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Everything is data. And as large-scale aggregation and computational analysis of data become more common and manageable, it becomes more important to rhetoric and composition. It is increasingly possible to examine thousands of documents and peer-review comments, labor-hours, and citation networks in composition courses and beyond. Composition and Big Data brings together a range of scholars, teachers, and administrators working with big-data methods and datasets to kickstart a collective reckoning with the role that algorithmic and computational approaches can, or should, play in research and teaching in the field. From ethical reflections to database design, from corpus linguistics to quantitative autoethnography, these chapters interpret and implement the drive toward data in diverse ways. Their work takes place in various contexts, including programmatic assessment, first-year pedagogy, stylistics, and learning transfer across the curriculum.