Data Visualization: What You Need to Know?
Data is at the heart of all discussions on the future of our societies. Already in 2017, Jeff Fochtman, marketing manager at Seagate announced: What is surprising is not that the production of data to be stored is increasing, but the frantic pace of this increase.
Today, data production is peaking at unprecedented levels and its growth is not about to slow down (connected objects, voice assistants, autonomous cars, Artificial Intelligence, Smart City…are all technologies which will increase this data flow). These reasons make data visualization a key issue for professionals.
What is data visualization?
The graphical representation of data (data visualization or dataviz) consists in visually structuring data collected and stored. So every organization has data. Small, medium, large business, public institution and even associations, all have data with their archives and newly collected data.
This archived data, once digitized, turns out to be real gold mines. As you can see, data visualization is the art and the way to transform this raw material into a great analytical tool. By showing the invisible, data visualization facilitates and accelerates decision-making. It is a valuable tool more effective than simple Excel tables. You get to the basics. Data visualization simplifies the dissemination of information. It brings points of comparison and trend analysis. It then refines the prediction on future trends.
A good graphical representation of the data takes into account its target. The information presented must therefore be in line with the functions and the time available to your audience. It is therefore necessary to go to the basics and keep consistency in your ideas.
Form is essential
The type of graph is a criterion of choice in the representation of your data. We do not represent a change over time as we would for a comparison.
- Change over time: Line charts, bar charts, stacked bar charts, candlestick charts, pie charts, timelines, horizon charts, waterfall charts.
- Comparison: Bar charts, grouped bar charts, bubble charts, multi-line charts, parallel coordinate charts, bulleted charts ·
- Classification: ordered bar diagrams, ordered column diagrams, parallel coordinate diagrams ·
- Distribution: histograms, box plot diagrams, violin diagrams, density graphs
- Correlation: Point cloud diagrams, bubble diagrams, column and curve diagrams, heat map.
However, the appearance of a graph changes your perception of the data. A line graph shows trends and fluctuations in a fraction of a second. A pie chart is useful for quickly comparing data but is not recommended for accuracy.
In addition, the angles and arcs of circles are difficult for the human eye to appreciate, the measurement of the data is reduced. So choose the graphic that best tells your story. In addition, avoid anything that does not provide information to your data presentation. Texts, illustrations and 3D, if they are superfluous, have no place! Also remember to prioritize your information. As an example, on a bar graph, place the highest values at the top as below.
Use the right colors
You certainly know that colors affect our emotions! These influence our decision-making. To convince, do not neglect the choice of your colors! One of the basic rules in data visualization is the use of a single color to represent the same type of data.
The use of several colors is not prohibited but is not recommended. Your palette should be limited, and your colors should provide information to your presentation. Do not use totally different colors. They make your presentations unsightly but above all participate in an unconscious hierarchy of information while blurring the perception of data.
Colors provide information on the quantities. They make it possible to highlight certain data. They also provide information on the interest to be given to data sets (danger levels, positivity, negativity etc.). The colors have a symbolism that must be taken into account!
Other rules of use are essential. Your data visualizations are studied via screens or projectors, the bright colors (even fluorescent) are aggressive and will be lacking in the understanding of your presentations. We mentioned above taking into account your targets, if in your audience there are individuals with visual impairments (color blindness, photophobia, visually impaired …) use pastel colors and fills in the form of diagonal lines (be careful this type of filling is to be avoided in the case where there is no handicap).
As with the shapes, your colors should be as refined as possible. They contribute to a better understanding of your data presentation.
Typography and text
The choice of your typography is crucial. That said, some good textual practices will make it easier to understand your data visualizations. Again, you will need to take your audience into consideration and make your texts as inclusive as possible.
Always add a title to your graphics. This title contributes to the contextualization of your presentation and brings precision. However, do not have a title that is too long or complicated, be concise.
Adding captions is done at the top of the graphs. Why? Simply because the legend provides information on how to read your graphics. We must follow the direction of the reading, and this reading must be as fluid as possible! Adding the legend should only be done if necessary.
Write in the present. The present is a descriptive time that involves the audience.
The text holds a secondary place in data visualization so it must be restricted to the strict minimum. Your audience should not be dispersed, it should be focused on the highlighted data.
Conclusions
the graphical representation of the data facilitates understanding of the world. It is a great tool for analysis and projection into the future. It quickly established itself as one of the keystones of decision-making. Today it becomes accessible to the greatest number. How to make a good presentation of your data? Here is a brief summary:
- Take into consideration your audience (function, available time, disability, etc.)
- Choose the graphic that best suits your needs
- Do not insert superfluous elements (3D, blinking…)
- Text and images should be used sparingly
- Choose your colors carefully
- Use modern typographies
- Add titles, and captions if necessary
- Write in the present
- Get to the point
