This document provides an overview of data visualization. It discusses the importance of visualization and provides a brief history. It then describes common types of visualizations like line graphs, bar charts, scatter plots and pie/doughnut charts. The document outlines tools for creating visualizations and discusses interactive visualization. It covers challenges and trends in the field, such as interactive visualization becoming more common. The document provides guidance on choosing visualizations based on common roles like showing change over time, part-to-whole compositions, distributions, comparisons and relationships. It concludes with thanks.

1. DATA VISUALIZATION

2. “A picture is worth a
thousand words”

3. Outline
 Introduction
 Types of Visualization
 Choosing Visualizations
 Visualization Tools
 Interactive Visualization
 Challenges and Trends in
Data Visualization
 Conclusion

4. ?

6. Importance of
Data Visualization
Picture 1: Doesn’t make any sense
Picture 2: This makes sense(because of visualization)
After Visualization

7. the historyof data
visualization

8. the history of data visualizationz
18th -19th century
19th-21th century
18th Century William Playfair
19th Century John Snow
21st Century Business Intelligence

9. Types of Visualization
Line graphs have values plotted as lines across
the X and Y-axis.
Line Graph
Bar charts or column charts have rectangle bars arranged on the
X or Y-axis..
Bar Graph
Scatter plot shows the relationship of the
common attribute between two numerical
variables plotted along both X and Y axes.
Scatter Plot
A Doughnut chart slices a doughnut into multiple parts based
on the field value..
Pie Chart
A histogram is similar to a bar graph but has a
different plotting system.
Histogram Chart

10. Bar Graph
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A 1 A 2 A 3 A 4
• Comparing a numerical value across categories
• Identifying the order within a category
 Bar charts are most suitable for :

11. Doughnut Chart or Pie Chart
 A donut chart is much like a pie chart but with the center area taken out. The difference between them is
essentially visual.
You can have more sections than a pie chart in a donut chart and it will still be readable.

12. Line Graph or Line Chart
 Line graphs are best used to:
• Display trend over a time series
• Pinpoint outliers
• Visualize forecasted data

13. Tableau Power BI Excel
Visualization Tools

14. CHOOSING
VISUALIZATION
Common roles for data
visualization include:
 Showing change over time.
 Showing a part-to-whole
composition.
 Looking at how data is
distributed.
 Comparing values between
groups.
 Observing relationships
between variables.
 Looking at geographical
data.

15. Choosing Visualization
One of the most common applications for visualizing data is to
see the change in value for a variable across time. These charts
usually have time on the horizontal axis, moving from left to
right, with the variable of interest’s values on the vertical
axis. There are multiple ways of encoding these values:
Charts for showing change over time

16. Choosing Visualization
Sometimes, we need to know not just a total, but the components
that comprise that total. While other charts like a standard bar
chart can be used to compare the values of the components, the
following charts put the part-to-whole decomposition at the
forefront:
Charts for showing part-to-whole composition

17. Choosing Visualization
One important use for visualizations is to show how data points’
values are distributed. This is particularly useful during the
exploration process, when trying to build an understanding of
the properties of data features.
Charts for looking at how data is distributed

18. Choosing Visualization
Another very common application for a data visualization is to
compare values between distinct groups. This is frequently
combined with other roles for data visualization, like showing
change over time, or looking at how data is distributed.
Charts for comparing values between groups
.

19. Choosing Visualization
Another task that shows up in data exploration is understanding
the relationship between data features. The chart types below
can be used to plot two or more variables against one another to
observe trends and patterns between them.
Charts for observing relationships between variables
.

20. Choosing Visualization
Sometimes, data includes geographical data like latitude and
longitude or regions like country or state. While plotting this
data might just be extending an existing visualization onto a
map background, there are other chart types that take the
mapping domain into account. Two of these are highlighted below:
Charts for looking at geographical data
.

21. Interactive Visualization

22. Challenges and trends in
Dataviz 2024
Interactive Visualization
Becomes More Common
Virtual and Augmented Reality
Could Be A New Reality
Real-time Data Visualization

23. Conclusion

24. THANK YOU
For your attention!