Definition:
Data visualization is a general term that describes any effort to help people understand the meaning of data by placing it in a visual context. For example, patterns, trends, and correlations that might not be detected in text-based data can be exposed and recognized more easily with data visualization software.
Data visualization has its origin in the birth of Web 2.0 as a result of the abundance of interpretable data and the need to create methods for them, since then more and more types of data visualizations are available.
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Types of data visualizations
There are many ways in which we can arrange the data for interpretation, as many as we want to give them. Some of the most important would be the following:
- Tables: The data are presented by tables formed by rows and columns so that we can associate contents quickly, it is also a very useful tool to perform mathematical calculations and that has become enormously popular thanks to the success of programs such as Microsoft Excel.
- Graphs: Graphs or graphs is a type of visual representation of very visual data with the aim of expressing the numerical relationship that the data keeps with each other at a glance. The most used visual resources are lines, vectors, surfaces, bars, etc …
- Infographics: infographics are combinations of images and texts of an explanatory nature and with a careful aesthetic with the aim of communicating information in a visual way.
- Treemap: Treemaps represent hierarchical data using nested figures by means of rectangles.
- Word clouds are visual representations of the words that make up a website or a text, being the largest those that appear more times.
Images can include interactive capabilities, allowing users to manipulate or inquire into the data for query and analysis. Indicators designed to alert users when data has been updated or predefined conditions occur can also be included.
Importance of data visualization
Because of the way the human brain processes information, data visualization is very important. Using tables or graphs to view large amounts of complex data is easier than poring over spreadsheets or reports. Data visualization is a quick and easy way to convey concepts in a universal way, and you can experiment with different scenarios, simply by making small adjustments.
Frequently asked questions about Data Visualization
What does Data Visualization mean in digital marketing?
Data Visualization refers to the concept described in this glossary entry: Definition: Data visualization is a general term that describes any effort to help people understand the meaning of data by placing it in a visual context. For example, patterns, trends, and correlations that might not be detected in text-based data can be exposed and recognized more easily with data visualization software. It gives teams a shared vocabulary for analysing digital projects.
When should teams pay attention to Data Visualization?
Teams should review Data Visualization when it affects acquisition, measurement, user experience, content, automation or campaign performance. The important step is to connect the definition with a real decision.
How is Data Visualization used in a digital strategy?
Data Visualization is used by translating the concept into practical checks: where it appears in the funnel, which data or channel is involved and whether it needs optimisation, monitoring or documentation.
What is a common mistake when interpreting Data Visualization?
A common mistake is using Data Visualization too broadly. It is better to verify the context, the tool or the metric involved before making strategic or technical conclusions.