TRANSFORM FOR OUTLIER DETECTION IN EXTRACT, TRANSFER, LOAD ENVIRONMENT

Systems and methods that cleanse data in Extract, Transform, Load environments (ETL), via employing an outlier detect component that is positioned in data pipeline to data warehouse(s). Such outlier detect component employs a cluster mining model to split data into normal and outlier data. Different predictive models can be employed to detect outliers in different data slices to enhance the accuracy of the predictions. In addition, a graphical user interface (GUI) enables a user to interact with cluster groups that are created and/or analyzed by the outlier detect component.