Great Ways to Present Your Data

Reporting the findings of a study is often thought of as the final step in program analytics. People that view data presentation as of lesser importance misinterpret it. People that are interested in data-driven discovery and transformation should prioritize data presentation and take advantage of solutions such as stale slideshows and Powerpoint presentations. No matter how sophisticated and streamlined a display is, it doesn’t make sense if it doesn’t address the right audience. The following are incredible tips for overcoming the barriers of data presentation and becoming more effective at reporting data-driven findings.


Visualization may not leave adequate space for words, but data presenters can still use images to sell their story. However, that doesn’t make words less useful; instead, data presenters should think of it as meaning that every word counts and ensure no word goes to waste. Even without a room for wording, data presenters can use wording techniques to make their presentations unique. You should start by making headings and titles less generic, and instead, use that front page for highlighting the key points. Like other storytelling processes, data-driven storytelling can be done in many ways, but the only difference is that no audience needs a surprising ending. Of course, the viewers want to get the facts they paid for before the end of a story.

Become a Numbers Artist

It involves more than the use of numbers and logic to figure out how to present data-driven discoveries. Research has shown that speaking to both the heart and head of the audiences can persuade them to change their mind and take action. Though numbers are effective at presenting quantifiable information, data presenters might need some forms of grounding or humanizing data when communicating how things impact the lives of their target audience. Sometimes data presenters can achieve this by attaching an image that relates to their topic next to the chart or graph.


The use of colors is one of the useful storytelling and data visualization tools. The eyes of the target audience are attracted to color, so data presenters should use colors that drive the eyeballs towards the key aspects when telling stories. Data presenters can use various colors such as grey or brown to de-emphasis anything that isn’t essential at that point.

Don’t Be Stuck to the Past

At least half of the target audience is likely to use their mobile devices to read business analytics. You can present reports as if they are intended to bound into a book or printed. However, the habit has become unnecessary today because it tends to prevent actual readers from engagement. Ideas such as leaving blank pages and carrying over old things are no longer useful. Bloating reports of a data-driven discovery can be an effective way to leave insights unexploited and findings ignored.

Start at the End

Though it alludes to the above, starting at the end deserves its unique heading. Data presentation experts recommend flipping the script to the order in which data presenters report their findings. That means students and any other presenters should consider re-arranging their ways of communicating their reports.

People that have come through academia are indoctrinated with the culture that says they should explain their message, discuss the findings that people have discovered, and give their background. However, starting at the end fails the color consideration test option because it doesn’t consider things from their viewpoint and describe them in a way the target audience can understand.

Therefore, data presenters should start with the findings, conclusions, and action items to ensure the target audience understands the results clearly. It also gives data presenters a chance to report their findings in a way that other people will understand and remember.

Everything discussed above including words and colors and speaking to the hearts and heads of the target audience as well as becoming a number artists impacts the way people report their data-driven discoveries.