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multidimensional model meaning in English

多维模型

Examples

  1. In a multidimensional model , the data aggregation path is the important part of dimension table design
    在多维模型中,数据聚集路径是维度表设计中的重要部分。
  2. With the example of water and rainfall analysis of flood decision support system , the paper gives how to build a multidimensional model and develop a data - driven dss application
    最后,以水雨情分析作为决策主题,给出了开发实例,围绕典型的olap多维分析应用,对数据-驱动dss的实际开发进行了有益的探索。
  3. The advantage of such multidimensional model is that query speed is quick , it is also rapid to make report forms ; the shortcoming is that the course of modeling is comparatively slower because of a large amount of preconditioning existing
    这种多维模型的优点是查询速度快,做报表也快;缺点是由于存在大量的预处理,其建模过程相对来说就比较慢。
  4. This paper is in the discussion in - depth the technology of data warehouse , especially based on the on - line analytical processing ( olap ) , summarizing through an analysis of complicated medical activity , puts forward a special , large - scale and unified storage sets suiting practical application of the hospital , sets up a hospital topic data warehouse based on multidimensional model , and organizes the data by analyzing the topic for the basic frame
    本文在深入探讨数据仓库技术、特别是联机分析处理( olap )的基础上,通过对复杂的医疗活动的分析概括,提出了适合医院实际应用的一个专门的、大型统一的数据存储集合,建立起基于多维模型的医院主题数据仓库,以分析主题为基本框架来组织数据。
  5. The author have studied data warehouse and olap and data mining , then discussed the relevant concepts , development status , system structure and implementation in details ; meanwhile , through studying the data model of university enrollment examination , integrating with data obtaining technology , multidimensional modeling technology and olap in data warehouse , designed a data mart of university enrollment examination and thus developed a data analyzing system of university enrollment examination based on model supporting decision and olap and data mining
    本论文对数据仓库、联机分析处理和数据挖掘技术进行了研究,并详细介绍了有关的概念、发展状况、体系结构和实现手段;同时,通过对普通高校招生考试的数据模型进行研究,结合数据仓库中的数据获取技术、多维建模技术设计了一个以普通高校招生考试数据分析为主题的数据集市,并在此基础上综合运用联机分析处理技术、数据挖掘技术和模型辅助决策技术实现了一个招生考试数据分析系统。
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