Abstract: Methods, apparatus, and processor-readable storage media for automatically purging data using a deep neural network are provided herein. An example computer-implemented method includes training a neural network model using multiple types of attribute data and job-related data associated with historical workflow data maintained within multiple data structures of an enterprise system; dynamically analyzing workflows derived from the enterprise system, wherein dynamically analyzing the workflows comprises determining the multiple types of attribute data for the workflows and processing job-related data associated with the workflows into multiple data structures within one or more databases; applying the neural network model to the determined attribute data; and removing at least a portion of the multiple data structures from the one or more databases based at least in part on the application of the neural network model to the determined attribute data.

Abstract: Methods, apparatus, and processor-readable storage media for machine learning techniques for automated processing of workflow approval requests are provided herein. An example computer-implemented method includes generating a machine learning model for workflow approval requests, wherein generating the machine learning model comprises automatically learning temporal-based patterns from historical data related to previous workflow approval requests; generating, in response to an additional workflow approval request, an output value by applying the machine learning model to input data related to the additional workflow approval request; comparing the output value to at least one predefined threshold value; and automatically rejecting the additional workflow approval request responsive to a result of the comparing of the output value to the at least one predefined threshold value.

Abstract: Methods, apparatus, and processor-readable storage media for request approval using blockchain technology are provided herein.

Abstract: Methods, apparatus, and processor-readable storage media for machine learning techniques for automated processing of workflow approval requests are provided herein. An example computer-implemented method includes generating a machine learning model for workflow approval requests, wherein generating the machine learning model comprises automatically learning temporal-based patterns from historical data related to previous workflow approval requests; generating, in response to an additional workflow approval request, an output value by applying the machine learning model to input data related to the additional workflow approval request; comparing the output value to at least one predefined threshold value; and automatically rejecting the additional workflow approval request responsive to a result of the comparing of the output value to the at least one predefined threshold value.

Abstract: Methods, apparatus, and processor-readable storage media for automatically purging data using a deep neural network are provided herein. An example computer-implemented method includes training a neural network model using multiple types of attribute data and job-related data associated with historical workflow data maintained within multiple data structures of an enterprise system; dynamically analyzing workflows derived from the enterprise system, wherein dynamically analyzing the workflows comprises determining the multiple types of attribute data for the workflows and processing job-related data associated with the workflows into multiple data structures within one or more databases; applying the neural network model to the determined attribute data; and removing at least a portion of the multiple data structures from the one or more databases based at least in part on the application of the neural network model to the determined attribute data.

Abstract: Methods, apparatus, and processor-readable storage media for request approval using blockchain technology are provided herein.