Cells of the immune system are exceptionally diverse. As a consequence, immunological processes such as the formation of an immune response may depend on the fates of individual cells. Experimental and theoretical studies have traditionally been restricted to study events at the population level. The advent of novel experimental techniques like single cell imaging, cellular barcoding, microfluidics, and deep sequencing now allows immunologists to directly investigate single-cell events. Results obtained in these studies suggest that migration, activation, differentiation, and proliferation of immune cells are highly stochastic.In large high-dimensional datasets, it is notoriously challenging to distinguish stochastic fluctuations from biological meaningful features. Advanced data analysis techniques and mathematical modelling are thus emerging as key tools for this field.