Control charts are one of the principal tools to monitor dynamic processes with the aim of rapid identification of changes in the behaviour of these processes. Such changes are usually associated with a move from an in-control condition to an out-of-control condition. The paper briefly reviews the historical origins and includes examples of recent developments, focussing on their use in fields different from the industrial applications in which they were initially derived and often employed. It also focusses on cases which depart from the commonly used Gaussian assumption and then considers potential effects of the big data revolution on future uses. A bibliometric analysis is also presented to identify distinct groups of research themes, including emerging and underdeveloped areas, which are hence potential topics for future research.