Object

Title: Data Quality Alerting Model for Big Data Analytics

Co-author(s) :

Aligon Julien ; Franck Ravat ; Astsatryan Hrachya

Abstract:

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.

Publisher:

Springer

Identifier:

oai:noad.sci.am:136212

DOI:

10.1007/978-3-030-30278-8_47

ISBN:

978-3-030-30278-8

ISSN:

978-3-030-30277-1

Language:

English

Journal or Publication Title:

New Trends in Databases and Information Systems

URL:

click here to follow the link

Affiliation:

Institute for Informatics and Automation Problems of NAS RA ; IRIT-CNRS (UMR 5505), Université Toulouse

Object collections:

Last modified:

May 3, 2021

In our library since:

Apr 30, 2021

Number of object content hits:

45

All available object's versions:

https://noad.sci.am/publication/149777

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