Abstract: A control system controls tenant services to various tenants by obtaining tenant attributes for each tenant, with respect to a particular workload. A model is generated that models tenant usage performance for a set of best performing tenants. The model is then applied to a remainder of the tenants to obtain a metric indicative of a likely tenant capacity for incremental usage of the workload. The control system controls the services provided to the tenant based upon the likelihood of adoption metric.

Abstract: Methods, systems, and computer programs are presented for providing self-help. One method includes operations for detecting a request for self-help for a user, and obtaining, using a first ML model for rule mining, a first score for a set of cases from a database of historical cases of self-help for aiding users. The method further includes an operation for obtaining, using a second ML model for similarity based on user information, a second score for each case based on a similarity between and an environment of the user requesting self-help and an environment of each case. Further, the method includes obtaining a combined score for each case based on the first score and the second score, and ranking the set of cases based on the combined score. The information for at least one of the cases is presented on a user interface (UI) based on the ranking.

Abstract: In a data asset curating system including a processor, computer-readable medium and data storage storing source data assets, each source data asset including content data and source metadata, the data storage stores instructions causing the system to perform converting, based on a conversion rule defining a set of standard attributes, the source data assets to curatable data assets, each curatable data asset including the content data of the corresponding source data asset and curatable metadata, the curatable metadata including one or more standard attributes; causing a user device to render a GUI configured to provide filtering options for querying the curatable data assets; receiving, from the user device, a curation query including a set of the filtering options selected via the GUI; and identifying, from the curatable data assets, a set of the curatable data assets satisfying the received curation query.

Abstract: In a data asset curating system including a processor, computer-readable medium and data storage storing source data assets, each source data asset including content data and source metadata, the data storage stores instructions causing the system to perform converting, based on a conversion rule defining a set of standard attributes, the source data assets to curatable data assets, each curatable data asset including the content data of the corresponding source data asset and curatable metadata, the curatable metadata including one or more standard attributes; causing a user device to render a GUI configured to provide filtering options for querying the curatable data assets; receiving, from the user device, a curation query including a set of the filtering options selected via the GUI; and identifying, from the curatable data assets, a set of the curatable data assets satisfying the received curation query.

Abstract: A plurality of different hosted services each includes enabling logic that enables a set of actions. Usage data for a plurality of different tenants are accessed and actions are grouped into features based upon underlying enabling logic. A correlation score between features is identified based on tenant usage data for those features. A tenant under analysis is selected and usage data for the tenant under analysis is used to identify related features that the tenant under analysis is not using, based upon the correlation scores for the features. An output system is controlled to surface the related features for the tenant under analysis.

Abstract: A control system controls tenant services to various tenants by obtaining tenant attributes for each tenant, with respect to a particular workload. A model is generated that models tenant usage performance for a set of best performing tenants. The model is then applied to a remainder of the tenants to obtain a metric indicative of a likely tenant capacity for incremental usage of the workload. The control system controls the services provided to the tenant based upon the likelihood of adoption metric.

Abstract: Collaborative actions among users are detected and an indication of a graph, illustrating those collaborative actions, is generated. Nodes in the graph identify users and connections among nodes are indicative of collaborative actions between users. A connection metric, based upon a number of connections between nodes, is generated for each node, and an inheritance value is also generated for each given node, based upon a connection metric corresponding to other nodes connected to the given node. A centrality metric is generated for each node, and a control signal is generated, to control a user interaction system, based upon the centrality metric.

Abstract: A control system controls tenant services to various tenants by obtaining tenant attributes for each tenant, with respect to a particular workload. A model is generated that models tenant usage performance for a set of best performing tenants. The model is then applied to a remainder of the tenants to obtain a metric indicative of a likely tenant capacity for incremental usage of the workload. The control system controls the services provided to the tenant based upon the likelihood of adoption metric.

Abstract: Collaborative actions among users are detected and an indication of a graph, illustrating those collaborative actions, is generated. Nodes in the graph identify users and connections among nodes are indicative of collaborative actions between users. A connection metric, based upon a number of connections between nodes, is generated for each node, and an inheritance value is also generated for each given node, based upon a connection metric corresponding to other nodes connected to the given node. A centrality metric is generated for each node, and a control signal is generated, to control a user interaction system, based upon the centrality metric.

Abstract: A plurality of different hosted services each include enabling logic that enables a set of actions. Usage data for a plurality of different tenants is accessed and actions are grouped into features based upon underlying enabling logic. A correlation score between features is identified based on tenant usage data for those features. A tenant under analysis is selected and usage data for the tenant under analysis is used to identify related features that the tenant under analysis is not using, based upon the correlation scores for the features. An output system is controlled to surface the related features for the tenant under analysis.

Abstract: A control system controls tenant services to various tenants by obtaining tenant attributes for each tenant, with respect to a particular workload. A model is generated that models tenant usage performance for a set of best performing tenants. The model is then applied to a remainder of the tenants to obtain a metric indicative of a likely tenant capacity for incremental usage of the workload. The control system controls the services provided to the tenant based upon the likelihood of adoption metric.