Information Visualization and Visual Analytics: providing a flexible human-in-the-loop system that, in a data preparation cycle, identifies potential performance, data quality, and critical issues, guided by the user, resolves them to generate a new model and continues this cycle until a satisfactory model is achieved. The visual analytics layer balances the trade-off between result accuracy and interactivity by minimizing latency, ensuring a smooth exploratory data analysis experience through predictive techniques for anticipating user interactions and progressive visualizations. These combined approaches enable a more efficient workflow, allowing analysts to explore data ahead of simulation completion, confirming promising runs and discarding unproductive ones, thereby conserving computational resources. Predicting user interactions also facilitates optimal resource allocation, focusing computational power on areas where the user prioritizes accuracy for critical decision-making.