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引用次数: 93
摘要
在数据仓库系统的新领域中,软件工程师需要定义一个与许多异构源集成的解决方案,以提取、转换和聚合数据,并提供灵活性来运行检索分析信息的特殊查询。此外,这些活动应该基于一个简洁的维度模式来执行。这个复杂的过程及其特定的多维性要求需求工程方法来帮助精确定义数据仓库应用程序。本文对传统的需求工程过程进行了改进,提出了一种数据仓库需求定义方法DWARF。一个案例研究演示了该方法如何成功地应用于为巴西联邦税务局(Brazilian Federal Revenue Service)存储数百gb战略数据的大型数据仓库系统的公司开发中。
DWARF: an approach for requirements definition and management of data warehouse systems
In the novel domain of data warehouse systems, software engineers are required to define a solution that integrates with a number of heterogeneous sources to extract, transform and aggregate data, as well as to offer flexibility to run adhoc queries that retrieve analytic information. Moreover, these activities should be performed based on a concise dimensional schema. This intricate process with its particular multidimensionality claims for a requirements engineering approach to aid the precise definition of data warehouse applications. We adapt the traditional requirements engineering process and propose DWARF, a data warehouse requirements definition method. A case study demonstrates how the method has been successfully applied in the company wise development of a large-scale data warehouse system that stores hundreds of gigabytes of strategic data for the Brazilian Federal Revenue Service.