• 论文 •    

水电工程行业中数据仓库设计的关键技术

李军治,夏国平,史晓霞   

  1. 1.北京航空航天大学 经济管理学院,北京  100083;2.北京建筑工程学院 电气工程与自动化系,北京  100044
  • 收稿日期:2004-11-08 修回日期:2005-04-15 出版日期:2006-01-15 发布日期:2006-01-25
  • 基金资助:
    国家自然科学基金资助项目(70371004);航空科学基金(04JK51057)。

Key technology of data warehouse design in water and electricity engineering industry

LI Jun-zhi,XIA Guo-ping,SHI Xiao-xia   

  1. 1.Sch. of Economics & Management, Beihang Univ., Beijing  100083, China; 2.Dep. of Electric Eng. & Automation, Beijing Inst. of Civil Eng. & Architecture, Beijing  100044, China
  • Received:2004-11-08 Revised:2005-04-15 Online:2006-01-15 Published:2006-01-25
  • Supported by:
    Project supported by the National Natural Science Foundation, China (No. 70371004)and the Aeronautic Science Foundation, China (No. 04JK51057).

摘要: 为了提高数据仓库的开发效率,提出了一种复杂报表驱动的设计方法,分析了这种方法与应用驱动和数据驱动两种方法之间的不同,指出了复杂报表驱动方法的4个特点,定义了用这种方法进行数据仓库开发应该遵循的5个步骤。通过对该方法在国内某水电工程集团的应用,详细阐述了在数据仓库开发的需求分析与设计过程中如何执行复杂报表驱动方法的5个步骤,证明了这种方法的优越性。最后,针对水电工程行业中数据析取环节存在的特殊问题,对数据析取的过程进行了研究,并提出了适用于水电工程行业的数据析取解决方案。

关键词: 数据仓库, 数据析取, 水电工程, 报表驱动

Abstract: To improve the development efficiency of data warehouse, a complex table-driven method to build a data warehouse was proposed. Then the differences between the proposed method and the data-driven or application-driven method was analyzed and four characteristics of complex table-driven method were illuminated. After that five steps to build a data warehouse which were needed to be followed were defined. Through the case study on the application of the proposed method in a large water and electricity engineering enterprise of China, how to execute the five steps of complex table-driven method during the requirement analysis and data warehouse design were discussed in particular and the superiority of the method was also proved. Finally, to solve specific problems in data extraction from multiple data sources particularly some unformatted EXCEL-tables in the case, the process of data-extraction was studied, and then a data-extraction solution for water and electricity engineering industry was proposed.

Key words: data warehouse, data-extract, water and electricity engineering, table-driven

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