Vastly increasing rates of data collection in the field of crystallography are resulting in processing challenges, but also unlock new scientific opportunities. The ability to collect many data sets quickly means that dynamics can be explored through triggering events (such as a laser pulse, or addition of a substrate), or by collecting many datasets of the same system to investigate flexibility. However, these experiments also require fast, automatic processing software to churn through the raw data, lest critical discoveries be lost in the “I don’t have time” pile. The VMXi Beamline (Mikolajek et al., 2023) at Diamond Light Source is a room temperature, in-situ, high-throughput beamline that takes advantage of multi-crystal data collections to probe macromolecular crystals. This talk will explore some of the ways VMXi are tackling the challenges of “Big Data”, both through high-throughput experimental capabilities, and the development of software pipelines. Rapid screening of samples for serial crystallography will be demonstrated (Thompson et al., 2024), as well as current developments in identifying subtle differences within groups of rotation datasets using modern clustering methods in xia2.multiplex (Gildea et al., 2022).