Mastery learning promises more equitable outcomes in large CS courses, yet instructors lack a full array of tools to support their implementation. Popular Learning Analytics Dashboards (LADs) and adaptive platforms excel at grade analytics but offer limited support for custom mastery policies. We present an open-source, instructor-focused dashboard integrated into a custom LMS to support mastery learning for high-enrollment CS courses. The system features a data pipeline that gathers scores from multiple sources and provides a view into the effectiveness of equitable grading policies, such as retakes, resubmissions, and flexible deadlines. The central interface, the Students view, provides a way to see the scores for a particular student across all assignments and exams. The system was deployed for two semesters in a large introductory CS course, where instructors reported ease of use, increased visibility into class performance, and effective support for mastery-learning policies. Based on this feedback, we are extending the platform with a Statistics view that surfaces assignment–and concept-level statistical summaries and interactive histograms to further support scalable mastery learning. To support broader adoption, we plan to release the system as an open-source platform to assist instructors and institutions seeking to implement mastery learning at scale.