Data Governance - Defining Accountabilities for Data Quality Management
Data Governance - Defining Accountabilities for Data Quality Management
复制标题
数据治理 - 定义数据质量管理的责任
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
Kristin Wende
中科院分区：
文献类型：
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作者：
Kristin Wende
企业需要数据质量管理 (DQM) 来应对需要高质量企业数据的战略和运营挑战。迄今为止，公司主要将 DQM 职责分配给 IT 部门。因此，他们忽视了对于 DQM 成功至关重要的组织问题。然而，通过数据治理，公司可以在整个公司范围内实施 DQM 责任，其中包括来自业务和 IT 的专业人员。本文提出了一种数据治理的应急方法。它概述了基于 IT 治理研究的数据治理模型。该模型包含第一组数据质量角色、决策领域和职责。数据治理模型记录了数据质量角色及其与 DQM 活动的交互类型。此外，本文还确定了意外事件及其对模型配置的影响。公司可以根据这些发现实施公司特定的数据治理模型。
Enterprises need data quality management (DQM) to respond to strategic and operational challenges demanding high-quality corporate data. Hitherto, companies have assigned accountabilities for DQM mostly to IT departments. They have thereby ignored the organisational issues that are critical to the success of DQM. With data governance, however, companies implement corporate-wide accountabilities for DQM that encompass professionals from business and IT. This paper proposes a contingency approach to data governance. It outlines a data governance model based on IT governance research. The model comprises a first set of data quality roles, decision areas and responsibilities. The data governance model documents the data quality roles and their type of interaction with DQM activities. In addition, the paper identifies contingencies and their impact on the model configuration. Companies can implement their company-specific data governance model based on these findings.