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Tips for Effective Data Visualization

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By Myra More Last Updated on Jun 15, 2021
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  • Posted By Myra More
  • Categories Big Data

Big Data Analytics has made understanding data easier than ever before. The amount of data generated now is ten folds than a few years ago. It is much more than ten folds. Drawing inferences and insights into patterns related to a business are both efficient and effective, thanks to Big Data Analytics. While it is exciting to know the minute details that good data can provide, it is also taxing to understand how best to present it. This is exactly what Data Visualization deals with.

Data Visualization is a term used for all procedures which help present data in an easy to understand and visually attractive manner. The representation of data can be in the form of charts including and beyond the general Excel-based charts and graphs. Data Visualization software allows you to present data that might go ignored in the text. Important correlations or patterns hit the eye and minds of the people seeing data in the form of a chart faster than text. The newest software’s in Data Visualization help present data in formats like infographics, geographic maps, thorough charts, dials, and gauges. All these formats help drive a point home in the shortest time!

Take, for example, the following chart: One look at it and you know how 30 companies performed since the 1950s till date. That’s a lot of time and a lot of data. All presented in one chart that is not taxing to the eye. It is also visually delightful. It helps understand the various milestone events that happened since the 1950s. Impressive isn’t it!? Wait, there is more to floor you.

Suggested Read: Data quality and intelligent AI

If you go to the original chart made by Tableau Software you can hover on the chart and see more details. It is factually a mountain load of important information about these 30 companies, all packed and presented in one single chart. Admirable! Imagine, presenting this wealth of information in the text. It is going to be one volume of a book! In this sense, Data Visualization is an art custom!

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Attention to the following rudimentary elements will help you in your journey of perfecting Data Visualization. These elements are the essence of good Data Visualization practices by the best in the industry.

Keep it Simple

This is probably the most important yet the most ignored element in Data Visualization. It is not necessary to have a complicated looking chart to prove a point. Simple charts can do the same thing too. They drop all the unnecessary angles which distract you from the important points a chart is presenting. You are making a chart to say something. If your end-user is confused because your chart is complicated, then it’s a lost cause. As a case in point, if a unicolor simple two-dimensional chart can do the job for you, there is no need to create a 3D multicolor chart.

Use Colors to Convey

Yes, a chart gives you the freedom to present data brightly. No, there is no need to splash a multitude of colors in one chart. Unless of course, the chart so demands it, like the 30 Companies chart we discussed a while ago!

Many people seem to think that a colorful chart is imperative. On the contrary, just the right amount of color is good enough. It is also important to understand what colors to use. Every color has an instinctive meaning that we all associate with. For instance, red means danger. It means the same crossways the globe.

Also read: Python programming for data science

Another important feature of colors is using the right combinations. Obvious combinations put your viewers off! Defaulting choices might not always work best for you. Feel free to use your combinations of colors with utmost importance to the viewer. Colors, if they do not help convey the point, are a nuisance! Here’s a really good blog post on the practice of colors. The whole post is great and points no. 3 discusses colors in detail with relevant images.

Maintain Data Accuracy

Numbers don’t lie! It is the same case with all data. All data depicting graphs and charts should do the same too. They must maintain data accuracy at all costs. After all, what good is a chart if there is no truth in it!

Data accuracy is like the depth of a chart. It shouldn’t be tampered with. A graph released by Reuters on Gun Deaths in Florida is a good example to know what not to do concerning data accuracy.

Attention Retention

As the case with all things technology, attention retention is an important aspect with graphs. Any visual that doesn’t carry the core of its message within 5 seconds is a wasted effort. Graphs or charts created using a good quality data visualization software help in retaining the essence of the data and present it in a less than 5-sec format. But, relying totally on software is not a great idea. You as the creator of a specific chart should be clear about the main idea that you want to convey.

Just like language has rules about grammar, vocabulary, and spellings, the design has rules too. Sticking to these rules helps! It makes your data.

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