Data Visualization Data Storytelling 2 — Questions and Answers
Question 1: What is 'declarative visualization' in data storytelling?
- Charts that declare their data source
- Visualizations that present a clear, pre-determined message or finding to the audience (Correct answer)
- Charts requiring no interaction
- Visualizations created using declarative programming languages
Correct answer: Visualizations that present a clear, pre-determined message or finding to the audience
Declarative visualizations are designed to communicate a specific, pre-formed message and guide the audience to a particular conclusion.
Question 2: What technique involves guiding a viewer's attention to specific chart elements through visual emphasis?
- Data aggregation
- Highlighting or call-out techniques (Correct answer)
- Data normalization
- Axis truncation
Correct answer: Highlighting or call-out techniques
Highlighting uses color contrast, size, boldness, or annotations to draw the viewer's eye to the most important data points or trends.
Question 3: In data storytelling, what is the 'Martini glass' narrative structure?
- A structure shaped like a cocktail glass
- An author-driven sequence that transitions to open-ended user exploration at the end (Correct answer)
- A visualization shaped like a funnel
- A chart type for bar-like data
Correct answer: An author-driven sequence that transitions to open-ended user exploration at the end
The Martini glass structure guides the audience through a curated narrative first, then opens into free exploration — combining storytelling with interactivity.
Question 4: What is 'emotional resonance' in the context of data storytelling?
- Using emoticons in charts
- Connecting data to human experiences or stakes to make findings feel meaningful (Correct answer)
- Measuring user emotional response with biometrics
- Using warm colors in visualizations
Correct answer: Connecting data to human experiences or stakes to make findings feel meaningful
Emotional resonance is achieved when data stories connect numbers to real human impact, making abstract statistics feel tangible and motivating to the audience.
Question 5: What is a 'data-driven narrative' presentation technique?
- Reading data values aloud during a presentation
- Using sequential visualizations to walk an audience through evidence that supports a central message (Correct answer)
- Letting the audience choose which charts to view
- Automating slide generation from data
Correct answer: Using sequential visualizations to walk an audience through evidence that supports a central message
Data-driven narratives use a structured sequence of charts and explanations to build a logical argument, each visual adding evidence toward a central conclusion.
Question 6: What is the purpose of a 'call-to-action' at the end of a data story?
- Citing data sources
- Directing the audience toward a specific decision or next step based on the evidence presented (Correct answer)
- Summarizing all the charts shown
- Asking the audience for feedback
Correct answer: Directing the audience toward a specific decision or next step based on the evidence presented
A call-to-action converts data insights into decisions by explicitly stating what action the audience should take based on the evidence.
Data Visualization Data Storytelling 2
What is 'declarative visualization' in data storytelling?