Big qualitative data researchers have suggested modified descriptors of the features of big data. Such defining criteria include high volume of textual or visual data, highly complex data involving multiple points of triangulation, or complex data analyses that provide unusually deep insights. Big qualitative data can be distinguished in terms of whether the big data sets are created or found. Despite the speed of mathematical computation performed by big data analytics, current quantitative analytic methods are not able to capture the subtlety, creativity, and personality that real human beings demonstrate across social contexts. The development of research using big data sets with qualitative and mixed methods approaches has moved beyond rhetorical debates, with productive examples of methodologically thorough and theoretically substantiated practice emerging in different scholarly fields. Qualitative and mixed methods researchers can engage critically and creatively with emerging forms of big data that often require working in interdisciplinary ways to generate new social insights.