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Course Outline
Introduction to Data Storytelling
- The definition of data storytelling and its significance.
- Key components of effective storytelling: narrative, visuals, and data.
- Typical use cases in public and corporate environments.
Understanding Audience and Context
- Identifying the target audience and their requirements.
- Designing content for technical versus non-technical stakeholders.
- Establishing the appropriate tone: persuasive, explanatory, or exploratory.
Selecting Appropriate Visuals
- Criteria for choosing bar charts, line graphs, scatter plots, and other visual types.
- Avoiding common errors in visual encoding.
- The role of color, layout, and hierarchy in narrative design.
Building the Narrative Structure
- Defining the core insight or “so what” of the data.
- Techniques for storyboarding and visual sequencing.
- Incorporating annotations and visual cues to guide attention.
Practical Tools and Methods
- Essentials of Excel, Power BI, Tableau, and Google Data Studio.
- Storytelling through slide-based presentations and dashboards.
- Utilizing templates and reusable structures for efficiency.
Workshop and Critical Review
- Collaborative analysis of example stories.
- Comparing visual transformations before and after refinement.
- Peer feedback sessions on draft storyboards.
Conclusion and Future Directions
Requirements
- A solid grasp of fundamental data visualization concepts.
- Practical experience working with charts, graphs, or dashboards.
- Familiarity with spreadsheets or visualization software.
Target Audience
- Data analysts.
- Public sector communicators.
- Policy advisors and managers responsible for interpreting data.
14 Hours
Testimonials (3)
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Bame Duncan Koko - Bentel Technologies (Pty) Ltd
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Tshering Dorji - Druk Holding and Investments
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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.
