The demand for college graduates with skills in big data analysis is on the rise. Employers in all industry sectors have found significant value in analyzing both separate and combined data streams. However, news reports continue to script headlines drawing attention to data improprieties, privacy breaches and identity theft. While data privacy is addressed in existing information system (IS) programs, greater emphasis on the significance of these privacy issues is required as big data technology advances. In response to this demand, some colleges and universities are developing big data programs and degrees (Gupta, Goul & Dinter, 2015). Yet not every university has the resources to allow for such expansion; some institutions struggle just to cover their IS core program courses. For these latter programs, awareness of the importance of privacy and privacy methods--like the application of security controls--is best integrated academically through a layered approach. Therefore, in this paper, the authors illustrate the important role that data privacy plays in the realm of big data, and suggest methods for providing a layered approach to applying big data privacy concepts to the IS2010 Model Core Curriculum.