Visual Analytics with Tableau

Order Instructions

Visual Analytics with Tableau

Data description

There is a vast amount of open data on the web, ranging from Twitter data to weather data

to taxi records. I use an open dataset from San Francisco in the instructions.

First choose a dataset that seems interesting to you. You are welcome to use open data

from other cities; quality and variety of available datasets varies (exploring this is part of

the task). A google search for “ + open data” will most likely give you the

data source (examples provided below). You can also use openly available data from

federal agencies (census data, bureau of labor statistics, CDC, …); pick a specific one (e.g.,

American Time Use Survey from BLS) as these sources have various datasets.

• San Francisco, https://data.sfgov.org/

• Memphis, https://data.memphistn.gov/browse?limitTo=datasets

• Boston, https://data.boston.gov/

• Chicago, https://data.cityofchicago.org/

• Denver, https://www.denvergov.org/opendata

• Bureau of Labor Statistics https://www.bls.gov/data/

• Center for Disease Control & Prevention (CDC) https://data.cdc.gov/

o Behavioral Risk Factor Surveillance System https://www.cdc.gov/brfss/index.html

• USDA Economic Research Service, https://www.ers.usda.gov/data-products/

o Food Environment Atlas, https://www.ers.usda.gov/data-products/food-

environment-atlas/

Note that very large datasets will take more time to load and process in Tableau on your

computer.

See the Instructions video (Instructions for Mini Project with Tableau) for an example of

downloading a dataset, loading it in Tableau and creating visualizations. You can load data

into Tableau directly. There are tutorials for Tableau online on their website. There are also

more videos on YouTube that can help you if you get stuck.

Tasks

1. The first task is to explore the data. In this step you will be searching for some

correlated variables in the data worth looking at more closely. You will be expected to

use the mapping feature in Tableau (except when your data does not have geo

identifiers). In my example using crime data, A packed bubble chart can be used to start

by identifying the major categories of crimes (see Figure 1a). Then, some simple

exploratory analysis might examine the Category of crime against the location of the

crime (you have to use X and Y as Dimensions, for longitude and latitude – see Figure

1b).

Figure 1a Figure 1b

2. The second task is to identify a relationship that you want to further analyze and

provide a data-driven narrative for.

3. The third task is to conduct more thorough analysis of the relationship you identified in

the exploratory data analysis. You can develop a hypothesis based on your exploratory

analysis to test (no statistical testing required), although this is not necessary if you

identify some interesting correlations. There is no right or wrong feature of the dataset

to explore, but you drill down from something you observed in the original exploratory

analysis. The methods you use for this are also up to you, but be thorough because you

will be graded on this.

4. The fourth task is to compile the figures you’ve generated into a narrative. You should

explain the steps in your analysis with the graphics you’ve created. This should be

accompanied by labels and or comments and explanations of what the figures depict.

Tips

• Tableau tutorials may be useful. Select videos that cover topics that seem appropriate

for your story and try to use them. The tutorials can be found here:

https://www.tableau.com/learn/training

• There is a video included with the lecture that goes over an example of the analysis

and story that you should create.

What to submit

You should submit your Tableau Packaged Workbook (twbx file, so that I can open your

visualizations without the need to have your dataset(s)) and Powerpoint presentation

containing your story/narrative. Make sure to provide your data source in the slide notes

of the initial slide(s) where you explain your data and topic. Your presentation should

contain a visual report explaining your analysis and conclusions. It should contain 5-10

figures generated from Tableau. You can take screenshots and copy & paste them into the

presentation. The presentation should look professional, so the screenshots should be

cropped neatly, and white space should be used efficiently. The presentation should look

like something you would present at work, and points will be deducted if it looks sloppy.

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