An intelligent decision support system in construction management by data warehousing technique

Author name used in this publication: K. W. Chau2002-2003 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Application of data warehouse and Decision Support System in construction management

Author name used in this publication: K. W. Chau2002-2003 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

An Intelligent Decision Support System in Construction Management by Data Warehousing Technique

The integration of a Data Warehouse and a Decision Support System (DSS) can provide construction managers with sufficient information for decision making without interrupting daily work of an On-Line Transaction Processing system. In this paper, the concepts of the data warehouse, On-Line Analysis Processing and DSS are first reviewed. 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. An application example is given to illustrate the use of the Construction Management Decision Support System developed in this study. This prototype system can enable the right data to be tracked down and provides 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 more efficiently. Moreover, the approach can be applied to other fields.Department of Civil and Environmental EngineeringAuthor name used in this publication: K. W. Cha

Modélisation des bases de données multidimensionnelles : analyse par fonctions d'agrégation multiples

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Modelling and optimisation issues for multidimensional databases

On-Line Analytical Processing (OLAP) is a trend in database technology based on the multidimensional view of data. Although multidimensional data cubes form the basic logical data model for OLAP applications, there seems to be no agreement on a common model for cubes. In this paper we propose, a logical model for cubes based on the key observation that a cube is not a self-existing entity, but rather a view over an underlying data set. The model is powerful enough to capture all the commonly encountered OLAP operations such as selection, roll-up and drill-down, through a sound and complete algebra. We accompany our model with results on processing cube operations and provide syntactic characterisations for the problem of cube usability (i.e., the problem of using the tuples of a cube to compute another cube). As part of the solution to this problem, we have developed algorithms to check whether (a) the marginal conditions of two cubes are appropriate for a rewriting, in the presence of aggregation hierarchies and (b) an implication exists between two selection conditions that involve functionally dependent attributes (levels of aggregation in our context). For the latter, we have extended the well-known set of axioms for conjunctive query containment [Ullm89] with axioms describing the role of the functional dependencies. Finally, we present a rewriting algorithm for the cube usability problem. 1