Abstract: A system and method for configuring an application is described. The system identifies user collaboration data of users of an application. The user collaboration data indicates durations of collaborations between one or more users using the application. The system computes an influencer score of a first user based on the duration of collaborations between the first user and the other users. The system determines that the influencer score of the first user exceeds an influencer score threshold and generates a configuration setting of the application for the first user. The system applies the configuration setting to the application for the first user.

Abstract: A system and method for identifying a user is described. The system identifies collaboration metrics based on user interaction data of users of an application from an enterprise. The system accesses enterprise organizational data of the enterprise and identifies topic data from the user interaction data and the enterprise organizational data. The system trains a machine learning model based on the collaboration metrics, the enterprise organizational data, and the topic data.

Abstract: A system and method for identifying a user is described. The system identifies collaboration metrics based on user interaction data of users of an application from an enterprise. The system accesses enterprise organizational data of the enterprise and identifies topic data from the user interaction data and the enterprise organizational data. The system trains a machine learning model based on the collaboration metrics, the enterprise organizational data, and the topic data.

Abstract: A computing device, including a processor configured to receive a plurality of database entries. The plurality of database entries may include a first portion organized according to a predefined database schema and a second portion not organized according to the predefined database schema. The processor may be further configured to generate an estimated database schema for the second portion and organize the second portion according to the estimated database schema. The processor may be further configured to determine at least one database entry included in the first portion that does not have the estimated data type indicated in the estimated database schema. The processor may be further configured to modify the estimated database schema such that the modified data type matches the estimated data type of the at least one database entry. The processor may be further configured to generate a database analytics model based on the modified database schema.

Abstract: A system and method for configuring an application is described. The system identifies user collaboration data of users of an application. The user collaboration data indicates durations of collaborations between one or more users using the application. The system computes an influencer score of a first user based on the duration of collaborations between the first user and the other users. The system determines that the influencer score of the first user exceeds an influencer score threshold and generates a configuration setting of the application for the first user. The system applies the configuration setting to the application for the first user.

Abstract: A system and method for identifying a user is described. The system identifies collaboration metrics based on user interaction data of users of an application from an enterprise. The system accesses enterprise organizational data of the enterprise and identifies topic data from the user interaction data and the enterprise organizational data. The system trains a machine learning model based on the collaboration metrics, the enterprise organizational data, and the topic data.

Abstract: A computing device, including a processor configured to receive a plurality of database entries. The plurality of database entries may include a first portion organized according to a predefined database schema and a second portion not organized according to the predefined database schema. The processor may be further configured to generate an estimated database schema for the second portion and organize the second portion according to the estimated database schema. The processor may be further configured to determine at least one database entry included in the first portion that does not have the estimated data type indicated in the estimated database schema. The processor may be further configured to modify the estimated database schema such that the modified data type matches the estimated data type of the at least one database entry. The processor may be further configured to generate a database analytics model based on the modified database schema.

Abstract: A method may include presenting a graphical user interface (GUI) configured to define a network for analysis, the GUI including: a first portion configured to define a network boundary of an organizational network graph (ONG) in a dataset; a second portion configured to define a beginning time and ending time for the network analysis; and a third portion configured to define a set of one or more graph metrics for vertices in the ONG; retrieving a portion of the dataset based on the network boundary, beginning time, and ending time; transmitting instructions to a distributed computing platform to generate the set of graph metrics on the portion of the dataset; and storing the generated set of graph metrics as associated with the network analysis.

Abstract: A method may include presenting a graphical user interface (GUI) configured to define a network for analysis, the GUI including: a first portion configured to define a network boundary of an organizational network graph (ONG) in a dataset; a second portion configured to define a beginning time and ending time for the network analysis; and a third portion configured to define a set of one or more graph metrics for vertices in the ONG; retrieving a portion of the dataset based on the network boundary, beginning time, and ending time; transmitting instructions to a distributed computing platform to generate the set of graph metrics on the portion of the dataset; and storing the generated set of graph metrics as associated with the network analysis.