As data become more available and integrated into daily life, there has been growing interest in developing data science curricula for youth in conjunction with scientific practices and classroom technologies. However, the "what" and "how" of data science in pre-collegiate education have not yet reached consensus. This paper analyzes two prominent self-identified data science curricula, "Introduction to Data Science" (Gould et al. 2018) and "Bootstrap: Data Science" (Krishnamurthi et al. 2020), in order to ascertain what is thus far being presented to schools as data science. We highlight overlapping content and practices by the curricula while noting some key differences between the curricula and with professional practice. Moreover, we examine how lessons are structured and what kinds of data sets are used as well as introduce a measure of data set proximity. We conclude with some recommended areas for further coverage or elaboration in future iterations and future curricular efforts.