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 is Data Visualization?
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. In the Arimetrics glossary it is placed in a digital marketing context to clarify its role, uses and practical implications.
What is Data Visualization used for in digital marketing?
It is used to better analyse an action, tool, channel or behaviour related to acquisition, measurement, communication, sales or user experience. Its value depends on applying it to a concrete decision.
How is Data Visualization related to a digital strategy?
It is related to digital strategy when it affects objectives, data, content, technology, campaigns or conversion processes. That is why it should be reviewed together with the business context, not as an isolated term.
What should be considered when working with Data Visualization?
It is advisable to review its definition, context, associated metrics, limitations and possible risks. It is also useful to validate whether the concept has a real impact on performance, user experience or decision-making.