Data quality metadata (DQM) is a set of quality measurements associated with the data. Prior research in data quality has shown that DQM improves decision performance. The same research has also shown that DQM overloads the cognitive capacity of decision-makers. Visualization is a proven technique to reduce cognitive overload in decision-making. This paper aims to describe a prototype decision support system with a visual interface and examine its efficacy in reducing cognitive overload in the context of decision-making with DQM.
The authors describe the salient features of the prototype and following the design science paradigm, this paper evaluates its usefulness using an experimental setting.
The authors find that the interface not only reduced perceived mental demand but also improved decision performance despite added task complexity due to the presence of DQM.
A drawback of this study is the sample size. With a sample size of 51, the power of the model to draw conclusions is weakened.
In today’s decision environments, decision-makers deal with extraordinary volumes of data the quality of which is unknown or not determinable with any certainty. The interface and its evaluation offer insights into the design of decision support systems that reduce the complexity of the data and facilitate the integration of DQM into the decision tasks.
To the best of my knowledge, this is the only research to build and evaluate a decision-support prototype for structured decision-making with DQM.
The authors are grateful to Babson College Faculty Research Fund (BFRF) for supporting the initial phases of this research. They are also grateful to the anonymous reviewers for their insightful comments and suggestions.
Shankaranarayanan, G. and Zhu, B. (2021), "Enhancing decision-making with data quality metadata", Journal of Systems and Information Technology, Vol. 23 No. 2, pp. 199-217. https://doi.org/10.1108/JSIT-08-2020-0153
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