With the advent of No Child Left Behind (NCLB) legislation in 2002 and its attendant increases in accountability pressure, many districts and schools currently embrace data analysis as an essential part of the instructional decision making process. In their attempts to overcome low achievement on state-mandated tests, some districts have begun employing data coaches. The study reported here, which was set in three middle schools in a northeast Texas school district, assessed the influence of the campus data coach on a middle school mathematics teachers' use of analyzed data to make instructional decisions. It also examined the extent to which the Data Coach/teacher relationship resolved teacher concerns about data-driven decision making. Phenomenological interviews with data coaches were guided by Seidman's (2006) three-series interview. Measurement of teacher use of data to make decisions was based on the concerns-based adoption model's levels of use interview protocol, stages of concern questionnaire, and innovation configuration map. By the end of one school year, two out of the three teachers never used data to make instructional decisions, although the non-users both had moved closer toward employing the innovation in their classroom. Data indicated all teachers were aware of the innovation, but all three ended the study with high personal concerns, signifying that the minimal efforts made by the data coaches to resolve concerns were not successful. This study's small sample gave the research paradigm of data-based decision making an in-depth glimpse into the process of implementing data-based instructional decision making and the Data Coach position on three middle school campuses in one large northeast Texas district.