Abstract: A computer-implemented method, a computer program product, and a computer system for automated model lineage inference. A computer system identifies training datasets which is used to train a machine learning model. A computer system identifies parent datasets from which the training datasets are derived. A computer system identifies associated feature transformations when the training datasets are derived from the parent datasets.

Abstract: Methods, systems, and computer program products for identifying anomalous transformations using lineage data are provided herein. A computer-implemented method includes generating a set of column profiles for a corresponding set of columns within one or more datasets based at least in part on lineage data and glossary data, wherein the lineage data comprises information related to transformations performed on each column in the set by a computing platform, and wherein the glossary data comprises information related to one or more terms assigned to one or more of the columns; obtaining information related to a new transformation involving at least one column in the set of columns; comparing the new transformation to the set of column profiles to determine whether the new transformation is anomalous; and in response to determining the new transformation is anomalous, outputting an alert to a user of the computing platform.

Abstract: Using a data catalog to determine whether or not to migrate data on a potentially enterprise-level scale (such as large-scale Cloud-based data) from a source location to a target location based on classification of the substantive data and automated policies.