APPROACH FOR EVALUATING DATA QUALITY PROJECTS

Abstract

Data in our era is characterized by overwhelming volume, variety tends towards unstructured architecture and very high and continuous speed of production and sharing. These characteristics lead organizations to demand a level of quality from their data that must meet the needs and requirements of those requesting their service. Despite the existence of numerous quality procedures, a reference method is essential for the evaluation of data remediation projects. It is in this perspective, this article proposes an approach aimed at helping in the choice of the most profitable scenario according to the gains and benefits expected during the evaluation of data quality projects. The approach assesses the positive impact of process quality and data quality, as well as the complexity of its implementation. It is based on a cost-benefit analysis and a cost-effectiveness analysis as well as on a multi-criteria analysis for the classification of the processes and subsequently of the projects according to their weight of importance. The approach focuses on data. It is also interested in the prioritization of key processes and their collaboration between different process managers. The approach has been put into practice in the health sector for the identification and strengthening of important processes and objects, eligible to be the subject of data quality improvement projects. The approach has been applied to the healthcare sector for the identification and strengthening of important business processes and objects, eligible to be the subject of data quality improvement projects.

Keywords

• evaluation of quality projects
• multi-criteria analysis
• cost-benefit analysis
• cost-effectiveness analysis
• data quality
• prediction of the completeness of the business object
• business processes collaboration