top of page

Data Visualization: How to Eliminate Visual “Noise”

Perhaps you’ve heard the classic acronym, KISS. Keep. It. Simple. Sweetheart.

Simplifying a message is an essential part of the communication process. Simplicity gives a message clarity. It refines it and provides ease of understanding.

a man reaches on tip toes toward a large confusing  illustration of icons and symbols

Effective data stories should be easy for your audience to understand. The goal is to communicate insights in such a way that convinces or compels an audience. Data visualization is one of the data storytelling essentials and simplifying your data visuals is one of the steps in their creation.

Communication is not just imparting information; it is a process of creating shared meaning from that information. Similarly, data storytelling is an act of communication that distances itself from data showing or data sharing, by focusing on the receiver’s understanding of what the insights mean.

Before you can focus attention, you must first eliminate data visualization noise to the extent to which you can.

In a previous post, I discussed selecting the right tool to graphically represent your data. In this article, we will look at a strategy to eliminate visual noise in graphs and charts.

Data Dump

Avoid data dump in your visualizations. Data dump is the tendency to crowd a data story with too many graphs and/or charts and with too much information. Too much information reduces message effectiveness and impact. Most people are aware of this but do it anyway. Why? Because brevity takes time. Ironic, isn't' it?

If I had more time, I would have written a shorter letter.

Whichever bar chart, line graph, or other visualization that you end up selecting to represent your data, the next step is to prepare it to effectively communicate your message.

Since Excel doesn’t know your business question, the chart and graph selections return everything in the table with labels and legends as needed. With all the information present, none of it and all of it stand out at the same time.

An effective data story doesn’t show or share all the data. In order to focus the audience’s attention on where you want it, you first need to get rid of all the visual distractions.

Watch this short video. How many passes does the team in white make?

If you are like most people, you got the count right. 13. But chances are you did not see the moonwalking bear until you knew where to focus your attention. Why didn’t you see it the first time? There were too many distractions in the visual field!

Remove and Reduce: Eliminate Data Visualization Noise

One strategy for eliminating noise in the visual is to remove and reduce. This strategy is adapted from Cole Nussbaumer Knaflic’s book “Storytelling with Data”.

With remove and reduce you first remove extra chart features and then reduce remaining elements to a shade of gray.


First, remove all the distracting noise in the chart itself.

  • axis titles

  • chart titles

  • data labels

  • legends

  • grid lines

These chart elements can be helpful, but they are often more of a hindrance. As you remove the items, note which ones add to understanding the data and which ones do not make a difference.

Some chart elements may be helpful for context and sense-making. The fewer chart elements you have, the better. Once you have removed the elements, review your chart to see if you need to return any. You may want to return gridlines or an axis, but not labels and titles, those you can add back in PowerPoint.


Next, reduce any remaining lines, shapes, and labels to the color gray. Use the format options to change the color of each of these items. Each part of the graph can be independently formatted.

Compare the two visuals. The first one is the initial software generated bar chart. The second is the bar chart with the visual noise eliminated.

Eliminating the noise even affects your own eye’s ability to notice trends and patterns. This technique is helpful when creating data visualizations for exploratory and explanatory analysis.

The resulting gray chart is now a canvas upon which to reintroduce design elements with intention. Using design elements to emphasize the key takeaway in the next step in the data visualization creation process. And that will be a great topic for another post!


One of the key steps in the creation of a data visualization is to eliminate the visual noise in the selected chart of graph. One strategy to use in eliminating noise is the remove and reduce strategy, which was described. By using the remove and reduce strategy, the visualization is freed of distracting elements. Keep it simple.

profile photo of blog author

Roseanna Galindo is Principal at Periscope Business Process Analysis and a champion for data literacy, the human experience in healthcare, and leaders of volunteers everywhere. Learn more about Roseanna and her blog, The Periscope Insighter, by reading the opening post, Venn The Time Is Right

Roseanna is available for training, keynotes, and executive coaching. Visit for more information or click on the button below to schedule a time to talk

If you have found this article insightful, please share on social to help other like-minded business leaders to find their way here.


Comment. Share. Like. Subscribe.  Thank you!



bottom of page