Text analytics refers to the process of analyzing unstructured data from documented sources, including open-ended surveys, blogs, and other types of web dialog. Text analytics has enveloped the concept of text mining, an analysis approach influenced heavily from data mining. While text mining has been covered extensively in various computer science curriculums, text mining or text analytics has appeared only briefly in information systems curriculums from business schools, generally within the context of data mining or other quantitatively-oriented analysis techniques. With the emergence of text analytic commercial technology products and the business opportunities afforded to organizations, a full course addressing text analytics is an opportunity for business schools to support industry and innovate offerings within their curricula. This paper provides an experience report as an Innovation in Practice on the introduction of Text Analytics into the graduate curriculum of a business school in the United States. This experience introduces text analytics as a full semester, business school course. Its orientation is distinctly different from Computer Science where the focus is solely technical; here, the emphasis is analysis, its validity, and the use of technology. The course was introduced in the spring of 2010 as a graduate level course to a controlled registration of seven MSIS and MBA students. Highly positive student feedback supports the success of the course in terms of structure, objectives, interest, and applicability to immediate student interest and toward perceived future career opportunities. In order to instill practical as well as conceptual knowledge, the course incorporates both traditional and constructivist learning techniques to enhance learning objectives. The Introduction section relates to the emerging interest of text analysis and brief assessment of the overall market. Included is a brief discussion of the growth of the technology and how it deviates from data mining. Teaching objectives are discussed in the second section and details of the class activities can be found in the third section. It is not in the scope of this paper to provide a tutorial on how to conduct text analytics research, but to demonstrate how the course can be managed as a semester-long course. A number of formal feedback sessions were conducted with the students and these results are reported in the fourth section. Lessons learned and Limitations are discussed in the fifth and sixth sections. (Contains 7 tables and 6 figures.)