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In our increasingly digitized world, data plays a crucial and persuasive role in decision-making. While data is often perceived as objective, data collection and dissemination processes are inherently biased and have powerful influences over individuals' lives. The data feminism framework offers a lens to recognize power imbalances, advocating for intersectional feminist perspectives and challenging the neutrality of data. This framework has significantly impacted research on data visualizations and creating a pedagogy for social justice within statistics and data science education. By integrating critiques on data feminism from transnational feminism, this work aims to consider where data feminism is currently being used in statistics and data science education and examine possible paths forward in the field.