MARC Record from harvard_bibliographic_metadata

LEADER: 03999nam a22005175a 4500
001 014199197-6
005 20141107200428.0
008 140910s2014 gw | s ||0| 0|eng d
020 $a9783642546556
020 $a9783642546556
020 $a9783642546549
024 7 $a10.1007/978-3-642-54655-6$2doi
035 $a(Springer)9783642546556
040 $aSpringer
050 4 $aQA76.9.D3
072 7 $aUN$2bicssc
072 7 $aUMT$2bicssc
072 7 $aCOM021000$2bisacsh
082 04 $a005.74$223
100 1 $aVaisman, Alejandro,$eauthor.
245 10 $aData Warehouse Systems :$bDesign and Implementation /$cby Alejandro Vaisman, Esteban Zimányi.
264 1 $aBerlin, Heidelberg :$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
347 $atext file$bPDF$2rda
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 20 $aInformation retrieval.
650 20 $aInformation organization.
650 20 $aDatabase management.
650 10 $aComputer science.
650 0 $aComputer science.
650 0 $aDatabase management.
650 0 $aInformation storage and retrieval systems.
650 0 $aInformation systems.
650 0 $aManagement information systems.
650 24 $aBusiness Information Systems.
650 24 $aComputer Appl. in Administrative Data Processing.
700 1 $aZimányi, Esteban,$eauthor.
776 08 $iPrinted edition:$z9783642546549
830 0 $aData-Centric Systems and Applications.
988 $a20141002
906 $0VEN