Process exploration is a critical task in process mining, enabling analysts to uncover insights and generate hypotheses about process behavior from event log data. Traditional approaches often rely onstatic, single-facet (control-flow) visualizations, such as Directly-Follows Graphs, that limit flexibility and obscure multi-perspective dependencies. In this paper, we introduce a novel visual analytics approach that leverages coordinated projections to support multi-faceted process exploration. Through dimensionality reduction (e.g., UMAP, t-SNE) and topic modeling, our method generates coordinated views that dynamically link different facets of process data, enabling cross-perspective exploration. Interaction techniques, such as brushing-and-linking and glyph-based representations, could further enhance the analyst’s ability to correlate patterns across dimensions. We demonstrate the effectiveness of our approach using a real-world traffic fines event log.