Data Warehouse Systems
Design and Implementation
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Beschreibung
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.
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 Map Reduce, 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.
Extensive coverage of all data warehouse issues, ranging from basic technologies to the most recent findings and systems Each chapter summarized by review questions and detailed exercises Concepts illustrated by an on going example based on the North wind database using Microsoft Analysis Services and Pentaho Business Analytics Additional website available with further teaching material, including slides for each chapter and solutions to all exercises Includes supplementary material: sn.pub/extras
Autor*in
Alejandro Vaisman
Themen in »Data Warehouse Systems«
OLAP Oracle TimesTen RDFS SAP HANA SPARQL business intelligence conceptual modeling data analytics data warehouses hadoop in-memory databases online analytical processing spatial-temporal systems
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“The book is very well suited for one or more data warehouse courses, ranging from the most basic to the most advanced. It has all the features that are necessary to make a good textbook. (…) The one thing which really set this book apart from its peers is the coverage of advanced data warehouse topics (…) The book also provides a useful overview of novel “Big Data" technologies like Hadoop, and novel database and data warehouse architectures like in-memory databases, column stores, and right-time data warehouses.” from the foreword by Torben Bach Pedersen, Aalborg Universiteit, Denmark
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