Educating young learners to reason with data is increasingly important given our data-saturated society; yet teachers need support in recognizing and facilitating apt epistemic performance (which involves the beliefs and practices necessary to successfully establish, critique, and use data and knowledge within a domain) regarding data literacy with elementary students. In this exploratory study, we aimed to understand (a) what apt epistemic processes within data literacy look like in practice with children, and (b) to what extent a curriculum built on a simulation-based data analysis intervention (where students engage in experimentation and data analyses through the use of simulations) promotes the epistemic processes of data literacy. We used the Apt-AIR framework, which expounds on the components needed for successful epistemic education, as a tool to identify students' apt epistemic processes. The results illustrate that elementary students were able to activate cognitive, emotional, and--to a lesser extent--metacognitive and collaborative epistemic processes related to data literacy skills in this context. Additionally, the design features embedded in the experimentation lesson were more successful in engaging students in apt epistemic processes; yet the data analysis lesson, while engaging students in fewer processes overall, was successful in promoting students' ability to make accurate inferences using an aggregate view of data. We discuss the trends in the apt epistemic processes related to data literacy that emerged and their implications for instruction and learning.