Differentiation encompasses a range of practices aimed to ensure that learning is accessible and meaningful for all students. While teachers value opportunities for all students to engage in cognitively demanding tasks, they encounter barriers in providing these opportunities equitably (Russo et al., 2021). Using assessment data narrowly can contribute to teachers’ fixed view of students’ abilities (Fitzgerald et al., 2021). As part of a larger study investigating teachers’ data usage beliefs and practices, and their influence on teaching and learning, semi-structured interviews were conducted with eight participants. In this study, data is defined as any information that can be utilised to promote students’ learning and well-being. Participants were from two government schools in Victoria, Australia, and included two teachers from grades 3 and 5, a numeracy leader and an assistant principal from each school. One of the themes that emerged from the analysis was how data informed teachers’ differentiation beliefs and practices. Participants reported using different types of data, with most referring to assessment data from a commercial platform involving multiple-choice tests. Consistent with previous studies, when teachers relied on this data, they employed homogeneous ability groups and focused on reteaching concepts, often through procedural tasks (Fitzgerald et al., 2021). In contrast, participants’ motivation to employ open-ended problem-solving tasks and heterogenous groups stemmed from other types of data, including formal and informal affective data. This presentation will discuss how various types of data shaped the differentiation practices of these participants.