Data analysis in mass cytometry involves processing and interpreting complex datasets generated from single-cell measurements, allowing for the identification of cellular heterogeneity and functional states in biological samples. This requires sophisticated computational tools and algorithms to manage high-dimensional data and extract meaningful insights from millions of cells analyzed simultaneously.