Detect outliers and use dedicated transforms to handle outliers in AWS Glue DataBrew

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.  

Source:: Amazon AWS