What would you do to fix these pitfalls? How can you avoid making future mistakes in your own visualizations?

There are countless graphs and charts to choose from when converting raw data into a visual format. For many, it can be difficult to decide whether to rely on a straightforward pie chart or bar graph or to opt for a more spatially complex chart type.

Two common questions we often hear are: “How do you know which graph to use?” and “How do you know which chart to use?” The answer, as always, depends ton he nuances of your readership, including their experience level and familiarity with big data analytics.

Based upon your understanding of data visualizations, what are 5 Data Visualization pitfalls? What would you do to fix these pitfalls? How can you avoid making future mistakes in your own visualizations?
Discussion Length (word count): At least 250 words

References: At least two peer-reviewed, scholarly journal references.

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