Methods and Supporting Technologies for Data Analysis, Paperback by Zakrzewsk...

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Item Weight: 16 Oz Publication Year: 2014 Book Title: Methods and Supporting Technologies for Data Analysis Item Width: 6.1 in Format: Trade Paperback Subject: Engineering (General), Intelligence (Ai) & Semantics, Data Processing, Databases / General width: 6.1 in Type: Textbook Publisher: Springer Berlin / Heidelberg Series: Studies in Computational Intelligence Ser. Number of Pages: Xii, 244 Pages Subject Area: Computers, Technology & Engineering Language: English Item Length: 9.3 in Author: Ernestina Menasalvas ISBN: 9783642424960 Publication Name: Methods and Supporting Technologies for Data Analysis

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Methods and Supporting Technologies for Data Analysis, Paperback by Zakrzewsk.... Datawarehouse technology and m- eling are presented in the ?. rst chapter together with the deep review of datawarehouse techniques for supporting e-learning processes with special emphasis on data cubes, all the tools are considered in the context of imp- ilar technology and deals with the community data warehouse architecture. Methods and Supporting Technologies for Data Analysis, Paperback by Zakrzewska, Danuta (EDT); Menasalvas, Ernestina (EDT); Byczkowska-lipinska, Liliana (EDT), ISBN 3642424961, ISBN-13 9783642424960, Like New Used, Free shipping in the US The overwhelming pace of evolution in technology has made it possible to develop intelligent systems which help users in their dayly life activities. - cordingly, methods of recording, managing and analysing data have evolved from the very simple ?le systems into complex ambient supportive intelligent systems. This book arises as a compilation of methods, techniques and tools c- nected with data related issues: from modelling to analysis. A broad range of approaches such as database self-* techniques for ubiquitous environments, multimedia data, or data driven models will be reviewed. Di?erent areas of applications, in which data models conceptualize nowadays reality, starting from e-learning to electric transformers will be considered. Th is a collection of representative contributions to cover the sp- trum related to data bases, which support decision making and data mining methods as well as conceptualization. Datawarehouse technology and m- eling are presented in the ?rst chapter together with the deep review of datawarehouse techniques for supporting e-learning processes with special emphasis on data cubes, all the tools are considered in the context of imp- ilar technology and deals with the community data warehouse architecture.