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The Art of Data Storytelling: How Data Scientists Can Communicate Impactful Insights

Last updated on: 
December 27, 2023
Abhinav Rawat
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About The Author!
Abhinav Rawat
Abhinav Rawat
Product Manager at Interview Kickstart. The skilled and experienced mastermind behind several successful product designs for upscaling the ed-tech platforms with an outcome-driven approach for skilled individuals.

Every day, several business decisions are driven by data. Currently, we hold more data than ever. From satellites to Fitbit, we can access a high percentage of complex data sets, also called big data.

To extract and infer actionable insights from all the present data, decision-makers and business leaders look up to data science professionals who use advanced technologies and methods to interpret and analyze the present data. The data science professionals convey their findings to the leadership in the form of data-driven decision-making. However, at the stage of translation, problems can arise very often. Poor storytelling is the reason behind it.

According to Forbes, on the importance of storytelling in data science: 'Many of the heavily recruited individuals with advanced degrees in economics, statistics or mathematics struggle with communicating their insights to others effectively and essentially telling the story of their numbers.'

One of the most important non-technical skills for data scientists is storytelling. Organizations have upskilled their data professionals by teaching them the skill of data storytelling.

This article covers the following topics-

  • What is Data Storytelling?
  • Importance of Data Storytelling
  • Data Storytelling- Audience Engagement
  • Data Storytelling- Key Steps
  • Excel Data Storytelling as a Data Scientist with IK!
  • FAQs About Data Storytelling

What is Data Storytelling?

Data storytelling is a data science skill that requires data, visuals and narrative to persuade decision-makers to take a certain action. Data scientists can bring data to life through data storytelling by transforming the data from mere statistics and figures into narratives that inform, inspire and persuade data scientists. They can engage the audience with well-crafted stories and meaningful context. Also, they bridge the gap between data and understanding, hence enabling their audience to make informed decisions and take significant action.

How to tell a story with data

Importance of Data Storytelling

Data storytelling is important to capture and maintain audience attention in this data-driven world where overloaded information is a continuous challenge. It goes beyond presenting data and transforming it into a meaningful context.

  • Making data relatable: Data storytelling can humanize data by offering real-world, context and relatable examples. Frame data within familiar scenarios as a storytelling technique to help your audience connect emotionally with the information.
  • Simplifying complex concepts: Storytelling with data can be overwhelming and tricky at the same time, especially while dealing with technical jargon or complex data sets. Data storytelling holds the power to simplify complex concepts and distill information into a clear narrative, making it easily accessible to the audience.
  • Enhancing retention and comprehension: It is easier for people to remember stories instead of raw data. By presenting data with a framework, you can engage multiple cognitive processes and make it easier for the audience to retain, comprehend and remember the information longer.
  • Influence decision-making: The power of Storytelling with data lies in its ability to affect decision-making. When presented in a relatable and compelling manner, data stories can switch opinions, drive meaningful changes and inspire action. You might have all the evidence in your dashboard, but it depends on you on how to convey those insights to your audience.

By harnessing the power of storytelling with data, scientists can cut through the noise, capture keen attention and leave a long-lasting impact with data-driven information and messages.

Data Storytelling- Audience Engagement

To cut through the power of narratives in data storytelling is crucial to engage the audience. When humans are drawn to stories, integrating narratives in your data presentation will create an emotional connection between your story and the audience. When you frame your data with a compelling story structure, you captivate the audience's attention from the start and keep them engaged till the end of your presentation.

Identify your audience for impactful storytelling
  • Ensure to craft a coherent and clear storyline: It is important for compelling storytelling with data. A well-structured storyline outlines a roadmap for your data presentation. Start with a captivating and engaging introduction, setting the stage with energy and clearly state the questions and problems addressed by you. Guide your audience through the data and ensure logical transition by maintaining a clear information flow. At the end, conclude with the main message or call to action.
  • The data point in the data storytelling acts as the main character: Identify the most impactful and relevant data points that support your overall message and align with your narratives. Ensure to highlight the insights that explain and reveal their significance to the audience and enable them to clearly understand the story behind the numbers.
  • Leveraging data representations and visuals in your storytelling: Data plays a crucial role in engaging the audience. Visualization acts as a potent tool to enhance the understanding of the data. Select the most appropriate visual format that clearly aligns with the narrative and helps in the effective communication of the insights. Utilize graphs, infographics, charts, and other visual elements For a more presentable way to explain your data. Make it easier for the audience to understand the information.
  • Use anecdotes, descriptive language and real-world examples: It makes the data more meaningful and relatable. The combination of storytelling data and case studies creates a powerful narrative, satisfying the audience and helping them connect with the information in depth.
  • Create a sense of suspense and curiosity: It is one of the most effective strategies to engage your audience. Throughout the presentation, drop in thought-provoking questions, reveal the data gradually and introduce unexpected and sudden insights. It keeps the audience actively involved and eager to indulge in the next piece of information.
  • Understand the knowledge, pain points and goals of your target audience: Draw your narratives according to the understanding. This personalized approach ensures that your data resonates with the specific concerns of your audience, making it more relevant and meaningful for them.
  • Incorporate real-life context as the key point to make your data impactful: When you relate your data to real-world scenarios and experiences, the audience connects with you very well. Make use of examples highlighting the practical implications of the data. It helps in bridging the gap between abstract numbers and the life of the audience. Hence increasing the engagement and understanding of the information.

Data Storytelling- Key Steps 

A number of frameworks have been designed for storytelling through data. Each framework aligns well with certain data. One of those frameworks has been listed below.

Key elements of Data storytelling
  • Define your problem: For data-driven storytelling, focus on one clear problem that has to be met with a resolution.
  • Analyze the data: Analysis helps you to monitor the correlations in your data. Then, you can consider casual relationships behind your data and bring in a solution to your problem.
  • Know your audience: Focus on your target audience and the data they really care about. When you understand your audience well, it helps you to connect with them emotionally. Only then can you motivate them to bring in a change with their actions.
  • Data narrative: This is the most crucial point. Here, you must take your numerical understanding and put it into words that the audience could easily understand. Your narrative must be a clear story, including the beginning, middle and end, along with characters and visual representations to make your storytelling more clear and appropriate.

Excel Data Storytelling as a Data Scientist with IK!

The art of data storytelling is extremely important for the data scientist. It empowers them to bridge the gap between the decision-makers and the data. With good data storytelling, data scientists can increase data literacy among organizations. By following key principles and practical tips, data scientists can effectively communicate impactful insights that drive informed decision-making and positive change. In doing so, they elevate the value of data and contribute significantly to their organizations' success. Effective data storytelling is not just a skill; it's a powerful tool for change. 

Nail your career as a data scientist and master data storytelling with the wide range of data science interview courses and videos offered by Interview Kickstart.

FAQs About Data Storytelling

Q1. How do you become a data storyteller?

Using tools like Tableau or Power BI, people can learn data storytelling. The key is to pick up what matters the most to your audience and explain it to them with clarity.

Q2. Is storytelling a part of data science?

Storytelling is a powerful tool used by data scientists to make their findings more relatable, impactful and memorable.

Q3. Is data storytelling a skill?

Data storytelling and communication are essential skills for people working with data and willing to share insights or drive action.

Q4. What are the elements of data storytelling?

Narrative, visuals and data are the 3 key elements of storytelling.

Q5. Can I make a good career in data storytelling?

With the right skills, practice, education and experience, one can make a good career in storytelling. The most essential element is to engage your audience and draw their attention towards your storytelling presentation to bring them into action.

Posted on 
October 7, 2023

Abhinav Rawat

Product Manager @ Interview Kickstart | Ex-upGrad | BITS Pilani. Working with hiring managers from top companies like Meta, Apple, Google, Amazon etc to build structured interview process BootCamps across domains

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