Abstract
The field of data quality management has long recognized the negative impact of data quality defects on decision quality. In many decision scenarios, this negative impact can be largely attributed to the mediating role played by decision-support models - with defected data, the estimation of such a model becomes less reliable and, as a result, the likelihood of flawed decisions increases. Drawing on that argument, this study presents a methodology for assessing the impact of quality defects on the likelihood of flawed decisions. The methodology is first presented at a high level, and then extended for analyzing the impact of missing values on binary Linear Discriminant Analysis (LDA) classifiers. To conclude, we discuss possible directions for extensions and future directions.
Original language | English |
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Title of host publication | Proceedings of ICIQ 2012 |
Subtitle of host publication | 17th International Conference on Information Quality |
Editors | Laure Berti-Equille, Isabelle Comyn-Wattiau, Monica Scannapieco |
Publisher | MIT |
Pages | 229-242 |
Number of pages | 14 |
ISBN (Electronic) | 9781627483964 |
State | Published - 1 Jan 2012 |
Event | 17th International Conference on Information Quality, ICIQ 2012 - Paris, France Duration: 16 Nov 2012 → 17 Nov 2012 |
Conference
Conference | 17th International Conference on Information Quality, ICIQ 2012 |
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Country/Territory | France |
City | Paris |
Period | 16/11/12 → 17/11/12 |
Keywords
- Classification
- Data Quality
- Decision Making
- Linear Discriminant Analysis
- Missing Values
ASJC Scopus subject areas
- Information Systems
- Safety, Risk, Reliability and Quality