The "Next-Generation Science Standards" emphasize the importance of teaching the practices of science alongside content ideas and crosscutting concepts (NGSS Lead States 2013). Chief among these practices is the ability to gather, assess, analyze, and interpret data. Authentic inquiry near the leading-edge of science offers a wonderful opportunity for students to have ownership of their data sets and to personalize the learning experience. While many teachers welcome authentic inquiry in their classrooms, they know that real-world data are often messy, in contrast to the picture-perfect graphs and data typical of a textbook illustration. Do messy data confuse students and obscure the point of a lesson? That was the authors' initial concern when they developed the Laboratory for the Study of Exoplanets (ExoLab), an online astronomical laboratory designed to increase students' data literacy, while engaging them in the search for habitable worlds and life beyond Earth (Gould et al. 2012). What they found was that messy data help students think more deeply about data. The authors discuss several reasons that they came to this conclusion including: (1) Messy data invite students to become data detectives; (2) Messy data show students the need for an interpretive model; (3) Messy data invite students to focus on results rather than answers; and (4) Messy data can help keep us honest.