Discovering dependencies among data quality dimensions : a validation of instrument.
Improving data quality is a basic step for all companies and organizations as it leads to increase opportunity to achieve top services. The aim of this study was to validate and adapt the four major data quality dimensions’ instruments in different information systems. The four important quality dim...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Asian Network for Scientific Information
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/30562/1/Discovering%20dependencies%20among%20data%20quality%20dimensions.pdf http://psasir.upm.edu.my/id/eprint/30562/ http://scialert.net/archivedetails.php?issn=1812-5654&issueno=201 |
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| Institution: | Universiti Putra Malaysia |
| Language: | English English |
| Summary: | Improving data quality is a basic step for all companies and organizations as it leads to increase opportunity to achieve top services. The aim of this study was to validate and adapt the four major data quality dimensions’ instruments in different information systems. The four important quality dimensions which were used in this study were; accuracy, completeness, consistency and timeliness. The questionnaire was developed, validated and used for collecting data on the different information system’s users. A set of questionnaire was conducted to 50 respondents who using different information systems. Inferential statistics and descriptive analysis were employed to measure and validate the factor contributing to quality improvement process. This study has been compared with related parts of previous studies; and showed that the instrument is valid to measure quality dimensions and improvement process. The content validity, reliability and factor analysis were applied on 24 items to compute the results. The results showed that the instrument is considered to be reliable and validate. The results also suggest that the instrument can be used as a basic foundation to implicate data quality for organizations manager to design improvement process. |
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