Inproceedings,
Data quality requirements analysis and modelling
IEEE ICDE, page 670--677. (1993)
Abstract
Data engineering is the modeling and structuring of data in its design, development and use. An ultimate goal of data engineering is to put quality data in the hands of users. Specifying and ensuring the quality of data, however, is an area in data engineering that has received little attention. In this paper we: (1) establish a set of premises, terms, and definitions for data quality management, and (2) develop a step-by-step methodology for defining and documenting data quality parameters important to users. These quality parameters are used to determine quality indicators, to be tagged to data items, about the data manufacturing pr"s9 such as data source, creation time, and collection method. Given such tags, and the ability to query over them, users can filter out data having undesirable characteristics. The methodology developed provides a concrete approach to data quality requirements collection and documentation. It demonstrates that data quality can be an integral part of the database design process. The paper also provides a perspective for the migration towards quality management of data in a database environment.
