Ethnography is traditionally a qualitative and inductive methodology – with its origins in cultural anthropology – that is now widely used to holistically investigate people’s lived experiences in and across cultures. In this talk, I define and discuss two ways of thinking about the role of ethnographic methods around computation, then discuss how my research relates to both. The ethnography of computation involves using traditional ethnographic methods (including interviews, observation, participant-observation, case studies, archival research, and surveys) to study how people relate to computation in various ways. For example, this approach investigates issues around how people design, develop, deploy, document, debate, maintain, manage, use, not use, learn, or teach computation in their everyday life and work. Computational ethnography involves extending ethnography’s traditionally-qualitative methodological toolkit with computational methods, conducting mixed-method scholarship in line with the broader principles that make ethnography a rich method for holistically investigating cultural phenomena. Both approaches bring new insights to our understanding of various issues in and around data science, and I discuss projects of both types relating to issues including career paths, managing open source software projects, and open science and reproducibility.