Want to make comparing multiple measures across multiple dimensions in Tableau easy to understand? Traditional charts can quickly get messy and hard to interpret, but a Multi-Column Dot Plot offers a simple, effective solution! In this tutorial, you’ll learn how to:

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The requirements for week 15 are here. This is another super useful challenge as it helps you develop a dashboard you could easily use in your own organization.

My go-to blog post for working with and formatting time is this one from Jonathan Drummey. I'd say it's critical for solving this challenge. Also, think about the calcs for the reference lines and the BANs. As a hint, they're not just simple reference lines based on the measure on the rows. You WILL need to calculate the overall average separately.

Click on the image to interact with the dashboard and/or download the workbook here.

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Today I had the pleasure of speaking at the Barclays Enabling Modern Analytics symposium. Nandu Govindankutty of Barclays did an amazing job organizing this event. He runs a charity called MADTA (Making A Difference Through Analytics) and focused this event on senior leaders from Charities and Social Enterprises.

Naturally I wanted to speak about the amazing work that The Data School did on the Connect2Help 211 project for the Tableau Foundation. Nandu also asked me to speak about my experience in data visualization and why I think data visualization is import in analytics.

I was able to record the presentation. You can watch the presentation below, view the slides and some of the visualizations I built during the talk.

Quite often I listen to presentations from other manufacturers on an “Insights & Analytics” share group.  Much of the content presented is directly applicable to my work; the education and ideas are great.  Unfortunately, far too often the presentations are of poor quality.  One thing I need to learn is to look past these “mistakes” and focus more on the story, but I’m struggling to do that.

Here are couple examples from a recent presentation:

These pie charts took several minutes for the presenter to explain, which is an immediate sign of their weaknesses.  The only part that works well is that the slices are ordered by the amount of time.  Other than that there are problems throughout.  I’ve gone into these in plenty of detail in the past.

The second charts that took my breath away are these 3D cylinder column charts.  I don’t see too many of these, for which I’m thankful.

There was no explanation whatsoever for how to interpret these charts.  My eyes take me back and for between the charts in an effort to compare like colors.  I can’t be convinced that was the intent though without the background commentary. 

I did a quick Google search for cylinder chart and the first site that came back was from anychart.com.  My terror increased when I read their definition.

Cylinder charts are column (or bar chart) that use cylinder shaped items to show data. Although cylinder charts do not add any additional data, sometimes using this shape allows to achieve a better visual appearance of your data.

The best visualization of Cylinder charts can be seen in 3D mode, so we will present all examples of them in this mode.

Seriously?  They achieve a better visual appearance?  How?  Their best us is in 3D mode?  OMG!  You really should checkout their site.  The examples are frightening!

So how can the cylinder charts presented be improved?

1. Change the cylinder to plain old bars
2. Add a scale
3. Make it a clustered column chart.  This would allow you to compare the categories for each color to see the relationship between “Likelihood to Shop” and “Ease of Use”
4. Consider a scatter plot

These are incredibly simple changes to make, which is what frustrates me so much.  It actually takes more work to make it look this bad versus using Excel’s defaults.

I struggle with charts like this each and every day, but the culture needs to change.  Have you been able to influence change?  How?

I started this blog 624 days ago on August 17, 2009 with the goal of helping others (and me) learn best practices for data visualization.  There have been many twists and turns and the backlog of blog posts has gotten quite long.  The breadth of the audience of this blog worldwide has both fascinated and humbled me.  145 blog posts later, here are the stats, visualized of course.

The bubbles are sized based on the rank of the country for the stat & time frame chosen.  The color is based on the stat chosen.

Thanks for the visits and comments.  I learn a lot from your feedback.

Recently Google added the Stats feature to Blogger blogs. It's basically a dashboard very similar to Google Analytics, just stripped down (like Tableau Public vs. Tableau Desktop). There are four tabs, three of which are well done (Overview, Posts and Traffic Sources). However, the Audience dashboard is poorly designed.

This is the Google version of my blog stats from May 2010 - October 2010:


The map is well done, as you would expect, though it's tough to see the light green on the countries with less pageviews. I like the table below the map as a reference.

My issue is with the pie charts on the right. The tables are sufficient for my needs, especially since it has the total pageviews as well as the % of total. The pie charts are shown in descending order, but you have to work to find the starting point; as I've said in the past, pie charts should always start at the 0 degree mark when used.

If I were to visualize this dashboard, I would create it like this.


I've made the following changes/improvements:

1. The left half of the dashboard the same, except that I was limited to bubbles on the map since I built this with Tableau's standard features. I prefer the filled in countries, and I know there are workarounds in Tableau, but I think this map makes the variance easier to see since I used an orange-brown color pallet.
2. I did not change the reference table below the map.
3. On the right, I have combined the pie charts and tables into a single view. The bar charts are listed in descending order by % of total pageviews and labeled with the # of pageviews. It's much easier to make sense of the bar charts than the pie charts.

I'm fairly certain at some point in the near future that Google will begin following visualization best practices. They certainly have the money to pay for the expertise (hint, hint).