Data Visualization
  • ISOM 675
  • ISOM 475/575

ISOM 675 · Data Visualization

Course information, schedule, and materials for ISOM 675 Data Visualization.

ISOM 675 · Data Visualization

Course
ISOM 675, Fall 2026
Instructor
Prasanna Parasurama
TA
Kevin Sheng
Class meetings
MoWe 11:30 AM–12:45 PM · GBS 201
Course home
This site + Canvas
Syllabus
View syllabus →

This course will introduce students to the techniques and tools used to create effective visualizations that clearly and efficiently communicate relationships within data. Students will learn how to perform exploratory analysis through visualization, how to create professional looking visualizations for use in business reports and presentations, and how to design interactive visualizations and dashboards that include time series, rankings, proportions, deviations, frequencies and distributions, correlations, categorical comparisons, and geospatial plots. Students will analyze real data sets and utilize Python, R, Tableau, and other tools to design and prototype their visualizations. This course is for MSBA students only.

Schedule

This is a living document for all course activities, and will be updated and modified as we go along.

Week Date Topic Notes
Week 1 Wed, Aug 26 00 · Class Intro
Week 2 Mon, Aug 31 01 · Fundamentals of Data Visualization Required readings: Few, Show Me the Numbers, Chapter 5 (Canvas)
Healy, Chapter 1: “Look at Data”
Wed, Sep 2 01 · Fundamentals of Data Visualization
Week 3 Mon, Sep 7 Labor Day — no class
Wed, Sep 9 01 · Fundamentals of Data Visualization
Week 4 Mon, Sep 14 02 · Python/Pandas/Altair Primer
Wed, Sep 16 03 · Tableau Primer
Week 5 Mon, Sep 21 04 · Exploratory Visual Analysis
Wed, Sep 23 04 · Exploratory Visual Analysis
Week 6 Mon, Sep 28 04 · Exploratory Visual Analysis
Wed, Sep 30 04 · Exploratory Visual Analysis
Week 7 Mon, Oct 5 04 · Exploratory Visual Analysis
Wed, Oct 7 05 · Visualization for Model Evaluation Python project due
Week 8 Mon, Oct 12 Fall break — no class
Wed, Oct 14 06 · Visualization for Communication
Week 9 Mon, Oct 19 06 · Visualization for Communication
Wed, Oct 21 06 · Visualization for Communication
Week 10 Mon, Oct 26 06 · Visualization for Communication
Wed, Oct 28 06 · Visualization for Communication
Week 11 Mon, Nov 2 Midterm exam
Wed, Nov 4 06 · Visualization for Communication
Week 12 Mon, Nov 9 06 · Visualization for Communication
Wed, Nov 11 06 · Visualization for Communication
Week 13 Mon, Nov 16 07 · Interaction and Dashboard Design
Wed, Nov 18 07 · Interaction and Dashboard Design
Week 14 Mon, Nov 23 07 · Interaction and Dashboard Design
Wed, Nov 25 Thanksgiving break — no class
Week 15 Mon, Nov 30 07 · Interaction and Dashboard Design
Wed, Dec 2 07 · Interaction and Dashboard Design
Week 16 Mon, Dec 7 Tableau project presentations
Wed, Dec 9 Review
Final Fri, Dec 11 Final exam · 11:30 AM–2:30 PM

Course materials

Module 00 · Class Intro
Lecture slides 1
  • Class Intro Introductions, course goals, tools, grading, assessment expectations, and AI-use policy.
Module 01 · Fundamentals of Data Visualization

Focus: definitions, viewer tasks, visual encoding, perception, Gestalt grouping, and misleading design.

Lecture slides 3
  • Lecture 01: What Is Data Visualization? Definitions, purposes, and viewer tasks.
  • Lecture 02: Perception and Cognition Visual channels, attention, grouping, and memory.
  • Lecture 03: Bad Practices Misleading scales, dimensions, and decoration.
In-class activity 1
  • Graphical Perception Lab Estimate values and compare the accuracy of different encodings.
Required readings 2
  • Stephen Few, Show Me the Numbers, Chapter 5. Available on Canvas.
  • Kieran Healy, Data Visualization: A Practical Introduction, Chapter 1: “Look at Data.”
Quiz 1
  • Module 01 quiz on perception, encoding, grouping, and misleading design. Complete it in Canvas.
Module 02 · Python/Pandas/Altair Primer
Module 03 · Tableau Primer
Module 04 · Exploratory Visual Analysis
Module 05 · Visualization for Model Evaluation
Module 06 · Visualization for Communication
Module 07 · Interaction and Dashboard Design