Abstract: A device may receive data stored in one or more data sources associated with an organization based on utilizing one or more data discovery-related application programming interfaces (APIs) to access the data. The device may process, utilizing one or more data feature models via the one or more data discovery-related APIs, the data received from the one or more data sources to identify types of data included in the data based on a contextualization of the data. The one or more data feature models may identify a respective set of attributes expected to be included in the types of data. The device may perform multiple analyses of the data after identifying the types of data. The device may determine, based on a result of the multiple analyses, a score for the data. The device may perform one or more actions based on a respective result of the multiple analyses.

Abstract: An on-demand learning system provides an enhanced leaning environment capable of delivering relevant content on virtually any topic to specific learners. The learning system implements technical features that facilitate curation and subject matter validation of many different types of content. The technical architecture of the learning system also supports intelligent matching of learners to subject matter areas, creation of specific subject matter boards, and resilient maintenance of the boards.

Abstract: A device may evaluate first data to identify a plurality of users, where each user, of the plurality of users, is assigned to complete a portion of a group task. The device may evaluate the first data to select a first user, of the plurality of users, for completion of a particular portion of the group task based on a first set of decision criteria. The device may provide, to the first user, information identifying the particular portion of the group task. The device may receive second data relating to the particular portion of the group task after providing information identifying the particular portion of the group task. The device may evaluate the first data to select a second user, of the plurality of users, based on a second set of decision criteria. The device may provide, to the second user, information associated with the second data.

Abstract: A device may receive data stored in one or more data sources associated with an organization based on utilizing one or more data discovery-related application programming interfaces (APIs) to access the data. The device may process, utilizing one or more data feature models via the one or more data discovery-related APIs, the data received from the one or more data sources to identify types of data included in the data based on a contextualization of the data. The one or more data feature models may identify a respective set of attributes expected to be included in the types of data. The device may perform multiple analyses of the data after identifying the types of data. The device may determine, based on a result of the multiple analyses, a score for the data. The device may perform one or more actions based on a respective result of the multiple analyses.

Abstract: A data intelligence platform may include a role-based workbench component configured to control access to or use of the data intelligence platform to identify an issue associated with data associated with an organization. The data intelligence platform may include a data intelligence component configured to: process the data to identify the issue related to the data, or perform a set of actions related to fixing the issue related to the data based on a result of processing the data. The data intelligence platform may include a data management component configured to facilitate access to a corpus component or to a source of the data. The data intelligence platform may include the corpus component configured to facilitate processing of the data to identify the issue or to perform the set of actions.

Abstract: An on-demand learning system provides an enhanced leaning environment capable of delivering relevant content on virtually any topic to specific learners. The learning system implements technical features that facilitate curation and subject matter validation of many different types of content. The technical architecture of the learning system also supports intelligent matching of learners to subject matter areas, creation of specific subject matter boards, and resilient maintenance of the boards.

Abstract: An on-demand learning system provides an enhanced leaning environment capable of delivering relevant content on virtually any topic to specific learners. The learning system implements technical features that facilitate curation and subject matter validation of many different types of content. The technical architecture of the learning system also supports intelligent matching of learners to subject matter areas, creation of specific subject matter boards, and resilient maintenance of the boards.

Abstract: A comprehensive multi-skilling framework system provides technology tailored for managing and staffing multi-skilled IT professionals. Multi-skill data and proficiencies generated for each individual user are defined, enabled, measured and tracked in the multi-skilling framework. An automated multi-skilling manager receives data that defines technical platforms and a plurality of multi-skill roles within each technical platform. Multiple skills are associated with each multi-skill role and each user is mapped to a multi-skill role. An overall proficiency level that pertains to a user's respective multi-skill role is determined based on multi-skill assessment data for the user. By assigning a multi-skill role to each user and automatically generating a unique proficiency level for each user based on their multi-skill role information, the process of staffing IT projects from large populations of IT professionals is streamlined and conserves processing resources.

Abstract: A device may evaluate first data to identify a plurality of users, where each user, of the plurality of users, is assigned to complete a portion of a group task. The device may evaluate the first data to select a first user, of the plurality of users, for completion of a particular portion of the group task based on a first set of decision criteria. The device may provide, to the first user, information identifying the particular portion of the group task. The device may receive second data relating to the particular portion of the group task after providing information identifying the particular portion of the group task. The device may evaluate the first data to select a second user, of the plurality of users, based on a second set of decision criteria. The device may provide, to the second user, information associated with the second data.

Abstract: An on-demand learning system provides an enhanced leaning environment capable of delivering relevant content on virtually any topic to specific learners. The learning system implements technical features that facilitate curation and subject matter validation of many different types of content. The technical architecture of the learning system also supports intelligent matching of learners to subject matter areas, creation of specific subject matter boards, and resilient maintenance of the boards.