Fuzzy Data Warehousing for Performance Measurement Concept and Imple
The numeric values retrieved from a data warehouse may be difficult for business users to interpret, and may even be interpreted incorrectly. Therefore, in order to better understand numeric values, business users may require an interpretation in meaning
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Daniel Fasel
Fuzzy Data Warehousing for Performance Measurement Concept and Implementation
Fuzzy Management Methods
Series Editors Andreas Meier University of Fribourg, Switzerland Witold Pedrycz University of Alberta, Alberta, Canada Edy Portmann University of California at Berkeley, CA, USA
For further volumes: http://www.springer.com/series/11223
Daniel Fasel
Fuzzy Data Warehousing for Performance Measurement Concept and Implementation
123
Daniel Fasel Scigility Inc. Marly, Switzerland
ISSN 2196-4130 ISSN 2196-4149 (electronic) ISBN 978-3-319-04225-1 ISBN 978-3-319-04226-8 (eBook) DOI 10.1007/978-3-319-04226-8 Springer Cham Heidelberg New York Dordrecht London Library of Congress Control Number: 2014933209 © Springer International Publishing Switzerland 2014 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
For my daughter Leola Mai Ly
Foreword
Data warehouses provide an important source of information for enterprises by homogenizing and concentrating business relevant data. In order to retrieve business critical information from the huge collection of data in the warehouse, data must be interpreted in the context of the information one wants to obtain from them. Data in the warehouse, however, are usually imprecise due to imprecisions in the collect
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