For many Tableau beginners, making high density, interactive visualizations can be a challenge. Tableau woes – Part 1 addressed this challenge with three strategies for combining data variables into a single display rather than plotting them in individual rows and columns (Tableau’s default mode, that makes direct comparison difficult to impossible): Measure Values Blending Axes Dual Axes This post will explain two more tools that can be used to add.]]>
For many Tableau beginners, making high density, interactive visualizations can be a challenge.
Tableau woes – Part 1 addressed this challenge with three strategies for combining data variables into a single display rather than plotting them in individual rows and columns (Tableau’s default mode, that makes direct comparison difficult to impossible):
This post will explain two more tools that can be used to add data density to a Tableau viz and give it a bit more interactivity.
As with the previous post, I’m using Tableau’s superstore sales dataset.
Create Calculated Field
Starting where we left off in Tableau Woes – Part 1, what if you had created the viz above, but wanted to compare sales in one province, say Quebec, to national sales. If you tried to filter by province, Tableau would apply the filter all the Dimensions and Measures in the display and the end result would be a comparison of Quebec sales to Quebec sales, which is not useful.
The solution is to use Create Calculated Field. CCF is one of Tableau’s real strengths. It allows the user to create new Measures and Dimensions that were not in the original dataset, directly from inside Tableau and on the fly. With it, you can avoid having to back out of Tableau, revise the original Excel file, re-connect to Tableau and start all over again. Here’s an example:
Tableau Parameters are another tool for controlling what is displayed. Parameters also make use of the Create Calculated Field function.
Hierarchy
The Hierarchy tool can also add interaction and dimensionality to a visualization, making it possible to drill down into detail or aggregate back up to bigger buckets. Here’s how it works:
It is worth noting that Hierarchy isn’t equally interactive for all viz types in dashboard view. A treemap, for example, doesn’t have any axes and I found it impossible to find a Plus or Minus sign to click. I imagine the same goes for a Bubble chart. If anyone has a solution for this problem, I’m all ears.
DataViz in 6 Weeks is my blog about teaching Introduction to Visual Analytics at OCAD University in Toronto. Comments, follows and shares welcome. #DataVizInSixWeeks
Anne Stevens I am a multidisciplinary designer working in data visualization, interaction design, innovation and critical design. I am particularly interested in non-screen based physical representations of data and tangible user interfaces.
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