Data Visualization for Business With Tableau

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Visualisation for Business

ANL 201

Advanced Data Visualisation Techniques

Study Unit 5

January 2020

Visualisation of

Spatial Data

3

Visualisation of Spatial Data Best practices for visualising spatial data (1/2)

‣ The most common way to visualise spatial data is with maps that place values within a geographic coordinate. We can visualise the geographic coordinate of a

location by mapping the latitude and longitude coordinates to two-dimensional

space, and draw a point on the space

‣ When the density of individual locations across a region is more informative than the overlapping points on a map, we may want to colour code the region based

on the density scale, or use lines to show data continuously over geography

4

Visualisation of Spatial Data Best practices for visualising spatial data (2/2)

‣ We can also size the regions by the data and ignore the physical area, so that the regions with high density data will appear bigger than the regions with low

density data

‣ If we want to explore relationships between entities, we can plot each entity on a map, and draw lines to connect each with the others they are associated with

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Visualisation of Spatial Data Visualising spatial data

‣ Map

‣ Mapping Point-to-Point Details on Map

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Visualisation of Spatial Data Visualising spatial data — map

https://help.tableau.com/current/pro/desktop/en-us/maps_howto_simple.htm

Mun Teng
Sticky Note
instead of the colour the size can be adjusted

7

Visualisation of Spatial Data Visualising spatial data — point-to-point details on map

https://help.tableau.com/current/pro/desktop/en-us/maps_howto_origin_destination.htm

Mun Teng
Sticky Note
for example, mrt lines. thickness of the size of the note can represent how many passengers are stopping at this point - size of it shows how populated they are

Visualisation of

Multi Variable Data

9

Visualisation of Multi Variable Data Best practices for visualising multi variable data

‣ To visualise multi-variable data, we can fit all data onto a screen and display the relationships amongst variables or trends in each variables

‣ We can use scatterplots to visualise the relationships amongst variables

‣ However, if the relationships amongst variables are not so straightforward, we should consider using multiple views through more straightforward charts

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Visualisation of Multi Variable Data Visualising multi variable data

‣ Scatterplot

‣ Circle View

‣ Side-by-Side Circle Plots

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Visualisation of Multi Variable Data Visualising multi variable data — scatterplot

https://help.tableau.com/current/pro/desktop/en-us/buildexamples_scatter.htm

Mun Teng
Sticky Note
see how 2 variables relate to each other

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Visualisation of Multi Variable Data Visualising multi variable data — circle view

https://www.interworks.com/sites/default/files/blog/TECTCircle2.jpg

Mun Teng
Sticky Note
size of the circle represents the profit margin, bringing in very little sales strategy -
Mun Teng
Sticky Note
try to expand the grey areas to increase the sales volume
Mun Teng
Sticky Note
use shapes to determine the range of profits (different form of representing data)

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Visualisation of Multi Variable Data Visualising multi variable data — side-by-side circle plot

http://www.theinformationlab.co.uk/wp-

content/uploads/2015/03/Side-by-side-Circle-

view2.png

Mun Teng
Sticky Note
to allow easy comparison of product - compare how all these are doing in the south side

What type of chart will you recommend for the scenarios listed?

(a) The Customer Service Director of a network service

provider is interested to know where majority of their customers

are residing so that he is able to plan the location of the new

service centre.

(b) The Sales Director of a mobile phone manufacturer is

interested to compare the sales performance of a new mobile

model that had just been launched in the various regions.

(c) The Product Director of a mobile phone manufacturer is

interested to compare the sales performance of a new mobile

model that had just been launched with other mobile models of

the company in the various regions.

Discussion

Mun Teng
Sticky Note
represent with bar chart. represent the period of time and how much is the increase in the sales. can also use a circle view for this example. very hard to find the center of the circle or measure for charts that are not plotted in lines

Visualisation of

Data Distributions

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Visualisation of Data Distributions Best practices for visualising data distributions

‣ We can visualise the distribution of data at different granularities with bullet charts, bubble charts, and histograms

‣ For single-variable distributions, using a histogram will enable us to see where the data is clustered and any outliers, by keeping track of where the outliers sit

on the vertical axis

‣ For multi-variable distributions, sometimes values come as pairs, so it makes more sense to visualise both values at the same time

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Visualisation of Data Distributions Visualising data distributions

‣ Bullet Chart

‣ Bubble Chart

‣ Histogram

‣ Box Plot

‣ Pareto Chart

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Visualisation of Data Distributions Visualising data distributions — bullet chart

https://help.tableau.com/current/pro/desktop/en-us/qs_bullet_graphs.htm

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Visualisation of Data Distributions Visualising data distributions — bubble chart

https://help.tableau.com/current/pro/desktop/en-us/buildexamples_bubbles.htm

Mun Teng
Sticky Note
the gradient of the sum(profit) tells us how much is the amount - sales represented by the size of the bubble and profits represented by the color
Mun Teng
Sticky Note
no exact value displayed - suitable for rough overview

20

Visualisation of Data Distributions Visualising data distributions — histogram

https://help.tableau.com/current/pro/desktop/en-us/buildexamples_histogram.htm

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Visualisation of Data Distributions Visualising data distributions — box plot

https://help.tableau.com/current/pro/desktop/en-us/buildexamples_boxplot.htm

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Visualisation of Data Distributions Visualising data distributions — pareto chart

https://help.tableau.com/current/pro/desktop/en-us/pareto.htm

Forecasting

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Forecasting The general approach

‣ Forecasting is the act of predicting future values based on historical values

‣ Parameters are variables that allow data visualisation users to alter the content of a formula or change a dimension or measure contained in the view

‣ Using parameters, data visualisation users can change normally static values into dynamic entities that facilitate ad-hoc analysis without the need to change

the design of the data visualisation

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Forecasting Creating forecasts

‣ Trend and season

‣ Trend only

‣ Season only

‣ No trend or season

‣ Parameters: Reference Line, Bin Size (Histogram), Ranking (in-value comparison)

Please read these two webpages to understand how

to perform forecasting in Tableau…

https://help.tableau.com/current/pro/desktop/en-us/forecast_options.htm

https://help.tableau.com/current/pro/desktop/en-us/forecast_how_it_works.htm

Mun Teng
Sticky Note
xtra reading

Tableau (Class Activity)

Tableau (Class Activity)

1. Follow your instructor to create the following visuals:

• Map View

• Scatterplot with filter

• Histogram

• Boxplot

• Create Parameter

• Forecast chart

Map View

Tableau (Class Activity)

Scatterplot Histogram

Tableau (Class Activity)

Boxplot Create Parameter

Tableau (Class Activity)

Forecast Chart

Tableau (Class Activity)

suss.edu.sg

Course Homepage https://canvas.suss.edu.sg/courses/21575

Study Guide https://ibookstore.suss.edu.sg/

Tableau Desktop https://www.tableau.com/products/trial

Tableau Tutorials https://www.tableau.com/learn/get-started/creator

Academic Calendar https://www.suss.edu.sg/docs/default-

source/contentdoc/cel/ft-2020acadcalendar.pdf