Data Reliability Engineering

Data Reliability Engineering is a framework within data observability that systematically ensures the accuracy, consistency, and trustworthiness of data across pipelines by applying automated monitoring, validation, and remediation practices analogous to site reliability engineering in software systems.

29

Publications

1.1K

Citations

119

Authors

54

Institutions

Publications per year

2017–2026

16

Authors

119

  1. SH
    Sumi Helal

    University of Florida, United States

    1 publications · 15 citations

    1

    h-index

  2. FB
    F. B. Hagedorn

    1 publications · 11 citations

    1

    h-index

  3. AJ
    Anupam Joshi

    University of Maryland, Baltimore County, United States

    1 publications · 15 citations

    1

    h-index

  4. MA
    Mark A. Neifeld

    University of Arizona, United States

    1 publications · 34 citations

    1

    h-index

  5. BZ
    Bowen Zhao

    South China University of Technology, China

    1 publications · 132 citations

    1

    h-index

1–5 of 119

Venues

  1. ACM Transactions on Storage

    TOS · 1 publications · 135 citations

    1

    h-index

  2. Optics Letters

    1 publications · 34 citations

    1

    h-index

  3. International Journal of Contents

    IJoC · 1 publications · 15 citations

    1

    h-index

  4. 1

    h-index

  5. Tsinghua Science & Technology

    1 publications · 16 citations

    1

    h-index

1–5