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Data Warehouse Systems electronic resource Design and Implementation / by Alejandro Vaisman, Esteban Zimányi.

By: Vaisman, Alejandro [author.]Contributor(s): Zimányi, Esteban [author.] | SpringerLink (Online service)Material type: TextTextSeries: Data-Centric Systems and ApplicationsPublication details: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014Description: XVI, 625 p. 133 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642546556Subject(s): Computer Science | Database management | Information storage and retrieval systems | Information systems | Management information systems | Computer Science | Database Management | Information Storage and Retrieval | Business Information Systems | Computer Appl. in Administrative Data ProcessingDDC classification: 005.74 LOC classification: QA76.9.D3Online resources: Click here to access online
Contents:
Part 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.
In: Springer eBooksSummary: With 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.
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Part 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.

With 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.

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