Data Quality Alerting Model for Big Data Analytics

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.