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Tips: - Use color meaningfully, e.g., only use color when needed to communicate something about the data. - For categorical data, avoid using too many different colors - no more than 6 colors is best; 12 colors max. - For sequential data, don't use rainbows, use white to highly saturated.
Right at the onset credit unions should internalize the three most important principles of good visualization, the 3 s's: simple, standard and scalable.
Data visualization helps to reach decisions faster and enables viewers to glean far better insights about patterns and trends. With visualization, the benefits of data analytics are available to various roles throughout your organization, who may not be experts in the field.
Correct: The three basic visualization considerations are headlines, subtitles, and labels.
Data visualization allows business users to gain insight into their vast amounts of data. It benefits them to recognize new patterns and errors in the data. Making sense of these patterns helps the users pay attention to areas that indicate red flags or progress. This process, in turn, drives the business ahead.

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Understand the audience, work within a clear framework, and tell a good story.
First, a purpose must be defined. Second, content that supports that purpose must be selected. Third, an appropriate layout or graph type must be chosen. After that, other choices regarding elements such as fonts, colors, and icons can be made.
Data visualization allows business users to gain insight into their vast amounts of data. It benefits them to recognize new patterns and errors in the data. Making sense of these patterns helps the users pay attention to areas that indicate red flags or progress. This process, in turn, drives the business ahead.
Visualization of data makes it possible for re- searchers, analysts, engineers, and the lay audience to obtain insight in these data in an efficient and effective way, thanks to the unique capabilities of the human visual system, which enables us to detect interesting features and patterns in short time.
An important factor in choosing a data visualization tool is knowing how data will import into the tool. Regardless of whether data lives in Google Analytics or an internal SQL database, you should confirm that the data visualization tool will connect directly to your data sources whenever possible.

the amount of data being shared should not influence the type of visualization selected