Data Visualization:Art/Science

1.5 Credits · Level: Graduate, Undergraduate

According to Google Trends, interest in data visualization has quadrupled in the past decade, due in part to a growing abundance of user-friendly tools to make sense of and visualize quantitative and qualitative data. How can we navigate this increasingly congested space to use the right tool for different purposes? What visuals are best for which types of data? What skills do we need to turn raw data into actionable insights? This course equips students with the resources they need to perform meaningful and even beautiful data visualization in business policy, research, or even personal environments—including skills like defining problems, selecting data, and communicating about data visuals. It includes an introduction to theories of leading information designers, practical strategies and techniques, an overview of data viz platforms, hands-on exercises to build concrete familiarity with some specific tools, and examples of data viz applied in the field of international relations and development. This course will be taught over two weekends through immersive and stimulating workshops designed to facilitate project-based learning. Students will develop a specific project driven by data visuals, such as a presentation or blog post, and present not only about their final output but also about the decisions they went through as information designers to develop that final product. Students will gain experience with specific free online tools that they can immediately apply to their school and work, likely including Google Data Studio, PowerBI, Infogram, Flourish, and Kumu. Students should have some familiarity with data preparation and cleaning tools like Excel. Programming tools like R or Python will not be covered.