I didn’t have much time today for a makeover, so this will be a bit brief. I had tagged this article from the Facebook internet.org team as needing a makeover. It’s the cover of the report that caught my attention.


I guess what bothers me most is that this simple bar chart is completely unreadable. I can’t find any countries unless I use a microscope. I assume this was by design, but I don’t see the value in it.

Of course the data was not provided, so I did a quick Google search and found the data in Wikipedia. I then used the InterWorks Web Data Connector for import.io to extract the data. I blended that with another data set I had of country abbreviations.

I started by recreating the original in Tableau.


Ok, I still can’t read it, but I can hover over a bar at least. I wanted something better, something easier to understand, something people might want to quickly explore. I created this three chart layout which includes a map, bar chart (same as the original, but larger), and a slope graph.

I’m not totally sold that this is complete or great, but it’s definitely better than the original. And remember, I timebox myself on these makeovers, so once I reach my time limit I stop. Rules are rules.

By default, Tableau includes the gridlines when your date dimension is continuous. You also get that border around the whole chart. Now consider this cleaned up version.


To get this view, all you have to do is make some simple formatting changes. First, format the borders by setting the Pane to None for both the Row Divider and the Column Divider.


Next, go to the Format Lines options and set the Grid Lines to None.


Your chart should now look like this:


The last step is to go back to the Format Lines options and set the Axis Rulers to a line and make them a light gray.


That’s all there is to it! You now have a super clean line chart.


Put several of these together on a dashboard and you really see a big difference.


Download the sample workbook here.

My colleagues and I at Facebook had the honor of presenting at the 2013 Tableau Customer Conference alongside Kate Treadwell of Interworks, who was subbing for Mike Roberts. The topic of our talk was "Data Discovery at Facebook: Why Culture & Flexibility Matter for Modern Analytics". We based the session around four of Facebook's company values:

• Move fast
• Be open
• Be bold
• Focus on impact

During the "Be open" section of the talk, Heather Torres, who leads HR & Recruiting Analytics for us, revealed a method for encoding statistical comparisons of survey results. The basic premise is for a manager to be able to view their survey results compared to the company in total, but also understand the statistical significance of the results. Heather had created something similar to this in her past life at AOL in Excel and she challenged me to build something similar in Tableau. It didn't end up being very complicated, once the data was in the correct format of course.

I need to pause for a moment and thank two Tableau Zen Masters for their help and inspiration.

First, thank you to Jonathan Drummey for his help in getting both the manager and company results into the same view.  Jonathan taught me about Data Source Filters, which I had never used before.  We ended up aggregating the data so that we didn't have to have multiple data sources, but without his help early on, we wouldn't have gotten there.

Second, we need to thank Steve Wexler for his awesome work in visualizing survey results.  We based many of our other reports off of work that he's done.

And now back to our regularly scheduled program...

In order to help aid with understanding, here are some tips for how to read and interpret the results:

1. The dark bar represents the company in total.
2. The colored bar represent the chosen manager's results.
3. The width of the bars represents the statistical variation. The manager bar will always be wider than the company bar because there are less results for a manager, thus more less statistical significance.
4. The color of the manager bars represents how statistically significantly different they are vs. the overall company results.
5. If you see a gap between the company and manager bars, then the difference is statistically significant.
6. You can filter by Manager.
7. You have three chart types to choose from (more below about them).
8. You have three sorting options, which allow you to answer different questions depending on what you want to compare.

Note: All of this data has been altered randomized, so it doesn't reflect our actual survey.  The manager IDs are all fake, etc.

The view that Heather showed in our session was the Double Gantt (TM) option.  I've provided two other alternatives as well: Candle Gantt (TM) and Dots Gantt (TM).

The Candle Gannt is more or less the same as the Double Gantt, but the company bar is thinner and there are reference lines for the ends.  The idea here was to make it look somewhat like a candlestick chart.

The Dots Gantt is nice because it clearly shows the outer ends of the statistical range without concern for the range itself.

I had no idea what to call these types of charts, so the names are simply a combination of the chart types (And they aren't really trademarked.  Maybe I should TM them). These are all dual axis charts. Download the workbook and pull the charts apart if you're interested in seeing how they're built.

For those of you that came to our session, we owe you a heartfelt thank you.  We appreciated all of the questions, comments and great interaction.

If you’re not following the InterWorks blog, you should be.  They routinely crank out fantastic tips and tricks for Tableau.  Dustin Wyers, a BI Analyst for InterWorks, recently wrote about “Creating Calendar Views in Tableau”. 

Dustin’s post does an excellent job of taking you through creating a calendar viz step-by-step.  But I felt it fell a bit short in the end since you didn’t actually see a calendar.  Dustin’s end product looks like this: