Data-driven engineering empowers engineers to significantly reduce development times. A key challenge within this paradigm is the ability to understand large amounts of complex engineering data such as simulation results or measurements. The software solutions developed by Renumics rely on automated machine learning techniques and enable engineers to interactively explore and understand these kinds of datasets very quickly. The approach is especially helpful for result validation, the identification of outliers and reference points as well as correlation and sensitivity analysis. Applications include the validation and evaluation of simulation studies, the analysis of measurement data and the curation of data sets for machine learning based process automation.