Integration of Data Mining Results into Multi-dimensional Data Models

Volker Meyer (), Wolfram Höpken (), Matthias Fuchs () and Maria Lexhagen ()
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Volker Meyer: University of Applied Sciences Ravensburg-Weingarten
Wolfram Höpken: University of Applied Sciences Ravensburg-Weingarten
Matthias Fuchs: Mid-Sweden University
Maria Lexhagen: Mid-Sweden University

A chapter in Information and Communication Technologies in Tourism 2015, 2015, pp 155-168 from Springer

Abstract: Abstract The travel and tourism domain as a global competitive service business has a special need to understand the customer and market trends. Typically, available customer-based data is stored in data warehouses and analysed by either OLAP queries or data mining techniques. However, a more powerful approach is to combine these techniques and to integrate data mining results directly into the original data warehouse structures. This comprehensive data source builds the basis for further applications of business intelligence. This paper presents a novel approach to integrate data mining results into multi-dimensional data warehouse structures and to store data mining results with the original information. A first implementation for the leading Swedish mountain destination Åre has shown the advantages of this new concept: the end-user can now easily access data mining results by simple OLAP queries and even combine them with the original information stored in the data warehouse.

Keywords: Business intelligence; Data mining; Multi-dimensional data modelling; Data warehousing; Online analytical processing (OLAP); Tourism knowledge destination (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-3-319-14343-9_12

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