Abstract: A method includes monitoring, by a digital assistance system, a voice-enabled communication session established as an exchange between two or more users through two or more user systems using one of a plurality of communication channels. The method also includes collecting input, by the digital assistance system, for a command sequence while the voice-enabled communication session is active. The method further includes generating, by the digital assistance system, the command sequence for a project management subsystem and a scheduling subsystem based on one or more requested tasks detected through the voice-enabled communication session.

Abstract: A system includes a development system and a digital assistance system. The development system includes a network interface configured to communicate with a plurality of communication channels, a processing system configured to interface with a project management subsystem, a scheduling subsystem, and the network interface, and an application programming interface configured to receive a command sequence for the project management subsystem and the scheduling subsystem. The digital assistance system includes a natural language processing engine configured to interface with a voice-enabled communication session through one of the communication channels. The digital assistance system also includes a command generator configured to generate the command sequence based on one or more requested tasks detected through the voice-enabled communication session and provide the command sequence to the application programming interface to execute the one or more requested tasks.

Abstract: A method includes analyzing an enterprise data warehouse to determine name attribute scores based on occurrences of enterprise terms and abbreviations in the enterprise data warehouse. The method also includes generating a scoring summary of phrases, applying fuzzy reasoning logic to identify one or more relationship patterns and weights for the phrases including at least one shared word to produce training data for a data model associated with the enterprise data warehouse, and updating the data model with a new abbreviated field name associated with a new field name based on identifying a closest match of the new field name with the training data.

Abstract: A system includes a development system and a digital assistance system. The development system includes a network interface configured to communicate with a plurality of communication channels, a processing system configured to interface with a project management subsystem, a scheduling subsystem, and the network interface, and an application programming interface configured to receive a command sequence for the project management subsystem and the scheduling subsystem. The digital assistance system includes a natural language processing engine configured to interface with a voice-enabled communication session through one of the communication channels. The digital assistance system also includes a command generator configured to generate the command sequence based on one or more requested tasks detected through the voice-enabled communication session and provide the command sequence to the application programming interface to execute the one or more requested tasks.

Abstract: A system includes a network interface configured to access an enterprise data warehouse and an enterprise abbreviation list that maps enterprise terms to abbreviations. A processing device can communicate with the network interface and a memory device that stores instructions to analyze the enterprise data warehouse to determine name attribute scores based on occurrences of the enterprise terms and the abbreviations in the enterprise data warehouse. Execution of the instructions can also generate a scoring summary of phrases, apply fuzzy reasoning logic to identify one or more relationship patterns and weights for the phrases including at least one shared word to produce training data for a data model associated with the enterprise data warehouse, and update the data model with a new abbreviated field name associated with a new field name based on identifying a closest match of the new field name with the training data.