Abstract: Techniques for validating large amounts of sensitive data migrated across multiple platforms without revealing the content of the sensitive data are provided. For example, a processing device can transform data in a first data file stored on a first platform to common data formats. The processing device can generate a first set of hash values. The processing device can receive a second set of hash values for a second data file stored on a second platform. The processing device can compare the first set of hash values and the second set of hash values and cause the first data file or the second data file to be modified based on a difference between the sets of hash values.

Abstract: Techniques for validating large amounts of sensitive data migrated across multiple platforms without revealing the content of the sensitive data are provided. For example, a processing device can transform data in a first data file stored on a first platform to common data formats. The processing device can generate a first set of hash values. The processing device can receive a second set of hash values for a second data file stored on a second platform. The processing device can compare the first set of hash values and the second set of hash values and cause the first data file or the second data file to be modified based on a difference between the sets of hash values.

Abstract: A system receives, from a remote computing device, a query for a timing of an adverse event associated with a target entity. The system determines, using a timing prediction model trained using a training process, the timing of the adverse event for the target entity from predictor variables associated with the target entity. The training process includes accessing an observational journal comprising historical panel data of the target entity including values of predictor variables for one or more time points and generating, from historical panel data, an augmented time series by augmenting the historical panel data with values of predictor variables for at time points for which the historical panel data does not include values of predictor variables. The system transmits to the remote computing device, a responsive message including at least the timing of the adverse event for use in controlling access of the target entity to one or more interactive computing environments.

Abstract: Techniques for validating large amounts of sensitive data migrated across multiple platforms without revealing the content of the sensitive data are provided. For example, a processing device can transform data in a first data file stored on a first platform to common data formats. The processing device can generate a first set of hash values. The processing device can receive a second set of hash values for a second data file stored on a second platform. The processing device can compare the first set of hash values and the second set of hash values and cause the first data file or the second data file to be modified based on a difference between the sets of hash values.