sample text

The business software and user’s data are executed and stored on servers hosted in cloud data centers that provide storage and compute resources. Resources include thousands of servers and storage devices connected to each other through an intracloud network. The transfer of data between data center and users takes place on wide-area network. Several technologies and standards are used by the different components of the architecture. For example, users can interact with cloud services through SOAP-based or RESTful Web services (Richardson and Ruby, 2007).

1 Microsoft Azure Azure3 is an environment and a set of cloud services that can be used to develop cloud-oriented applications, or to enhance existing applications with cloud-based capabilities. The platform provides on-demand compute and storage resources exploiting the computational and storage power of the Microsoft data centers. com/azure 1 2 Introduction to Cloud Computing 33 Fig. 2. Microsoft Azure. high availability and dynamic scaling services that match user needs with a pay-per-use pricing model.

Least squares quantization in PCM. Unpublished Bell Lab. Tech. Note, portions presented at the Institute of Mathematical Statistics Meeting Atlantic City, NJ, September 1957. Also, IEEE Trans. Information Theory (Special Issue on Quantization), IT-28, pp. 129–137, March 1982. , 1967. Some methods for classification and analysis of mutivariate observations. 1, pp. 281–296. , 1995. Parallel algorithms for hierarchical clustering. Parallel Comput. 21, 1313–1325. , 1994. A coarse-grained parallel induction heuristic.

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