CBSE Textbook: Data Exploration | Artificial Intelligence (AI) for Class 9 PDF Download

 Page 1


37 
 
1.2.3 Data Exploration 
 
Title: Data Exploration Approach: Activity 
Summary: Students will explore different types of graphs used in data visualization and will 
be able to find trends and patterns out of it. 
Learning Objectives: 
? Students will explore various types of graphical representations. 
? Students will learn how to visualize the data they have. 
Learning Outcomes: 
? Recognize different types of graphs used in data visualization. 
? Exploring various patterns and trends out of the data explored. 
Pre-requisites: Basic computer literacy 
Key-concepts: Data Visualization 
Let us Recap! 
Quiz Time! 
1. Which one of the following is the second stage of AI project cycle? 
a. Data Exploration 
b. Data Acquisition 
c. Modelling 
d. Problem Scoping 
2. Which of the following comes under Problem Scoping? 
a. System Mapping 
b. 4Ws Canvas 
c. Data Features 
d. Web scraping 
3. Which of the following is not valid for Data Acquisition? 
a. Web scraping 
b. Surveys 
c. Sensors 
d. Announcements 
4. If an arrow goes from X to Y with a – (minus) sign, it means that 
a. If X increases, Y decreases 
b. The direction of relation is opposite 
c. If X increases, Y increases 
d. It is a bi-directional relationship 
Page 2


37 
 
1.2.3 Data Exploration 
 
Title: Data Exploration Approach: Activity 
Summary: Students will explore different types of graphs used in data visualization and will 
be able to find trends and patterns out of it. 
Learning Objectives: 
? Students will explore various types of graphical representations. 
? Students will learn how to visualize the data they have. 
Learning Outcomes: 
? Recognize different types of graphs used in data visualization. 
? Exploring various patterns and trends out of the data explored. 
Pre-requisites: Basic computer literacy 
Key-concepts: Data Visualization 
Let us Recap! 
Quiz Time! 
1. Which one of the following is the second stage of AI project cycle? 
a. Data Exploration 
b. Data Acquisition 
c. Modelling 
d. Problem Scoping 
2. Which of the following comes under Problem Scoping? 
a. System Mapping 
b. 4Ws Canvas 
c. Data Features 
d. Web scraping 
3. Which of the following is not valid for Data Acquisition? 
a. Web scraping 
b. Surveys 
c. Sensors 
d. Announcements 
4. If an arrow goes from X to Y with a – (minus) sign, it means that 
a. If X increases, Y decreases 
b. The direction of relation is opposite 
c. If X increases, Y increases 
d. It is a bi-directional relationship 
38 
 
5. Which of the following is not a part of the 4Ws Problem Canvas? 
a. Who? 
b. Why? 
c. What? 
d. Which? 
 
 
Let us explore: 
 
Session Preparation 
Logistics: For a class of 40 Students. [Group Activity – Groups of 4] 
Materials Required: 
 
ITEM QUANTITY 
Computers 10 
 
Resources: 
Link to visualisation website: https://datavizcatalogue.com/ 
Purpose: To understand why we do data exploration before jumping straight into training an AI 
Model. 
Say: “Why do you think we need to explore and visualize data before jumping into the AI model? 
When we pick up a library book, we tend to look at the book cover, read the back cover and skim 
through the content of the book prior to choosing it as it helps us understand if this book is 
appropriate for our needs and interests. Similarly, when we get a set of data in our hands, spending 
time to explore it will help get a sense of the trends, relationships and patterns present in the data. It 
will also help us better decide on which model/models to use in the subsequent AI Project Cycle 
stage. We use visualization as a method because it is much easier to comprehend information 
quickly and communicate the story to others.” 
Brief: 
In this session, we will be exploring various types of Graphs using an online open- sourced website. 
Students will learn about various new ways to visualise the data. 
When to intervene? 
Ask the students to figure out which types of graphs would be suitable for the data features that 
they have listed for their problem. Let them take their time in going through each graph and its 
description and decide which one suits their needs the best. 
Page 3


37 
 
1.2.3 Data Exploration 
 
Title: Data Exploration Approach: Activity 
Summary: Students will explore different types of graphs used in data visualization and will 
be able to find trends and patterns out of it. 
Learning Objectives: 
? Students will explore various types of graphical representations. 
? Students will learn how to visualize the data they have. 
Learning Outcomes: 
? Recognize different types of graphs used in data visualization. 
? Exploring various patterns and trends out of the data explored. 
Pre-requisites: Basic computer literacy 
Key-concepts: Data Visualization 
Let us Recap! 
Quiz Time! 
1. Which one of the following is the second stage of AI project cycle? 
a. Data Exploration 
b. Data Acquisition 
c. Modelling 
d. Problem Scoping 
2. Which of the following comes under Problem Scoping? 
a. System Mapping 
b. 4Ws Canvas 
c. Data Features 
d. Web scraping 
3. Which of the following is not valid for Data Acquisition? 
a. Web scraping 
b. Surveys 
c. Sensors 
d. Announcements 
4. If an arrow goes from X to Y with a – (minus) sign, it means that 
a. If X increases, Y decreases 
b. The direction of relation is opposite 
c. If X increases, Y increases 
d. It is a bi-directional relationship 
38 
 
5. Which of the following is not a part of the 4Ws Problem Canvas? 
a. Who? 
b. Why? 
c. What? 
d. Which? 
 
 
Let us explore: 
 
Session Preparation 
Logistics: For a class of 40 Students. [Group Activity – Groups of 4] 
Materials Required: 
 
ITEM QUANTITY 
Computers 10 
 
Resources: 
Link to visualisation website: https://datavizcatalogue.com/ 
Purpose: To understand why we do data exploration before jumping straight into training an AI 
Model. 
Say: “Why do you think we need to explore and visualize data before jumping into the AI model? 
When we pick up a library book, we tend to look at the book cover, read the back cover and skim 
through the content of the book prior to choosing it as it helps us understand if this book is 
appropriate for our needs and interests. Similarly, when we get a set of data in our hands, spending 
time to explore it will help get a sense of the trends, relationships and patterns present in the data. It 
will also help us better decide on which model/models to use in the subsequent AI Project Cycle 
stage. We use visualization as a method because it is much easier to comprehend information 
quickly and communicate the story to others.” 
Brief: 
In this session, we will be exploring various types of Graphs using an online open- sourced website. 
Students will learn about various new ways to visualise the data. 
When to intervene? 
Ask the students to figure out which types of graphs would be suitable for the data features that 
they have listed for their problem. Let them take their time in going through each graph and its 
description and decide which one suits their needs the best. 
39 
 
In the previous modules, you have set the goal of your project and have also found ways to acquire data. 
While acquiring data, you must have noticed that the data is a complex entity – it is full of numbers and 
if anyone wants to make some sense out of it, they have to work some patterns out of it. For example, if 
you go to the library and pick up a random book, you first try to go through its content quickly by turning 
pages and by reading the description before borrowing it for yourself, because it helps you in 
understanding if the book is appropriate to your needs and interests or not. 
Thus, to analyse the data, you need to visualise it in some user-friendly format so that you can: 
• Quickly get a sense of the trends, relationships and patterns contained within the data. 
• Define strategy for which model to use at a later stage. 
• Communicate the same to others effectively. To visualise data, we can use various types of visual   
representations. 
Are you aware of visual representations of data? Fill them below: 
 
 
 
As of now, we have a limited knowledge of data visualisation techniques. To explore various 
data visualisation techniques, visit this link: https://datavizcatalogue.com/ 
On this website, you will find various types of graphical representations, flowcharts, hierarchies, 
process descriptors, etc. Go through the page and look at various new ways and identify the 
ones which interest you the most. 
Page 4


37 
 
1.2.3 Data Exploration 
 
Title: Data Exploration Approach: Activity 
Summary: Students will explore different types of graphs used in data visualization and will 
be able to find trends and patterns out of it. 
Learning Objectives: 
? Students will explore various types of graphical representations. 
? Students will learn how to visualize the data they have. 
Learning Outcomes: 
? Recognize different types of graphs used in data visualization. 
? Exploring various patterns and trends out of the data explored. 
Pre-requisites: Basic computer literacy 
Key-concepts: Data Visualization 
Let us Recap! 
Quiz Time! 
1. Which one of the following is the second stage of AI project cycle? 
a. Data Exploration 
b. Data Acquisition 
c. Modelling 
d. Problem Scoping 
2. Which of the following comes under Problem Scoping? 
a. System Mapping 
b. 4Ws Canvas 
c. Data Features 
d. Web scraping 
3. Which of the following is not valid for Data Acquisition? 
a. Web scraping 
b. Surveys 
c. Sensors 
d. Announcements 
4. If an arrow goes from X to Y with a – (minus) sign, it means that 
a. If X increases, Y decreases 
b. The direction of relation is opposite 
c. If X increases, Y increases 
d. It is a bi-directional relationship 
38 
 
5. Which of the following is not a part of the 4Ws Problem Canvas? 
a. Who? 
b. Why? 
c. What? 
d. Which? 
 
 
Let us explore: 
 
Session Preparation 
Logistics: For a class of 40 Students. [Group Activity – Groups of 4] 
Materials Required: 
 
ITEM QUANTITY 
Computers 10 
 
Resources: 
Link to visualisation website: https://datavizcatalogue.com/ 
Purpose: To understand why we do data exploration before jumping straight into training an AI 
Model. 
Say: “Why do you think we need to explore and visualize data before jumping into the AI model? 
When we pick up a library book, we tend to look at the book cover, read the back cover and skim 
through the content of the book prior to choosing it as it helps us understand if this book is 
appropriate for our needs and interests. Similarly, when we get a set of data in our hands, spending 
time to explore it will help get a sense of the trends, relationships and patterns present in the data. It 
will also help us better decide on which model/models to use in the subsequent AI Project Cycle 
stage. We use visualization as a method because it is much easier to comprehend information 
quickly and communicate the story to others.” 
Brief: 
In this session, we will be exploring various types of Graphs using an online open- sourced website. 
Students will learn about various new ways to visualise the data. 
When to intervene? 
Ask the students to figure out which types of graphs would be suitable for the data features that 
they have listed for their problem. Let them take their time in going through each graph and its 
description and decide which one suits their needs the best. 
39 
 
In the previous modules, you have set the goal of your project and have also found ways to acquire data. 
While acquiring data, you must have noticed that the data is a complex entity – it is full of numbers and 
if anyone wants to make some sense out of it, they have to work some patterns out of it. For example, if 
you go to the library and pick up a random book, you first try to go through its content quickly by turning 
pages and by reading the description before borrowing it for yourself, because it helps you in 
understanding if the book is appropriate to your needs and interests or not. 
Thus, to analyse the data, you need to visualise it in some user-friendly format so that you can: 
• Quickly get a sense of the trends, relationships and patterns contained within the data. 
• Define strategy for which model to use at a later stage. 
• Communicate the same to others effectively. To visualise data, we can use various types of visual   
representations. 
Are you aware of visual representations of data? Fill them below: 
 
 
 
As of now, we have a limited knowledge of data visualisation techniques. To explore various 
data visualisation techniques, visit this link: https://datavizcatalogue.com/ 
On this website, you will find various types of graphical representations, flowcharts, hierarchies, 
process descriptors, etc. Go through the page and look at various new ways and identify the 
ones which interest you the most. 
40 
 
 
 
Identify the icons of different graphs: 
 
 
 
 
 
 
 
 
Page 5


37 
 
1.2.3 Data Exploration 
 
Title: Data Exploration Approach: Activity 
Summary: Students will explore different types of graphs used in data visualization and will 
be able to find trends and patterns out of it. 
Learning Objectives: 
? Students will explore various types of graphical representations. 
? Students will learn how to visualize the data they have. 
Learning Outcomes: 
? Recognize different types of graphs used in data visualization. 
? Exploring various patterns and trends out of the data explored. 
Pre-requisites: Basic computer literacy 
Key-concepts: Data Visualization 
Let us Recap! 
Quiz Time! 
1. Which one of the following is the second stage of AI project cycle? 
a. Data Exploration 
b. Data Acquisition 
c. Modelling 
d. Problem Scoping 
2. Which of the following comes under Problem Scoping? 
a. System Mapping 
b. 4Ws Canvas 
c. Data Features 
d. Web scraping 
3. Which of the following is not valid for Data Acquisition? 
a. Web scraping 
b. Surveys 
c. Sensors 
d. Announcements 
4. If an arrow goes from X to Y with a – (minus) sign, it means that 
a. If X increases, Y decreases 
b. The direction of relation is opposite 
c. If X increases, Y increases 
d. It is a bi-directional relationship 
38 
 
5. Which of the following is not a part of the 4Ws Problem Canvas? 
a. Who? 
b. Why? 
c. What? 
d. Which? 
 
 
Let us explore: 
 
Session Preparation 
Logistics: For a class of 40 Students. [Group Activity – Groups of 4] 
Materials Required: 
 
ITEM QUANTITY 
Computers 10 
 
Resources: 
Link to visualisation website: https://datavizcatalogue.com/ 
Purpose: To understand why we do data exploration before jumping straight into training an AI 
Model. 
Say: “Why do you think we need to explore and visualize data before jumping into the AI model? 
When we pick up a library book, we tend to look at the book cover, read the back cover and skim 
through the content of the book prior to choosing it as it helps us understand if this book is 
appropriate for our needs and interests. Similarly, when we get a set of data in our hands, spending 
time to explore it will help get a sense of the trends, relationships and patterns present in the data. It 
will also help us better decide on which model/models to use in the subsequent AI Project Cycle 
stage. We use visualization as a method because it is much easier to comprehend information 
quickly and communicate the story to others.” 
Brief: 
In this session, we will be exploring various types of Graphs using an online open- sourced website. 
Students will learn about various new ways to visualise the data. 
When to intervene? 
Ask the students to figure out which types of graphs would be suitable for the data features that 
they have listed for their problem. Let them take their time in going through each graph and its 
description and decide which one suits their needs the best. 
39 
 
In the previous modules, you have set the goal of your project and have also found ways to acquire data. 
While acquiring data, you must have noticed that the data is a complex entity – it is full of numbers and 
if anyone wants to make some sense out of it, they have to work some patterns out of it. For example, if 
you go to the library and pick up a random book, you first try to go through its content quickly by turning 
pages and by reading the description before borrowing it for yourself, because it helps you in 
understanding if the book is appropriate to your needs and interests or not. 
Thus, to analyse the data, you need to visualise it in some user-friendly format so that you can: 
• Quickly get a sense of the trends, relationships and patterns contained within the data. 
• Define strategy for which model to use at a later stage. 
• Communicate the same to others effectively. To visualise data, we can use various types of visual   
representations. 
Are you aware of visual representations of data? Fill them below: 
 
 
 
As of now, we have a limited knowledge of data visualisation techniques. To explore various 
data visualisation techniques, visit this link: https://datavizcatalogue.com/ 
On this website, you will find various types of graphical representations, flowcharts, hierarchies, 
process descriptors, etc. Go through the page and look at various new ways and identify the 
ones which interest you the most. 
40 
 
 
 
Identify the icons of different graphs: 
 
 
 
 
 
 
 
 
41 
 
List down 5 new data visualisation techniques which you learnt from https://datavizcatalogue.com 
 
 
Data Visualisation Technique 1 
Name of the 
Representation 
 
One-line 
Description 
 
 
 
 
 
 
How to draw it 
 
Suitable for 
which data 
type? 
 
 
Data Visualisation Technique 2 
Name of the 
Representation 
 
One-line 
Description 
 
 
 
 
 
 
 
How to draw it 
 
Suitable for 
which data 
type?