Lecture 5 Data Visualisation

Data Visualisation
Psychology of Data Visualisation
Charts
Bits and Pieces

@Victoria UniversityBCO6007 Business Analytics

Audience Considerations

Common Data Visualisation Issues

Why Data Visualisation?
A picture is worth 1,000 words

Why Data Visualisation

This process consists of the following six fundamental stages:
1. Determine your message and identify the data necessary to
communicate it.
2. Determine if a table, graph, image or combination is needed to
communicate your message.
3. Determine the best means to encode the values.
4. Determine where to display each variable.
5. Determine the best design for the remaining objects.
6. Determine if particular data should be featured above the rest, and if so,
how.
Few

In the Beginning

William Playfair 1786
Trade balance

John Snow 1854

The Value of Data Visualisation

Exploration or Explanation?

Member Engagement (Harvard Business Review)
https://hbr.org/2013/04/when-visualizing-data-you-have

Why the visualisation
What am I looking at?
Why are you showing it to me?
Examples

Youth Unemployment Rates in Europe

Why are you showing me?
Youth Unemployment Rates in Europe
Historically high and dividing Europe

Memory

Hick’s Law

Working Memory

Chunking

More details

Pre-attentive Processing
Pre-attentive processing is the unconscious accumulation of
information from the environment. All available information is pre-
attentively processed. Then, the brain filters and processes what is
important. (Wikipedia)

Preattentive Processing
Attentive Processing
Preattentive Processing
Goal: How many 5’s

Compare and contrast objects to make a point

Face of Meth Campaign
2001 2004 2006

Group objects so that relationships between the elements becomes
clear

Relationships

Break elements down so that the individual parts become clear

CO2 per capita emissions per country

Pictorial Representations

Raleigh Bicycle – exploded

Storyboard a narrative so that it unfolds in a logical way

Create cutaways to see inside an object

Measure or compare

Scale is relative

Label Parts

Location

Colour

Interference Effects

Colour
Use Colour sparingly
Use 2 colours at most where possible
Avoid colour gradients

Smartphones Dominating Sales

Smartphone Dominating sales

Avoid Colour Gradients

Colour Blind – 8% Males

Deuteranopia Tritanopia
Protanopia

Tables Vs Charts
Tables
Need to looked up individual
values
Data needs to be precise
Charts
The message you wish to
communicate resides in the
shape of the data

Business Data Relationships
Time-Series Relationships
When quantitative values are expressed as a series
of measures taken across equal intervals of time,
this relationship is called a time series.
Ranking Relationships
When quantitative values are sequenced by size,
from large to small or vice versa, this relationship is
called a ranking.
Part-to-Whole Relationships
When quantitative values are displayed to reveal the
portion that each value represents to some whole,
this is called a part-to-whole relationship.

Business Data Relationships
Deviation Relationships
When quantitative values are displayed to feature
how one or more sets of values differ from some
reference set of values, this is called a deviation
relationship.
Distribution Relationships
When we show how a set of quantitative values are
spread across their entire range, this relationship is
called a distribution.
Correlation Relationships
When pairs of quantitative values, each measuring
something different about an entity are displayed to
reveal if there is significant relationship between
them.

Encoding Quantitative Data in Charts
Recommended

Not Recommended – 2 dimension

Use line charts to show time series
Notes on Matters Affecting the Health, Efficiency, and Hospital Administration of the British Army and sent to Queen Victoria in 1858

A better visualisation

Enrolments
2011, 45
2012, 48
2013, 55
2014, 50
Enrolments By Year
ERP, 50
MBA, 45
Accounting
, 43
Marketing,
20
2014 Enrolments By Course
 

What is the problem?

NO 3D!

Reporting Guidelines - Charts

Label axis

Always Scale to Zero

Direct labelling

Andrew Ablea

Reduce Data Ink / Non data Ink Ratio

Maps

Maps
Mercator map accuracy?

Resources
http://labs.juiceanalytics.com/chartchooser/index.html
Google Charts
Stephen Few
SlideShare

Lecture 5 Data Visualisation

Recommended

Recommended

More Related Content

Similar to Lecture 5 Data Visualisation

Similar to Lecture 5 Data Visualisation (20)

Recently uploaded

Recently uploaded (20)

Lecture 5 Data Visualisation