Authors:
- Presents an innovative approach for qualitative data analysis that is close to human reasoning
- A practical use case example explains how to integrate fuzzy concepts in existing data warehouses
- Provides a fuzzy data warehouse architecture overview using common open-source technologies
Part of the book series: Fuzzy Management Methods (FMM)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (6 chapters)
-
Front Matter
-
Concept
-
Front Matter
-
-
Application
-
Front Matter
-
-
Implementation
-
Front Matter
-
-
Evaluation and Conclusion
-
Front Matter
-
-
Back Matter
About this book
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 meaningful, non-numeric terms. However, if the transition between non-numeric terms is crisp, true values cannot be measured and a smooth transition between classes may no longer be possible. This book addresses this problem by presenting a fuzzy classification-based approach for a data warehouses. Moreover, it introduces a modeling approach for fuzzy data warehouses that makes it possible to integrate fuzzy linguistic variables in a meta-table structure. The essence of this structure is that fuzzy concepts can be integrated into the dimensions and facts of an existing classical data warehouse without affecting its core. This allows a simultaneous analysis, both fuzzy and crisp. A case study of a movie rental company underlines and exemplifies the proposed approach.
Â
Authors and Affiliations
-
Scigility Inc., Marly, Switzerland
Daniel Fasel
About the author
Dr. Daniel Fasel is the founder, CEO and President of the Managerial Board at Scigility. Previously, he served as the first data scientist on the business intelligence team at Swisscom and was key in implementing NoSQL technologies for explorative analytics during his time there. Before focusing on data science and NoSQL technologies, he was a BI Engineer for the contract and customer field - a core component of the Swisscom Data Warehouse. He also served as a BI Architect and Administrator for the Oracle Hyperion Essbase cubes. In 2012, he received his Ph.D. in economics from the University of Fribourg.
Â
Bibliographic Information
Book Title: Fuzzy Data Warehousing for Performance Measurement
Book Subtitle: Concept and Implementation
Authors: Daniel Fasel
Series Title: Fuzzy Management Methods
DOI: https://doi.org/10.1007/978-3-319-04226-8
Publisher: Springer Cham
eBook Packages: Business and Economics, Business and Management (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-04225-1Published: 17 March 2014
Softcover ISBN: 978-3-319-35581-8Published: 03 September 2016
eBook ISBN: 978-3-319-04226-8Published: 08 July 2014
Series ISSN: 2196-4130
Series E-ISSN: 2196-4149
Edition Number: 1
Number of Pages: XXIV, 236
Number of Illustrations: 109 b/w illustrations
Topics: IT in Business, Information Systems and Communication Service, Data Mining and Knowledge Discovery