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Data Visualization and its different types
12 November 2019
is pretty a
self-explanatory term. At its simplest, it is all about visualizing data. But
what information is
visualized, why, and how? And where does
the data that is
visualized come from? These questions take a seat at the core of this activity. We can apprehend Data Visualization as
the illustration or graphic representation of the data that groups generate from a wide variety of sources. And
these sources should be without a doubt somewhere from the Net, such as
the social media, for instance. Big Data, the buzzword in the world of
technology, turns up colossal amounts of
data, all of which can be of widespread use
for businesses, however only if
they are explained and
represented meaningfully in a visual format.
This is what Data Visualization genuinely is. A statistics visualizer makes use of strategies such
as graphs, charts, maps and so on, to explain business data.
At the coronary heart of
Data Visualization lies the concept that information should not only be in
a palatable manner, but should also supply companies the
perspicacity to enable commercial enterprise decisions.
This ability that Data
Visualization is no
longer only about presentation, however also about evaluation and insightfulness.
Now, the different types of data
How does Data Visualization go
about doing its job of making data look attractive and useful? Are there
different types of
Data Visualization? Yes, and these are a few of them:
Column chart: This is mainly about using columns to represent what
is contained in data. The vertical columns are drawn to help understand the
difference between various units of data. Column Data is useful in helping
explain medium to small data.
Line chart: Line
charts are considered a vital type of Data Visualization. Why? Simply because
they can show how and to what extent data varied over a specified point of
time. This is an important tool for analysis that helps to understand the
degree of change of many important units.
Bar chart: Bar
charts are a popular form of Data Visualization tools, because they help to
understand data better by enabling them to be read using different axes.
Another advantage bar charts have over column charts is that they can analyze
larger amounts of data.
Pie chart: As indicated in the name, a pie chart
represents data in a circular figure. This kind of statistical graphic divides
data into slices, each of which can explain a specified value in numbers. Pie
charts are of enormous value in helping to understand how subsets or components
contribute to the whole. A pie chart is useful in describing hierarchies of
plot: Want to describe two variables of a data set in the form of
points to understand how they relate to each other? You could use scatter plots
to do so. The way in which the data points are distributed explains how they
interact with each other. This is useful when huge volumes of data has to be
Bubble chart: One can describe multitudes of data of a scatter
plot in the form of bubbles. This is suited when limited amounts of data are
What we have described here is a
small set of the various Data Visualization types. You can explore more about
this fascinating area of study by looking at some of our online
courses on Data Visualization. We are confident that you will
find them very interesting and fun to learn from!
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