This talk will focus on my recent work in the utilization of space filling curves for the exploration of all possible projections of a multivariate data set. I will describe several new approaches employing a number of different hyperspace filling curves. I will discuss approaches using Peano curves, Hilbert curves, and curves obtained using the method of Steinhaus based on stochastically independent functions. The talk will include the discussion of large amounts of incomprehensible mathematics in conjunction with a healthy dose of stunning visual imagery and animations. It is the speaker's intent to leave the audience dazed but happy. Time and speaker's mood permitting there may even be results presented which relate this work to the original grand tour work of Daniel Asimov and which indicate the utility of the approach within a discriminant analysis framework.