SQL is not just for managing and manipulating databases, but also extends to spatial data analytics and visualization. It allows for the creation of 5 types of spatial data visualizations: thematic maps, dasymetric maps, dot density maps, spider maps, and great circles. These visualizations can help combat area bias in maps, provide a more representative view of data distribution, and enable modeling of individual data points. SQL's query-based nature allows for the creation of temporary subsets of datasets, eliminating the need to generate new files every time changes are made. Spatial indexes like H3 and Quadbin can be used to create regular grids, reducing bias and simplifying interpretation. Various SQL functions, such as ST_INTERSECTION, ST_ISEMPTY, ST_GENERATEPOINTS, ST_MAKELINE, and ST_GREATCIRCLE, enable the creation of these visualizations. These capabilities make SQL a powerful tool for spatial data analysis and visualization, allowing users to easily create next-level data visualizations.