Data Visualization in UI Design Explained
For a far easier method of data interpretation, a human mind needs to take in the data’s visual representation.
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While data visualization types vary and can be multi-purposeful, there are some prevalent and effective ways to use data visualization.
● Periodic Change Tracking: The most common and widely used data visualization method illustrates how the data collected changes over time.
● Frequency Identification: Typically working in tandem with the time-related changes are also data points that reflect variances in frequency.
● Correlation: Determining a relationship between two distinct variables is very challenging without being able to visualize it. Yet, it is a vital part of data analysis, one in which data visualizations’ involvement is paramount.
● Analyzing Risk/Value: With many complex metrics and variables involved, assessing the value or risk factor can be nearly impossible without the ability to visualize that data. Through charts or color-coding plot points via a formula, it is much easier to assess otherwise less apparent factors that could be game-changers in decisions made about a business.
● Study Of Networks: Marketers need to be able to break down their audience into segmented clusters, understand those clusters, assess the influencers in that sphere, and figure out how they relate to each other, as well as the outlier examples relevant to the particular area. Data visualization helps to classify this information into more evident, distinguished regions.
● Effective Scheduling: Complex projects entail the creation of often confusing schedules. This can be assisted by visual representations of the data, such as Gantt charts, helping to develop a more precise illustration of the projects, their stages, and the length required to complete them.
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