You’re struggling to explain complex data. How can you make it easy to understand?

3 Simplify and summarize

One of the biggest challenges of explaining complex data is to avoid overwhelming or boring your audience with too much information. You need to simplify and summarize your data in a way that preserves its accuracy and relevance, but also makes it easy to grasp and remember. You can do this by using simple language, avoiding jargon and acronyms, and providing definitions and examples when needed. You can also use filters, categories, or segments to group your data into meaningful and manageable chunks. Finally, you can use headlines, captions, or bullet points to highlight the main points or takeaways of your data.

4 Visualize and contextualize

Another way to make your data more understandable and appealing is to use visual elements and context clues to enhance its meaning and impact. You can use colors, shapes, sizes, or symbols to differentiate your data points, show contrasts, or emphasize trends. You can also use scales, axes, labels, or legends to provide reference points and clarify your data dimensions. Moreover, you can use comparisons, benchmarks, or analogies to relate your data to something familiar or relevant to your audience. For example, you can compare your data to the size of a country, the population of a city, or the budget of a project.

5 Engage and interact

Finally, you can make your data more interesting and memorable by engaging and interacting with your audience. You can do this by asking questions, soliciting feedback, or inviting participation. You can also use stories, anecdotes, or humor to connect with your audience on an emotional level. Furthermore, you can use animations, transitions, or effects to create movement and dynamism in your data presentation. You can also use tools, features, or functions to allow your audience to explore, manipulate, or customize your data. For example, you can use sliders, filters, or buttons to let your audience change the variables, scenarios, or perspectives of your data.