How can you highlight outlier data in Oracle Analytics Cloud?

Highlighting outlier data in Oracle Analytics Cloud can effectively be achieved by adding an outlier visualization to your canvas. This specific type of visualization is designed to detect and emphasize data points that deviate significantly from the norm. Outlier visualizations use statistical methods to identify these points, making it easier for users to focus on anomalies that could indicate important trends, errors, or unique cases in the dataset.

The outlier visualization is adept at providing insights into how the data behaves under normal circumstances and pinpointing those unusual values that might require further investigation. This functionality helps analysts and decision-makers swiftly recognize instances that might merit additional context, such as data quality issues or remarkable performance metrics.

Other potential methods for visualization may serve certain purposes, but they do not specifically focus on highlighting outliers in the same targeted way. While a box plot could help in visualizing the spread and interquartile ranges of data, it does not distinctly highlight outliers as its primary function. Similarly, modifying the color palette to highlight unique values may change how data is visually represented, but it doesn’t inherently identify or emphasize outliers based on statistical deviations. A data sequence chart is useful for observing trends over time but lacks the capability to specifically isolate outliers.