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Communication Dans Un Congrès Année : 2019

Data Quality Alerting Model for Big Data Analytics

Résumé

During Big Data analytics, correcting all the problems of large, heterogeneous and swift data, in a reasonable time, is a challenge and a costly process. Therefore, organizations are confronted with performing analysis on massive data, potentially of poor quality. This context is the starting point of our current research: how to identify data quality issues and how to notify users without solving these quality issues in advance? To this end, we propose a quality model, as the main component of an alert system, which allow to inform users about data quality issues, during their analysis. This paper discusses about the conceptual and implementation frameworks of the quality model, as well as examples of usage.
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Dates et versions

hal-02947780 , version 1 (24-09-2020)

Identifiants

  • HAL Id : hal-02947780 , version 1
  • OATAO : 26343

Citer

Eliza Gyulgyulyan, Julien Aligon, Franck Ravat, Hrachya Astsatryan. Data Quality Alerting Model for Big Data Analytics. International Workshop on Qualitative Aspects of User-Centered Analytics - European Conference on Advances in Databases and Information Systems (QAUCA@ADBIS 2019), Sep 2019, Bled, Slovenia. pp.489-500. ⟨hal-02947780⟩
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