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020 _a9783642546556
_9978-3-642-54655-6
024 7 _a10.1007/978-3-642-54655-6
_2doi
035 _ato000545112
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA76.9.D3
072 7 _aUN
_2bicssc
072 7 _aUMT
_2bicssc
072 7 _aCOM021000
_2bisacsh
082 0 4 _a005.74
_223
100 1 _aVaisman, Alejandro.
_eauthor.
_9453652
245 1 0 _aData Warehouse Systems
_helectronic resource
_bDesign and Implementation /
_cby Alejandro Vaisman, Esteban Zimányi.
260 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2014.
300 _aXVI, 625 p. 133 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aData-Centric Systems and Applications
505 0 _aPart I Fundamental Concepts -- 1 Introduction -- 2 Database Concepts -- 3 Data Warehouse Concepts -- 4 Conceptual Data Warehouse Design -- 5 Logical Data Warehouse Design -- 6 Querying Data Warehouses -- Part II Implementation and Deployment -- 7 Physical Data Warehouse Design -- 8 Extraction, Transformation and Loading -- 9 Data Analytics: Exploiting the Data Warehouse -- 10 A Method for Data Warehouse Design -- Part III Advanced Topics -- 11 Spatial Data Warehouses -- 12 Trajectory Data Warehouses -- 13 New Data Warehouse Technologies -- 14 Data Warehouses and the Semantic Web -- 15 Conclusion.
520 _aWith this textbook, Vaisman and Zimányi deliver excellent coverage of data warehousing and business intelligence technologies ranging from the most basic principles to recent findings and applications. To this end, their work is structured into three parts. Part I describes “Fundamental Concepts” including multi-dimensional models; conceptual and logical data warehouse design; and MDX and SQL/OLAP. Subsequently, Part II details “Implementation and Deployment,” which includes physical data warehouse design; data extraction, transformation, and loading (ETL); and data analytics. Lastly, Part III covers “Advanced Topics” such as spatial data warehouses; trajectory data warehouses; semantic technologies in data warehouses; and novel technologies like MapReduce, column-store databases, and in-memory databases. As a key characteristic of the book, most of the topics are presented and illustrated using application tools. Specifically, a case study based on the well-known Northwind database illustrates how the concepts presented in the book can be implemented using Microsoft Analysis Services and Pentaho Business Analytics. All chapters are summarized using review questions and exercises to support comprehensive student learning. Supplemental material to assist instructors using this book as a course text is available at http://cs.ulb.ac.be/DWSDIbook/, including electronic versions of the figures, solutions to all exercises, and a set of slides accompanying each chapter. Overall, students, practitioners and researchers alike will find this book the most comprehensive reference work on data warehouses, with key topics described in a clear and educational style.
650 0 _aComputer Science.
_9155490
650 0 _aDatabase management.
_9566224
650 0 _aInformation storage and retrieval systems.
_9137013
650 0 _aInformation systems.
_9303226
650 0 _aManagement information systems.
_9299049
650 1 4 _aComputer Science.
_9155490
650 2 4 _aDatabase Management.
_9566226
650 2 4 _aInformation Storage and Retrieval.
_9303027
650 2 4 _aBusiness Information Systems.
_9299050
650 2 4 _aComputer Appl. in Administrative Data Processing.
_9307999
700 1 _aZimányi, Esteban.
_eauthor.
_9322157
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
830 0 _aData-Centric Systems and Applications
_9300695
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-54655-6
912 _aZDB-2-SCS
999 _c403123