Big Data Applications

Professor: Winkelman
Units: 1.0
Elective Course
Concentration: Quantitative Methods

This course will present a survey of Big Data tools and applications and will show how both techies and non-techies can easily use these technologies to facilitate analysis for complex policy challenges. The course will begin with an overview of major Big Data techniques as well as a review of existing projects and publications that demonstrate the potential impact that these techniques can have on policy research. The course will then introduce students to new open source and commercial tools for data analysis that mine the web, social media, and other ‘big’ data sets for policy relevant insights. After this initial exploration of tools, students will nominate other similar tools or techniques of interest for further exploration by the rest of the class.

In the second phase of the course, each student will identify an existing dataset (or one they could feasibly collect during the semester) and formulate a set of policy relevant questions that might be answered via exploration of the data with the previously identified tools. All ‘project’ ideas will be presented to the class, and students will be given the opportunity either to work individually, or to self organize into teams in order to execute projects. Project work might include direct use of any tools explored by the class, innovative combinations of those tools, or the creation of new tools by the students.

A third and final phase of the course will require project teams to devise strategies to effectively communicate the methods used and their results, for example, through dynamic and/or interactive visualizations. The course will culminate with a showcase in which teams will brief their projects to the broader Pardee RAND and RAND community. We expect the showcase to serve as an opportunity for students to lead RAND researchers in the discovery of how Big Data techniques can positively supplement other policy research methods.