Is there a single best visualization for a given set of data? Should you always use a bar chart when looking at categorical data with a single metric? Is a timeline always best for viewing trends over time? Is there only one data story to tell?
There are a couple of different viewpoints on this issue. Some would argue, “Absolutely there is one best way to visualize certain sets of data based on the question being asked! And it can be scientifically determined.” (See Stephen Few’s recent post and discussion in the comments). Another group says, “It depends! There are many different ways of seeing the same data and what works depends on lots of different factors.” (See Cole Nussbaumer Knaflic’s post)
I lean toward the “there’s multiple ways to visualize data” viewpoint – but the debate not what this post is about. Instead, let me offer the following observations and then move to the main point:
I think there’s more agreement between the camps than appears at first glance.
While I’m not convinced that there’s always a single “best” way to visualize data, there are often wrong (misleading, false) ways and “not-as-good” (confusing, lacking clarity, boring) ways that should be avoided.
What I love about Tableau is that it makes it easy to iterate through various views of the data – all the while asking, answering, and raising new questions – that lead to new visualizations that answer and raise new questions. The flexibility and ease of changing a visualization allows me to have a conversation with the data. A single view gives me a single viewpoint. Multiple different views of the same data allow me to see things I might have otherwise missed.
It is amazing the difference a single change to a data visualization can make – sometimes it changes the whole story – or at least gives a totally new perspective.
And that leads me to my main point: even a small tweak to your dataviz can uncover new perspectives and new data stories.
An example: Absolute versus Relative Time
Take for example, this view:
How many cumulative views of posts on VizPainter.com?
Notice the variations:
X-Axis is Date: You see a running total of page views for every post on the popular Tableau blog, VizPainter.com, starting with the date of the first view.
X-Axis is Age: You see a running total of page views for every post, starting at day 0.
Now consider the similarities:
Both are timelines (technically, you might consider the second a scatter-plot).
Both have the same number of lines
Both have the same exact shape of lines
The only thing that’s really changed is the origin of the lines.
In the first, the origin is absolute: the date on which the post was introduced
In the second, the origin is relative: all posts start on day 0.
And yet, the data story that is told is very different.
Data Story 1: How Many and When?
This story is focused on “when” and “how many” and there are certain aspects of the story that are relatively easy to see:
When were posts published? (A)
How long between posts? (A)
What are the most popular posts (in rank order)? (B)
How popular were posts? (B)
How fast did posts grow in popularity? (C)
But contrast that with this story:
Data Story 2: How Fast?
This story is focused on “how fast” and there are different aspects of the story that are easy to see:
How old is a given post? (A)
How popular has a given post become? (B)
How fast did a post grow in popularity? (C)
How fast did a post grow in popularity compared to others? (C)
How popular was a post X days after being published (D)
And now consider one final tweak that enhances the story in other ways:
Notice how the animation adds a few elements to the story:
The absolute date becomes easier to see and understand again
There is a hint of relationship between posts (notice how once the most popular post comes into play, the trajectory of other posts change).
Now you’ve seen my example. What examples do you have? What existing data visualizations do you have that could tell a different story if they were tweaked? What answers can you uncover in the data based on different visualizations?
So go home, take out your old data vizzes and experiment! Let me know what you uncover!
And of course, you’d like to know how to build the relative time series and even animate it, wouldn’t you? You’d even like me to give you a Tableau workbook? Absolutely! That’s the next post… (so check back soon!)
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Joshua Milligan is a three-time Tableau Zen Master. His passion is training, mentoring, and helping people gain insights and make decisions based on their data through data visualization using Tableau. He is a principal consultant at Teknion Data Solutions, where he has served clients in numerous industries since 2004.
Joshua served as technical reviewer on several Tableau titles and is the author of the book Learning Tableau.