This article explains how to visualize information and make complex data understandable.
We work a lot with information and Big Data and we believe that half of the success (if not most of it) in data visualization is their beauty. How to understand when what type of chart to use and whether it is necessary to visualize this data at all? In this article, we share our own experience, repeatedly tested “in battle”.
Key Benefits of Visualization
Information in this form:
- Reads faster
- Better remembered – a person remembers about 80% of what he saw
- Pleasing to the eye, effortlessly understands its essence
- Presented comprehensively: this way you can show the relationship of different data
How can you visualize data
In our experience, any information can be divided into groups according to the design principle:
Factoids . It happens that one large-sized figure with a signature can be indicative. In this case, you can not make a diagram that will show it in comparison with other data, but present the information as key and self-sufficient.
Quotes . If any quote is important, it is enough, like a number, to highlight it on the slide and accompany it with a photo of the author.
Schemes . There are many options for them. This is information built in a certain graphical logic. So it is possible to depict a large amount of text in an organized and uncluttered way.
Images . It can be photos, pictures, icons, screenshots, logos. A well-chosen image replaces 2-3 paragraphs of text.
Maps . If the topic of information is related to geography, beautiful maps can replace difficult-to-read tables and graphs. For example, this way you can show the economic or any other rating of regions.
Graphs and Diagrams . And here we will talk separately below.
Less noise
Making the complex simple requires a lot of skill. Visualization is no exception. We clean the information from the superfluous, highlight the main thing, pack it into readable diagrams, graphs and pictures so that the reader does not get confused.
We recently shared our experience on how to clean a chart from visual noise. And here we will dwell in more detail on how to choose the types of graphs so that they help to correctly convey information and draw conclusions from it.
First you need to answer yourself the following questions:
- What exactly do you want to show with this diagram?
- Wouldn’t it be better to write text instead?
- Maybe you should leave the data in the form of a table?
And if it turned out that the diagram would be the best option, then our task is to determine which type of diagram suits us better. Here’s how. And let’s analyze it on the most common data visualization function – comparisons.
How can you compare data
- A donut (donut chart) or a pie (pie chart) is ideal for comparison by percentage (for example, how the age composition of the consumer audience has changed from one year to the next).
- Bar chart – for a ranking that will show leaders and outsiders (great for understanding where we and our competitors are in a certain indicator).
- A histogram, a line chart with areas, is suitable for dynamic indicators where growth and decline points are visible (for example, how profit and revenue have changed over the past 5 years).
- Tree plot with areas – to look at the distribution of objects, how many of them meet the specified criteria, or, for example, to visualize the algorithm of actions.
- A correlation chart or bubble chart shows the relationship between variables – for example, it can be used when you need to show how market participants are distributed according to two indicators
(for example, by time on the market on the X axis and revenue on the Y axis).
In general, there is nothing complicated in data visualization and there is only one secret – to put yourself in the place of a reader who sees your chart for the first time in his life and must not only understand it, but also draw conclusions from it, to which we want to push him . Working? So you are on the right track.
