[1]陈映西 刘解放.信息化时代企业数据质量管理研究[J].南通航运职业技术学院学报,2019,(03):20-23.[doi:10.3969/j.issn.1671-9891.2019.03.005]
　CHEN Ying-xi LIU Jie-fang.Study on Enterprises’ Data Quality Management in Informationized Era[J].Journal of Nantong Vocational & Technical Shipping College,2019,(03):20-23.[doi:10.3969/j.issn.1671-9891.2019.03.005]
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信息化时代企业数据质量管理研究(/HTML)
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南通航运职业技术学院学报[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2019年03期
页码:
20-23
栏目:
人文社科
出版日期:
2019-09-25

文章信息/Info

Title:
Study on Enterprises’ Data Quality Management in Informationized Era
作者:
陈映西 刘解放
武汉市城乡建设局武汉市海绵城市和综合管廊建设管理站 湖北交通职业技术学院交通信息学院
Author(s):
CHEN Ying-xi LIU Jie-fang

Wuhan Sponge City and Integrated Pipe Gallery Construction Management Station, Wuhan Urban

and Rural Construction Bureau School of Traffic Information, Hubei Communications Technical

College

关键词:
数据质量;  数据质量框架;  数据质量管理模型
Keywords:
data quality;  data quality framework;  data quality management model
DOI:
10.3969/j.issn.1671-9891.2019.03.005
文献标志码:
A
摘要:

在信息化飞速发展的时代，数据是企业至关重要的资源，是企业的核心，而数据质量是企业提升业绩和盈

利能力的关键。为了确保企业的数据质量，从数据维度及其定义、质量标准及其定义和评定方法等方面提

出了企业数据质量框架。该框架可用于指导企业获取高质量的数据，同时针对企业不同用户和任务对数据

质量的不同要求，提出了数据质量管理模型，为企业开展数据质量管理提供了参考依据。

Abstract:

In the era of rapid development of information technology, data is a vital resource and the

core for enterprises, while data quality is the key to improving enterprises’ performance and

profitability. In order to ensure data quality of enterprises, the data quality framework is

proposed from the aspects of data dimension and its definition, quality standards and their

definitions and assessment methods, etc. The framework can be used to guide enterprises to

obtain high-quality data. Meanwhile, based on different requirements of different users and

tasks for data quality, a data quality management model is proposed, which provides reference

for enterprises to carry out data quality management.

参考文献/References:

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Institute,2002.

[4]TDWI.Modernizing business-to-business data exchange[EB/OL].(2016-04-29)[2019-02-

09].https://tdwi.org/blogs/tdwi-blog/2016/04/modernizing-b2b-data-exchange.aspx.

[5]Batini C,Scannapieco M.Data and information quality:dimensions,principles and techniques

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[6]Weber K,Otto B,sterle H.One size does not fit all—a contingency approach to data

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更新日期/Last Update: 2019-11-11