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Course Outline
Introduction to Data Storytelling
- Definition and importance of data storytelling
- Key components of effective stories: narrative, visuals, and data
- Common applications in public and corporate environments
Understanding the Audience and Context
- Identifying audience needs and expectations
- Designing for technical versus non-technical stakeholders
- Establishing the tone: persuasive, explanatory, or exploratory
Selecting Appropriate Visuals
- Guidelines for using bar charts, line graphs, scatter plots, and others
- Avoiding common errors in visual encoding
- Utilizing color, layout, and hierarchy in storytelling
Structuring the Narrative
- Defining the core takeaway ('so what') of your data
- Storyboarding and visual sequencing
- Employing annotations and visual cues
Practical Tools and Techniques
- Basics of Excel, Power BI, Tableau, and Google Data Studio
- Storytelling through slides and dashboards
- Leveraging templates and reusable structures
Workshop and Critique
- Group analysis of example stories
- Before-and-after visual transformations
- Peer feedback on draft storyboards
Summary and Next Steps
Requirements
- Familiarity with basic data visualization principles
- Experience working with charts, graphs, or dashboards
- Knowledge of spreadsheets or visualization tools
Audience
- Data analysts
- Public sector communicators
- Policy advisors and managers who interpret data
14 Hours
Testimonials (2)
Doing Exercise
Joe Pang - Lands Department, Hong Kong
Course - QGIS for Geographic Information System
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
