Topological Data Analysis: Topological Data Analysis is the application of algebraic topology to data science. Noisy data in the form of a geometric point-cloud can be interrogated with topological tools to extract qualitative features. Because of the inherent invariance of algebraic topological quantifiers, the features obtained are true to the intrinsic nature of the data, independent of uncertainty in measurement. Such topological invariants come in a cascade of dimensional variants, reflecting increasing dimensions of connectivity within the data. This illustration uses color, luminance, and reflection to capture the subtle properties of simplicial approximations to a data set.