Introduction

What you're holding isn't just another book about the general concepts of data storytelling or a set of strategies for best visualizing your data. This book takes you far beyond the basics, equipping you with a proven framework borrowed from the world of cinema and literature-where stories captivate hearts and minds. Step by step, you'll learn how to craft data-driven stories that mirror the structure of great films and novels. You'll understand how to build characters (yes, even in data!), create a gripping plot, and arrange your narrative into a sequence that resonates with your audience. The inspiration for this book is simple: As data storytelling becomes increasingly essential in today's world, there's a pressing need for a guide that not only explains why stories matter but shows you exactly how to tell them. This is that guide.

I have always had a passion for stories, but until I met my Italian teacher in high school, I never knew how to organize and tell them following a logical structure. I remember feeling incredibly frustrated when I wrote stories that started and never finished or went on too long in the introduction and ended suddenly. I crafted very unbalanced stories. Even at school, the essays I did in class weren't that great. They had no structure; they talked about everything and nothing. Then, a flash of genius: My Italian teacher one day explained how to structure a story. From that day, I learned to write balanced, well-organized stories that follow a logical thread. I was only 15 years old. Many years have passed since then, but the desire to tell stories is still alive.

This book derives from the desire to share what I have learned with you, dear reader, to ensure that your data-driven stories are also structured, balanced, and follow a logical thread from beginning to end. Surely, you already know how to analyze data, and perhaps you also know how to present it appropriately. But have you ever thought about organizing your data precisely like a story with characters and a plot? Have you ever thought each story phase must last a certain time to be balanced? Have you ever thought that in order to make the audience listen to you while presenting your story, you must create a certain suspense? In one sentence, have you ever thought about designing your own data-driven story using the techniques that screenwriters, directors, or novelists use?

Well, in this book, you'll do just that: apply cinematic techniques to data storytelling! You will extract a hero from the data, a sidekick, and even an antagonist. You will build a plot based on the goal you want to achieve and structure it in three acts, just like screenwriters and novelists do. Each act will play a role in the story.

Throughout the book, I will use the story of rising temperatures in recent years as an example. I am not an environmental expert, so the example is only for demonstration. If you find any inaccuracies, please be patient and possibly report them to me through the contacts you see in this book.

So, are you ready to face this journey together?

What Does This Book Cover?

This book covers the following topics:

• Chapter 1: Why You Need to Become a Data Storyteller

  This chapter introduces the concept of data storytelling and explains why it is essential for communicating insights effectively. Data storytelling differs from data reporting and presentation in that it focuses on creating a narrative involving a "hero" and a "plot." Unlike simple data presentations, data storytelling constructs a coherent story around data points, highlighting the people, events, and transformations the data represents. The chapter emphasizes that stories are powerful because they resonate emotionally, creating a bridge between the storyteller and the audience.

• Chapter 2: The Role of the Storyteller

  This chapter explores the qualities of a great data storyteller, likening their role to a director who must make data the focus rather than themselves. It identifies three types of storytellers-apathetic, authoritarian, and authoritative-and emphasizes the importance of being authoritative by engaging, collaborating, and building trust with the audience. Essential skills for great data storytelling include humility, sincerity, vulnerability, empathy, flexibility, openness, and patience. The chapter also outlines three roles a storyteller can play-external, internal, or absent-and discusses synchronous and asynchronous storytelling methods.

• Chapter 3: Making a Successful Data-Driven Story

  This chapter delves into the "making" phase of creating a data-driven story, focusing on planning and structuring the narrative through three essential stages: preproduction, production, and postproduction. Preproduction requires selecting a theme, defining the subject, and planning scenes. Production is the story implementation and can be done using any tool. The final step, postproduction, refines and organizes the story by selecting and polishing scenes, ensuring smooth transitions, and enhancing visual and narrative clarity.

• Chapter 4: First Act: Defining the Hero

  This chapter focuses on the foundational aspect of data storytelling: defining the hero. A hero in data storytelling differs from literary heroes, as they emerge directly from the data rather than from the imagination. Heroes in data stories are characterized by their quest for an "object of desire" but face obstacles that hinder their journey. Unlike traditional storytelling, the hero in data storytelling must be grounded in real-world elements, either human-like (connected directly to people) or non-human-like (such as abstract concepts or phenomena).

• Chapter 5: First Act: Defining the Sidekick

  This chapter explores the role of the supporting character (i.e., the sidekick) in data storytelling, emphasizing that while the hero remains central, a well-crafted sidekick adds depth and resonance to the story. In data storytelling, a sidekick can serve several functions, from being a confidant who reveals the hero's inner thoughts to acting as a proxy for the audience, simplifying complex data.

• Chapter 6: Second Act: Defining the Problem

  This chapter centers on defining the problem in data storytelling, which is essential for crafting a compelling narrative. A hero's journey in storytelling only gains meaning with a clear problem that needs solving. Without a problem, there's no story-just a straightforward data presentation. This chapter explains the importance of the problem and describes how to identify and describe it.

• Chapter 7: Second Act: Defining the Antagonist

  This chapter defines the antagonist in data storytelling and structuring the story's second act. An antagonist in storytelling opposes the hero and heightens the story's conflict, making the hero's journey to achieving their goal more compelling. In data-driven stories, antagonists aren't just villains but can be forces, circumstances, or even internal conflicts that create obstacles for the hero.

• Chapter 8: Third Act: Setting the Climax and Next Steps

  This chapter delves into the structure and elements of the third act in data storytelling, which is critical for resolving the story's tension and providing a satisfying conclusion. Known as the climax phase, this act includes a series of steps to bring the story to its peak: the Dark Night, the Climax, and the Next Steps. Together, these elements provide closure, impact, and motivation for the audience to take action based on the story's message.

• Chapter 9: From Making to Delivering a Data-Driven Story

  This chapter discusses the transition from creating a data-driven story to effectively delivering it, focusing on crafting and adapting the story for the audience. With the story completed, the delivery phase involves tailoring it to the specific audience. The chapter emphasizes that while the story's core remains unchanged, its presentation and emphasis should adapt to the audience's expectations and knowledge level.

• Chapter 10: What the Audience Wants and Knows

  This chapter begins by underscoring that every audience is unique. Even a small group may consist of individuals with varied responses shaped by their personal beliefs and backgrounds. Therefore, effective data storytelling involves recognizing and respecting this diversity while striving to engage each person individually. This understanding is foundational to audience analysis, a critical skill in storytelling that involves identifying the characteristics, interests, and knowledge levels of different audience segments.

• Chapter 11: What the Audience Thinks

  This chapter continues the story adaptation to the audience. While the previous chapter focused on the audience's needs and knowledge, this chapter focuses on the audience's perceptions, which specify how the audience behaves after encountering the story.

• Chapter 12: Retelling the Story

  This chapter highlights the importance of repeating data-driven stories to overcome the forgetting curve, which causes most people to forget 90 percent of what they hear within a week. Retelling through varied channels and formats keeps the message alive, helps audiences internalize it, and broadens its reach. Techniques...