January 3, 2018 In the first part we saw how to “hard code” the creation of a dimension from row-based survey data using a Level-of-Detail expression. In this second part we’ll see how we can turn any row-based survey data into a dimension “on the fly” using a parameter. Where we left off You [...]
January 3, 2018 Note: I first wrote about this five years ago and while the approaches I suggested then do in fact work, the advent of Level of Detail (LoD) expressions in Tableau gives us a much better way to get the job done. A very big “thank you” to my friend and colleague [...]
December 18, 2017 Updated September 27, 2018 to include single-select questions. Special thanks to Shaelyn McCole at Hootology who suggested the topic, Ryan Gensel at CPI who came up with a wonderful enhancement to the connected dot plot, and Jeffrey Shaffer at Data Plus Science who suggested some cosmetic improvements. Note: The original blog post only [...]
Overview Tableau’s automatic axis feature can often present problems with survey data. In this blog post we’ll look at how the problem crops up and what you can do to both fix the problem and make your visualizations more insightful. The problem with auto-adjusting bars Tableau’s automatic axis does a great job extending and contracting [...]
September 20, 2017 Overview As anyone who has read anything on my blog that relates to survey data knows, the number one impediment to success with Tableau is getting your data “just so.” Until recently I recommended two different approaches. You can either use Alteryx and have a rock solid, robust, fully-featured, (and expensive) solution [...]
Why you may be missing important insights if you only look at Percent Top 2 Boxes. August 23, 2017 Overview Anyone who has looked to this blog for insights into visualizing survey data knows that my “go to” visualization for Likert scale sentiment data is a divergent stacked bar chart (Figure 1). Figure 1 [...]
May 10, 2017 Overview A nod of appreciation to Tom Davenport who first brought this issue to my attention. Most organizations want to wildly exceed customer expectations for all facets of all their products and services, but if your organization is like most, you're not going to be able to do this. Therefore, how should [...]
And… what did they choose? March 8, 2017 Overview I’ve discussed how to visualize check-all-that-apply questions in Tableau. Assuming your survey is coded as Yes = 1 and No = 0, you can fashion a sorted bar chart like this the one shown in Figure 1 using the following calculation. SUM([Value]) / SUM(Number of Records) [...]
By Steve Wexler, January 15, 2017 Overview Before going any further this post assumes you’ve gotten your data “just so”; that is, you’ve reshaped your data and have the responses in both text and numeric form. If you’re not sure what this means, please review this post. Taking inventory by finding the universe of all questions [...]
Note: Major thanks to Nazirah Garrison and Christie Clark at Tableau for suggesting this approach. Overview With Tableau 10.x it is in fact possible to get your survey data, “just so” without having to invest in new tools and / or a engage in a time-consuming, error-prone procedure every time you need receive updated survey [...]
