Download or read book The Impact of Data Quality Metadata on Decision Making written by Yu Cai and published by . This book was released on 2007 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: The quality of the data used in a decision process has a direct impact on the quality of the decisions. Unfortunately, data quality (DQ) issues are inherent in information systems. Quality metadata is data that describes the quality of the data. It can inform decision makers about the quality of the data used in the decision process and can potentially enhance decision performance. While research has shown that quality metadata can change decision outcomes, it has not shown whether it improves decision performance. This dissertation first investigates whether and how DQ metadata improves decision performance in structured decision environments. When the DQ metadata is available, integrating it into the decision process requires allocating extra information processing capacity to it. This may impact overall decision performance differently, subject to other factors like task complexity and decision makers' experience. Using a set of experiments, we explore those important relationships. The findings support our general proposition that when there is sufficient amount of cognitive capacity available, the provision of DQ metadata will improve the overall quality of decision-making. However, when the complexity of the decision task increases, thereby reducing the cognitive capacity that the decision-maker has to spare, the provision of DQ metadata can negatively affect decision performance. This research further investigates the use of data visualization to reduce this cognitive load. Building upon the findings from the first part, we develop a prototype decision support system that utilizes visualization to reduce the cognitive effort in integrating quality metadata into the decision process. Using an experimental setup, we assess the impact of data visualization on decision performance using a common type of decision task, structured choice. The results confirm the benefits of visualization for integrating DQ metadata into the decision process. This research has important implications for decision-making, data management and decision support systems. The findings can help (a) identify the conditions under which the provision of DQ metadata is beneficial for decision making, (b) justify the need of including DQ metadata in data management, and (c) shed light on designing decision support systems that integrate DQ metadata for effective decision-making.