Class Intro

ISOM 475/575 · Data Visualization

Prasanna Parasurama

About me

• Assistant Professor, Information Systems and Operations Management
• Research focus: AI, labor markets, and online platforms
• Fourth year at Emory
  • Before Emory: UMich (undergrad), San Francisco (industry), NYU (PhD)

About you

• Name
• Relevant background
  • Education
  • Industry experience
• Why are you taking this course?

About this course—what you will learn

• Fundamentals and principles of data visualization
• How to read, interpret, and evaluate data visualizations
• How to create good data visualizations
  • For exploratory data analysis
  • To effectively communicate data stories to others

Tech stack

• Tableau (Desktop version); I’ll give you the activation key in a few days.
• Exposure to other tools:
  • Python / Altair
  • R / ggplot2
  • Power BI
• Codex for agentic coding (4 months free for students).
• No prior coding experience is necessary.

Course site and Canvas

• Course site
  • Lectures and course materials
• Canvas
  • Quizzes
  • Assignments
  • Grades
  • Announcements

Course components

Component	Type	Weight
Attendance and participation	Individual	5%
Canvas quizzes	Individual	20%
Exercises and assignments	Individual	15%
Midterm exam	Individual	25%
Viz critique	Group	10%
Final viz project	Group	25%

Attendance and participation

• Attendance is mandatory; there will be a sign-in sheet.
• You can miss up to one class without penalty.
• Participate in class discussions and exercises.

Quizzes

• In-class quiz after each module
• 10 questions
• 15 minutes
• Closed book
• LockDown Browser

Required readings

• Readings will be available on the course site or Canvas.
• Questions from the readings may appear on quizzes.

Exercises and assignments

• Individual work applying course concepts and tools
• Instructions and submissions on Canvas
• More information later

Midterm exam

• October 19
• Conceptual and application-based questions
• Multiple choice
• Closed book
• More information later

Viz critique

• Group project
• Evaluate an existing visualization
• Present a clear, evidence-based critique
• In-class presentations: November 2
• More information later

Final viz project

• Group project
• Apply the course’s analytical and design principles
• Final project presentations: December 7
• More information later

Policy on AI use

• AI is powerful, and its capabilities are improving rapidly.
• It can enhance learning or replace learning.
• My goal is to teach you how to use AI tools without replacing your learning.
• Assignments and projects: AI use is allowed.
• Quizzes and exams: AI use is prohibited.
  • These are closed-book assessments.
  • They account for 45% of your grade.

A cautionary tale on AI and learning

Source: Strömberg, Lei, and Wu (2026); visualization from The Economist, August 18, 2026.