Since industry 4.0 was introduced in 2013, industries across the globe have been rushing towards the era of intelligent manufacturing. The advances in data sensing technologies have further helped the collection of massive industrial data, providing an excellent opportunity for innovations in industrial informatization. However, it remains a major challenge to analyze industrial data because of its large scale,
high dimensionality, heterogeneity and complexity. Constantly changing application scenarios also lead to strict requirements in the flexibility of analyses, which demand placing domain experts in the analysis loop. Therefore, visualization has been widely applied to analyzing industrial data. This review article first summarizes the data types commonly used in the industrial scenarios based on the production stages and properties. Then, based on the data properties, this paper introduces visualization methods for the temporal, spatial and spatio-temporal types. Further, this paper overviews the applications of visual analytics in the industrial scenarios and discusses the integration of automated analysis methods in the visual analytics systems. Finally, this paper prospects the development of industrial data visual analytics and possible research directions for the future.