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For College Students

Good Data Visualization In Tableau

Traffic Words
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Imagine one day traffic lights suddenly have no colors; instead, they are just words in the same color. This would create a lot of chaos. For instance, take a look at this image.

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The human brain is wired in such a way that it responds much faster to images than to words. It is estimated that we process visual information up to 60,000 times better than textual information. Hence, if you want your audience to comprehend the data, it is always better to visualize it. So data visualization is a key skill in a data scientist's toolbox. 

 

In the forthcoming video, Sean will explain his views on data visualization. 

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One of the critical factors that make a data visualization good is its effectiveness in communicating the intended information. However, it is just one aspect of a good data visualization. In the forthcoming video, you will learn about other factors that make for effective data visualization.

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So, as you saw in the video, data visualization is a way to make complex data understandable. It is a way to tell stories. And similar to how there are good stories and bad stories, there are good data visualizations and bad data visualizations. 

 

 

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So, as you saw in the video, visualizations can be manipulated easily. So, you need to ensure that when you present data, you keep its sanctity. 

 

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You can read this article to understand the differences between visual and textual forms of data in terms of marketing:

Visuals vs text

 

In the next segment, you will learn about the uses of data visualization.

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So, in the video, Sean explained the properties of a good data visualization: 

  1. It meets the audience’s needs.
  2. It communicates clearly.
  3. It provides a gradual learning curve.
  4. It adds value to the data.
  5. It tells the truth.

 

Although the ideals discussed above might appear quite obvious, often people manipulate visualization to present the story they want to tell. In the next video, Sean will show some examples of bad data visualizations.