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

Authors

171

  1. SB
    Shivnath Babu

    Duke University, United States

    3 publications · 394 citations

    3

    h-index

  2. FN
    Felix Naumann

    Hasso Plattner Institute, Germany

    3 publications · 121 citations

    3

    h-index

  3. JZ
    Jianfeng Zhan

    Chinese Academy of Sciences, China

    2 publications · 103 citations

    2

    h-index

  4. AA
    Ashraf Aboulnaga

    University of Waterloo, Canada

    2 publications · 24 citations

    2

    h-index

  5. ZS
    Zhaohao Sun

    Papua New Guinea University of Technology, Papua New Guinea

    2 publications · 74 citations

    2

    h-index

1–5 of 171

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 3 publications · 483 citations

    3

    h-index

  2. SSRN Electronic Journal

    Repository · 2 publications · 134 citations

    2

    h-index

  3. Neurocomputing

    1 publications · 22 citations

    1

    h-index

  4. RepositóriUM (Universidade do Minho)

    Repository · 1 publications · 24 citations

    1

    h-index

  5. Journal of Computer Information Systems

    1 publications · 50 citations

    1

    h-index

1–5