Profiling Of Big Data
Profiling of Big Data is a systematic analytical process that characterizes the structural, syntactic, and semantic properties of large-scale, heterogeneous datasets to assess data quality, discover metadata, and identify patterns, anomalies, or inconsistencies inherent in big data environments.
59
Publications
4.3K
Citations
171
Authors
93
Institutions
Publications per year
2017–2026
25
Parents
59
Big data and its technical challenges
H. V. Jagadish, Johannes Gehrke, Alexandros Labrinidis et al. · Communications of the ACM · 2014 · 1K citations
Towards felicitous decision making: An overview on challenges and trends of Big Data
Hai Wang, Zeshui Xu, Hamido Fujita et al. · Information Sciences · 2016 · 264 citations
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93
Duke University
Durham, United States
4 h-index
5 publications
788 citations

Chinese Academy of Sciences
Beijing, China
3 h-index
20 publications
1K citations
Hasso Plattner Institute
Potsdam, Germany
3 h-index
8 publications
418 citations

University of Waterloo
Waterloo, Canada
3 h-index
3 publications
56 citations
University of Chinese Academy of Sciences
Beijing, China
3 h-index
5 publications
229 citations
University of Potsdam
Potsdam, Germany
2 h-index
3 publications
31 citations
Qatar Cardiovascular Research Center
Doha, Qatar
2 h-index
2 publications
110 citations
Chalmers University of Technology
Gothenburg, Sweden
2 h-index
2 publications
121 citations
1–8 of 93
PVLDB · 3 publications · 483 citations
3
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Repository · 2 publications · 134 citations
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1 publications · 22 citations
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Repository · 1 publications · 24 citations
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1 publications · 50 citations
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