With the growth of data science in industry, academic research, and government planning over the past decade, there is an increasing need to equip students with skills not only in responsibly analyzing data, but also in investigating the cultural contexts from which the values reported in data emerge. A risk of several existing models for teaching data ethics and critical data literacy is that students will come to see data critique as something that one does in a compliance capacity prior to performing data analysis or in an auditing capacity after data analysis rather than as an integral part of data practice. This article introduces how I integrate critical data reflection with data practice in my undergraduate course Data Sense and Exploration. I introduced a series of R Notebooks that walk students through a data analysis project while encouraging them, each step of the way, to record field notes on the history and context of their data inputs, the erasures and reductions of narrative that emerge as they clean and summarize the data, and the rhetoric of the visualizations they produce from the data. I refer to the project as an ''ethnography of a dataset'' not only because students examine the diverse cultural forces operating within and through the data, but also because students draw out these forces through immersive, consistent, hands-on engagement with the data.