Data-driven decision making is the process of using data to inform decisions to improve teaching and learning. Schools typically engage in two kinds of data-driven decision making--at the school level and at the classroom level. The first leads to the second. In this article, the author describes how Marylin Avenue Elementary School successfully employed data-driven decision making to improve student achievement. She suggests that for schools to see student achievement increases in every subject, at every grade level, and with every student group, educators must look at big-picture data. They must understand what is being implemented to know what needs to change. It is not enough for educators to focus on just one thing they think can change; they must look at all the data. Armed with a big-picture view, schools have the ability to improve all of their processes--and students will be the ultimate beneficiaries.