Meeting Health Care Research Needs in a Kimball Integrated Data Warehouse

R. Hart, A. Kuo
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引用次数: 4

Abstract

Business Intelligence and the Kimball methodology, often referred to as dimensional modelling, are well established in data warehousing as a successful means of turning data into information. These techniques have been utilized in multiple business areas such as banking, manufacturing, marketing, sales, healthcare and more. Several articles have also shown how the Kimball approach can and has been used in the development of clinical research databases. However, these articles have also shown that there are weaknesses to the Kimball methodology when applied to complex areas such as clinical research. This paper describes our approach to address these weaknesses and meet the more sophisticated needs of health researchers by leveraging relationships within the underlying data and advanced techniques in the Kimball methodology.
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在Kimball集成数据仓库中满足医疗保健研究需求
商业智能和Kimball方法(通常称为维度建模)在数据仓库中已经很好地建立起来,是将数据转换为信息的一种成功方法。这些技术已用于多个业务领域,如银行、制造、营销、销售、医疗保健等。一些文章也展示了Kimball方法如何能够并且已经用于临床研究数据库的开发。然而,这些文章也表明,Kimball方法在应用于临床研究等复杂领域时存在弱点。本文描述了我们的方法,以解决这些弱点,并满足卫生研究人员更复杂的需求,利用关系的基础数据和先进的技术在金博尔方法。
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