Data is increasingly shaping the way people interact with each other and the world more broadly. For youth growing up in an increasingly data-driven society, it is critical they have foundational data literacy skills. A central component of data literacy is the ability to collect, analyze, visualize, and make meaning from data. All of these activities are mediated and shaped by the tools that youth use to carry out these data practices. Given the essential role tools play in enabling and supporting youth in engaging with and interpreting data, understanding what tools are used and how they are used in educational contexts will help us understand how youth are being prepared to be data-literate citizens. In this paper, we present the analysis of the data collection and analysis tools used in 4 widely adopted high school data science curricula. The analysis attends to both what tools are used as well as what datasets they are used to analyze. This work contributes to our understanding of the way youth are being introduced to concepts and practices from the field of data science and the role the tools play in shaping those experiences.