CS 109, “Data Science for Social Good,” exemplifies cross-disciplinary education, preparing students for a data-centric world where technology and social consciousness unite. The course is co-taught by a Software Development (programming) instructor, and a Social Science (Geography) instructor. This introductory course empowers students to harness the power of data for addressing societal issues. Participants learn data collection, computation, analysis, and visualization techniques while exploring themes of equity and socioeconomic inequality. Through data-driven advocacy, students emerge as catalysts for social change and justice. No prior experience is necessary. Our lightning talk will delve into how CS 109 breaks traditional disciplinary boundaries to achieve the following learning outcomes: • Create Computational Artifacts: Students develop practical computing skills to tackle real-world problems. • Collaborative Learning: Collaboration is at the core of our course, fostering teamwork in both programming and problem solving. • Abstract Thinking: Students master abstraction principles while writing programs or creating computational artifacts. • Data-Driven Insight: We empower students to discern patterns, test hypotheses, and gain insights into equity and socioeconomic inequities. • Advocacy Through Visualization: Students effectively communicate insights using visualization, notations, and precise language, championing social change. • Descriptive Statistics: Our curriculum equips students to summarize data, uncover patterns, and address pressing social issues. • Data Management: Students learn to clean, summarize, and visualize data related to social concerns.