As important as data is to business decision making, data is barely comprehensible to people in its raw form. Business leaders interested in harnessing the power of data need to translate it into a visual format, like charts, plots, graphs or maps — but selecting the wrong data visualization is a quick and easy way to reduce the comprehensibility of a data set and thus negatively impact the effectiveness of business decisions.
Business leaders who lack experience in data science should make use of augmented analytics services that utilize artificial intelligence to select the best data visualization for any information. Still, it might be useful for business leaders to understand more about different types of data visualization and how to choose the correct option in the future.
There Are Over 32 Types of Data Visualizations
Data can be visualized in myriad ways, depending on the type of data and the creativity of the data scientist. However, most data experts accept as many as 32 ways of visualizing data for business use. These include common charts and graphs as well more esoteric tables, wheels and keys. Most businesses will make use of no more than about 15 types of visualizations, and some of the most popular visualizations include:
- Line graphs, which has a Y axis for quantitative data and X axis for time
- Column or bar charts, which compare values of different categories, which can include time
- Pie charts, which show composition of a total, usually in the form of percentages
- Scatter plots, which place points at intersecting numerical values to show comparison and correlation
- Geospatial maps, which displays data tied to region
Some visualizations are exclusive to specific types of information. For example, it would be essentially impossible to force data appropriate for a business timeline into a pie chart. However, there are many visualizations that overlap in their capabilities. For instance, both pie charts and stacked bar charts are capable of visualizing compositions of totals. So, how does one go about selecting the right visualization for one’s data?
How to Choose the Exact Right Data Visualization
The best way to choose a data visualization is to consider what one needs that visualization to achieve. Visualizations make it easier for the human mind to understand data, and certain visualizations are better at demonstrating certain concepts. Thus, the first step to choosing the right visualization is considering, in general, what task that visualization needs to perform. Some of the basic tasks visualizations might be assigned include:
- Showing change over time
- Showing part-to-whole composition
- Looking at data distribution
- Comparing values between groups
- Observing relationships between variables
- Looking at geographical data
Once one has a sense of the essential task the visualization must accomplish, one should think about different features of the visualization that can make the data even easier for the audience to comprehend. During this step, professionals should think deeply about their audience, striving to give themselves a similar perspective as a typical audience member. Some audiences will be capable of comprehending visualizations that are denser with data, while other audiences will need the simplest and most straightforward visualizations.
One way to make a more complex visualization easier for an audience to read and understand is to introduce color. Shading can clearly differentiate different categories and values, transforming even the densest data into an easy-to-read visualization. This method works well for every type of visualization, even more advanced visualizations.
Some other features that can be added to visualizations include:
- Trend lines, which connect pivots in graphs to show a prevailing direction
- Annotations, which are text boxes over visualizations to provide context or explanation
- Extra dimensions, which layer on top of visualizations for more information in less space
However, it is critical that all business professionals remember that clarity should be the primary and ultimate goal of data visualization. If any feature accidentally obscures key insights, the visualization will not be able to accomplish its goal of guiding business decision making in a positive way. Finding the perfect visualization can take practice, but as long as one knows what one is hoping to accomplish with their visualization, they should be able to choose a chart or graph that suits their needs.