![]() ![]() ![]() However, from a scientific perspective, a lot of research has been published about the measurement (i.e., the detection) of data quality issues and different generally applicable data quality dimensions and metrics have been discussed. In practical scenarios, data quality is typically associated with data preprocessing, profiling, and cleansing for subsequent tasks like data integration or data analytics. High-quality data is key to interpretable and trustworthy data analytics and the basis for meaningful data-driven decisions. 2Software Competence Center Hagenberg GmbH, Hagenberg, Austria.1Institute for Application-Oriented Knowledge Processing (FAW), Johannes Kepler University, Linz, Austria.
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