Abstract
The new data-oriented shape of organizations inevitably imposes the need for the improvement of their data quality (DQ). In fact, growing data quality initiatives are offering increased monetary and non-monetary benefits for organizations. These benefits include increased customer satisfaction, reduced operating costs and increased revenues. However, regardless of the numerous initiatives, there is still no globally accepted approach for evaluating data quality projects in order to build the optimal business cases taking into account the benefits and the costs. This paper presents a model to clearly identify the opportunities for increased monetary and non-monetary benefits from improved data quality within an Enterprise Architecture context. The aim of this paper is to measure, in a quantitative manner, how key business processes help to execute an organization’s strategy and then to qualify the benefits as well as the complexity of improving data, that are consumed and produced by these processes. These findings will allow to select data quality improvement projects, based on the latter’s benefits to the organization and their costs of implementation. To facilitate the understanding of this approach, a Java EE Web application is developed and presented here.
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Belhiah, M., Benqatla, M.S., Bounabat, B. (2016). Decision Support System for Implementing Data Quality Projects. In: Helfert, M., Holzinger, A., Belo, O., Francalanci, C. (eds) Data Management Technologies and Applications. DATA 2015. Communications in Computer and Information Science, vol 584. Springer, Cham. https://doi.org/10.1007/978-3-319-30162-4_1
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DOI: https://doi.org/10.1007/978-3-319-30162-4_1
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