Dynamic data warehouse design with abstract state machines

Zhao, Jane, Schewe, Klaus-Dieter and Koehler, Henning (2009) Dynamic data warehouse design with abstract state machines. Journal of Universal Computer Science, 15 1: 355-397. doi:10.3217/jucs-015-01-0355

Author Zhao, Jane
Schewe, Klaus-Dieter
Koehler, Henning
Title Dynamic data warehouse design with abstract state machines
Journal name Journal of Universal Computer Science   Check publisher's open access policy
ISSN 0948-695X
Publication date 2009-09-01
Sub-type Article (original research)
DOI 10.3217/jucs-015-01-0355
Open Access Status DOI
Volume 15
Issue 1
Start page 355
End page 397
Total pages 43
Place of publication Graz, Austria
Publisher Verlag der Technischen Universität Graz [Graz University of Technology], and Universiti Malaysia Sarawak
Language eng
Subject 01 Mathematical Sciences
08 Information and Computing Sciences
Formatted abstract
On-line analytical processing (OLAP) systems deal with analytical tasks that support decision making. As these tasks do not depend on the latest updates by transactions, it is assumed that the data required by OLAP systems are kept in a data warehouse, which separates the input from operational databases from the outputs to OLAP. However, user requirements for OLAP systems change over time. Data warehouses and OLAP systems thus are rather dynamic and the design process is continuous. In order to easily incorporate new requirements and at the same time ensure the quality of the system design, we suggest to apply the Abstract State Machine (ASM) based development method. This assumes we capture the basic user requirements in a ground model and then apply stepwise refinements to the ground model for every design decisions or further new requirements. In this article, we show that a systematical approach which is tailored for data warehouse design with a set of formal refinement rules can simplify the work in dynamic data warehouse design and at the same time improves the quality of the system.
Keyword Abstract state machine
Data warehouse
On-line analytical processing
Q-Index Code C1
Q-Index Status Provisional Code

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
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Created: Wed, 29 Sep 2010, 16:20:41 EST by Jon Swabey on behalf of Faculty Of Engineering, Architecture & Info Tech