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Data quality management in a Business Intelligence environment: From the Lens of Metadata

机译:商业智能环境中的数据质量管理:从元数据的角度

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Business Intelligence is becoming more pervasive in many large and medium-sized organisations. Being a long term undertaking Business Intelligence raises many issues that an organisation has to deal with in order to improve its decision making processes. Data quality is one of the main issues exposed by Business Intelligence. Within the organisation data quality can affect attitudes to Business Intelligence itself, especially from the business users group. Comprehensive management of data quality is a crucial part of any Business Intelligence endeavour. It is important to address all types of data quality issues and come up with an all-in-one solution. We believe that extensive metadata infrastructure is the primary technical solution for management of data quality in Business Intelligence. Moreover, metadata has a more broad application for improving the Business Intelligence environment. Upon identifying the sources of data quality issues in Business Intelligence we propose a concept of data quality management by means of metadata framework and discuss the recommended solution.
机译:商业智能在许多大中型组织中变得越来越普遍。长期从事商务智能会带来许多组织必须解决的问题,以改善其决策流程。数据质量是商业智能面临的主要问题之一。在组织内部,数据质量会影响对商业智能本身的态度,尤其是业务用户组的态度。全面质量管理数据是任何商务智能工作的关键部分。解决所有类型的数据质量问题并提供多合一的解决方案非常重要。我们认为,广泛的元数据基础结构是用于在Business Intelligence中管理数据质量的主要技术解决方案。此外,元数据在改善商业智能环境方面具有更广泛的应用。在确定了Business Intelligence中数据质量问题的来源之后,我们提出了一种通过元数据框架进行数据质量管理的概念,并讨论了推荐的解决方案。

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