Data Quality Completeness
Data Quality Completeness is a data quality dimension that pertains to the extent to which all required data elements are present in a dataset, distinguishing itself from other dimensions by focusing specifically on the absence of missing values relative to a defined domain or business rule.
29
Publications
1.4K
Citations
105
Authors
44
Institutions
Publications per year
2017–2026
17
Parents
29
The Effects of Data Quality on Machine Learning Performance on Tabular Data
Lukas Budach, Moritz Feuerpfeil, Nina Ihde et al. · arXiv (Cornell University) · 2022 · 137 citations · Full text
The effects of data quality on machine learning performance on tabular data
Sedir Mohammed, Lukas Budach, Moritz Feuerpfeil et al. · Information Systems · 2025 · 135 citations · Full text
1–5 of 29
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United Arab Emirates University, United Arab Emirates
3 publications · 166 citations
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1–5 of 105
44

Concordia University
Montreal, Canada
3 h-index
7 publications
412 citations
United Arab Emirates University
Al Ain, United Arab Emirates
3 h-index
4 publications
204 citations

Middlesex University
London, United Kingdom
2 h-index
4 publications
132 citations
Middlesex University
Flic en Flac, Mauritius
2 h-index
2 publications
52 citations

Karolinska Institutet
Stockholm, Sweden
2 h-index
1 publications
81 citations
The University of Texas at Dallas
Richardson, United States
2 h-index
5 publications
383 citations

Uppsala University
Uppsala, Sweden
2 h-index
1 publications
81 citations
Institute of Engineering
Pulchowk, Nepal
1 h-index
4 publications
88 citations
1–8 of 44
2 publications · 68 citations
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1 publications · 32 citations
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Repository · 1 publications · 137 citations
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JAMIA · 1 publications · 55 citations
1
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1 publications · 40 citations
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