Why do we need data visualization?
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We need data visualization because a visual summary of information makes it easier to identify patterns and trends than looking through thousands of rows of data on a spreadsheet. It’s the way the human brain works (Merieb & Hoehn, 2007) as our eyes are drawn to colours and patterns. We can quickly identify red from blue, square from circle. Our culture is visual, including everything from art and advertisements to TV and movies (Ubani, 2016). Even if someone were to gain insights from a spreadsheet of data, it would be much more difficult to share the extrapolated information without the use of visualizations. Charts and graphs make communicating findings easier even if you could explain your findings without them.
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Without a visual representation of your insights, it becomes difficult for an audience to grasp and decipher the meaning of the data you’re presenting. As an example, rattling off a bunch of numbers in a meeting may not communicate the importance of a school’s reading program, but having visualized graphics outlining an increase in student engagement, demand and growth may better articulate your perspective.
Almost 50% of your brain
is involved in visual processing.
(Merieb & Hoehn, 2007)
We can get the sense of a
visual scene in less than 1/10 of a second.
(Semetko & Scammell, 2012)
70% of all your sensory receptors are in your eyes.
(Merieb & Hoehn, 2007)
Click here and explore a live data-visualized dashboard. Notice how your interactions with the dashboard affects the data being presented?
Data Exploration with Visualizations
Data exploration is the initial step in data analysis. This is the part of a data analysis where one explores large sets of data in an unstructured way to uncover initial patterns, points of interest, and characteristics. This portion of one’s analysis isn’t meant to reveal every possible connection and bit of information, but rather helps create a broad picture, identifies important trends and provides one with a direction to focus their study. Visualization compliments data exploration because it creates a more straightforward view of data sets than simply examining thousands of individual numbers or names.
Dashboards are becoming a prominent tool in data exploration. Dashboards allows the viewer to not only view, but to also manipulate the data using a graphical interface.
Communicating Information
While data exploration takes advantage of how easy it now is to draw and redraw graphics (with the use of data visualization and graphic design tools), presentation graphics are quite different animals. Presentation graphics tend to be more polished than data exploratory graphics. They are often designed for a wider audience, are accompanied with explanatory text and they account for the medium in which they are presented by being multimodal and visually attractive.
A good presentation visualization tells a story by removing the noise from data and highlighting useful information. With that said, a good visualization must find an equilibrium between its form and function. The plainest graph could be too boring to catch any notice or it may make a powerful point; the most stunning visualization could utterly fail at conveying the right message or it could speak volumes. The data and the visuals need to work together, and there’s an art to combining great analysis with great storytelling (tableau.com).
Discussion
There are many great examples of data visualization floating around the internet. Look for an example of data visualization that particularly speaks to you and share why the method it uses to display data resonates with you.
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Hint:
The following subreddits can be a great place to start your search for a data visualization. Try sorting by 'Top' and see what comes up.
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Data Visualization Examples