Avoiding Common Pitfalls in Data Storytelling

One way to approach storytelling is to do everything right. In several previous posts, including Data Storytelling and Structuring Your Data Story, I offer guidance on how to tell a data story the right way. Another approach is to avoid the most...

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The Power of Metaphors in Data Storytelling

A metaphor is a figure of speech used to describe an object or action in comparison to something that is dissimilar but has something in common. Here are a few examples:

  • Living on the razor's edge
  • Swimming with the sharks
  • Climbing the...
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Getting Personal with Data Storytelling

In Paul Smith's book Lead with a Story, he describes how the CEO of Procter & Gamble would come to presentations and sit with his back to the screen. Smith describes how he delivered a presentation to the CEO, who didn't once turn around to...

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Making Your Data Story Pop!

In several previous posts, including Data Storytelling, I cover the essential elements of a data science story, but storytelling goes beyond the story itself. It's the telling of the story that separates a gripping story from one that is merely an...

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The Data Story’s in the Details

In a previous post, Structuring Your Data Story, I provide guidance on the big picture of storytelling — nailing down the five key elements of a story: characters, setting, plot, conflict, and resolution. However, if you've ever heard...

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Sizing Up the Audience for Your Data Story

When your data science team is composing a story, it needs to understand the audience in order to connect with it on a personal and emotional level. I witnessed this myself when working for a large political campaign and observed two candidates...

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Data Storytelling

Have you ever watched a movie that had great actors, costumes, sets, cinematography, and special effects but a terrible plot? If so, you probably left the movie theater or walked away from your television feeling disappointed. On the other hand,...

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Conducting Data Analytics in Sprints

In my previous post, Building a Data Science Life Cycle (DSLC), I encourage you to adopt a structure for your data team's activities that is conducive to the type of work it does — exploration. I refer to this structure as the Data Science...

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Approaching Data Analytics with the Right Mindset

Many organizations think that data science is solely about crunching numbers. Put a bunch of analysts in room, give them access to the data, and within a reasonable period of time, they’ll report back with their numbers and graphs revealing...

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Defining Areas of Responsibility for Your Data Science Team

Scottish novelist and folklorist Andrew Lang once wrote, “I shall try not to use statistics as a drunken man uses lamp-posts, for support rather than for illumination.” Unfortunately, many organizations that consider themselves...

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