Despite a decade of advocacy and advances in technology, data driven decision making remains an elusive vision for most high schools. This article identifies key data systems design needs and presents methods for monitoring, managing, and improving programs. Because of its continuing salience, we focus on the issue of tracking (ability grouping). We provide specific examples of useful analyses for measuring the conditions and consequences of tracking. We also discuss how to make transcript data useful for analyzing inter-track mobility, for monitoring course placement decisions, and for drilling down to plan interventions for subsets of students.