Tools for data warehouse quality

M. Gebhardt, M. Jarke, M. Jeusfeld, C. Quix, Stefan Sklorz
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引用次数: 7

Abstract

We show three interrelated tools intended to improve different aspects of the quality of data warehouse solutions. Firstly, the deductive object manager ConceptBase is intended to enrich the semantics of data warehouse solutions by including an explicit enterprise-centered concept of quality. The positive impact of precise multidimensional data models on the client interface is demonstrated by CoDecide, an Internet-based toolkit for the flexible visualization of multiple, interrelated data cubes. Finally, MIDAS is a hybrid data mining system which analyses multi-dimensional data to further enrich the semantics of the meta database, using a combination of neural network techniques, fuzzy logic and machine learning.
用于数据仓库质量的工具
我们展示了三个相互关联的工具,旨在提高数据仓库解决方案质量的不同方面。首先,演绎对象管理器ConceptBase旨在通过包含明确的以企业为中心的质量概念来丰富数据仓库解决方案的语义。CoDecide演示了精确多维数据模型对客户端界面的积极影响,CoDecide是一个基于internet的工具包,用于灵活地可视化多个相互关联的数据立方体。最后,MIDAS是一个混合数据挖掘系统,它分析多维数据,进一步丰富元数据库的语义,使用神经网络技术,模糊逻辑和机器学习的组合。
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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