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Posted by Eric

October 29, 2013


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How to Design and Build Effective Dashboards in Tableau

The Data Visualization & Dashboards Seminar we hosted in Toronto last week was a tremendous success, and I would like to extend a thank you to all those who attended! We have received so many requests for the dashboards presented during the “How to Design and Build Effective Dashboards” demonstration session, I thought I would share them in this blog. The underlying story/premise and methodology used to support the story are described for each of the four dashboards.

Keep in mind two foundational decisions for creation of an effective, useful dashboard… what story are you telling (a.k.a., the premise of your dashboard), and how you will support the story through visual elements and interactivity specifically targeted to the story.


It is best practice to narrow the focus of your dashboard to a central premise. Dashboards that attempt to address a wide variety of stories or premises often become overly complex. In general, if you end up needing to create help or user guides for your dashboard it may lack the focus required to be optimally effective.

To quote a famously brainy person, Albert Einstein: “If you can’t explain it simply, you don’t understand it well enough.” The same is true for your dashboard. If you can’t explain the story or premise of your dashboard in a single sentence, it may be time to expend more thought on what you’re trying to accomplish.


There are a number of ways Tableau facilitates telling your story, and there are a number of themes you can take advantage of when using Tableau. It is not uncommon to have several different methodologies presented in a single workbook, but it’s most intuitive for end-users when a single dashboard supports the story with a single methodology. Some of the most frequent methodologies are:

  • Geography-centred dashboards: One or two choropleth maps (i.e., filled maps) with ancillary supporting elements to refine your story as it relates to geography.
  • Time-centred dashboards: One or two key charts with a primary dimension being time. Some time-centric dashboards may also include a time-based paging element, frequently including historical values, for animating the dashboard over time.
  • Guided analytics: Sequence-specific interactive elements that build/compound on each other. Be careful when using this approach as end-users can get lost if your elements result in circular filtering (i.e., element A filters element B, which filters element C, which filters element A).
  • Ad-hoc investigation: The central element(s) vary quite a lot, but most ad-hoc dashboards will provide a variety of parameters and quick filters to allow the end-user to “tweak” or refine their path of investigation. Ad-hoc dashboards generally cannot predict every possible investigative path end-users might take, but a number of key paths should be supported with a variety of possible add-on filters for each.

Toronto Parking Infractions Dashboard

Data on parking infractions has a fairly simple structure, but this does not mean that a dashboard built on it will be simple. This dashboard has a large number of records and numerous time, geography, and filtering mechanisms to drill down on the large volume of data very quickly.

Story: There are discernible patterns and noteworthy exceptions in location and time in the parking infractions issued around Toronto.

Methodology: Guided analytics


Note: The Tableau Public version of the dashboard is limited to 1 million rows of data. To obtain the version that contains all 14 million records, contact Unilytics directly.

Click on image below to view and interact with dashboard on Tableau Public.

Google AdWords Keyword Performance Dashboard

This workbook consists of numerous dashboards focused on Google AdWords performance. Twelve different data sets are required to run this dashboard, and as such it is a good example of blending data from a wide variety of sources. The dashboard highlights differences between status dashboards (i.e., the “managers” dashboard) and investigation dashboards which would most likely be used by data analysts.

Story: AdWords is a complex topic, and there are a number of ways to investigate the effectiveness and ROI on AdWords spend.

Methodology: Time-centric visualizations designed for ad-hoc investigation

Click on image below to view and interact with dashboard on Tableau Public.


Life Expectancy & Fertility Rate

This dashboard highlights the usefulness of using time when playing back data over numerous time periods. In this case, life expectancy and fertility rates are compared between 1960 and 2010. The use of data animation quickly highlights patterns in the data that aren’t readily apparent when viewed statically.

Story: There is an obvious correlation between birth rate and average life expectancy and huge discrepancies between various areas of the world.

Methodology: Time-centric, animated visualization

Click on image below to view and interact with dashboard on Tableau Public.


Custom Geocoding

This dashboard highlights the ability to use non-standard geographic areas in Tableau. This dashboard specifically highlights various forward sortation areas (FSA) in the Greater Toronto Area (GTA). The dashboard also demonstrates the ability to blend multiple sets of data in a single dashboard. In this case, sales data, demographic data, and custom geocoding data are all blended together to facilitate this dashboard.

Story: Detailed geography aligned with sales and demographic information will identify useful, advantageous sales patterns.

Methodology: Geographic-centred investigation

Click on image below to view and interact with dashboard on Tableau Public.
Parking Ticket2016-05-26_13-54-14

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