| Data quality is a critical success factor to many activities of the information age, including the development and operation of a data warehouse (Wixom and Watson 2001). The issue of data quality is recognized in the development of the warehouse; however, there is no formal methodological approach to dealing with the quality issues.; This research was targeted at the development of a framework and relational database tool to improve the process of making data quality decisions in the creation of a data warehouse. A framework for examining data quality issues, the Data Quality Analysis Framework (DQAF), is proposed. An associated tool for the collection of metadata, the Data Quality Knowledge Management (DQKM) tool, is also proposed. An exploratory study was conducted to determine if data gathered using the DQKM would support resource allocation decisions for data quality efforts.; The research presented in this paper reflects two processes: the development of the DQAF and DQKM, and the exploratory study of the tool. The process involved analyzing qualitative data from a series of interviews and quantitative data from the results of the exploratory studies. It involved the construction and population of the DQKM, based on data obtained from a case study conducted at the Center for Technology in Government. Thus, the work reflects a multi-method approach, providing a result that has practical value as well as academic rigor. Additionally, it lays the groundwork for a stream of research that is expected to last many years.; This research contributes to knowledge in three areas: (1) It addresses the need for a methodological approach for assessing data quality in the context of a data warehouse project; (2) It provides a tool for effectively capturing and managing metadata in the complex environment that results when integrating multiple data sources; (3) It builds on the concept of fitness for use, providing a mechanism for allocating resources for data quality projects based on the interaction of the data field, the data quality dimension, and the use of the data. |
