What Is Data Storytelling? Components, Advantages, & Examples


In today’s data-driven world, data storytelling is becoming increasingly vital for decision-making and business growth. Data analytics roles akin to market research analyst, financial analyst, and operations research analyst are getting prevalent as firms realize the importance of data-driven insights.

Based on U.S. BLS Occupational Outlook Handbook 2021-2031, these job roles are experiencing considerable growth:

These analysts employ various data storytelling techniques to perform effective analytics operations. Let’s discuss what data storytelling is, its major components and advantages, and should you are an analyst, how are you going to turn into higher at data storytelling.

What Is Data Storytelling?

Data storytelling involves analyzing data using visual and compelling narratives to speak data insights to stakeholders. An information storyteller explains the “why” in the information using visualization. The aim is to clarify the information attributes clearly and supply a meaningful context for what that data represents. Presenting the underlying insights in data and trends is essential for effective decision-making.

For instance, a financial analyst can show a candlestick chart to investors to exhibit the worth movement of a stock or asset. A candlestick chart visualizes the historical stock patterns using 4 trading indicators (“open price,” “close price,” “high price,” and “low price”) to predict the upcoming market trend.

A candlestick illustration showing an increasing and decreasing price trend. Wikimedia Commons

For a greater understanding, take a look at the bitcoin price candlestick chart below. The graph visualizes bitcoin prices for the primary two months of 2023. The green bars represent an increasing price trend, while the red bars show decreasing bitcoin price trend.

Bitcoin candlestick chart Jan-Feb 2023

Bitcoin candlestick chart Jan-Feb 2023

An important data storytelling aspect is that data storytellers need to know the business context and stakeholder requirements. Research shows that 60% of the investment done in data analytics goes to waste since the insights obtained don’t align with decision-making and business goals. Consequently, decision-makers only use 22% of the information insights they receive.

3 Major Components of Data Storytelling

Data, visuals, and narrative are the three essential components of knowledge storytelling. Let’s explore them further below.

  1. Data: Data storytellers gather and preprocess the information they should tell a story. They perform statistical evaluation and visualize key trends and patterns for thorough data evaluation.
  2. Narrative: Creating an enticing story and providing context to the important thing findings obtained from data is known as narrative. A very good narrative inspires the audience to take motion.

, a thought leader in business management, says:

  1. Visuals: An image is value 1000 words. Visualization adds weight to the narrative and creates an impactful data story. Visuals may be in the shape of graphs, images, or videos.

An information analyst can use an information storytelling framework like characters, setting, conflict, and determination to inform a compelling story. For instance, within the e-commerce domain, characters may be customers, the setting is an organization scuffling with customer retention, conflict may be an increasing churn rate, and determination is the set of steps the information storyteller suggests to cut back the churn rate.

How Can a Data Analyst Get Higher at Data Storytelling?

Understand Your Audience

Understanding the audience is the important thing to forcing data storytelling. Should you are talking to business executives, it could be significant to offer them with high-level evaluation and actionable insights for business strategy. But when talking to the team, you should explain the methods used to succeed in a conclusion intimately.

Select Appropriate Visualizations

Data visualization highlights different features of knowledge, akin to;

  • Comparison (Bar chart, line chart)
  • Relationship (Scatter plot, bubble chart)
  • Distribution (Histogram, scatterplots)
  • Composition (Waterfall chart, stacked area chart)

Understand what you are attempting to realize with data and what number of variables you’ve to contemplate. Select the very best visualization to convey your idea.

Avoid Clutter

Declutter the visualization by aggregating or removing information that just isn’t required. For instance, within the charts below, WGM, WIM, WCM, and WFM are the leading women titles in chess; the remaining data may be aggregated as “others”.

Unnecessary FIDE title labels on the x-axis

Unnecessary FIDE title labels on the x-axis


An easy-to-read aggregated bar chart

A simple-to-read aggregated bar chart

Use Vibrant Colours

Use color palettes accessible to everyone, including those that are visually impaired or color blind. Keep contrast in colours and avoid using the identical colours next to one another. As an example, within the bar charts below, the colour combination in the primary chart may be hard to differentiate in comparison with the second chart.

Difficult to interpret the chart due to color combination

Difficult to interpret the chart resulting from color combination


Easy to interpret the chart due to color combination

Easy to interpret the chart resulting from color combination

What Are the Advantages of Data Storytelling for Organizations?

Promotes Data Literacy Amongst Employees

Data storytelling can enhance the information literacy of the staff within the organization. Based on a survey by Accenture and Qlik, only 21% of employees feel confident in reading, analyzing, and discussing data. Hence, compelling data storytelling encourages them to explore and discuss data inside the organization.

Create Engaging & Useful Experiences for All Stakeholders

Understanding and grabbing the audience’s attention is critical to effective communication. The human brain processes visuals 60,000 times faster than text, and folks remember stories 22 times greater than facts. Hence, telling data stories to your product users or shareholders using compelling narratives and visualization may be highly engaging and beneficial.

Influence Decision-Making

Compelling data storytelling provides a latest perspective or uncovers hidden features. It communicates what must be done. It allows stakeholders to make informed decisions and take motion regarding their business strategy.

Data Storytelling – Way Forward for Data Analysts

Data storytelling is the art and science of communicating insights about data. As data keeps increasing exponentially and getting more complex, data-driven storytelling is becoming a necessary skill.

In a company, the role of knowledge storytellers is performed by data analysts or data engineers. Tools akin to Tableau and PowerBI enable data analysts to construct compelling visualizations and dashboards without much effort. In actual fact, Gartner estimates that by 2025 many of the data stories will probably be mechanically generated.

Data analysts should stay in contact with the newest trends and tools in the information analytics industry to inform impactful data stories. For more AI-related content, visit unite.ai.


What are your thoughts on this topic?
Let us know in the comments below.


0 0 votes
Article Rating
Newest Most Voted
Inline Feedbacks
View all comments

Share this article

Recent posts

Would love your thoughts, please comment.x