In pursuit of more nuanced answers about ourselves and each other, we must shift from metrics and models to interpretation and applications of genomic analyses, both in scientific and medical contexts, and in broader culture and politics. Accordingly, this chapter presents six general empirical patterns of human genomic variation. The patterns emerge from many data points, layered through measures and metrics such as heterozygosity and Euclidean genetic distance, statistical modeling machinery, such as variance partitioning protocols and Bayesian clustering algorithms, and theoretical concepts, such as population and genetic variation. Because the six patterns form an indelible, complex mix of genomic data, statistical methods, and evolutionary genetic theory, I call them neither facts nor data, nor empirical results nor states of affairs. They are also neither models nor methodologies. They are much too complex and unique for such simple and straightforward denominations.