This assignment will familiarize you with one of the most popular commercial information visualization systems available, Tableau.

The goals of the assignment are for you to learn the capabilities provided by this system, learn the visualization methods that it provides, and assess its utility in analyzing information repositories. You will work with some provided data sets in the assignment. Think about the kinds of questions that an analyst would be asking about the data sets.

The assignment has four parts:

1. Gain familiarity with the system
Familiarize yourself with the visualization techniques and the user interface of Tableau. View a tutorial, read some of its whitepapers, and just experiment. Your goal is to become familiar with the system, its interface and its capabilities.

2. Examine the sample data sets
Tableau includes a few sample data sets, but often it's best to learn with something new. Five data sets are supplied the Resources page of t-square for you to consider: foods' nutritional data (5976 items, 32 vars.), stocks (500 items, 30 vars.), baseball statistics (322 items, 24 vars.), college information (51 items, 22 vars.) and professor's salaries (1160 items, 16 vars.). You must work with the food nutrition data set and you are free to pick the one other set that is most interesting to you. Briefly scan the text of the files and familiarize yourself with the variables. Generate and write down (you will need to turn them in) a few hypotheses to be considered, tasks to be performed, or questions to be asked about the data elements. Think about all the different kinds of analysis tasks that a person might want to perform in working with data sets such as these. For instance, someone working with a data set about breakfast cereals might have tasks like:

• Identify the cereals with the most salt.
• Do the different companies producing cereals have different styles of cereal that they favor?
• Does high fat mean high calories?
• What cereals would you recommend to someone on a diet who still wants some good taste?
• Does the nutritional value of cereals vary a lot? If so, how?
• etc.

3. Load and examine the data sets into the system
Load the nutrition and other data set that you selected into Tableau, then consider your hypotheses, tasks, and questions. Also use the system to explore the data sets and see if you can discover other interesting or unexpected findings in the data sets. Put yourself in the shoes of a data analyst, and consider questions that such a person would confront.

4. Write a report on your findings
Write up a summary of your exploration process, findings, and impressions of the system. Include your hypotheses/tasks/questions and what you found. Furthermore, critique the system in a general sense. (Feel free to include screenshots to help explain your analyses and critiques.) What are its strengths and weaknesses, in your opinion? How useful are its visualization capabilities? For what kinds of user tasks is the system suited? Focus more here on the visualization techniques as opposed to the particular user interface quirks, though you should feel free to comment on UI aspects when they are particularly good or bad. Additionally list one unexpected finding, insight, or discovery made while exploring each of the datasets with the system. Explain how the system helped to facilitate the finding.

In your report, we recommend that you not walk through each question/task one-by-one for each of the data sets you used. (There simply won't be space to do so.) You might want to include specific examples of how the system assisted or did not assist work on specific tasks, however. Point out interesting, insightful observations; you don't need to tell us how a system works -- we already know that. Think of this like a report to your manager who wants to know what Tableau can provide, its pros and cons. Focus specifically on how its visualizations help or hinder analysis.

Your document is limited to a maximum of 10 pages, single-spaced, reasonable font size, including embedded screenshots. Please bring two hardcopies to class on the day that it is due.

Acknowledgments: Tableau's data visualization software is provided through the Tableau for Teaching program. We thank Tableau for making the system available to students in class.