Data Storytelling Professional (DSP)
The Data Storytelling Professional (DSP) certification is designed to teach how to transform data into narratives that create real impact. While analysts and data scientists uncover valuable insights, these often fail to drive action due to a communication gap with decision-makers. This course bridges that gap by using storytelling as the link between data and decisions—blending logic, emotion, and visualization to inspire change.
ADDRESSED TO
This course is ideal for both technical and strategic profiles. It is tailored for data analysts, data scientists, machine learning engineers, statisticians, and data professionals who want to drive greater impact through their findings. It is also designed for executives, managers, communicators, journalists, and decision-makers seeking to understand how data can be turned into stories that inspire organizational change and action.
PURPOSE
The purpose of this certification is to:
- Learn how to lead change using data-driven insights.
- Understand why storytelling with data is more effective than isolated statistics.
- Explore the psychology behind data storytelling.
- Master the structure and components of a compelling data narrative.
- Apply best practices in data visualization.
- Recognize common cognitive biases and pitfalls when communicating data.
- Develop your own stories that drive clarity, impact, and action.
MAIN TOPICS
The course is structured into 9 thematic chapters that guide participants from understanding the power of storytelling to crafting their own impactful data stories:
Chapter 1: Introduction to Change and the Power of Data
- What is an insight and how to communicate it
- Data literacy for today’s economy
- Turning information into action
- Barriers to insight adoption and narrative solutions
Chapter 2: Core Elements of Data Storytelling
- Aristotle’s rhetorical triangle
- Explain, illuminate, and engage
- Using narrative to generate real action
Chapter 3: The Psychology of Storytelling
- Logic vs. emotion in decision-making
- How people react to facts versus stories
- Classic examples that reveal storytelling power
Chapter 4: Anatomy of a Data Story
- Foundations, structure, and visual anchors
- Direct vs. indirect communication
- Knowing when a story is needed
Chapter 5: Building Insight and Effective Narrative
- The 4D model for meaningful insights
- Avoiding data manipulation and bias
- Common fallacies and poor data practices
Chapter 6: Storytelling Structures in Practice
- Aristotle’s structure, Freytag’s pyramid, and Campbell’s hero’s journey
- The storytelling arc applied to data
- Common narrative types in data visualization
Chapter 7: Visualizations I – Foundations
- Visual attention principles
- Choosing the right chart for the message
- Aligning visuals with your core insight
Chapter 8: Visualizations II – Refinement
- Reducing noise and avoiding chartjunk
- Designing accessible, focused visuals
- Use of palettes, typography, layers, and clarity techniques
Chapter 9: Creating Your Own Data Story
- Identifying your “Aha Moment”
- Building a data-driven hero and storyline
- Writing the script and using analogies for deeper connection
Details
Duration:
Number of questions:
Minimum passing:
Pre Requirements:
No
Available languages:
Third chance (free):
Take your exam online.
$150.00
