Introduction to data storytelling

1. Introduction to data storytelling

Welcome, storytellers! My name is Leondra Gonzalez, and I'm excited to help you learn about the process of telling data stories.

2. What is storytelling?

...But what is data storytelling? To begin, we must first understand storytelling. Stories are engaging and have the unique ability to inspire audiences with compelling narratives. Books, film, TV, and even video games may come to mind as some of the more dominant forms of storytelling. These are some of the more common forms that we see on a daily basis. But there's more to the story! There is another form of storytelling to consider.

3. Data storytelling

You guessed it - data storytelling! Not unlike other types of stories, data storytelling is about conveying a concise, digestible story. Specifically, data storytelling is the process of communicating relevant, actionable insights in an understandable and widely accessible format. Some of the most common data story requirements include: A question or problem to solve, supportive and relevant data-driven facts, a story arc, and a call to action. However, there are more specific elements that we will discuss later in the course.

4. Three I's: Data story maturity

If you're wondering what's the difference between data stories and any other form of conveying analytical results, it's helpful to remember the 3 Is of data storytelling maturity. Each one reflects the outcomes of an analysis, becoming progressively more accurate and mature. The least mature example is "Informative". This is just raw numbers and facts. Next is "Interesting". This is a step closer to a data story. An interesting analysis is one with some trends and patterns, but not necessarily of immediate business value. Last is "Insightful". An insightful analysis is informative, interesting, useful and actionable. This often means the story provides a valuable insight.

5. Why learn storytelling?

This brings us to why data storytelling is so important. For starters, it's accessible and inclusive. This makes it easy to follow, allowing the audience to focus on the insights and not the complexity of the data or process. This is especially important for non-technical audiences. Furthermore, data stories are more engaging than raw information. A study by Skyword found that content with both words and visuals drive 34% more engagement than those with only text and numbers. This allows you, the storyteller, to convey value and impact, which is the ultimate goal for any analysis. This prompts your audience to act on your story, and make business decisions.

6. High demand skills

One study that sampled over 5,000 data job listings found that most of the top desired skills reflected communication aptitude. These skills include verbal, non-verbal, written, and visual communication. These are all skills necessary for being a data storyteller. In short, mastering the art of data storytelling is a stand-out skill for any data professional, advancing your technical skills from useful, to valuable.

7. Let's practice!

Now that you're acquainted with data storytelling, let's review some high-level concepts.

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