Unit 1: Introduction to data visualization
Data Visualization notes · PTU syllabus (UGDSE103)
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Unit summary
A good chart can explain in seconds what a table of numbers hides. This unit defines data visualisation, explains its role in decision-making, the types of data it handles, the visualisation process, and its challenges and limitations.
After this unit you can
- Define data visualisation and explain its importance
- Match chart types to numerical, categorical, temporal and geographical data
- Describe the steps of the visualisation process
- Discuss the challenges and limitations of visualisation
PTU syllabus topics
- Definition and importance of data visualization
- its role in decision making
- types of data (numerical, categorical, temporal, geographical)
- the visualization process (collection, exploration, analysis, visualization, interpretation)
- challenges and limitations
- 1Collect
- 2Explore
Look for patterns and gaps
- 3Analyse
Find the insight
- 4Visualise
Choose the right chart
- 5Interpret
Explain what it means
Topic 1
What is data visualisation?
Data visualisation is the graphical representation of data using charts, graphs, maps and dashboards so that patterns, trends and outliers are easy to see. Importance: quick understanding, spotting trends and anomalies, comparing values, communicating findings to non-technical audiences and supporting faster decisions.
Example
A sales manager scanning a line chart can spot a fall in March immediately — the same insight could take minutes to find in a table of 12 × 20 numbers.
Topic 2
Types of data and suitable visuals
| Data type | Example | Suitable charts |
|---|---|---|
| Numerical | Marks, revenue | Histogram, box plot, scatter plot |
| Categorical | Course, region | Bar chart, pie chart, treemap |
| Temporal (time) | Monthly sales | Line chart, area chart |
| Geographical | Sales by state | Choropleth map, bubble map |
Topic 3
The visualisation process
- 1Collection
Gather data from sources
- 2Exploration
Understand structure and quality
- 3Analysis
Find patterns and relationships
- 4Visualisation
Choose and design charts
- 5Interpretation
Draw conclusions and act
Topic 4
Challenges and limitations
- Misleading charts: truncated axes, 3-D effects and distorted scales exaggerate differences.
- Too much information: cluttered dashboards hide the message.
- Poor data quality produces wrong conclusions however good the chart.
- Wrong chart choice: pie charts with too many slices, line charts for unrelated categories.
- Accessibility: colour-blind viewers may not tell red from green.
Exam tip
Mention "Start bar chart axes at zero" as a rule to avoid misleading visuals — a common short-answer point.
Key terms
- Data visualisation
- Representing data graphically
- Temporal data
- Data recorded over time
- Choropleth map
- A map coloured by data values for each region
- Outlier
- A value far from the rest
- Dashboard
- A single view combining several visuals
Quick revision
- Visuals reveal patterns, trends and outliers fast.
- Numerical → histogram; categorical → bar; temporal → line; geographic → map.
- Process: collect → explore → analyse → visualise → interpret.
- Avoid truncated axes, clutter and 3-D distortion.
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.Define data visualisation.
- Q2.Which chart suits time-series data?
- Q3.List the steps of the visualisation process.
- Q4.Give two ways charts can mislead.
- Q5.What is a choropleth map?
Long-answer questions
- Q1.Explain the importance of data visualisation in decision-making.
- Q2.Explain the types of data and suitable visualisations for each.
- Q3.Discuss the challenges and limitations of data visualisation.
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