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	Due
Week 1	Wed, Aug 26	00 · Class Intro
Week 2	Mon, Aug 31	01 · Fundamentals of Data Visualization	Few, Show Me the Numbers, Chapter 5 (Canvas) Healy, Chapter 1: “Look at Data”
	Wed, Sep 2	01 · Fundamentals of Data Visualization	Few, Show Me the Numbers, Chapter 6 (Canvas)
Week 3	Mon, Sep 7	Labor Day — no class
	Wed, Sep 9	01 · Fundamentals of Data Visualization
Week 4	Mon, Sep 14	01 · Fundamentals of Data Visualization	Few, Show Me the Numbers, Chapter 2 (Canvas)
	Wed, Sep 16	01 · Fundamentals of Data Visualization	Introduction to Altair Data Types, Graphical Marks, and Visual Encoding Channels
Week 5	Mon, Sep 21	02 · Python/Pandas/Altair Primer Module 1 Quiz (in class)
	Wed, Sep 23	02 · Python/Pandas/Altair Primer	Data Transformation Scales, Axes, and Legends
Week 6	Mon, Sep 28	02 · Python/Pandas/Altair Primer	Multi-View Composition tutorial Altair Assignment 1 due
	Wed, Sep 30	03 · Exploratory Visual Analysis
Week 7	Mon, Oct 5	03 · Exploratory Visual Analysis	Altair Assignment 2 due
	Wed, Oct 7	03 · Exploratory Visual Analysis
Week 8	Mon, Oct 12	Fall break — no class
	Wed, Oct 14	03 · Exploratory Visual Analysis
Week 9	Mon, Oct 19	Coding with AI Agents Module 2/3 Quiz (in class)	Altair Viz Project due
	Wed, Oct 21	Coding with AI Agents
Week 10	Mon, Oct 26	04 · Tableau Primer	Tableau Primer Tutorials
	Wed, Oct 28	05 · Quantitative Messages	Quantitative Messages 1
Week 11	Mon, Nov 2	05 · Quantitative Messages	Quantitative Messages 2
	Wed, Nov 4	05 · Quantitative Messages	Quantitative Messages 3
Week 12	Mon, Nov 9	05 · Quantitative Messages
	Wed, Nov 11	Midterm exam
Week 13	Mon, Nov 16	06 · Interaction and Dashboard Design
	Wed, Nov 18	06 · Interaction and Dashboard Design
Week 14	Mon, Nov 23	06 · Interaction and Dashboard Design
	Wed, Nov 25	Thanksgiving break — no class
Week 15	Mon, Nov 30	06 · Interaction and Dashboard Design
	Wed, Dec 2	06 · 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 2

• Graphical Perception Lab Estimate values and compare the accuracy of different encodings.
• Fix the Chart Diagnose and redesign misleading charts. Answer key slides.

Required readings 4

• Stephen Few, Show Me the Numbers, Chapter 5 (Canvas).
• Stephen Few, Show Me the Numbers, Chapter 6 (Canvas).
• Kieran Healy, Data Visualization: A Practical Introduction, Chapter 1: “Look at Data.”
• Stephen Few, Show Me the Numbers, Chapter 2 (Canvas).

Quiz 1

• Module 01 quiz on perception, encoding, grouping, and misleading design. Complete it in Canvas.

Module 02 · Python/Pandas/Altair Primer

Lecture slides 1

• Lecture 04: Introduction to Altair Marks, encoding channels, data types, chart composition, and customization.

Tutorials 5

• Pandas/Altair Primer (Jupyter notebook)
  Dataset for the notebook: Netflix titles workbook (.xlsx). Save it as datasets/netflix_titles.xlsx relative to the notebook.
• Introduction to Altair
• Data Types, Graphical Marks, and Visual Encoding Channels
• Data Transformation
• Scales, Axes, and Legends

Module 03 · Exploratory Visual Analysis

Lecture slides 1

• Lecture 05: Exploratory Visual Analysis Distributions, summary statistics, relationships, and comparisons across groups.

Datasets 1

• ATS dataset

Assignments 1

• Altair Assignment 2: ATS Job–Resume Fit Due Monday, October 5 at 11:30 a.m.

Module 04 · Tableau Primer

Module 05 · Quantitative Messages

Lecture slides 2

• Lecture 06: Quantitative Messages Nominal comparisons, time series, rankings, part-to-whole relationships, deviations, maps, and flows.
• Lecture 07: Tableau Calculations Row-level and aggregate calculations, level of detail expressions, and table calculations.

Module 06 · Interaction and Dashboard Design