데이터 품질진단을 위한 자동화도구 개발

• 영문명: Development of Automated Tools for Data Quality Diagnostics
• 발행기관: 한국IT서비스학회
• 저자명: 고재환(Jae-Hwan Ko) 김동수(Dong-Soo Kim) 한기준(Ki-Joon Han)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제11권 제4호, 153~170쪽, 전체 18쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2012.12.31

영문 초록

When companies or institutes manage data, in order to utilize it as useful resources for decision-making, it is essential to offer precise and reliable data. While most small and medium-sized enterprises and public institutes have been investing a great amount of money in management and maintenance of their data systems, the investment in data management has been inadequate. When public institutions establish their data systems, inspection has been constantly carried out on the data systems in order to improve safety and effectiveness. However, their capabilities in improving the quality of data have been insufficient. This study develops an automatic tool to diagnose the quality of data in a way to diagnose the data quality condition of the inspected institute quantitatively at the stage of design and closure by inspecting the data system and proves its practicality by applying the automatic tool to inspection. As a means to diagnose the quality, this study categorizes, in the aspect of quality characteristics, the items that may be improved through diagnosis at the stage of design, the early stage of establishing the data system and the measurement items by the quality index regarding measurable data values at the stage of establishment and operation. The study presents a way of quantitative measurement regarding the data structures and data values by concretizing the measurement items by quality index in a function of the automatic tool program. Also, the practicality of the tool is proved by applying the tool in the inspection field. As a result, the areas which the institute should improve are reported objectively through a complete enumeration survey on the diagnosed items and the indicators for quality improvement are presented quantitatively by presenting the quality condition quantitatively.

목차

Abstract

1. 서론

2. 관련 연구

3. 자동화도구 제안

4. 감리적용 검증사례 연구

5. 결론

참고문헌

저자소개

키워드

Data Quality Quality Diagnostic Data Profiling Automation Tools