5 Data Visualization Errors: Learn How to Avoid Them

Our ancestors from decades,have been using charts to help us understand business data. But even when the data was different, the graphics were basically the same.

Now everything is changing. Our charts have become more detailed and interactive. We can work directly with the data we see, interact with the images to achieve greater depth, and navigate through all the information like never before.

It makes complex data clearer and understandable. You can see outliers, patterns, trends, and correlations that are not visible in single rows and columns.

But to experience the benefits of data visualization, we must avoid making these 5 mistakes. Know about these 5 big mistakes highlighted by Data visualization gurus and learn how to avoid them.

Mistake 1: Color abuse

When choice of wrong color takes its place, there's no need to overdo it on data visualizations. Choosing the wrong color for visualization can lead to confusion or, even worse, misinterpretation.

Tips 1: Always choose your colors carefully

• Analysis always comes first. Therefore, the colors of a brand are often not the best choice for displays.
• Always consider aware of colour-blind people. Use shapes and colors that are easier for most people to see.
• Don't rely on color just to convey meaning.

Error 2: Incorrect use of pie charts

While everyone loves cake graphics, nothing is less satisfying than a small slice.If you try to compress too much information into a pie chart, the large image is lost. Too much detail will leave your audience unsatisfied and confused.
Avoid using pie charts side by side as it is an awkward way to compare data.

Tip 2: Use Pie Charts to Get the Right Data

• Pie charts work best for limited data sets that make it easy to distinguish each slice.
• Use pie charts or charts.js to compare parts of a whole. Do not use them to compare different data sets.
• Order your slices from largest to smallest for easier comparison.

Error 3: Visual Disorder

Too much information threatens clarity.Unnecessary elements overwhelm the visualization, obscure the meaning, and lead to inaccurate conclusions.

Tip 3: Keep it simple

• Limit the number of KPIs on a dashboard to 9 or less. Too many indicators create distraction.
• Keep visualization simple. The less you have to interpret, the easier it will be to understand.
• If your visual looks messy, try a different format. The cleanest format is generally the best.

Error 4: Poor design

Just because a data visualization is pleasing to the eye does not mean that it is effective.Effective visualizations incorporate design best practices to improve data communication.

Tip # 4: Hire Professional Designers

• Don't just create visualizations and dashboards; design them.
• Work with designers to ensure visualization is as effective as possible.

Error 5: Incorrect data

Great visualizations start with big data.If your visualization reveals unexpected results, you may be a victim of incorrect data.Don't let your visualization become the incriminate for incorrect data.

Tip 5: Spot and fix data problems early

• Use your charts to detect problems with your data.
• Address issues before submitting your data. Don't let your display take responsibility for incorrect information.
• Understand the difference between an unexpected discovery and a data problem.