Visualising Data

Objectives

By the end of the course, participants will be able to:

• Understand when and why data visualisation can be used.

• Recognise how audience, purpose and intended action influence visual design.

• Understand how different types of data affect the choice of visualisation.

• Select appropriate charts and visual approaches for different situations.

• Apply principles of visual perception and design to improve clarity.

• Use colour, position, size and other visual cues appropriately.

• Recognise the importance of logical structure and visual hierarchy.

• Reduce unnecessary clutter and complexity.

• Integrate words, labels and annotations effectively with visual information.

• Recognise common problems that can make charts and dashboards difficult to interpret or misleading.

• Develop visualisations that communicate insights and support decision-making.

These objectives reflect the aims and major themes of the existing course material.

Training Methodology

The course combines tutor-led explanation with examples, discussion and practical exercises. Participants are encouraged to think about data visualisation from the perspective of the person receiving the information rather than simply from the perspective of the analyst producing it.

Real-world examples are used to explore why some visualisations communicate successfully while others do not. Participants will have opportunities to critique existing visualisations, consider alternative ways of presenting information and apply the principles covered during the course to practical situations.

The course is deliberately not tied to a particular software package. The emphasis is on developing principles and judgement that can subsequently be applied whether participants are working in Excel, Power BI, Tableau or another visualisation environment.

Organisational Impact

Organisations increasingly rely on charts, reports, dashboards and visual summaries to communicate information and support decisions. However, increasing the quantity or sophistication of visual reporting does not automatically improve decision-making.

Participants will develop an understanding of how to create clearer, more focused and more accessible visual information. This can help organisations communicate analytical findings more effectively, reduce unnecessary complexity in reporting and focus attention on the information that matters.

The course also considers problems including distorted scales, inappropriate data, overloading visuals, poor data quality, excessive decoration and misleading presentation. This provides an important link between good visual design and the accurate and ethical communication of data

Personal Impact

Participants will develop greater confidence in deciding how information should be presented rather than simply accepting the default charts produced by software.

They will gain a practical framework for thinking about the audience, message, data and purpose before choosing a visualisation. They will also be better equipped to critically assess existing charts and dashboards, recognise weak or potentially misleading approaches and make informed decisions about how visual information can be improved.

Importantly, participants should leave the course understanding that an effective visualisation does not need to be complicated. Simplicity, relevance, accuracy and clarity are recurring principles throughout the course.

Who Should Attend?

This course is suitable for anyone who uses data to communicate information, including:

• Analysts

• Researchers

• Managers

• Information and intelligence professionals

• Performance staff

• Project and programme teams

• Public health professionals

• Healthcare professionals

• Business intelligence teams

• Staff who produce reports, presentations or dashboards

• Anyone who needs to communicate numerical information to others

The course is particularly useful for people who already work with data but want to improve how they communicate it, rather than learning a particular visualisation package.

Course Outline

The course will explore areas including:

• The purpose of data visualisation

• Understanding the audience and intended message

• Exploratory and explanatory visualisation

• Understanding data and data quality

• Data types and their implications for visualisation

• Principles of effective visual design

• Visual perception and cognitive load

• Colour, visual cues and visual hierarchy

• Structuring information and creating logical flow

• Selecting appropriate charts and visualisations

• Simple and more advanced visualisation techniques

• Geographic and flow-based visualisations

• Combining words and visual information

• Infographics and dashboards

• Reducing clutter and unnecessary complexity

• Common visualisation problems and misleading presentation

• Accuracy, relevance and ethical presentation of data

• Practical application through examples, discussion and exercises

Duration

1 day

Pre-requisites

None

No specialist visualisation software or previous knowledge of data visualisation is required.