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Data Warehouse Systems

Design and Implementation

  • Alejandro Vaisman
  • Esteban Zimányi

Part of the Data-Centric Systems and Applications book series (DCSA)

Table of contents

  1. Front Matter
    Pages i-xxvi
  2. Fundamental Concepts

    1. Front Matter
      Pages 1-1
    2. Alejandro Vaisman, Esteban Zimányi
      Pages 3-11
    3. Alejandro Vaisman, Esteban Zimányi
      Pages 13-52
    4. Alejandro Vaisman, Esteban Zimányi
      Pages 53-87
    5. Alejandro Vaisman, Esteban Zimányi
      Pages 89-119
    6. Alejandro Vaisman, Esteban Zimányi
      Pages 121-178
    7. Alejandro Vaisman, Esteban Zimányi
      Pages 179-230
  3. Implementation and Deployment

    1. Front Matter
      Pages 231-231
    2. Alejandro Vaisman, Esteban Zimányi
      Pages 233-284
    3. Alejandro Vaisman, Esteban Zimányi
      Pages 285-327
    4. Alejandro Vaisman, Esteban Zimányi
      Pages 329-383
    5. Alejandro Vaisman, Esteban Zimányi
      Pages 385-423
  4. Advanced Topics

    1. Front Matter
      Pages 425-425
    2. Alejandro Vaisman, Esteban Zimányi
      Pages 427-473
    3. Alejandro Vaisman, Esteban Zimányi
      Pages 475-506
    4. Alejandro Vaisman, Esteban Zimányi
      Pages 507-537
    5. Alejandro Vaisman, Esteban Zimányi
      Pages 539-576
    6. Alejandro Vaisman, Esteban Zimányi
      Pages 577-588
  5. Back Matter
    Pages 589-625

About this book

Introduction

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.

Keywords

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

Authors and affiliations

  • Alejandro Vaisman
    • 1
  • Esteban Zimányi
    • 2
  1. 1.Instituto Tecnológico de Buenos AiresBuenos AiresArgentina
  2. 2.Université Libre de BruxellesBrusselsBelgium

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-54655-6
  • Copyright Information Springer-Verlag Berlin Heidelberg 2014
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-54654-9
  • Online ISBN 978-3-642-54655-6
  • Buy this book on publisher's site
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