With AWS Glue DataBrew, you can now visually detect outliers in data from your data lake, data warehouses, and other JDBC-accessible data sources. You can further handle outliers by replacing, removing, rescaling, or flagging them using mathematical and algorithmic methods such as z-score (to find the difference from mean value and divide it by the standard deviation), modified z-score (to calculate the difference from median absolute deviation), interquartile ranges (to calculate values between the first quartile and the third quartile) and one or more transformations such as creating a flag column, applying window functions, or choose from over 250+ other transformations.  

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