TBDQ: A Pragmatic Task-Based Method to Data Quality Assessment and Improvement

PLoS One

Mehran Mohsenzadeh¹  Reza Vaziri¹  Jafar Habibi² 

[1]Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

[2]Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

关键词: Data management;    Internet;    Money supply and banking;    Business process reengineering;    Questionnaires;    Census;    Finance;    Surveys;   

DOI  :  10.1371/journal.pone.0154508

学科分类：医学（综合）

来源: Public Library of Science

【 摘 要 】

Organizations are increasingly accepting data quality (DQ) as a major key to their success. In order to assess and improve DQ, methods have been devised. Many of these methods attempt to raise DQ by directly manipulating low quality data. Such methods operate reactively and are suitable for organizations with highly developed integrated systems. However, there is a lack of a proactive DQ method for businesses with weak IT infrastructure where data quality is largely affected by tasks that are performed by human agents. This study aims to develop and evaluate a new method for structured data, which is simple and practical so that it can easily be applied to real world situations. The new method detects the potentially risky tasks within a process, and adds new improving tasks to counter them. To achieve continuous improvement, an award system is also developed to help with the better selection of the proposed improving tasks. The task-based DQ method (TBDQ) is most appropriate for small and medium organizations, and simplicity in implementation is one of its most prominent features. TBDQ is case studied in an international trade company. The case study shows that TBDQ is effective in selecting optimal activities for DQ improvement in terms of cost and improvement.

【 授权许可】

CC BY