Data exploration, like the larger notion of visualization, is most frequently a private activity in which unknowns are revealed in a highly interactive environment. The first two sections of this chapter consider the goals and methods of data exploration. Broad goals include: (1) identifying the spatial pattern associated with a single attribute at one point in time (2) comparing spatial patterns for two or more attributes at one point in time; (3) identifying how spatial patterns for a single attribute change over time, and (4) comparing spatial patterns for two or more attributes to see how they covary over time. In a sense, these same goals apply to static paper maps but the interactive environment of data exploration software permits us to discover spatial patterns that might not be seen in a single static map.