Batch Data Processing

Batch Data Processing is a data processing paradigm that belongs to the class of data handling techniques characterized by the collection, aggregation, and subsequent processing of data in discrete, finite groups or batches, distinguished from continuous or stream processing by its reliance on scheduled, periodic execution over accumulated datasets.

403

Publications

39.3K

Citations

1.5K

Authors

585

Institutions

Publications per year

2017–2026

167

Authors

1.5K

  1. PS
    Prashant Shenoy

    University of Massachusetts Amherst, United States

    4 publications · 210 citations

    4

    h-index

  2. EM
    Edward Mazur

    University of Massachusetts Amherst, United States

    3 publications · 194 citations

    3

    h-index

  3. ZT
    Zachary T. Pennington

    Icahn School of Medicine at Mount Sinai, United States

    3 publications · 319 citations

    3

    h-index

  4. BL
    Boduo Li

    University of Massachusetts Amherst, United States

    3 publications · 194 citations

    3

    h-index

  5. HA
    Henrik Antti

    Umeå University, Sweden

    3 publications · 158 citations

    3

    h-index

1–5 of 1.5K

Venues

  1. arXiv (Cornell University)

    Repository · 12 publications · 606 citations

    11

    h-index

  2. Bioinformatics

    8 publications · 1.7K citations

    8

    h-index

  3. Industrial & Engineering Chemistry Research

    5 publications · 141 citations

    5

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 5 publications · 193 citations

    5

    h-index

  5. PLoS ONE

    5 publications · 295 citations

    5

    h-index

1–5