In previous research we developed State Change, the theoretical basis for morphology of movement patterns in the context of design composition. State is used as an alternate word for type. Its adoption makes explicit that movement patterns are snapshots of form in motion which can be distinguished by a characteristic spatial form or shape, and secondly in terms of temporal behaviour or dynamic. Kinetic shape and dynamic enable the identification of three states – wave, fold, field – and the transitions between these – stratifying, swelling, atomizing, ribboning, aggregation, interweaving. Recently discourse in the field of Big data has proposed that the next generation of AR and VR technology have much potential for developing alternate forms of visual analytics. We pose the question – can the state change model be adapted to provide a framework for analytics when Big Data is represented as patterns of movement in virtual reality?