Andrew Gelman and Aki Vehtari identify the eight most important statistical ideas from the past 50 years of research: counterfactual causal inference, bootstrapping and simulation-based inference, overparameterized models and regularization, multilevel models, generic computation algorithms, adaptive decision analysis, robust inference, and exploratory data analysis. They argue that these ideas, many of which exploit Big Data and advances in computing, enabled new ways of approaching statistics and analyzing data. In their discussion, they provide a summary of each idea, overview of research contributions from various fields, and observations about the interrelation of the ideas to each other and to other new developments. They conclude with some predictions about what research threads might be the most influential ideas of the coming decades.