Data visualizations, commonly referred to as information graphics, is a powerful tool that will inform and educate the audience. Know more about it in this slide-deck

1. THUNDER THURSDAY
INSIGHTS – 11
VISUALIZATION 101

2. Data visualizations, commonly referred to as information graphics, is a powerful tool that
will inform and educate your audience. Often important data-heavy information can bog
down a narrative or slow the pacing of a story. That data might be edited out to
streamline a story or put into a table for readers to browse. A better solution is to use
simple graphics that can be created in minutes and delivered for free using web
tools. These information graphics will compliment and add context to your stories.
Graphics can help you highlight important information from a database in a way much
easier to understand than a text-only presentation.

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Visualization helps to:
• Analyze : Visual Comprehension is much faster than reading
• Discover : Interactive visualizations lead to information discovery
• Tell a Story : Great speaker use Visuals to make memorable story
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Visualization is any technique of creating images, diagrams, or animations to
communicate a message and it has been an effective way to communicate both abstract
and concrete ideas.
Why Visualize ?

4. What Is Data?
Data is any information you are
collecting: numbers, statistics,
measurements. It can also be
words, observations, or other
inputs.
If you are dealing with information
that represents something less
measurable, like how people feel
about a product, you are dealing
with qualitative data.
If you are dealing with numbers
that represent something
measurable, like sales of a product,
you are dealing with quantitative
data.

5. Each quantitative data point or variable you collect will be
continuous or discrete, but as a whole, you are dissecting your
data in one of two ways
Cross-Sectional
The sample of elements is
measured only once. This shows
you a snapshot of variables at a
point in time (e.g., market
survey).
Longitudinal
The data sample is measured
repeatedly over time (e.g., stock
prices, monthly sales data).

6. What Makes a Data Set?
A data set is comprised of
variables; each individual data
point—the thing that is measured
or counted—is a variable. Each
variable can be examined on its
own or in relation to other
variables to reveal insights,
including:
Mean: The sum of all variables divided
by the number of variables.
Range: The difference between the
highest and lowest variables in your data
set.
Quantiles: The values taken at regular
intervals from the inverse of the
cumulative distribution function (CDF) of
a random variable.
Distribution: The distribution of data
around a central value.
Outliers: A variable that is an abnormal
distance from other variables in your
data set.

7.  Line graph - demonstrating change over time or comparing change
over time
 Bar chart - comparing differences / similarities between groups
 Table - providing exact values
 Scatter plot - showing correlation (positive, negative, none) between
two variables
 Pie chart - illustrating large differences in proportions for simple data
DIFFERENT TYPES OF CHARTS
Chart Types for Time Series Chart Types for Ranking
Chart Types for Part-to-Whole Chart Type for Correlation

8. THINK.
CREATE.
VISUALIZE.