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Data Quality Management Maturity Model: A Case Study in BPS-Statistics of Kaur Regency, Bengkulu Province, 2017

机译:数据质量管理成熟度模型 - 以哈尔尔鲁省康尔鲁府的BPS统计为例

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摘要

Data are widely used in an organization not only for operation but also for strategic level use. Poor data quality can have negative impact for an organization such as poor decision making and planning. Therefore, data quality management becomes an issue growing today not only to the academic but also professional communities. Based on this issue, this paper presents and analyzes a case study developed in a governmental agency, BPS-Statistics of Kaur Regency. For analysis, a data quality maturity model is used to measure the implementation of data quality management in the organization. The results show that for the dimension of ‘Data quality expectations’ is at a maturity of 4.25. ‘Data quality protocol’ is at a maturity of 3.50. ‘Policies’ reaches a maturity of 3.67. ‘Data quality protocol’ and ‘Data standard’ are at a maturity of 4.42. ‘Data governance’ is at a maturity of 3.00. ‘Technology’ is at a maturity 3.17. ‘Performance management’ is at a maturity of 3.33. However, this also implies that implementing these particular dimensions will lead to a direct increase in overall maturity.
机译:数据广泛用于组织不仅适用于操作,而且用于战略层次。差的数据质量可能对差别决策和规划等组织产生负面影响。因此,数据质量管理成为今天不仅发展的问题,而且不仅仅是学术而且也是专业社区。基于此问题,本文提出并分析了在政府机构,哈尔格洛特的BPS统计数据中开发的案例研究。对于分析,数据质量成熟度模型用于衡量组织中数据质量管理的实现。结果表明,对于“数据质量期望”的维度为4.25的成熟度。 “数据质量方案”处于3.50的成熟度。 “政策”达到3.67的成熟度。 “数据质量协议”和“数据标准”处于4.42的成熟度。 '数据治理'处于3.00的成熟度。 “技术”在成熟3.17。 '绩效管理'处于3.33的成熟度。然而,这也意味着实施这些特定尺寸将导致总成熟度直接增加。

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