Check out our detailed infographic on data visualization to understand its importance in businesses, different data visualization techniques, and best practices. bit.ly/4j8WqQz

1. TRANSFORMING
BUSINESS WITH
DATA VISUALIZATION
EFFECTIVELY
THE GREATEST VALUE OF A PICTURE IS
WHEN IT FORCES US TO NOTICE WHAT
WE NEVER EXPECTED TO SEE.
This quote by John Tukey (renowned American Mathematician) states all on why Data
Visualization can transform presentation and reveal insights that could possibly change the world
DATA VISUALIZATION
WHY IS DATA VISUALIZATION IMPORTANT?
Data Visualization is an important process in the data science lifecycle that transforms data into
easy-to-understand visuals like charts and graphs for easier Understanding and Communication.
Data visualization has a huge role to play in the data-driven decision-making process, and it is
very important because-
It simplifies Complex Data and
makes it easier to understand
Supports Data-driven Decisions
with clear visual insights
Clear visuals can reveal
Trends and Outliers that might go
unnoticed in raw data
Makes communication easier and
concise with even non-technical
stakeholders
BENEFITS OF EFFECTIVE DATA VISUALIZATION
WIDELY-USED DATA VISUALIZATION TECHNIQUES
An effective visualization can benefit organizations in several ways, such as:
Some common and widely-used data visualization techniques include:
LINE GRAPHS
BAR CHARTS
SCATTER PLOTS
HEAT MAPS PIE CHARTS
STEPS FOR EFFECTIVE DATA VISUALIZATION
Identify what your data set tells Consider your audience and data points
Craft a compelling and engaging storyline Choose the right charts and graphs to present insights
When insights are presented with effective data visualization and a storyline, they can transform decision-making and business.
LEARN HOW TO CREATE A
VISUALLY APPEALING AND ENGAGING
DATA VISUALIZATION WITH THE
BEST DATA SCIENCE CERTIFICATIONS
FROM USDSI®
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Scatter Plots Bar Charts Pie Charts Heat Maps Histograms
Bubble Charts Tree Maps Line Graphs Dashboards
© Copyright 2025. United States Data Science Institute (USDSI®
). All Rights Reserved.
© Copyright 2025. United States Data Science Institute (USDSI®
). All Rights Reserved.
© Copyright 2025. United States Data Science Institute (USDSI®
). All Rights Reserved.
© Copyright 2025. United States Data Science Institute (USDSI®
). All Rights Reserved.
© Copyright 2025. United States Data Science Institute (USDSI®
). All Rights Reserved.
© Copyright 2025. United States Data Science Institute (USDSI ). All Rights Reserved.
Helps understand
how differ ent data
points relate to each
other
Improves
Engagement
Enhances
Retention
Assists with
Faster Analysis
prices over time
Best for depicting trends over time
that show changes and patterns in
continuous data.
Example Used for tracking stock
It is used to show the relationships between two numerical variables and is best
suited to depict correlations and patterns.
Example Relation between advertising spending and sales
It is used to compare categorical data
and is best for showing differences in
quantities between groups.
Example Comparing sales figures of
different products
Pie charts represent a portion of a whole
in slices of a circle. They show a share or
percentage of the whole.
Example Market share in different
industries
Heatmap uses a color gradient to
represent data values in a matrix. It is a
great way to visualize patterns in large
datasets.
Example Performance of a portfolio of
stocks