FA550 Data Visualization Applications



Course Catalog Description

Introduction

Effective visualization of complex data allows for useful insights, more effective communication, and making decisions. This course investigates methods for visualizing financial datasets from a variety of perspectives in order to best identify the right tool for a given task. Students will use a number of tools to refine their data and create visualizations, including: R and associated visualization libraries, Ruby on Rails visualization tools, ManyEyes, HTML5 & CSS 3, D3.js and related javascript libraries, Google Chart Tools, Google Refine, and image-editing programs.

Campus Fall Spring Summer
On Campus X X
Web Campus X X

Instructors

Professor Email Office
Brian Moriarty brian.moriarty@stevens.edu Babbio 629

More Information

Course Outcome

  • Use AI tools to generate, critique and refine data visualizations, and judge where a given tool is likely to be wrong from evidence the student gathered rather than from the tool's reputation.
  • Select visualization types and apply visual encoding principles to produce accurate and accessible presentations, and defend each choice against the alternative that was rejected.
  • Design and implement interactive dashboards whose coordination supports a named reader answering a named question.
  • Profile, clean and transform data into analysis-ready form, documented so that another person can reproduce the result from the committed artifacts.
  • Construct data narratives with a claim specific enough to be wrong, supported by the evidence shown, and adapted to a named audience.
  • Account for AI use in their own work: mark every consequential interaction Accept, Modify or Reject with reasoning specific to the data, and name the limits of what their work can show.
  • Scope and deliver an end-to-end visualization project, from a falsifiable question through a defensible artifact, and defend its decisions under questioning.



Course Resources

Textbook

There is no textbook, and no software required for this course. Everything the course asks for runs on a free tier or on your own machine. Tableau is available at no cost through Stevens if needed. Weekly readings are optional and are posted in Canvas.>

Additional References

TABLEAU LICENSING:

  • Download the latest version of Tableau Desktop here:
  • Click on the link above and select Get Started. On the form, enter your school email address for Business E-mail and enter the name of your school for Organization.
  • Activate with your product key: TBD
  • Already have a copy of Tableau Desktop installed? Update your license in the application: Help menu -> Manage Product Keys

Are your students new to Tableau? Share our free Student Resource Page to help them get started. Students can continue using Tableau after the class is over by individually requesting their own one-year license through the Tableau for Students

Additional Online Materials:

Tableau Free Training Videos
Tableau Elearning
Gephi Tutorials
Datawrapper Academy
Plotly Chart Studio Tutorials



Grading

Grading Policies

  • Five assignments(A1 to A5), 10 points each, 50%
  • AMR Retrospective(pass/fail) 5%
  • Capstone Proposal 10%
  • Capstone Check-in 10%
  • Capstone Final 25%

  • Lecture Outline

    Week or Module Topic Associated Reading Assignments
    Week 01 Introduction Optional, in Canvas
    Week 02 Research Methods and Data Discovery Optional, in Canvas
    Week 03 Visualization Types and Chart Selection Optional, in Canvas A1, Tool Calibration
    Week 04 Critique and Redesign Optional, in Canvas
    Week 05 Data Preparation and Pipeline Thinking Optional, in Canvas A2, Critique and Redesign
    Week 06 Dataset Selection and Dashboard Foundations Optional, in Canvas Dataset gate
    Week 07 Prompts the Elicit Analytical Reasoning Optional, in Canvas A3, The Pipeline
    Week 08 Statistical Analysis and Advanced Analytics Optional, in Canvas
    Week 09 Advanced Dashboard Development Optional, in Canvas A4, The Analysis
    Week 10 Data Storytelling and Narrative Design Optional, in Canvas A5, The Story
    Week 11 Capstone Project Launch Optional, in Canvas AMR Retrospective; Capstone Proposal
    Week 12 Performance and Cloud Deployment Optional, in Canvas
    Week 13 Capstone Check-in and Ethics Review Optional, in Canvas
    Week 14 MCP and Tool Integrations Optional, in Canvas Capstone Check-in
    Week 15 Capstone presentations Capstone Final