Techniques of Data Visualization for Data & Business Analytics

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Techniques of Data Visualization
for Data & Business Analytics
Ife Akinseinde
(Consulting & Research)
CAVIDEL Limited
Block D1 SO2
1004 Housing Estate
Victoria Island
Lagos
Tel: 08111106781
Email: ife.akinseinde@cavidel.com
Website: www.cavidel.com
27 March, 2019

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Outline
DATA
VISUALIZATION
Definition
Reasons for DataVisualization
Benefits
Essential Skills
Core Principles
TechnologyTools
Tableau
7
1
2
3
4
5
6
8
Objectives

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Objectives
The purpose of this training is to skill up the organisation's abilities in data
visualization.
This training aims to give staff:
A beginner’s skill-set for visualising and communicating data.
The ability to learn to simplify data and understand which
chart and graph types are useful for which types of data.
The ability to discover for themselves the tools &
techniques that are used for effective communication of
insights.
The ability to visualize data using cutting-edge tools and
techniques. (Tableau)
.

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Definition
Data visualization
“.. all types of visual representations
that support the exploration,
examination and communication of
data.”
-Stephen Few
NowYou See It: Simple Visualization
Techniques for Quantitative Analysis

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Definition
Cont’d
“when we represent quantitative
information in visual form, our ability to
think about it is dramatically enhanced.
Visual representation not only make
the patterns, trends, and exceptions in
numbers visible and understandable,
they also extend the capacity of our
memory.”
-Stephen Few
NowYou See It: Simple Visualization
Techniques for Quantitative Analysis

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Data
Visualization
Using pictures, graphs, charts, colours etc. to represent data.
Makes it easy to summarise large volumes of data.
Illustration of patterns, trends, relationship across time, geography, interactivity.
Seeing patterns among values such as change over time
Easily and rapidly comparing values and patterns
An overview summarizes the data’s essential characteristics.
A business analytic tool
Business analytics is about asking questions and using statistical and quantitative
tools for explanatory and predictive analysis.

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Reasons
for
DataVisualization
Task Goal
Discovery
Exploration: Searching for
significant facts
Sensemaking: Examining and
making sense of data
Understanding
Communication: Conveying
information to others
Informed decisions

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Benefits
Makes information readily
available by helping you
see things that would
rather go unnoticed and
gives you faster answer
Decision makers can
access the details
they need quickly
Helps to make data
driven or fact based
decision

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Essential
Skills
The design and artistic component.
This entails creating something that is
beautiful and compelling
Mathematical component
Being able to deliver the right insight,
through engaging and informing data
visualizations
1
2
3
Creating a good
visualization is a
combination of
these skills

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Core
Principles 01
02
03
04

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Context
Understand the context of your
visualization: Questions + Data = the story
Start with questions
WHY: You have to understand the context of what you need to show before you start
doing it.
WHO:To whom are you communicating to?
WHAT: what data will and will not be included, What do you want/need your audience
to know or do?
HOW: How can you use the data you have to make your point or support the story you
want to tell?
How can you communicate to your audience
Knowing your audience will ensure your message is being heard

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Purpose
of
Visualization
EXPLORATORY ANALYSIS
 This process is done before you find an insight
 Is what you do to understand the data and figure
out what might be note worthy or interesting to
highlight to others.
 Search for relationships in the data or hidden
insights
 Connecting questions about the data
 The visualizations built do not need to be perfect
because the main goal is to look for patterns.
EXPLANATORY ANALYSIS
 This process is done after you find an insight.
 The insights are often found during the exploratory
process.
 Highlight the insights
 It should be surrounded by a story that points the
reader to an insight that answers the questions.
 Focus the visualization on the answers to the
questions asked.
 No need for unnecessary information. When you have
a specific thing you want to explain, a specific story
you want to tell, concentrate on the information your
audience needs to know.

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Visual Display
Choose the appropriate
Visual Display:
Poor designs can ruin what you are trying to convey.
What is the best way to show the data you want to
communicate?
The right way to visualize a data is a way that best helps
you to answer the questions you want answered.

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Summary
Statistics
Vs
Visualization
Summary Statistics
 Summary statistics like the mean, mode,
median and standard deviation can be great for
attempting to quickly understand aspects of a
dataset
 They can be misleading if you make too many
assumptions about how the data distribution
looks
 They don’t tell the full story.
1
2
Visualization
 More useful for delivering insights
 Helps to identify, trends, visual patterns,
relationships during your analysis.
 They are used to tell a story

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Scatter plot
For correlation analysis and
identifying relationships e.g.
determine strength and
direction of price vs sales
etc.
Pie chart e.g. group
products etc.
Line plot
Find trends over time
e.g. trend in stock
prices, time line etc.
Bar chart
Great for comparison and
ranking.Commonly used e.g.
rank countries based on a set of
criteria
Stem and leaf plot
e.g. to show age or
score distribution etc.
Box and whisker plot e.g. to
show the 5 number summary of
a data distribution
Normal Quantile plot e.g.
shows the variability of a
data etc.
Histogram
For distribution e.g. frequency
of visits, score occurrences,
web traffic etc.
Categorical Data Quantitative or Numerical Data
Visual Plots

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Clutter is your
enemy
Identify and Eliminate clutter
or noise or distractions:
Our visuals should be simple as possible and
clutter makes it complicated
Avoid overloading your views

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ClassActivity
1
Answer:
• The chart border, gridlines and the data markers were removed.
• Axis labels were cleaned up, the data was labelled directly and
consistent colours were used
Question: What’s the difference between the two diagrams?

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Audience
Attention
Focus your audience’s
attention:
Define your audience before you create your visualization
Boss or committee or colleagues or big group or 100s of people?
Know their expectations prior to state of visualization?
Drawing your audience’s attention to where you want them to look
Emphasize the most important data
Create a visual hierarchy of information using certain attributes
Attributes: colour, size, outline, bold, italics, underline, highlights, case
sensitivity

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ClassActivity
2
Question - Identify the five highest revenue product region from
the data.

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• Colour is the most powerful tool to highlight important part of a visual.
• Create a hierarchy of information: Of the top designs concerns three are noise related
• Highlighting one aspect can make other things harder to see

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Tableau
Tableau is a software for creating
data visualization
 It is used for visualization and story telling.
 Due to the interactive nature of tableau, visualization makes it faster
to find insights.
 For this trainingTableau Public will be used.
 It is the free version but can’t save to workbooks on your computer.
Workbooks are save to a public work book online. You can then
download the workbook from there.

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Tableau
Products
Tableau Desktop
Tableau OnlineTableau Server
Tableau Public

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Tableau Public Tableau Desktop Tableau Server Tableau Online
Create visualization with public data and share it
with anyone.
It is the full version of tableau
public.
Allows the most flexibility of all
products. Can be shared with the public
intended to be a way to have control of
your data when embedding data
visualizations.
Price Free. Other available options to purchase should
you want to do more beyond Tableau Public’s
capabilities
Not free, license required
Tableau Creator- $70 annual (1
user/ month)
Tableau Explorer-$42 annual (5
users/month)
Tableau Viewer-$15 annual (100
viewers)
requires very large financial investment
in a local server for a company
Tableau Creator- $70 annual (1 user/
month)
users/month)
viewers)
No large investment of money to
server configuration. Trial version
available.
Tableau Creator- $70 annual (1 user/
month)
users/month)
viewers)
File storage Saved in the cloud not local Can be saved locally Visualizations saved in the cloud
Security No control over data privacy-public data.
Data imported cannot be made private
Very strong security of data More secured access to data
Has data control e.g. you can control
how people see your data even if
impeded on a public website.
Has control over data
Data source
connection
Connects to fewer data sources but can connect to
more than one data source at a time
An array of data sources Connects to more data sources Connects to more data sources
Data source Excel , csv files, text file, JSON file, Microsoft
Access, PDF file, Spatial File, Statistical file, OData
server, Live data source, Tableau data extract
Databases, data ware houses,
sequel server, google analytics,
oracle, amazon, web services
Limitations You cannot use Tableau unless you are connected
online.
Files cannot be saved locally.
All information are stored in the tableau cloud.
All information can be downloaded by anyone.
Data should be anonymized in excel or other
program before importing it into tableau public.
All other data sources such as Tableau servers, SAS
servers, MySQL servers, Amazon Redshift servers,
etc at this time are not supported by Tableau
Public.
for everyone that must read reports
but not directly use Tableau, they’ll
need Tableau Reader downloaded
Only available to those who can
support a server that is dedicated to
tableau.
installed on a Windows server and
accessible to users via a browser
To view visualization online the viewer
needs a tableau online account as well.
Data cannot be shared with the public
unless saved as a public file
Can only share with people who have a
tableau online license.
Restrictions apply to pricing options

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Products Built
in
Tableau
Worksheets
Dashboards
Stories
 There are three final products that
people build in tableau.
 A work sheet is where individual
visualizations are built. An unlimited
number of worksheets can be added in
Tableau Public to illustrate different
visualizations (testing things)
 Dashboards is a combination of multiple
worksheets.
 Stories is a combination of worksheets,
dashboards and a walkthrough of the
data and a multiple key points in a
connected way. It is a way to explain your
data in a systematic way.

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Tableau
LearningAreas
1. Installation: In this section you will learn how to install, setup and get your tableau
environment working.
2. Connecting to Data: In this section, you will get started with importing data intoTableau.
3. Combining Data: In this section, you will learn how to connect data from multiple sources
using SQL joins for use in your visuals.
4. Worksheets: In this section, the visuals you create will be stored in worksheets.
5. Aggregations: Tableau performs aggregations of our data by default. In this section, you will
learn more about how to work with different aggregations, as well as how to break your
aggregations into a more granular level of the data.
6. Hierarchies: In this section, you will learn how Hierarchies allow you to 'drill' into your data
and questions at different levels. One of the easiest ways to think of hierarchies is in relation to
time (year, month, day, hour and other levels). Moving across these levels is considered
working with hierarchies.

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Tableau
LearningAreas
(Cont’d)
7. Marks & Filters: Filtering is one of the most powerful techniques in creating dashboards. This
relates to the marks portion of a dashboard, which controls the colours, shapes and other attributes of
our data. Used to filter your data to only the parts you are interested in for a specific question.
8. Show Me: The Show Me portion of Tableau controls what your ending visual looks like. There are
a lot of options here.
9. Small Multiples & Dual Axis: Small multiples & dual charts are a way to visualize data that needs to
share an axis for comparison purposes.
10. Groups & Sets: Groups and sets are two ways to categorize our data within a visualization. The
difference between these two can be confusing, but we will see when and why you would use each.
11. Calculated Fields: Often you might add these fields to your dataset before adding your data to
Tableau, but sometimes you want to add them to a visualization on the fly. E.g. total or a cost per item.
12. Table Calculations: Table calculations are often used to perform comparisons of our data over time
or between groups.

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Installation
The best way to learn a software
is to use it.
Let’s start with:
Step1: InstallingTableau
 Go to
https://public.tableau.com/s/,
 Type in your email address
and click on “download the
app”
 Should look like this:
 You will see that it has already
stared downloading.
 If it doesn’t you can click on
try again.
 After it finishes downloading,
double click on the setup to
install.

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Installation
Cont’d
 Accept the license terms and
click install and it begins
installing.
 Once it finish installing you
will see it opened at the
bottom of your screen or you
click on windows to open
tableau, now you can use
tableau.

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Tableau Public
Work
Environment
 Click on open from tableau public assuming you don’t have an account, click on “create one now for free” and register
 Fill out all the information and thick the check box
 Check your email to verify the account.Then your account will be verified then you are all setup for use.
OR
 From the left side bar we can see the data sources that we can connect to.
 In most cases, you can get around Tableau Public’s data connection limitations by using Excel
 Click on “Excel”, then select the file

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Data
Connection
Primary types of data connection:
 OData Connection: Can access data from sources like relational DB, traditional websites, Content Management
Systems, File Systems.
 Tableau Web Data Connector: Connect to a data that doesn’t have a web data connector. It can be used to access
data from sources like internal web services, websites, HTTP, JSON data, XML data, REST APIs, and many other
sources.
 Live connection: Tableau sends queries to your underline database and retrieves up to date data whenever the
tableau is updated. A live data connection is best and should be used when the live connection between the
tableau dashboard and your data is possible. A live connection is recommended when you have a fast database
or when you need up to the minute data.
 Data extract connection: Tableau sends queries to your extracted or static database and not the underlying
data. A Tableau data extract is recommended when your database is too slow for interactive analytics or when
you need to be offline and when the size of the data is extremely large. This should be used when one does not
always have an internet or network connection to your data.

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Tableau Public
WorkSpace
 With tableau connected to the data, we should see the sheets in the Excel file (in the left
sidebar.
 There's big orange letters tell you to drag a sheet over there, so drag a sheet onto the
top panel.

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Cont’d
 You should see a preview of the data from the orders in the lower panel now.
 Check the box of the Data Interpreter(it's on the left). The Data Interpreter attempts to clean and format the
data so that it's easier to use inTableau.
 Tableau helps to detect the data type.The little icons in the header bar indicate the data type of the column.
DataType

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Cont’d
 With tableau you can set the data type manually by clicking on the data type symbol.
 We can also rename the column name by either click on the triangle which drops down a menu, or just
double click on the column name.
 With string columns, you can do some simple transformations such as splitting the data into multiple
columns

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Cont’d
 With tableau you can view the data in each sheet
View Data

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Joins
(Connecting
and Merging
Multiple data
sources)
 These are used to merge multiple data sources by joining multiple tables from different data sources.
 Join the Audit table to the payroll table and then Edit the join
 Types of joins:
 Inner Join-shows the rows or records present in both tables. This is used when you want to display all of the data that is
stored in both of the data sources, using a merge variable.
 Left Join: A left join returns all of the records or rows present in the left table and matching rows from the right
table. You would use a left join when you want to keep all of the data in the left table and only merge in limited data
from the table on the right.
 Right Join: A right join returns all of the records or rows present in the right table and matching rows from the left
table. You would use a right join when you want to keep all of the data in the right table and only merge in limited data
from the table on the left.
 Full Outer Join: A full outer join were shown all of the records or rows present in both left and the right table. You will use
a full outer join when you wanted display all of the data that is stored within all of the tables

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Joins
(Connecting
and Merging
Multiple data
sources)

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Work
Environment
Dimensions:
 This field uses/helps to categorize the data.
 You can view a visualization’s underlying data by clicking on the icon next to the text,
“Dimensions” in the data window.
Measures:
 This field is used to help determine the scale of a category. Continuous and Discreet
measure
 When measures are placed on a shelf, Tableau will do a calculation automatically, and
add that based on any dimensions that were added.
 Continuous measure: This role indicates that the field can take on any number

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References
 Tableau
 Udacity
 Coursera
 A Review of: “Now You See It: Simple Visualization Techniques for
Quantitative Analysis, by S. C. Few,”Oakland, CA: Analytics Press,
2009, ISBN 0-9706019-8-0, xi + 327 pp
 Wiley (2015), Storytelling With Data: A Data Visualization Guide for
Business Professionals

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The End
43
Thank You
for listening

Techniques of Data Visualization for Data & Business Analytics

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