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Introduction to Data Visualization Using Tableau Desktop In-Person
Data visualization gives us a better understanding of our data and helps us communicate that to others. It has the potential to generate insights, communicate findings, and illustrate evidence. Conversely, a poor visualization can undermine an argument or even mislead the reader.
Through a combination of lecture and demonstrations, this 1.5-hour workshop will introduce you to data visualization using a common data visualization tool, Tableau Desktop. Participants will create visualizations such as a bar graphs, line graphs, and scatter plots.
This workshop is designed for those new to data visualization and Tableau Desktop. There are no prerequisites or assumptions of knowledge of math, statistics, or programming.
In-Person Location: Robarts Library, 5th Floor, Room 5-053 (directly across from the elevator). Map & Data Library Computer Lab
Map & Data Library workshops, such as this one, are a welcoming and inclusive environment for learning. To learn more, check out our Code of Conduct.
This is a short, introductory workshop. If you would like to learn more on these topics, you are encouraged to self-enroll in our longer, online, self-paced workshops:
- Data Visualization - An Introduction (Part 1 – Theory and Critique)
- Data Visualization - An Introduction (Part 2 – Practice with Tableau)
For more information on Data Visualization and services offered by the libraries, see our Data Visualization Guide.
Photo modified from the original photo by Carlos Muza on Unsplash
- Date:
- Tuesday, March 21, 2023
- Time:
- 2:00pm - 3:30pm
- Time Zone:
- Eastern Time - US & Canada (change)
- Location:
- Map & Data Library
- Campus:
- St. George (Downtown) Campus
- Categories:
- Data & Statistics Digital Tools Programming & Software
Event Organizer
Kelly Schultz (she/her) is a Data Librarian at the Map & Data Library. She has a BASc (Computer Engineering) and a MI, both from UofT.
She supports Data Visualization; Qualitative Data Analysis; Data Cleaning; Text and Data Mining; Network Visualization and Analysis; Finding Data.