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here are a number of disadvantages that need to be mentioned as well. Before data can be stored within the warehouse, it must be cleaned, loaded, or extracted. This is a process that can take a long period of time. There may also be issues with compatibility. For example, a new transaction system may not work with systems that are already being used. Users who will be working with the data warehouse must be trained to use it. If they are not trained properly, they may choose not to work within the data warehouse. If the data warehouse can be accessed via the internet, this could lead to a large number of security problems.

　　Another problem with the data warehouse is that it is difficult to maintain. Any organization that is considering using a data warehouse must decide if the benefits outweigh the costs. Once you have paid for the data warehouse, you will still need to pay for the cost of maintenance over time. The costs involved with this must always be taken into consideration. When it comes to storing information, there are two techniques which are used. The first is called the dimensional technique. When the dimensional technique is used, information will be stored within the data warehouse as facts. These facts will take the form of either text or numerical information.

Conclusion
　　Historical project data can assist construction managers in answering questions about the business, the performance of interested operations, business trends, and what can be done to improve the business. Αlthough the data is there, it is always a challenge to find the needed data in time when a decision is made. Decisions can be slowed down due to inconsistency and/or inaccuracy of data. Data warehousing provides the technology for storing historical construction project data which can be extracted from existing operational databases/systems.
　　However, unlike many other application systems, an organization cannot simply buy a data warehouse off the shelf. Instead, a proper design is needed to ensure that the data structure of the warehouse can address the nature of the organization and meet its business needs so that the data to be captured in the warehouse will reflect what is available and what will be needed by the company.

　　As for Dean and Dyball company Data warehousing strategy, approach and technique can be used effectively to increase their business efficiency, because it is clear that if populated with data from a number of projects, the data warehouse could generate site selection patterns for different areas reflecting their unique characteristics. These patterns can help users to further refine the site selection criteria.

References
　　A. Sen and V.S. Jacob (1998), Industrial-strength data warehousing. Commun. ACM 41 9, pp. 28–31.
　　H.J. Watson, (2001) Developments in data warehousing, Communications of the AIS 8.
　　I. Ahmad, S. Azhar and P. Lukauskis, (2004) Development of a decision support system using data warehousing to assist builders/developers in site selection, Automation in Construction 13 (4), pp. 525–542.
　　K.W. Chau, Y. Cao and M. Anson, (2002) Application of data warehousing and decision support system in construction management, Automation in Construction 11 (5), pp. 607–616.
　　L. Soibelman and H. Kim, (2002) Data preparation process for construction knowledge genera本论文由英语论文网提供整理，提供论文代写，英语论文代写，代写论文，代写英语论文，代写留学生论文，代写英文论文，留学生论文代写相关核心关键词搜索。