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Nov 17, 2015 9:37:54 PM
How to Tell an Interesting Data Story

The Laffer Curve. Anyone know what this says? It says that at this point on the revenue curve, you will get exactly the same amount of revenue as at this point. This is very controversial. Does anyone know what Vice President Bush called this in 1980? Anyone? …Bueller?... Bueller?... Bueller?

Data stories, believe it or not, can be gripping. You worked on the project because there was some urgency to it. The story is interesting because of that urgency and how you dealt with it.

In prior posts on communicating about data, I’ve introduced what it means to use ‘story’ to connect with your audience and how to structure a post to catch a non-captive audience's attention. In this post, learn what kind of content makes a data story a pleasure to experience.

But don’t take it from me. Take it from a master. Marshall Ganz is one of the most influential people you’ve never heard of. If you have heard of him it’s probably because he helped Cesar Chavez unionize California farm workers. These are his thoughts on moving people with your story, applied to communicating data science.

Challenge, choice, outcome

A challenge in the face of some urgency sparks interest. Facing a challenge, the protagonist makes some choices, and those choices lead to an outcome. That’s the crucial part of your data story – challenge, choice, and outcome. I’m excited to hear the story just articulating that much.

My colleague, Mark Wissler, recently wrote about making an image recognition app in an hour. It wasn’t just a tutorial. It was an interesting story that began with a challenge, paraphrased, “There are great open source neural network technologies that allow a computer to identify the objects in an image. How do I kick the tires?”

Mark chose to rapidly prototype an image recognition app. He chose a couple neural networks technologies to try out and which adorable animal images to test them with. The outcome was a working web application that consumes an image file and identifies what’s in it. Well, almost:

GoogleNet Image Recognition Test Exaptive Xap

The stories of now, us, and self

There may have been many challenges in a project. The right challenge to focus on is what Ganz calls the “story of now.” You spent a lot of time working with some data. What made it worth doing now?

Your audience also shares a story that provides context for the challenge and adds urgency. The “story of us” is the shared values and shared purpose that create some fellowship around that challenge.

Your main character also has a story, the “story of self.” What put him or her in a position to take on the challenge? Why is the challenge important to that person?

Mark began with a story of now, how neural networks are spreading like wildfire. He explained how it’s a technology that touches diverse industries, the story of us, and he told us what it meant to him to try working with it. His workmanlike choices and tidy code snippets composed an engaging plot in that context. Thousands of people have read his story.

To tell a gripping data story, your best material is just reality.

Anyone?

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