Data Pipeline Design

Data Pipeline Design is the systematic methodology for structuring, orchestrating, and optimizing data flows and processing stages in batch computing environments to ensure efficient, reliable, and scalable transformation of raw data into usable forms.

171

Publications

12.3K

Citations

992

Authors

354

Institutions

Publications per year

2017–2026

93

Authors

992

  1. DC
    Dianne Cook

    Iowa State University, United States

    4 publications · 104 citations

    4

    h-index

  2. JB
    Jack B. Dennis

    Massachusetts Institute of Technology, United States

    3 publications · 129 citations

    3

    h-index

  3. RS
    Randal S. Olson

    University of Pennsylvania, United States

    3 publications · 628 citations

    3

    h-index

  4. GR
    Guang R. Gao

    University of Delaware, United States

    3 publications · 129 citations

    3

    h-index

  5. ZC
    Zach Cox

    Iowa State University, United States

    2 publications · 41 citations

    2

    h-index

1–5 of 992

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 190 citations

    8

    h-index

  2. 7

    h-index

  3. Bioinformatics

    5 publications · 2.5K citations

    5

    h-index

  4. The Astronomical Journal

    AJ · 3 publications · 408 citations

    3

    h-index

  5. Journal of Computational and Graphical Statistics

    JCGS · 3 publications · 93 citations

    3

    h-index

1–5