Data Lake Design

Data Lake Design is a scholarly framework that specifies the structural, organizational, and technological principles for integrating heterogeneous data sources into a centralized repository to enable scalable storage, efficient processing, and governed access within an enterprise data ecosystem.

39

Publications

2.3K

Citations

121

Authors

63

Institutions

Publications per year

2017–2026

30

Parents

Authors

121

  1. RH
    Rihan Hai

    RWTH Aachen University, Germany

    3 publications · 155 citations

    3

    h-index

  2. CQ
    Christoph Quix

    RWTH Aachen University, Germany

    3 publications · 155 citations

    3

    h-index

  3. AB
    Amin Beheshti

    Macquarie University, Australia

    2 publications · 162 citations

    2

    h-index

  4. MJ
    Matthias Jarke

    RWTH Aachen University, Germany

    2 publications · 122 citations

    2

    h-index

  5. AL
    Anne Laurent

    Centre National de la Recherche Scientifique, France

    2 publications · 102 citations

    2

    h-index

1–5 of 121

Venues

  1. 2021 IEEE International Conference on Big Data (Big Data)

    Conference · 3 publications · 80 citations

    3

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 2 publications · 323 citations

    2

    h-index

  3. 2

    h-index

  4. Procedia Computer Science

    2 publications · 117 citations

    2

    h-index

  5. MATEC Web of Conferences

    1 publications · 18 citations

    1

    h-index

1–5