Executive Summary/Abstract: Data Diagnosis a practical “RAD” approach to data quality from several years working with tricky telecommunications data. The lessons learned are applicable across any data in any sector. This presentation shares how these tactics can address gaps in data knowledge, ensure early wins, at the same time underpinning a “TQM” approach to data quality across an organizati...

• Introduction to Galaxy • Galaxy data quality program goals • Galaxy data quality program current components – Maintaining dimension tables and reviewing the integrity of primary and foreign keys – Monitoring, measuring and reporting on Galaxy’s data quality – Implementing improvements based on data quality findings • Business environment success factors • Throughout the presentation, we will ...

Decision making activities stress data and information quality requirements. The quality of data sources is frequently very poor, therefore a cleansing process is required before using such data for decision making processes. When alternative (and more trusted) data sources are not available data can be cleansed only using business rules derived from domain knowledge. Business rules focus on fi...

Using various administrative and tax data sources to replace key variables collected in business surveys can significantly reduce both survey cost and response burden. Data collected from administrative sources, however, are generally not subjected to the same data quality and consistency checks as those for survey data, and often do not correspond exactly with the variables targeted in the sur...

This talk addresses opportunities for the application of intelligent data analysis techniques at various stages of the value added chain for financial services. After introducing some basic notions and explaining the fundamental steps of data mining, we will have a closer look at various recent and ongoing projects and discuss issues of practical relevance such as data quality and expert knowle...

In this paper we present research in progress that has the aim of developing a set of data quality metrics for two aspects of the dimension of consistency, the semantic and representational aspects. In the literature metrics for these two aspects are relatively unexplored, especially in comparison with the data integrity aspect. Our goal is to apply these data quality metrics to interconnected ...

A multidisciplinary , collaborative project of