In the modern landscape of big-data, it has become increasingly important to synthesize and analyze data from unconventional sources. Topological Data Analysis has become a promising tool to uncover geometric and topological features from complex, high-dimensional data with rigorous, theoretical underpinnings. In this talk, we aim to provide an introduction to the Topological Data Analysis framework, and explore connections to statistical methodology.