Abstract: Systems, methods, and other embodiments associated with schema-based integration of back-end data analysis tools are described. In one embodiment, an example method includes receiving, through a graphical user interface, a selection of a component function for operation on a first dataset that spans a plurality of back-end tools. The example method translates the selected component function into a set of pre-configured commands specific to the back-end tools to expose the first dataset and exclude a second dataset of the back-end tools. The example method executes the pre-configured commands to create synonyms for the first dataset in a workspace schema associated with the graphical user interface. And, the example method executes the selected component function on the synonyms to generate a result from the first dataset.

Abstract: In one embodiment of systems and methods described herein, a computing device is configured to generate and display a user interface including one or more selectable generic options; receive a selection of a data analysis function to perform machine learning; translate the selected function into pre-configured commands for each back-end tool that are specific to each back-end tool for performing the selected function, wherein the pre-configured commands identify and access specific schema with a compatible format for reading the specific schema from each back end tool to expose retail-specific data sets in accordance with the specific schema; execute the preconfigured commands based on the specific schema and retrieve corresponding retail-specific data from a plurality of the back-end tools based on the specific schema; and execute the selected data analysis function on the retrieved retail-specific data from the plurality of back-end tools and generate a data analysis result using Artificial Intelligence-Ena

Abstract: Embodiments provide systems and methods for navigating a dialogue flow using a trained intelligence bot. Upon initiation of a chat session between a user and a trained intelligence bot, one or more utterances can be received. The utterances can be processed using the trained intelligence bot to resolve an intent from among a plurality of predefined intents, where the intelligence bot is trained to resolve predefined intents based on training data associated with the predefined intents. A predefined dialogue flow associated with the resolved intent can be navigated using the intelligence bot, where the intelligence bot guides the user through the dialogue flow using context variables that are associated with the user or the chat session. The user can be provided enterprise data retrieved by the intelligence bot using a retrieval request generated based on one or more of the navigation of the dialogue flow or the context variables.

Abstract: In one embodiment of systems and methods described herein, a computing device is configured to generate and display a user interface including one or more selectable generic options; receive a selection of a data analysis function to perform machine learning; translate the selected function into pre-configured commands for each back-end tool that are specific to each back-end tool for performing the selected function, wherein the pre-configured commands identify and access specific schema with a compatible format for reading the specific schema from each back end tool to expose retail-specific data sets in accordance with the specific schema; execute the preconfigured commands based on the specific schema and retrieve corresponding retail-specific data from a plurality of the back-end tools based on the specific schema; and execute the selected data analysis function on the retrieved retail-specific data from the plurality of back-end tools and generate a data analysis result using Artificial Intelligence-Ena

Abstract: Embodiments provide systems and methods for navigating a dialogue flow using a trained intelligence bot. Upon initiation of a chat session between a user and a trained intelligence bot, one or more utterances can be received. The utterances can be processed using the trained intelligence bot to resolve an intent from among a plurality of predefined intents, where the intelligence bot is trained to resolve predefined intents based on training data associated with the predefined intents. A predefined dialogue flow associated with the resolved intent can be navigated using the intelligence bot, where the intelligence bot guides the user through the dialogue flow using context variables that are associated with the user or the chat session. The user can be provided enterprise data retrieved by the intelligence bot using a retrieval request generated based on one or more of the navigation of the dialogue flow or the context variables.