  We consider concepts centered around modal analysis, data science, network
science, and machine learning to reveal the essential dynamics from
high-dimensional fluid flow data and operators. The presentation of the
material herein is example-based and follows the author's keynote talk at the
32nd Computational Fluid Dynamics Symposium (Japan Society of Fluid Mechanics,
Tokyo, December 11-13, 2018). This talk was delivered as a compilation of some
of the research activities undertaken by the author's research group.
