Question
Visual discovery in data analysis refers to the process of examining data visually to find patterns, trends, and anomalies. It is a complex process that can be used for testing a hypothesis or mining for patterns. The process can be focused or flexible depending on the complexity of the data and the knowledge of the analyst going in.
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Visual discovery is the most complicated quadrant because it consists of two categories: testing a hypothesis and mining for patterns, trends and anomalies. Berinato says: "The former is focused, whereas the latter is more flexible. The bigger and more complex the data, and the less you know going in, the more open-ended the work."
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