Topics:-
1.what is data visualization?
2.why data visualization is important?
3.types of data visualization techniques
4.tools for visualization of data
5.advantages and disadvantage of data visualization
6.Use-Cases and Applications of Data Visualization
What is Data Visualization?
Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.
Why is Data Visualization is important?
*Interactive data charts
*These charts allow users to explore data in engaging and insightful ways.
*Visual storytelling techniques
*Utilizing visuals aids in communicating complex data narratives effectively and clearly.
*Infographics for clarity
*Infographics simplify data, making it accessible and appealing to diverse audiences.
Example:-
Suppose you compile visualization data of the company’s profits from 2013 to 2023 and create a line chart. It would be very easy to see the line going constantly up with a drop in just 2018. So you can observe in a second that the company has had continuous
Types of data visualization:
Numerical data visualization:
Numerical data is also known as Quantitative data.
Data where data generally represents amount such as height, weight, age of a person, etc.
Continuous Data :-
It can be narrowed or categorized
Discrete Data :-
This type of data is not “continuous”
Categorical Data visualization:
Categorical data is also known as Qualitative data. Categorical data is any data where data generally represents groups. It simply consists of categorical variables that are used to represent characteristics such as a person’s ranking, a person’s gender, etc.
Binary Data :-
In this, classification is based on positioning
(Example: Agrees or Disagrees).
Nominal Data :-
In this, classification is based on attributes
(Example: Male or Female).
Ordinal Data :-
In this, classification is based on ordering of information
(Example: Student performance rating).
Tools for Visualization of Data:-
Advantages of Visualization:-
1.Improved understanding:
Visualizations simplify complex data, making it easier to grasp relationships and patterns.
2.Data storytelling:
Visualizations narrate stories with data, conveying meaning and context.
3.Better communication:
Visualizations communicate insights effectively across diverse audiences.
Disadvantages of Visualization:-
2.Time-consuming creation:
Crafting effective visualizations requires significant time and effort.
1.Technical limitations:
Software constraints or data quality issues hinder effective visualization.
3.Security concerns:
Sensitive data exposure through visualization.
Use-Cases and Applications of Data Visualization:-
1. Business Intelligence and Reporting
2. Financial Analysis
3. Healthcare
4. Marketing and Sales
5. Human Resources
What is Data Visualization?
Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.
Why is Data Visualization is important?
*Interactive data charts
*These charts allow users to explore data in engaging and insightful ways.
*Visual storytelling techniques
*Utilizing visuals aids in communicating complex data narratives effectively and clearly.
*Infographics for clarity
*Infographics simplify data, making it accessible and appealing to diverse audiences.
Example:-
Suppose you compile visualization data of the company’s profits from 2013 to 2023 and create a line chart. It would be very easy to see the line going constantly up with a drop in just 2018. So you can observe in a second that the company has had continuous
Types of data visualization:
Numerical data visualization:
Numerical data is also known as Quantitative data.
Data where data generally represents amount such as height, weight, age of a person, etc.
Continuous Data :-
It can be narrowed or categorized
Discrete Data :-
This type of data is not “continuous”
Categorical Data visualization:
Categorical data is also known as Qualitative data. Categorical data is any data where data generally represents groups. It simply consists of categorical variables that are used to represent characteristics such as a person’s ranking, a person’s gender, etc.
Binary Data :-
In this, classification is based on positioning (Example: Agrees or Disagrees).
Nominal Data :-
In this, classification is based on attributes (Example: Male or Female).
Ordinal Data :-
In this, classification is based on ordering of information (Example: Student performance rating).
Tools for Visualization of Data:-
Advantages of Visualization:-
1.Improved understanding:
Visualizations simplify complex data, making it easier to grasp relationships and patterns.
2.Data storytelling:
Visualizations narrate stories with data, conveying meaning and context.
3.Better communication:
Visualizations communicate insights effectively across diverse audiences.
Disadvantages of Visualization:-
2.Time-consuming creation:
Crafting effective visualizations requires significant time and effort.
1.Technical limitations:
Software constraints or data quality issues hinder effective visualization.
3.Security concerns:
Sensitive data exposure through visualization.
Use-Cases and Applications of Data Visualization:-
1. Business Intelligence and Reporting
2. Financial Analysis
3. Healthcare
4. Marketing and Sales
5. Human Resources
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