Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for managing computing systems according to detect and correct configuration gaps with specific system requirements frameworks. Specifically, the disclosed system accesses a digital data repository to determine attribute values of data objects representing functions or infrastructure associated with handling target data for an entity. The disclosed system determines a digital representation of a system requirements framework that indicates controls associated with handling specific data types. Based on the attribute values and a gap rules set associated with the system requirements framework, the disclosed system determines configuration gaps to be addressed via control actions for installing controls in connection with various data assets or data processing operations.

Abstract: Aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for detecting prejudice bias in machine-learning models and/or data sets used in training, testing, and/or validating the models. In accordance various aspects, a method is provided comprising: receiving a data set used for training, testing, and/or validating a model that comprises data instances; generating, using a classification model, a prediction of applicability for each sub-category of a plurality of sub-categories for each bias category of a plurality of bias categories for each data instance; determining that a particular sub-category for a particular bias category is applicable to a proportion of the data set, wherein predictions of applicability for the particular sub-category generated for the proportion of the data set satisfies a threshold; and determining, based on the proportion, that the data set has a prejudice bias with respect to the particular bias category.