ProtOLAP: rapid OLAP prototyping with on-demand data supply

S. Bimonte, Élodie Edoh-Alove, H. Nazih, Myoung-Ah Kang, S. Rizzi
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引用次数: 25

Abstract

The approaches to data warehouse design are based on the assumption that source data are known in advance and available. While this assumption is true in common project situations, in some peculiar contexts it is not. This is the case of the French national project for analysis of energetic agricultural farms, that is the case study of this paper. Here, the above-mentioned methods can hardly be applied because source data can only be identified and collected once user requirements indicate a need. Besides, the users involved in this project found it very hard to express their analysis needs in abstract terms, i.e., without visualizing sample results of queries, which in turn would require availability of source data. To solve this deadlock we propose ProtOLAP, a tool-assisted fast prototyping methodology that enables quick and reliable test and validation of data warehouse schemata in situations where data supply is collected on users' demand and users' ICT skills are minimal. To this end, users manually feed sample realistic data into a prototype created by designers, then they access and explore these sample data using pivot tables to validate the prototype.
ProtOLAP:快速OLAP原型与按需数据提供
数据仓库设计的方法是基于源数据事先已知和可用的假设。虽然这个假设在常见的项目情况下是正确的,但在一些特殊的上下文中却不是。这是法国国家项目的案例,用于分析充满活力的农业农场,这是本文的案例研究。在这里,上述方法很难应用,因为只有在用户需求表明需要时才能识别和收集源数据。此外,参与这个项目的用户发现很难用抽象的术语表达他们的分析需求,也就是说,如果没有可视化的查询样本结果,这反过来又需要源数据的可用性。为了解决这一僵局,我们提出了ProtOLAP,这是一种工具辅助的快速原型设计方法,可以在根据用户需求收集数据供应和用户ICT技能最低的情况下快速可靠地测试和验证数据仓库模式。为此,用户手动将样本真实数据输入设计师创建的原型中,然后使用数据透视表访问和探索这些样本数据以验证原型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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