"Big Data" refers to the enormous amount of quantitative, statistical, personal and other unstructured data being generated by people, companies, processes, and even objects. Data analytics can crunch the data in novel ways to uncover patterns and offer fresh insights for making better business decisions. This has critical implications for the media industry. New types of audience data, including social, mobile, and real-time data, are being created, and that is altering the kinds of tools, software, and strategies needed for measuring and making sense of it all. While Big Data can be a potential boon to researchers, there are cautions. First, how does one separate correlation from causation; pinpoint what truly matters; and take meaningful action? We may also face a temptation to rely on quantitative data and processes when it is not the most useful tool. There are also ethical dimensions in the use of socially generated big data, including scraping of online conversations and assumptions made about customers' preferences and behaviors. This course will explore the potential of data and analytics for media marketers and researchers, both through a popular cultural lens (for example, via Nate Silver's popular book The Signal and the Noise), as well as by focusing on how new types of data streams are changing media market research, including new ethical concerns . We'll also look at the ability to make predictions from the data ("predictive analytics") and how that is already changing the industry.