Much of the groundwork in spatial statistics is concerned with the description and exploration of spatial datasets. The generic term for such methods is exploratory data analysis (EDA), or in the context of spatial and spatio-temporal analysis, ESDA and ESTDA respectively. Such methods are by no means exclusively statistical in nature, and for ESDA special forms of data mapping are of considerable importance. In the past EDA or data mining tools have not offered ‘spatial’ visualization, although there are tools now available, such as those providing ‘network’ spatialization and visualization (e.g. Gephi), and neural network mapping (SOM Toolbox). The Datascape immersive 3D visualization software, which is linked to spatial mapping facilities, provides a further and highly novel way of exploring large spatio-temporal datasets. Readers are also recommended to refer to the Afterword on "Big Data and GIS" and the associated presentation resource: http://www.spatialanalysisonline.com/PPTS/BigData.pdf as this is becoming of increasing importance in any consideration of approaches to spatial data analysis.