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A Novel Data Quality Metric for Timeliness considering Supplemental Data

URN to cite this document:
Heinrich, Bernd ; Klier, Mathias
Date of publication of this fulltext: 28 Mar 2012 14:55


It is intensively discussed in both science and practice how data quality (DQ) can be assured and improved. The growing relevance of DQ has revealed the need for adequate metrics because quantifying DQ is essential for planning quality measures in an economic manner. This paper analyses how DQ can be quantified with respect to the DQ dimension timeliness. Based on an existing approach, we design ...


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