6.2.1.Visualizations in Tableau - sj50179/Google-Data-Analytics-Professional-Certificate GitHub Wiki

Get started with Tableau

Tableau

  • A business intelligence and analytics platform that helps people see, understand, and make decisions with data

Visualization galleries

One of the coolest features of Tableau Public is the public gallery, where you can explore what visualizations other people have created. In addition, you have the option to explore the data behind the visualizations, as well as download visualizations that you may want to explore in detail later on. You can find the gallery from the header on the home page, or use the search function, which appears as a magnifying glass icon, to explore data and vizzes about particular topics.

Here are a few useful links within Tableau Public:

  • Public Gallery: These are data visualizations created by other users that you can scroll through.
  • Featured Gallery: This is a collection of featured data visualizations created by other users. This is a great source of inspiration.
  • Viz of the Day: Tableau Public features a new data viz every day; check back for new visualizations daily!
  • Google Career Certificates page on Tableau Public: This gallery contains all of the visualizations created in the video lessons; you can explore these examples more here.
  • Tableau Public resources page: This links to the resources page, including some how-to videos and sample data.
  • Tableau user forum: Search for answers and connect with other users in the community on the forum page.

How visualizations differ in Tableau

As you have also learned, Tableau is an analytics platform that helps data analysts display and understand data. Most if not all of the charts that you can create in spreadsheets are available in Tableau. But, Tableau offers some distinct charts that aren’t available in spreadsheets. These are handy guides to help you select chart types in Tableau:

The following are visualizations that are more specialized in Tableau with links to examples or the steps to create them:

Test your knowledge on getting started with Tableau

TOTAL POINTS 3

Question 1

As a business intelligence and analytics platform, Tableau enables you to do what with data? Select all that apply.

  • Create and share interactive dashboards with data
  • Connect to data in databases, spreadsheets, or CSV files
  • Observe and understand data to make decisions
  • Check and clean data in databases

Correct. Tableau enables you to observe and understand data to make decisions, connect to data in databases, spreadsheets or CSV files, and create and share interactive dashboards with data.

Question 2

Compare Tableau to other data visualization software such as Looker and Google Data Studio. What feature is unique to Tableau?

  • Drag and drop functionality to create visualizations
  • Desktop version for users
  • Connectivity to SQL databases
  • Integration of multiple data sources

Correct. Tableau offers browser-based and desktop versions while Looker and Google Data Studio are strictly browser-based. Browser-based solutions are preferred by companies adopting cloud-based services while desktop solutions might be suitable for companies maintaining services on their private networks.

Question 3

Fill in the blank: When using Tableau Public, click the Gallery tab to access _____.

  • blog articles
  • public visualizations
  • sample data
  • how-to videos

Correct. Tableau Public’s Gallery features data visualization examples created by other Tableau Public users across the web.

Create visualizations in Tableau

Diverging color palette

  • Displays two ranges of values using color intensity to show the magnitude of the number and the actual color to show which range the number is from

How-to-choose-a-data-visualization.pdf

What makes an effective visualization?

The key to effective presentations is data visualizations that are clear and convincing. In turn, the key to effective visualizations is selecting the best way to depict your data.

You have learned about a few types of visualizations (e.g., bar graphs, pie charts) and what each type is best at emphasizing. Determining which type of visualization to use is essential to giving your presentation the impact it needs.

So far, you have considered a few rules about what makes a helpful data visualization:

  • Five-second rule: A data visualization should be clear, effective, and convincing enough to be absorbed in five seconds or less.
  • Color contrast: Graphs and charts should use a diverging color palette to show contrast between elements.
  • Conventions and expectations: Visuals and their organization should align with audience expectations and cultural conventions. For example, if the majority of your audience associates green with a positive concept and red with a negative one, your visualization should reflect this.
  • Minimal labels: Titles, axes, and annotations should use as few labels as it takes to make sense. Having too many labels makes your graph or chart too busy. It takes up too much space and prevents the labels from being shown clearly.

For a refresher, you can refer back to the readings from this section. Check out Designing a chart in 60 minutes, The wonderful world of visualizations, and Visualizations in spreadsheets and Tableau.

Question

Consider the guidelines for picking a visualization that you reviewed in this reflection:

  • What should you consider when deciding on the right data visualization?
  • What is your first step in determining the best data visualization for a presentation?
  • How the first step to identifying appropriate visualizations is understanding what kind of data I am presenting, and that I should apply the four rules (five-second rule, color contrast, conventions and expectations, minimal labels) to ensure the visualization has the biggest impact. After understanding the type of data (frequency, changes over time, categorical comparisons, etc.), then must determine what the audience needs to see to understand the analysis. After that, find which graph or chart style fits the goal. Finally, utilize the visual design guidelines above to create an accessible and aesthetically pleasing data visualization.

Creating effective visualizations

Identify the most effective visualization

Review the scenario and select the best data visualization from the list.

Scenario 1

Data type Changes in company stock price

Communication goal Demonstrate that your company’s stock price is trending upwards over the long term

  • Line chart
  • Histogram
  • Pie chart

Correct. A line chart is ideal for highlighting trends over time.

Scenario 2

Data type Number of customer support tickets closed by employee

Communication goal Help the customer service department identify their highest-performing employees

  • Histogram
  • Bar chart
  • Line chart

Correct. A bar chart is ideal for comparing similar data side by side.

Scenario 3

Data type Number of customers by company size (in revenue)

Communication goal Demonstrate that more customers does not always equal more revenue

  • Histogram
  • Line chart
  • Pie chart

Correct. A histogram is ideal for comparing the distribution of two variables by individual grouping.

Scenario 4

Data type IT requests by department

Communication goal Help executives understand which departments use the greatest proportion of IT resources at a company

  • Pie chart
  • Scatter plot
  • Line chart

Correct. A pie chart is ideal for measuring data as a proportion of the whole.

Scenario 5

Data type Employee happiness scores versus number of hours working from home

Communication goal Understand if working from home impacts employee happiness

  • Histogram
  • Bar chart
  • Scatter chart

Correct. A scatter plot is ideal for exploring potential relationships between two variables.

Test your knowledge on creating visualizations in Tableau

TOTAL POINTS 3

Question 1

A diverging color palette in Tableau displays characteristics of values using what color combination?

  • Intensity for the range and hue for the magnitude
  • Shade for the accuracy and grayscale for the reliability
  • Hue for the range and tint for the margin of error
  • Intensity for the magnitude and hue for the range

Correct. A diverging color palette in Tableau displays a value’s magnitude by color intensity and a value’s range by color hue.

Question 2

A data analyst creates a Tableau visualization to compare the trade (amount of goods and services exchanged) between the European Union (EU) and Australia. Which color choice could be misleading?

  • Blue for the EU and gray for Australia
  • Beige for the EU and purple for Australia
  • Green for the EU and red for Australia
  • Orange for the EU and brown for Australia

Correct. A lot of people associate green with positive results and red with negative results. Green could falsely represent a trade surplus for the EU and red could falsely represent a trade deficit for Australia.

Question 3

How could you adjust the labels to make the following visualization more effective? Select all that apply.

Each country has statistics for family, health, freedom, and generosity

  • Reduce the number of labels
  • Use a single font for the labels
  • Move the labels to white space on the map
  • Change the font color for the labels from black to white

Correct. You could make the visualization more effective by reducing the number of labels per country and using only one font. Doing this makes the labels easier to read.

Reflection

  • What did linking data from multiple sources allow you to do with your visualization in Tableau?
  • What other kinds of datasets could you link to the four you used in this activity? What kinds of comparisons or insights could you make?
  • If you couldn’t link data in this way, how would you make complex comparative datasets and visualizations like this?
  • Linking data allows data analysts to combine different features of multiple datasets without having to create a new dataset as analysts visualize comparisons and combinations of data. With Tableau and other visualization software, data analysts can simplify the process of combining and visualizing data. Otherwise, analysts would need to select the information analysts need and create a new data source, which takes a lot of time.

Tableau resources for combining multiple data sources

Now that you have some experience working with data in Tableau, you are ready to start doing more, including combining multiple data sources. This reading will provide you with some how-to guides for that, and other helpful resources you can use as you practice using Tableau on your own.

Resource Description
Set up data sources This page links to other resources explaining how to set up your data sources and prepare them for analysis once you have connected them to your Tableau account. It specifically includes articles explaining how to join or blend data, and what a union is and how they work. This is a great starting point as you get ready to begin using and combining data sources.
Join your data Joining refers to the process of combining data sources based on common fields. This article gives a more detailed explanation of the different joins, how to use them in Tableau, and an example join with a step-by-step guide.
Don’t be scared of relationships Relationships allow you to combine multiple data sources in Tableau. This is a more flexible alternative to joins, and doesn’t force you to create one single table with your multiple data sources. This article will give you more insight into how relationships work.
How relationships differ from joins This article goes into more detail about the differences between using relationships and joins, and guides you through the process of using relationships to combine data.
Blend your data Data blending is another method you can use to combine multiple data sources. Instead of truly combining the data, blends allow you to query and aggregate data from multiple sources. This resource goes into more detail about blending and includes a tutorial.
Combining multiple date fields This resource provides examples that explain how to combine date fields when using four different methods of data combination in Tableau.

These are just a few resources you can use. You can also find more information online or in the Tableau community forums.