Unit 2: Visualization tools and storytelling
Data Visualization notes · PTU syllabus (UGDSE103)
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Unit summary
Many tools can create visualisations, each with strengths. This unit compares Excel, Tableau, Power BI and Python, and explains data storytelling — using narrative and context — along with best practices for dashboard layout and interactivity.
After this unit you can
- Compare Excel, Tableau, Power BI and Python for visualisation
- Apply the principles of data storytelling
- Design a clear dashboard layout
- Add useful interactivity to dashboards
PTU syllabus topics
- Overview and comparison of Excel
- Tableau
- Power BI and Python for visualization
- principles of data storytelling — narrative and context
- best practices for dashboard layout and interactivity
Comparison
Bar chart
Sales by region
Trend over time
Line chart
Monthly revenue
Part of a whole
Stacked bar or pie (few parts)
Market share
Relationship
Scatter plot
Ad spend vs sales
Topic 1
Visualisation tools compared
Excel
Familiar, quick charts and PivotCharts
Small data, everyday reports
Tableau
Drag-and-drop, beautiful interactive visuals
Exploratory analysis, presentations
Power BI
Integrates with Microsoft tools; strong data modelling (DAX)
Business dashboards and sharing
Python (Matplotlib, Seaborn, Plotly)
Full control, automation, large data
Analysts and data scientists
Topic 2
Data storytelling
Data storytelling combines data, visuals and narrative to communicate an insight that drives action.
- 1Context
Why it matters and for whom
- 2Conflict
The problem or change the data reveals
- 3Insight
The key finding, shown with one clear chart
- 4Resolution
What should be done
- 5Call to action
The decision you want
Example
"Admissions fell 12% in the northern region (context) mainly because enquiries dropped after a website change (insight); restoring the enquiry form (resolution) should recover them — approve the fix this week (action)."
Topic 3
Dashboard layout best practices
- Put the most important KPI at the top-left, where eyes land first.
- Follow a logical flow: summary → trends → details.
- Use 3–5 key visuals; avoid clutter.
- Keep colours, fonts and scales consistent; label axes and units clearly.
- Group related charts and leave white space.
Topic 4
Interactivity
- Filters and slicers (by region, product, date).
- Drill-down from year to month to day.
- Tooltips that show details on hover.
- Cross-filtering: clicking one chart filters the others.
Exam tip
Interactivity should answer the user's next question — not add effects for their own sake.
Key terms
- Tableau
- A drag-and-drop visual analytics tool
- Power BI
- Microsoft's business intelligence and dashboard tool
- Data storytelling
- Communicating insights through data, visuals and narrative
- Slicer
- An interactive filter control
- Drill-down
- Moving from summary to detailed data
Quick revision
- Excel quick; Tableau exploratory; Power BI business; Python flexible.
- Story: context → conflict → insight → resolution → action.
- Top-left = most important; 3–5 visuals; consistent design.
- Filters, drill-down, tooltips, cross-filtering.
Important exam questions
Practice questions written to the PTU exam pattern for this unit's syllabus: short answers (Section A style) and long answers (Sections B and C style).
Short-answer questions
- Q1.Compare Tableau and Power BI.
- Q2.What is data storytelling?
- Q3.Where should the most important KPI be placed on a dashboard?
- Q4.What is cross-filtering?
- Q5.Name two Python visualisation libraries.
Long-answer questions
- Q1.Compare Excel, Tableau, Power BI and Python as visualisation tools.
- Q2.Explain the principles of data storytelling with an example.
- Q3.Discuss best practices for dashboard layout and interactivity.
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