![Animating Data Visualization: Bringing Analytics to Life](http://media.assettype.com/analyticsinsight%2Fimport%2Fwp-content%2Fuploads%2F2021%2F07%2FAnimating-Data-VisualisationsBringing-Analytics-to-Life.jpg?w=480&auto=format%2Ccompress&fit=max)
Data visualization is a powerful approach to present different types of data, big or small. The practice of translating information into visual text makes it easier for the human brain to perceive data and draw insights from it. The primary goal of data visualization is to make it easier to identify patterns, trends, and outliers in large data sets. Visualization is crucial for almost every career. It is that part of the data processing that states that the data collected, processed, and modeled can be visualized to reach conclusions.
Animation can bring data to life during both the visual exploration and storytelling phases. By animating data visualization, one can engage viewers in many ways. Static data visualization, especially the unique ones, can be persuasive and aid decision-making. Animating them will boost these advantages even further.
There are different ways in which animation can benefit the visualization of data.
The great Hans Rosling revealed various ways to make storytelling more captivating. The ways through which he enabled the creation of a wide range of dynamic data visualization related to financial and physical well-being. He introduced us to use the power of visualization to create an emotional impact and clear communication. He further refined the link between animation and data storytelling. Animating data visualization is an interesting topic and is an exceptionally effective method to engage viewers on a deeper level through emotions. The users can implement different presentation styles with data stories. The primary goal of animating data is to improve communication and drive change.
Visual analytics aids in clear communication, but it also benefits exploration and analytics. Without animation, when a chart is changed or filtered, it becomes difficult to intercept the movement of data points from one place to another. In these cases, animation steps in, based on a concept called object constancy. It allows a graphical element to be tracked throughout a transition. Object constancy allows the individuals to understand and see the changes, rather than having to identify each new point. The simple changes in charts and trends affect how we perceive data. We are connected to the insights we draw from the data.
The primary objective of illustrating data is to communicate to the viewers how something changes from one position to another. Time sequences or logically ordered series can benefit from animation. It might slow the process of communication, but they benefit from a new level of engagement, especially for audiences who might not usually engage with data.
According to studies conducted, animation improved the quality of data both at the syntactic and semantic levels of analysis. Even in highly predictable transitions, animation had a significantly lower rate of errors. The results also revealed a strong preference for animation, as the research subjects found it more helpful and engaging. Also, staged animation had a higher preference than direct animation in most cases.
Currently, several business leaders are getting more attracted to visual analytics. Animation plays a crucial role in the quality of insights drawn from the data. It works at a psychological level to keep the viewers attached to the data and appeals to the users' creative and storytelling side.
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