Learn more about data storytelling, including why it is important for clearly sharing data, the key parts of creating strong stories with data, and the types of jobs that often use this useful skill.

Data can offer valuable information, but making sense of what it means requires the ability to explain it clearly—especially to people without a technical background. That is where data storytelling comes in. Data storytelling is the process of building a story around data to share insights in a way that is more interesting, clear, and easier for people to understand.

While data storytelling and data visualization are related, they are not the same. Data visualization focuses on making visual or graphic displays of data. On the other hand, data storytelling is more about using data to communicate insights to others, often using visuals as part of the story.

In this article, you will learn more about data storytelling, why it matters, and tips to help you create your own data story.

What is data storytelling?
Data storytelling is the practice of building clear and engaging stories to share the meaning behind data with others. The goal is to take complex information and present only the most important parts in a way that is easy for people to understand through a well-thought-out story.

Examples of data storytelling
In many ways, data storytelling is like any other form of storytelling: a story unfolds through a series of steps. The difference is that, in data storytelling, these steps are made up of data points instead of characters or events.

Here are some examples:

• A social media manager shows how one post led to a big jump in user interaction compared to others. They arrange the data to make the reason for that post’s success clear to their team.
  
• A public health group publishes a report combining personal stories from people affected by a disease with data on infection rates, hospital visits, and trends by age group.

Why is data storytelling important?
Data storytelling helps share insights in a way that others can understand and use to take action. Studies show that stories can activate certain parts of the brain that support long-term memory, so people are more likely to remember what they learn from a story than from just plain numbers.

Along with helping people remember the information, storytelling makes data easier to follow. When people clearly understand what the data means, they feel more sure of their choices and can make decisions faster.

What is data storytelling used for?
There are many ways to use data storytelling. Inside your company, you can use it to share results with your team. For example, if sales for a product drop, you can use data storytelling to explain the situation and show why action is needed.

You can also use it to reach people outside your business. For example, you could tell a data story to show why choosing your service or product over a competitor’s can lead to better outcomes.

3 Key Parts of Storytelling with Data

Good data storytelling includes three main parts: data, visuals, and narrative. Here’s how each one helps shape your data story:

1. Data
You need to understand your data before you build a story from it. The insights from data analysis are the base of your story. This means you must first go through the data set to find the most important points. To do this well, you need to know how to work with data and how to draw insights from it.

2. Visuals
Visuals not only make your story more appealing, but they also help you explain your points more clearly.

You need to choose the right type of visual for your data. Think about who your audience is, what question the data answers, how much data you are working with, and what type of data it is. For example, you might use bar charts to show numbers or maps to explain location-based data.

3. Narrative
The narrative is what connects everything. Think about your audience and how to keep them interested while telling the story.

A strong narrative should have a few key features. First, it should include a “hero,” which could be a person or team working toward a goal—like improving customer satisfaction. Your story should have a clear beginning, middle, and end that makes sense and is easy to follow. Also, aim to make the story something your audience can connect with. This helps them care more and understand the message better.

Pros and Cons of Data Storytelling

There are many benefits to using data storytelling. It helps people understand and remember data more easily. It also makes them more likely to take action and supports better decision-making based on data. Over time, it can also improve your team’s understanding of how to use data.

Still, there are some challenges. One issue is choosing the wrong kind of visual, which can make the message confusing or incorrect. Another challenge is that there are not enough people with strong data skills. If you build your skills in data storytelling, you could become more in demand in the job market.

How to Get Started in Data Storytelling

To grow your data storytelling skills, start by learning how to analyze data. This includes knowing how to use computer programming and how to create visuals from data.

Some popular languages for working with data are SQL, Python, Julia, and R. To create good data stories, also learn how to use data visualization tools. Tableau is one option for making charts like bar charts, interactive visuals, and flow diagrams. Other good tools include Microsoft Power BI and Excel. You can also use Python libraries like Matplotlib or R libraries like ggplot2 to build visuals from your data.