Most of modern enterprises, institutions, and organizations rely on knowledge-based management systems. In these systems, knowledge is gained from data analysis. Nowadays, knowledge-based management systems include data warehouses as their core components. The purpose of building a data warehouse is twofold. Firstly, to integrate multiple heterogeneous, autonomous, and distributed data sources within an enterprise. Secondly, to provide a platform for advanced, complex, and efficient data analysis. Data integrated in a data warehouse are analyzed by the so-called On-Line Analytical Processing (OLAP) applications designed among others for discovering trends, patterns of behavior, and anomalies as well as for finding dependencies between data. Massive amounts of integrated data and the complexity of integrated data that more and more often come from WEB-based, XML-based, spatio-temporal, object, and multimedia systems, make data integration and processing challenging. The objective of NEW TRENDS IN DATA WAREHOUSING AND DATA ANALYSIS is fourfold: First, to bring together the most recent research and practical achievements in the DW and OLAP technologies.
Second, to open and discuss new, just emerging areas of further development. Third, to provide the up-to-date bibliography of published works and the resource of research achievements for anyone interested in up-to-date data warehouse issues. And, finally, to assist in the dissemination of knowledge in the field of advanced DW and OLAP.
Edited by:
Stanislaw Kozielski, Robert Wrembel Imprint: Springer-Verlag New York Inc. Country of Publication: United States Edition: 1st Edition. 2nd Printing. 2008 Volume: 3 Dimensions:
Height: 235mm,
Width: 155mm,
Spine: 19mm
Weight: 557g ISBN:9780387874302 ISBN 10: 0387874305 Series:Annals of Information Systems Pages: 364 Publication Date:21 November 2008 Audience:
College/higher education
,
Further / Higher Education
Format:Paperback Publisher's Status: Active