Storytelling with Data

Audience:

Professionals who want to strengthen their ability to work with data and create clear, effective visualizations

Duration: 1 Day

Delivery: Virtual (2 half days) or in-person (1 full days)

Course description:

Poorly designed visualizations—whether in charts, reports, dashboards, or presentations—can create confusion and, at worst, lead to misguided decisions. This course introduces participants to core principles of storytelling with data, best practices in visualization and design, enabling them to communicate insights more effectively. Whether working in Power BI, coding in R or Python, building charts in Excel, or presenting in PowerPoint, participants will learn to create clear, impactful, and meaningful visualizations.

Course overview:

  • How to storytell with data

  • Biases and risks

  • Learning from history

  • Human perception

  • How we visualize data (input, pre-attentive cognition, gestalt organization, attentive cognition)

  • Colour theory

  • Creating a narrative and story

  • Chart type deep dive

By the end of this course, participants will be able to:

  • Explain the core principles of data storytelling and why narrative structure improves comprehension

  • Identify common cognitive biases and risks that influence how audiences interpret data

  • Recognize historical examples of effective and ineffective data visualization and apply those lessons

  • Understand how human perception shapes the way people process charts, patterns, and visual cues

  • Apply principles of pre‑attentive attributes, Gestalt organization, and attentive cognition to improve clarity

  • Use colour theory intentionally to highlight insights, reduce noise, and support accessibility

  • Build a clear narrative arc that connects context, insight, and action in any data‑driven communication

  • Select appropriate chart types based on analytical intent, audience needs, and cognitive load

  • Design visualizations that communicate insights clearly across tools such as Power BI, Excel, R, Python, and PowerPoint

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