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Improving OLTP Data Quality Using Data Warehouse Mechanisms

机译:使用数据仓库机制提高OLTP数据质量

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Research and products for the integration of heterogeneous legacy source databases in data warehousing have addressed numerous data quality problems in or between the sources. Such a solution is marketed by Team4 for the decision support of mobile sales representatives, using advanced view maintenance and replication management techniques in an environment based on relational data warehouse technology and Lotus Notes-based client systems. However, considering total information supply chain management, the capture of poor operational data, to be cleaned later in the data warehouse, appears sub-optimal. Based on the observation that decision support clients are often closely linked to operational data entry, we have addressed the problem of mapping the data warehouse data quality techniques back to data quality measures for improving OLTP data. The solution requires a warehouse-to-OLTP workflow which employs a combination of view maintenance and view update techniques.
机译:数据仓库中异构遗留源数据库集成的研究和产品已经解决了源代码或之间的多种数据质量问题。这种解决方案由Team4为移动销售代表的决策支持而销售,使用基于关系数据仓库技术和Lotus Notes的客户端系统的环境中的高级视图维护和复制管理技术。但是,考虑到总信息供应链管理,在数据仓库后面稍后清理较差的运营数据捕获,出现次优。基于观察到决策支持客户端往往与运营数据输入密切相关,我们已经解决了将数据仓库数据质量技术映射回数据质量措施的问题,以改善OLTP数据。该解决方案需要仓库到OLTP工作流,该工作流程采用查看维护和查看更新技术的组合。

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