A Taxonomy for Evaluating Data Quality in Data Integration - Towards a Standardized Data Quality Management

Kurzfassung

In the age of data-driven decision-making, the quality of data plays a crucial role. Evaluating data quality is essential to ensure accurate and trustworthy data for decision-making processes. A multitude of concepts have been developed over the years for the purpose of data quality management. These concepts are typically unknown to non-experts, and their application often requires a significant investment of time and effort. In addition, these steps must be repeated for new data sources and use cases. In order to enable non-experts to conduct data quality evaluation, we introduce a streamlined and simplified approach that considers ISO standards as well as relevant literature. A developed taxonomy provides a generic template of a versatile data quality model for the use case data integration. The proposed evaluation process and implemented tool support standardize the measurement of data quality. To ensure applicability, an evaluation with non-domain experts has been carried out.