Project Data Warehousing In Construction
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论文字数:2158论文编号:org201406051542142679语种:英语 English地区:中国价格:免费论文
关键词:Project Data Warehousing项目数据仓库建设Historical project datacontractors and engineers
摘要: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.
Project Data Warehousing In Construction
Introduction
A construction project typically involves many participants such as the owner, contractors and engineers. The coordination of project participants is thus dependent on the large amount of information exchanged among project participants in forms of documents, oral messages and meetings, etc. Among these exchanged information, documents, either in paper or electronic form, are the carrier of most important management information pertaining to important aspects of construction project management.
A construction organization generates a great amount of operational data that are distributed across various functional systems to support its daily operations. Although those data may be potentially useful for future projects, they are not widely collected and centrally stored in the organization. This research presents a Project-oriented Data Warehouse (PDW) for contractors. PDW is designed with dimensional data models consisting of 26 tables.
Sixteen of the tables are dimension tables for storing general descriptive information, and the other ten are fact tables for detailing various facts that are captured in the lifecycle of construction projects. PDW can be directly populated with data from existing operational systems, such as P3 files, MS Access, P3/e databases, and Excel files. It maintains each data in the context of its associated project so that a user can retrieve a specific piece of information plus any background information of the related project. PDW has been populated with three sample project data. Through the user interface, a user can generate interested query reports as needed. The presented warehouse structure and data models are scalable. They may be adopted by medium or large contractors for developing company-level data facilities.
Conceptually the idea of a data warehouse is extremely simple. As popularized by Inmon (1994) and Inmon and Hackathorn (2002) a data warehouse is a “subject-oriented, integrated, time-invariant, non-updatable collection of data used to support management decision-making processes and business intelligence.” A data warehouse is a repository into which are placed all data relevant to the management of an organization and from which emerge the information and knowledge needed to effectively manage the organization (Watson, 2001).
While this is clearly a simplistic and idealistic view it allows us to begin the investigation of the foundations, key challenges, and research directions for this discipline. Importantly it highlights the purpose of a data warehouse: support for all levels of management decision-making processes through the acquisition, integration, transformation, and interpretation of internal and external data (Negash, 2004).
Data warehousing (DWG), which implements a shared data warehouse (DW) and/or subject-oriented data mart (DM), has become a central process for decision support-oriented data management. From its beginning as a little-understood experimental concept only a few years ago, it has reached a stage where nobody questions its strategic value.
Statistical indicators and surveys show that the number of companies that already own or are currently building the decision support platform is exploding; large enterprises are involved in at least one or more related projects (Sen & Jacob, 1998). Databases tuned f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。