Data visualization can help in detecting anomalies by providing a visual representation of data that can be easily interpreted. It allows for the identification of patterns, trends, and outliers that may not be immediately apparent in raw data. For example, in the case of Tesla Motors, data visualization was used to monitor the pressure in a car's tires over time. This allowed for the detection of anomalies such as improperly inflated tires, leak rates, and predictive modeling on when tires are likely to go flat.
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