Discovering and merging related analytic datasets - Archive ouverte HAL Access content directly
Journal Articles Information Systems Year : 2020

Discovering and merging related analytic datasets

Eric Simon
  • Function : Author
  • PersonId : 953249
Bernd Amann
Stéphane Gançarski


The production of analytic datasets is a significant big data trend and has gone well beyond the scope of traditional IT-governed dataset development. Analytic datasets are now created by data scientists and data analysts using big data frameworks and agile data preparation tools. However, despite the profusion of available datasets, it remains quite difficult for a data analyst to start from a dataset at hand and customize it with additional attributes coming from other existing datasets. This article describes a model and algorithms that exploit automatically extracted and user-defined semantic relationships for extending analytic datasets with new atomic or aggregated attribute values. Our framework is implemented as a REST service in the SAP HANA and includes a careful analysis and practical solutions for several complex data quality issues.
Fichier principal
Vignette du fichier
S0306437920300065.pdf (1.29 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02459098 , version 1 (21-07-2022)


Attribution - NonCommercial



Rutian Liu, Eric Simon, Bernd Amann, Stéphane Gançarski. Discovering and merging related analytic datasets. Information Systems, In press, 91, pp.101495. ⟨10.1016/⟩. ⟨hal-02459098⟩
153 View
10 Download



Gmail Facebook Twitter LinkedIn More