Course Overview

Well told data stories are change drivers within the modern organisation. But how do we find the most important insights in our business data and communicate them in a compelling way? How do we connect the data that we have to the key underlying business issue?

This course takes students from the fundamentals (what should we be measuring and why?) through to the elements of good visualisation design (what does a good chart look like?) through to proficiency in data storytelling. By the end of the course, students will know how to produce engaging, cohesive and memorable data stories using Excel and PowerPoint.

Who is this course suitable for?

This is our most popular course. It’s suited towards any professional, who works with data and charts. If you need to tell better stories with your data, then this course is for you.

Course Objectives

  • Provide participants with a grounding in the four ‘keys to data storytelling’ – Audience, Data, Visuals and Narrative
  • Provide participants with a methodology for selecting the right chart for a particular set of data
  • Provide participants with industry best practices for the most common chart types (including the bar, line and pie chart)
  • Provide participants with an understanding of the “Gestalt” principals of perception and how they can be used to focus audience attention
  • Provide participants with an overview of the scientific research surrounding chart design, including work from Edward Tufte

Participants who complete this course will be able to:

  • Design aesthetically pleasing data stories that adhere to the principals of good design
  • Select an appropriate chart type for a given set of data (e.g. When to use a bar chart versus a pie chart or a line graph versus a stacked bar chart)
  • Create data stories that ‘get to the point’ and utilize good design to focus audience attention on the matters of most importance


  • None.

Required Laptop Specs

  • 2GB RAM
  • Either Mac or Windows operating system

Software Requirements

  • Any data visualization software package (e.g. Excel, Tableau, PowerBI, Qlik, R, Python) and PowerPoint