We stop loving someone or something when we feel there is nothing more to discover, when we have no more questions, when we don’t care about the answers.

I started writing my Data Visualization for Excel Users series because I have an unhealthy number of open questions. I’d like to go beyond it depends but there are no right answers, only my answers (and, with your help, our answers). These are practical questions (from a business user perspective) that, once answered, will surely trigger new ones. Here is a sample, with a few starting points:

1. Reason or Emotion?

This is the big one. We’ve been discussing reason vs. emotion over the last 2,500 years, and we still disagree. The right answer would be reason and emotion (easier said than done). When applied to data visualization, this translates into charts that respect the data, attracts readers attention because they are beautiful and keeps it because they are interesting and insightful. And contain no cheap emotional tricks. This filters out 99,9% of all  infographics published nowadays.

2. Pies or No Pies?

No self-respecting data visualization expert likes pie charts. And there seems to be a daily contest to find the “worst pie chart ever”. And people keep making them, relentlessly… Why?

3. Are there interchangeable charts?

Everyone tells you that you should use bar charts instead of pies. Well, I think you should. Not because pie charts are bad, but because you’ll have to ask better questions. But that’s not the point. The point is that there are no interchangeable charts. Different charts tell us different stories. You cannot tell a part-of-a-whole story with a bar chart. You have to have a pie.

4. Should I use logarithmic scales?

I’m still trying to find a simple way to implement a logarithmic perspective in my eyes… Logarithmic scales are important to look at growth from a different perspective, but if you can’t find a way to tell the readers how to read the chart you should consider not to use them.

5. Should origin start at zero?

Yes, by default. If you need to improve resolution set the scale to 20% below minimum and 20% above maximum values . Don’t do it with bar charts (origin should always be set to zero).

I would consider this rule: to improve resolution you must have more than one series (see this example). In a line chart, comparing slopes is often more interesting than the slope itself.

6. What kind of data visualization skills the information worker needs?

Above all, know your business. Learn how to use a database (table structures, basic SQL). Refresh what you know about descriptive statistics. Choose a tool and be an advanced user or hire someone who is. Learn the basics on how human perception works. Understand how perception impacts design choices and the other ways around. Learn what each chart type is used for. Find your charting style. Spread this knowledge across your organization. Know your business (again).

7. What is the role of design in data visualization?

We saw that a chart is a visual representation of distances between data points. Everything else is design. The first role of design in data visualization is to improve cognition. The second role is to provide aesthetic consistency. The third role is to grab users attention.

8. How to design a dashboard?

I think we owe Tufte and Bertin a consistent approach to data visualization, at the chart level. We still need something similar for dashboard design.

9. How to sell data visualization?

Find a sponsor and make a lot of bad chart/(good chart comparisons. Compress a 100-slide presentation into 50 slides. They will get it, sooner or later.

10. Should I use animation?

You probably shouldn’t. Try small multiples first. Try animation if you have too many series, if the animation defines clear patterns and if it is consistent with the law of common fate. But remember: are no interchangeable charts.

11. Do I need to code?

No, but you should at least be able to understand what a recorded macro is and how to improve it with simple changes.

12. What tools should I use?

Learn everything in Excel then switch to Tableau/Qlikview/Spotfire.

How would you respond to these questions? Please share your thoughts in the comments below…