If you visit a district central office or a state department of education or a principal’s office these days, you will hear the current rhetoric about data use for school improvement. Since the passage of No Child Left Behind, data on school performance, disaggregated by racial/ethnic groups, special education and language status, and gender, are widely available, open to public consumption, and intended to lead to improvement. The disaggregation of these performance data is significant: pushing schools, school practitioners, and education policy makers to understand the performance of all students and not the average performance of students at any given school. Yet the ubiquitous nature of data now available in the public domain runs the risk of every other education fad that has preceded it: significant rhetoric that yields false promises about improving schools and the life chances of young people. Data-driven decision making. Performance management metrics. School indicator and warning systems. School climate measures. Formative assessments. Summative assessments. Administrative data. Graduation rates. Attendance patterns. Dropout metrics. Test scores. Value-added assessments. High-stakes evidence-driven reform. The implicit and explicit assumption is that if these data exist, improvement will soon be evident. It reminds me of the old quip about the American who goes to France and speaks English louder. Here are the data. . . . Improve. The articles in this issue call for a deeper and better understanding of data, their use, the conditions that are most conducive for using data well, how individuals and groups of practitioners make sense of the data before them, and the intended and unintended consequences of data use for school improvement. The authors together craft important messages about what type of research must be done to address these concerns. But perhaps even more important, the authors offer a clarion call to education policy makers and