How to tell a Data Story with Data & Visualization

In business, making good decisions depends on having the right information. But it's not just about having information and data; it's also about presenting it in a way that makes sense to people. If you can't make the information relatable to your audience, they might not care about it. That's where data storytelling comes in – it's the skill of turning data into a compelling story that motivates people to take action.

In this blog, we’ll explore what a data story is? And how to create one? Along with the important tools and resources.

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What is a Data Story ?

Data story is the idea of creating an interesting story using complicated data and visuals. This story is crafted to influence a specific audience.

Data storytelling isn't just about showing numbers and charts. It's about turning data into a story that makes sense and captures people's attention. It's like using data to tell a powerful story that informs, convinces, and encourages action.

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Why Does Data Storytelling Matters?

Good data storytelling helps connect data with decision-making and offers several advantages:

‍1. Clearer Understanding: It makes complicated data easier to understand, so everyone involved can see what it means and what to do about it.

2. Better Decisions: By presenting data in a convincing way, it helps decision-making by ensuring choices are based on solid evidence and insights from the data.

3. Encouraging Action: Data stories inspire people to do something about the information, leading to positive changes and outcomes.

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Data story v/s Data Visualization

Data storytelling and data visualization are closely connected, but it's important to understand their different roles in communicating with data:

• Data Visualization: It is the process of presenting data in a visually appealing format, using charts, graphs, maps, and other visuals to help people understand it better. 

• Data Storytelling: It's the skill of combining data visuals with a story to create an interesting and meaningful narrative that communicates insights in an engaging way.

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How to tell a good Data Story?

How do you find a good story, and, most importantly, how do you tell it well? Follow the steps below to begin. Although data storytelling can differ in its technical aspects and field, there are essential components that can be used for any successful data story:

Step 1: Find the Data story

Before you create a data story, figure out what the data is saying. If you find a connection or cause-and-effect in the data, that's like identifying the Message of data story you want to deliver. It can help in building the beginning point of a story that you can share with a bigger group, even if they have different technical backgrounds.

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Step2 : Know your audience

When telling a data story, always consider your audience. Make sure your story is relevant and interesting to them. Think about who they are, what they care about, and what they already know. Tailor your story to match their interests and background, whether they are executives focused on business implications or a data science team interested in statistical details. This ensures your data story has the impact you want.

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Step 3: Crafting a Narrative

Make a clear and interesting story with a logical order. Start by explaining the background, then show the data, point out the important discoveries, and finish with suggestions for what to do next. This way, your audience can easily follow the story and understand what actions to take based on the information.

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Step 4: Visualize Data Effectively

Using visuals can make your information more engaging and easier to understand, especially when talking to people who may not be familiar with technical details. When you tell a story with data using visuals, it helps simplify the information, point out the most important data, and get your message across faster.

You can choose from various types of visualizations, such as flowcharts, bar graphs, infographics, road maps, pie charts, and scatterplots. It's important to use visuals wisely and not overload your audience with too much information. The goal is to enhance understanding and complement your narrative without confusing your audience.

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Step 5: Tools and Resources

There are many data visualization tools available in the market that can help you make interactive visuals. Here’s a list of some popular tools:

Tableau

• What is it? Tableau is a tool that helps you create visual representations of your data, like charts and graphs. It's user-friendly, letting you make interactive dashboards without needing advanced technical skills.
• Features: You can easily arrange and display data in a way that's easy to understand. It works with different types of data sources, making it versatile for various needs.

Learning resource: Link

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Power BI

• What is it? Power BI is a tool by Microsoft that transforms data into reports. It's useful for businesses to analyze and track important information.
• Features: It lets you make reports that update in real-time, analyze and shape data, and easily share your reports with others.

Learning resource: Link

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Qlik Sense

• What is it? Qlik Sense helps you explore and analyze data to find patterns and insights. It's designed for those who want to interact with data and create their own dashboards.

• Features: You can easily navigate and analyze data, discover hidden patterns, and create customized dashboards to share your findings.

Learning resource:

1. Qlik portal: Qlik Learning

2. Youtube: Link

3. Courses: 

1. Qlik Sense for Beginners: Analyze and Visualize Data by coursera
2. Qlik Sense Certification Training by intellipaat

These tools are practical aids for working with data, offering different features to suit various needs and preferences. Choosing the right tool depends on factors such as the complexity of the data, the desired level of interactivity, and the specific needs of the audience.

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Step 6: Real-World Examples

Many companies use data storytelling to connect with people and make a difference. By telling stories with data, they can grab attention and create a meaningful impact.

Here we’re analysing some successful data stories:

1. Call Centre Analysis

You're looking at data about a call center's performance. There are different charts showing how happy customers are, like one for each topic they talked about. You can see the percentage of happy and unhappy customers for each topic, as well as the total number of satisfied and unsatisfied customers. By looking at these smaller stories together, you get a big picture of how well the call center is doing and where improvements might be needed. It's like putting all the pieces together to understand the whole story of customer satisfaction.

Source: Link

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2. Animated sport results

In the sports world, picture animated graphs that quickly show you how a game is going. These visuals use different styles to represent scores, making it more exciting than a regular scorecard. They help you follow the game in a fun and easy way, like bringing the action of a game right to your screen!

Source: Link

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3. Analyze your office365 in Power BI

You have a dashboard that shows all your important information in one place. Instead of overloading it with details, keep it simple. Start with a brief sentence introducing the topic and use a clear, easy-to-understand graphic to tell a short data story. For instance, you could begin by saying, "Our sales increased by 20% last month," and support it with a graph showing the upward trend. This straightforward approach quickly conveys the key message without overwhelming the audience.

Source: Link

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Future Trends

The future of telling stories with data looks really exciting! New technologies like artificial intelligence (AI), augmented reality (AR), and virtual reality (VR) are going to change the way we share and understand information. Here’s a brief overview of these emerging trends:

1. Artificial Intelligence (AI)

AI enables storytellers to focus on crafting narratives and drawing meaningful conclusions from the data. AI can tailor stories according to individual preferences and needs, providing a more personalized and relevant experience for the audience. This ensures that the information presented is more likely to resonate with each viewer.

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2. Augmented Reality (AR)

AR makes data exploration more interactive by allowing users to engage with information directly. This hands-on approach fosters a deeper understanding of the data and encourages active participation in the storytelling process.

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3. Virtual Reality (VR)

VR creates an immersive environment where users can step into a virtual space to explore data. Users are more likely to remember information presented in a VR environment compared to traditional methods, making data storytelling more impactful over the long term.

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4. Combination of Technologies

Combining these technologies allows for a comprehensive storytelling experience. AI can analyze data and generate insights, AR can overlay contextual information onto the real world, and VR can provide a deeply immersive exploration of the data. This combination creates a multi-dimensional and compelling narrative.

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Conclusion

In summary, data storytelling is about turning complicated data into a clear and interesting story that helps people make better decisions. By following steps like finding the main message in the data, knowing your audience, and using visuals effectively, you can create stories that everyone can understand. Real-world examples show how companies use data stories, and future trends like AI and AR promise even more exciting ways to share and understand information. In a world driven by data, learning to tell compelling data stories is a valuable skill for success.