Data Engineering

Data engineering is the discipline of designing, building, and maintaining systems and infrastructure that collect, store, process, and transform raw data into formats suitable for analysis and application.

4.4K

Publications

244.3K

Citations

12.2K

Authors

2.8K

Institutions

Publications per year

2017–2026

1.3K

Authors

12.2K

  1. JW
    Jennifer Widom

    Stanford University, United States

    26 publications · 6.7K citations

    23

    h-index

  2. AH
    Alon Halevy

    University of Washington, United States

    23 publications · 3.5K citations

    21

    h-index

  3. TB
    Torben Bach Pedersen

    Aalborg University, Denmark

    20 publications · 946 citations

    17

    h-index

  4. RJ
    Renée J. Miller

    University of Toronto, Canada

    19 publications · 1.4K citations

    17

    h-index

  5. SR
    Stefano Rizzi

    University of Bologna, Italy

    17 publications · 1.3K citations

    16

    h-index

1–5 of 12.2K

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 70 publications · 5.1K citations

    36

    h-index

  2. ACM SIGMOD Record

    53 publications · 5.2K citations

    35

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 44 publications · 3.7K citations

    27

    h-index

  4. IEEE Access

    40 publications · 2.2K citations

    27

    h-index

  5. ACM Transactions on Database Systems

    TODS · 25 publications · 3.3K citations

    24

    h-index

1–5

See also

Data Engineering

Core Methods

Infrastructure

Data Quality

Scalability

Applications