Myth busting the "data story"

What is a data story?

There are lots of terms thrown around the analytics industry (artificial intelligence, machine learning, data science, etc.) and we often tend to over-complicate their meaning. But one of these “buzz words” is near and dear to my heart, so I feel the need to defend its honour… or at least properly define it.

The data story.

A “data story” is a story supported by data. It’s not rocket (or data) science…

It is simply a narrative, written with data as supporting evidence.

For example:

"Churn is a problem for our business and churn rates have been increasing steadily over the last 18 months. But regional analysis shows areas with the highest churn rates also have the largest competitor activity. Therefore, if we target specific regions with offers more in-line with other providers, this could help to retain customers."

What is not a data story?

The lure of a buzz word… I’m pretty sure the number of Analysts declined at the same rate as the number of Data Scientists increased (disclaimer: I haven’t looked for data to back this up). Regardless of your job title, unless you do something to grow your skill set you are still only capable of doing the same thing.

As more people adopt a term it morphs into something else entirely, so I’m setting the record straight on the term “data story”, by explaining what it’s not:

A visualisation

Data visualisation can be an effective way to tell a data story (see below) but it relies on the story having been written first. If you are calling every data visualisation a data story - please stop. Some visualisation techniques (especially those based around design principles) lend themselves to enhance data storytelling, but these do not apply to all forms of data visualisation.

Data visualisations are not data stories.

A random statistic

Putting a number on a page (or in an email, or on a billboard) is not a data story. It is a statistic, usually a really big statistic and probably a statistic presented to the high visual standard of a graphic designer.

Statistics are not data stories.

Data science

Data science is a behaviour. It’s the technical practice/process followed to uncover data insights and ultimately add business value.

Data science is not a data story.

How do I write a data story?

If you take one thing from this blog post, let it be this:

Data is not the story – it just helps to support a bigger message.

A good data story will be written with a purpose (knowledge of the action it is trying to create), it will target a specific audience, and communicate a message (through narrative and supporting metrics). Data stories are so much bigger than the metrics that help support them.

You can download my Data Story canvas here. Techniques to complete each section of the Data Story canvas are covered in Rogue Penguin's Data Story workshops.

How do I tell a data story?

Only after a data story is written can it be told, and there are many ways to do this.


From the camp fires of our ancestors, this is perhaps the most common form of storytelling. Their stories served as instructions, warnings, and inspiration – all purposes still relevant today.


Written words, images and graphs can all be used to aid in telling a data story.

There are many different data visualisation tools but not all graphs/charts/dashboards created in them are appropriate for storytelling. Visual data storytelling relies less on the software and more on the storyteller. The book “Storytelling with Data” by Cole Nussbaumer Knaflic is a great starting resource.

Both verbal and visual

Combining verbal and visual methods of storytelling covers multiple communication preferences. Presentations are a great format for storytellers. An audience can hear a story and have it supported further with visuals.

I’m sure this definition of “data story” will continue to evolve as the industry matures - and that’s exciting! I hope the term doesn't get defined so broadly though, that its meaning is lost.