Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/975
Title: Application of data warehouse and Decision Support System in construction management
Authors: Chau, Kwok-wing
Cao, Ying
Anson, M.
Zhang, Jianping
Subjects: Decision Support System
Project management
Construction
Data warehouse
On-line analysis processing
Issue Date: Mar-2003
Publisher: Elsevier Science B.V.
Source: Automation in construction, Mar. 2003, v. 12, no. 2, p. 213-224.
Abstract: How to provide construction managers with information about and insight into the existing data, so as to make decision more efficiently without interrupting the daily work of an On-Line Transaction Processing (OLTP) system is a problem during the construction management process. To solve this problem, the integration of a data warehouse and a Decision Support System (DSS) seems to be efficient. ‘Data warehouse’ technology is a new database discipline, which has not yet been applied to construction management. Hence, it is worthwhile to experiment in this particular field in order to gauge the full scope of its capability. First reviewed in this paper are the concepts of the data warehouse, On-Line Analysis Processing (OLAP) and DSS. The method of creating a data warehouse is then shown, changing the data in the data warehouse into a multidimensional data cube and integrating the data warehouse with a DSS. Finally, an application example is given to illustrate the use of the Construction Management Decision Support System (CMDSS) developed in this study. Integration of a data warehouse and a DSS enable the right data to be tracked down and provide the required information in a direct, rapid and meaningful way. Construction managers can view data from various perspectives with significantly reduced query time, thus making decisions faster and more comprehensive. The applications of a data warehousing integrated with a DSS in construction management practice are seen to have considerable potential.
Rights: Automation in Construction © 2002 Elsevier Science B.V. The journal web site is located at http://www.sciencedirect.com.
Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/975
DOI: 10.1016/S0926-5805(02)00087-0
ISSN: 0926-5805
Appears in Collections:CEE Journal/Magazine Articles

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