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Make it Real
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
Make it Real
Outline
DATA
VISUALIZATION
Definition
Reasons for DataVisualization
Benefits
Essential Skills
Core Principles
TechnologyTools
Tableau
7
1
2
3
4
5
6
8
Objectives
Make it Real
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)
.
Make it Real
Make it Real
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
Make it Real
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
Make it Real
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.
Make it Real
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
Make it Real
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
Make it Real
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
Make it Real
Core
Principles 01
02
03
04
Make it Real
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
Make it Real
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.
Make it Real
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.
Make it Real
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
Make it Real
Example
Make it Real
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
Make it Real
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
Make it Real
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?
Make it Real
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
Make it Real
ClassActivity
2
Question - Identify the five highest revenue product region from
the data.
Make it Real
• 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
Make it Real
Technology
Tools
Make it Real
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.
Make it Real
Tableau
Products
Tableau Desktop
Tableau OnlineTableau Server
Tableau Public
Make it Real
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)
Tableau Explorer-$35 annual (5
users/month)
Tableau Viewer-$12 annual (100
viewers)
No large investment of money to
server configuration. Trial version
available.
Tableau Creator- $70 annual (1 user/
month)
Tableau Explorer-$42 annual (5
users/month)
Tableau Viewer-$15 annual (100
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
Make it Real
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.
Make it Real
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.
Make it Real
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.
Make it Real
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.
Make it Real
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.
Make it Real
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
Make it Real
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.
Make it Real
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.
Make it Real
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
Make it Real
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
Make it Real
Cont’d
 With tableau you can view the data in each sheet
View Data
Make it Real
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
Make it Real
Joins
(Connecting
and Merging
Multiple data
sources)
Make it Real
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
Make it Real
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
Make it Real
Make it Real
The End
43
Thank You
for listening

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Techniques of Data Visualization for Data & Business Analytics

  • 1. Make it Real 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
  • 2. Make it Real Outline DATA VISUALIZATION Definition Reasons for DataVisualization Benefits Essential Skills Core Principles TechnologyTools Tableau 7 1 2 3 4 5 6 8 Objectives
  • 3. Make it Real 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) .
  • 5. Make it Real 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
  • 6. Make it Real 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
  • 7. Make it Real 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.
  • 8. Make it Real 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
  • 9. Make it Real 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
  • 10. Make it Real 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
  • 12. Make it Real 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
  • 13. Make it Real 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.
  • 14. Make it Real 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.
  • 15. Make it Real 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
  • 17. Make it Real 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
  • 18. Make it Real 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
  • 19. Make it Real 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?
  • 20. Make it Real 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
  • 21. Make it Real ClassActivity 2 Question - Identify the five highest revenue product region from the data.
  • 22. Make it Real • 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
  • 24. Make it Real 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.
  • 25. Make it Real Tableau Products Tableau Desktop Tableau OnlineTableau Server Tableau Public
  • 26. Make it Real 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) Tableau Explorer-$35 annual (5 users/month) Tableau Viewer-$12 annual (100 viewers) No large investment of money to server configuration. Trial version available. Tableau Creator- $70 annual (1 user/ month) Tableau Explorer-$42 annual (5 users/month) Tableau Viewer-$15 annual (100 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
  • 27. Make it Real 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.
  • 28. Make it Real 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.
  • 29. Make it Real 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.
  • 30. Make it Real 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.
  • 31. Make it Real 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.
  • 32. Make it Real 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
  • 33. Make it Real 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.
  • 34. Make it Real 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.
  • 35. Make it Real 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
  • 36. Make it Real 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
  • 37. Make it Real Cont’d  With tableau you can view the data in each sheet View Data
  • 38. Make it Real 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
  • 39. Make it Real Joins (Connecting and Merging Multiple data sources)
  • 40. Make it Real 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
  • 41. Make it Real 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
  • 43. Make it Real The End 43 Thank You for listening