Development of a decision support system using data warehousing to assist builders/developers in site selection

Site selection process depends on a number of spatial and business-related factors, making it a complex decision-making task. It is common for the decision makers to use their subjective judgment and gut feelings based on their experience in selecting the most appropriate site for development. The reason is that data for site selection originate from varied sources and are not organized in a format that decision makers can readily use to derive any meaningful information. One possible solution of this problem is to develop a decision support system (DSS) to help retrieve data from different databases and information sources and analyze them in order to provide useful and explicit information. Based on this concept, a DSS is presented in this paper as an aid to builders/developers in site selection for residential housing development. The prototype DSS is developed using data warehousing technology, which is a fairly recent database management technique. It is an improved approach for integrating data from multiple, often very large, distributed, heterogeneous databases and other information sources. Data warehousing is based on online analytical processing (OLAP) concept. The OLAP analyzes data using special data warehousing schemas and enables users to view data using any combination of variables. The users can also generate data trends over a period of time to make any forecasts. First reviewed in this paper are the concepts of data warehousing, OLAP and advantages of the data warehouse over traditional databases in the context of decision making. Next, a step-by-step methodology is presented to illustrate the different stages of the prototype DSS development. The DSS design is illustrated with particular emphasis on the development of data warehousing schemas and analytical processing techniques. The prototype DSS has been developed with input and refined with feedback obtained from selected local builder/developer companies. Finally, the application of the prototype DSS for selecting the most appropriate residential site for development from among a list of several available sites is presented. (C) 2004 Elsevier B.V. All rights reserved.