Hate reading?! Watch this lil pitch video instead.
TL;DR:
- Data analysis is neat, but isn't enough
- Learn how to turn outputs of data analysis into compelling visualizations
- Tools will be Excel, Tableau, and Python/R (your choice)
- No programming background required, but you may have to work a bit harder and review tutorials outside of class
- Data analysis experience (e.g. BUS 32100/32120) is recommended, but there are no strict prereqs
- Grade will be mostly a group project (presentation in-person during finals aka week 10)
The world has become obsessed with data, and for good reason. Effective data analysis can give you valuable insights and lead to improved business and policy decisions. You can, and should, study data analysis (and there’s many courses for you to choose from right here at Booth!). But data analysis shouldn’t end with the analysis. In this course, we’ll learn how to take the tables of numbers that are often seen as the output of data analysis and transform them into tools of decision-making and communication. We’ll learn how to extract stories from our data and to use those visualizations to aid decision-making and persuasion.
Our tools will be Excel, Tableau, and Python/R. We’ll use GenAI tools like ChatGPT to explore our creativity. Beyond making one-off scatter plots and histograms, we’ll learn what it means to tell a story through data. We’ll also learn how to identify our target audience, peer into their eyes and brain to see how they process information, and how to use this insight to craft persuasive and compelling visual artifacts.
Think of this course as a blend of statistics, psychology, neurobiology, graphic design, and communication.
Data visualization is about more than picking pretty colors for your charts (though that’s also important!), but it’s about finding visual ways to represent information coded in your data that wouldn’t be intelligible to your audience otherwise.
Consider the table of per capita incomes in the syllabus. Scrolling through dozens of rows of data can never give you the information that a map can code about the spatial distribution of incomes in a city. Adding spatial and/or temporal elements to your data, through the use of maps and dynamic dashboards in Tableau, can be the difference between data that sits on the page and data that moves your audience to action.
How are customers reacting to your ad spend, and can you make changes to your allocations more quickly to take advantage of fluctuating trends in real time? What’s driving customer churn, and what interventions are working right now? Is your bank being targeted by bad actors in a coordinated fraud scheme? How is your portfolio performing in real-time in relation to your risk metrics? Are your manufacturing processes on track, or are cost overruns and production delays imminent? Data visualization can improve your answers to all of these questions.
