Data Cleaning
Data Cleaning is a data preprocessing activity within the broader category of data management and analysis processes, distinguished by its focus on detecting, correcting, or removing inaccurate, incomplete, irrelevant, or duplicated data entries to ensure data quality and consistency for subsequent analytics, mining, engineering, or clinical and spatial data applications.
1.2K
Publications
97.2K
Citations
3.2K
Authors
1.2K
Institutions
Publications per year
2017–2026
401
1.2K
Data management and analysis methods.
A. Michael Huberman, Matthew B. Miles · 1994 · 3.3K citations
Data Management and Analysis Methods
Gery W. Ryan, H. Russell Bernard · 2000 · 2K citations
The prevention and handling of the missing data
Hyun Kang · Korean journal of anesthesiology · 2013 · 1.7K citations · Full text
1–5 of 1.2K
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University of Waterloo
Waterloo, Canada
20 h-index
43 publications
4.8K citations
Tsinghua University
Beijing, China
19 h-index
56 publications
3.5K citations
Stanford University
Stanford, United States
14 h-index
25 publications
2K citations

University of Edinburgh
Edinburgh, United Kingdom
13 h-index
39 publications
4.8K citations
University of California, Berkeley
Berkeley, United States
12 h-index
36 publications
3.6K citations

Harbin Institute of Technology
Harbin, China
12 h-index
44 publications
3.4K citations
University of Technology Sydney
Sydney, Australia
12 h-index
20 publications
1.8K citations
AT&T (United States)
Bedminster, United States
12 h-index
20 publications
1.8K citations
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PVLDB · 40 publications · 3.2K citations
31
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18 publications · 1K citations
17
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Repository · 15 publications · 483 citations
13
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13 publications · 455 citations
13
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TKDE · 10 publications · 1.2K citations
10
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