The idea of the project is to take the DataVis knowledge that you are acquiring this semester and use it in a new, creative effort. A real key to a successful project is to select a topic/data that people want to know more about, and that is of interest to your team.

You will form four-person project teams (three people in a few cases). I will facilitate some in-class discussions about project groupings, but you should explore ideas amongst yourselves as well. I want the teams to be balanced in terms of background and experience: ideally a blend of computing, management, and other disciplines.

There are many sources of data on the web – financial, social/demographic, economic. Examples include Amazon AWS,, CDC, WHO, NASA, UN, NBA, ESPN, FAA, Yelp, Twitter, Crunchbase, USPTO, Google Scholar, WRDS, etc. It is important that you choose data that is already in a usable form, such as CSV, or quickly attainable. This course is not about data extraction and formatting, but on data visualization!!!

This semester I am asking you to explicitly focus on one of four domain areas. Your dataset MUST be related to one of those areas:

  • Healthcare (e.g. Patient, Population, Delivery)
  • Business (e.g. Finance, eCommerce, IT, Marketing, Supply Chain, Strategy, Innovation)
  • Social Media (e.g. Facebook, Twitter, LinkedIn, etc.)
  • Sports (e.g. Fantasy, Operations, Player Management)

No matter what domain/topic/data you choose, I am expecting a high-quality project. In particular, I’m seeking creative projects showcasing interesting ideas. A stellar project consists of an implementation of an visualization design with multiple, linked views of the data and good interaction, designed to allow users to answer interesting questions and gain insights. Note that I am explicitly NOT expecting user testing and evaluation, but your visualization has to work.

You are free to choose any software development environment and graphics/visualization support library that you want. There are many. We will focus on Tableau in class, but you are welcome to use others, such as Qlik, Spotfire, D3.js.

The project counts 30% of your final grade, slacking off is not a good idea. We will have two peer evaluation reviews, one at midterm, the other at the end of the semester. If you slack off in sharing the workload of the project, you will receive a lower grade than your partners.

Project Milestones

There are ten project milestones (see Schedule for due dates). First, after making your elevator pitch, you must form your team and settle on a topic/data. Second, you will maintain a detailed visualization design portfolio, including design sketches, ideas, data description, tasks and objectives. You will update the instruction team and receive feedback. Finally, you will create a blog/webpage, a poster, and a narrated video presentation about your data visualization project at the end of the semester. Material needs to be delivered via GitHub.

All deliverables are on T-Square unless otherwise indicated.

  • PM1 – Prepare and present a short (!) elevator pitch (30-second) in class.
  • PM2 – Team member names, emails, one sentence topic. Name your team.
  • PM3 – Please prepare a project description. Create a two-page document listing project members and topic/data to be addressed. Determine who will fill team roles (subject to change). Provide (initial ideas of) data source and format of the data (spreadsheet, SQL database, etc.). Describe 3 or 4 questions/tasks that users of your system should be able to investigate/answer. Provide a characterization of your target user (lay person, political analyst, sports junkie, movie executive, etc.); Provide a sketch of your possible DataVis design; and describe how users may interact with the data.
  • PM4 – Provide a link to your data, take a snapshot of your data in tabular format (CSV) or a schema of your database, and provide a list of all your variables.
  • PM5 – Designs. Sketch and provide an overview of several iterations (2-3) of your DataVis dashboard design and annotate the design. Explain your design evolution, the interactions you think will be embedded in them, etc. Think carefully about what you want to show and how. Make sure that Tableau or the software you chose for the project can handle the design/interactions you are providing. Creativity and depth of thinking is important here.
  • PM6 – Peer evaluation (midterm). Complete the evaluation form. You will find the link on T-Square in the announcement we sent out.
  • PM7 – Status I. Meet with a TA at a mutually convenient time (see sign-in sheet) to talk about your project, discuss problems and progress. Goal is to make sure you are on the right track. It is recommended that you have completed all data wrangling and have a functional dashboard design and implementation at this point.
  • PM8 – Status II. Demonstrate working system to the instructional team (Week of April 10-14, sign-up sheet will be posted). Start working on a poster to tell your “data-driven” story about your project. We’ll provide feedback to help you improve your system prior to your project presentation and final poster. Schedule your system demo and final video presentation on T-Square.
  • PM9 – Demo. Submit your final visualization system (files + data) via T-Square.
  • PM10 – Video, Poster, and Evaluation Form. Submit your final video, poster and final peer evaluation form. The video should be a 4-6 minute narrated video demonstrating your project. First give a general introduction to your system and then work through answering four questions that you posed in your project plan. Submit a link to your video on the T-Square assignment. Bring your poster to exam and present your narrated video to the entire class in a video watching session. Answer questions.

Grading: We will evaluate the overall quality of your project, including all milestones and components. While progress at each PM is important, ultimately the final deliverable is critical. We will give you as much feedback as possible, but the initiation for feedback has to come from the team.

Great projects will typically have multiple coordinated views, provide details on demand, and some means of selecting which aspects of the data set are displayed (controls, etc.). Whatever interactions you provide should support users in answering questions about the data!

Peer Evaluation


Final Presentation Line-Up

  1. TBA
  2. TBA
  3. TBA