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Quarry: A User-centered Big Data Integration Platform

Author

Listed:
  • Petar Jovanovic

    (Universitat Politècnica de Catalunya (BarcelonaTech))

  • Sergi Nadal

    (Universitat Politècnica de Catalunya (BarcelonaTech))

  • Oscar Romero

    (Universitat Politècnica de Catalunya (BarcelonaTech))

  • Alberto Abelló

    (Universitat Politècnica de Catalunya (BarcelonaTech))

  • Besim Bilalli

    (Universitat Politècnica de Catalunya (BarcelonaTech))

Abstract

Obtaining valuable insights and actionable knowledge from data requires cross-analysis of domain data typically coming from various sources. Doing so, inevitably imposes burdensome processes of unifying different data formats, discovering integration paths, and all this given specific analytical needs of a data analyst. Along with large volumes of data, the variety of formats, data models, and semantics drastically contribute to the complexity of such processes. Although there have been many attempts to automate various processes along the Big Data pipeline, no unified platforms accessible by users without technical skills (like statisticians or business analysts) have been proposed. In this paper, we present a Big Data integration platform (Quarry) that uses hypergraph-based metadata to facilitate (and largely automate) the integration of domain data coming from a variety of sources, and provides an intuitive interface to assist end users both in: (1) data exploration with the goal of discovering potentially relevant analysis facets, and (2) consolidation and deployment of data flows which integrate the data, and prepare them for further analysis (descriptive or predictive), visualization, and/or publishing. We validate Quarry’s functionalities with the use case of World Health Organization (WHO) epidemiologists and data analysts in their fight against Neglected Tropical Diseases (NTDs).

Suggested Citation

  • Petar Jovanovic & Sergi Nadal & Oscar Romero & Alberto Abelló & Besim Bilalli, 0. "Quarry: A User-centered Big Data Integration Platform," Information Systems Frontiers, Springer, vol. 0, pages 1-25.
    • Handle: RePEc:spr:infosf:v::y::i::d:10.1007_s10796-020-10001-y
    DOI: 10.1007/s10796-020-10001-y
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    References listed on IDEAS

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    1. Artur Wojciechowski, 2018. "ETL workflow reparation by means of case-based reasoning," Information Systems Frontiers, Springer, vol. 20(1), pages 21-43, February.
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    4. Artur Wojciechowski, 0. "ETL workflow reparation by means of case-based reasoning," Information Systems Frontiers, Springer, vol. 0, pages 1-23.
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