Abstract: In an example embodiment, a mechanism is provided to dynamically determine optimizations of data model execution at runtime at an engine-by-engine level, meaning that one optimization may be applied to one engine and not others. This mechanism is enabled by also providing a method by which model optimizations are stored and retrieved using a hash representation of each model, allowing past optimizations to be reused. Thus, the next time a similar model is built, optimizations of an earlier model can be reused. A definition store is also used as a basis to create new optimizations dynamically.

Abstract: A user interface may include one or more visualizations based on queries to a database using query model metadata. Updated metadata of columns of the database may be obtained which may be different from the query model metadata. A set of used columns and a set of unused columns may be determined based on the query model. One or more metadata mismatches may be determined based on a comparison of the query model metadata for the set of used columns and the updated metadata for the set of used columns. The one or more metadata mismatches may be presented in a user interface configured to enable a user to rectify each. One or more selections from the user may be obtained to rectify at least one of the one or more metadata mismatches. The corresponding columns may be deleted or replaced based on the one or more selections.

Abstract: Embodiments provide systems and methods that update analytical models which are changing over time. Upon receipt of a model creation request, a synchronization is performed to receive updated metadata reflecting a current state of a model. Where such updating indicates a change in status (e.g., privacy) of the model metadata, the user is prompted with a sensitive metadata field, and an empty context metadata field. The user must fill in the context metadata field (e.g., with an appropriate ID) thereby providing authorization to access data of the model. Then, a model view including sensitive information can be passed to the user. Absent successfully inputting the context metadata field, error message(s) are returned to the user, and the model view will not be passed. Embodiments may find particular use in efficiently updating analytical models to ensure their continuing compliance with evolving privacy regulation (e.g., ongoing revision and/or interpretation of GDPR language).

Abstract: Systems, methods, and techniques for implementing a defined configuration for an application. A request is received to provision an instance of an application for a external entity. A resource identifier is obtained based on the request. A defined configuration of a plurality of defined configurations for the application is identified based on the resource identifier. A set of features is determined that are specified in the defined configuration. The instance of the application is generated having the set of features. A connection is established with an application resource of a plurality of application resources of the application based on the resource identifier. The instance having the set of features is provisioned over one or more networks to the external entity.

Abstract: Embodiments implement efficient localized handling of metadata in connection with the retrieval of data from a remote source. A request including content, is received by a localization engine. In response to the request and based upon the content, only a portion of metadata relevant to the request is initially retrieved from the remote source. Remaining metadata relevant to the query, is only retrieved later according to execution of background jobs. One example relates to language translation in connection with querying of a remote source. Based upon a locale of the user posing the query, only metadata relevant to that particular locale (e.g., Germany) is returned immediately. Metadata relevant to languages of users residing in locales other than the current user (e.g., USA; France), is only returned later according to background jobs. Thus contact with a remote source does not serve as a bottleneck to efficient performance of local activities.

Abstract: Embodiments provide systems and methods that update analytical models which are changing over time. Upon receipt of a model creation request, a synchronization is performed to receive updated metadata reflecting a current state of a model. Where such updating indicates a change in status (e.g., privacy) of the model metadata, the user is prompted with a sensitive metadata field, and an empty context metadata field. The user must fill in the context metadata field (e.g., with an appropriate ID) thereby providing authorization to access data of the model. Then, a model view including sensitive information can be passed to the user. Absent successfully inputting the context metadata field, error message(s) are returned to the user, and the model view will not be passed. Embodiments may find particular use in efficiently updating analytical models to ensure their continuing compliance with evolving privacy regulation (e.g., ongoing revision and/or interpretation of GDPR language).

Abstract: A user interface may include one or more visualizations based on queries to a database using query model metadata. Updated metadata of columns of the database may be obtained which may be different from the query model metadata. A set of used columns and a set of unused columns may be determined based on the query model. One or more metadata mismatches may be determined based on a comparison of the query model metadata for the set of used columns and the updated metadata for the set of used columns. The one or more metadata mismatches may be presented in a user interface configured to enable a user to rectify each. One or more selections from the user may be obtained to rectify at least one of the one or more metadata mismatches. The corresponding columns may be deleted or replaced based on the one or more selections.

Abstract: Embodiments allow a tenant to customize a configuration that is used in accessing an application over the cloud. At a provisioning time, a user accesses a tenant Application Program Interface (API) and creates a customized configuration including a payload that defines particular features to be available from the application. Such features can include but are not limited to available buttons, toolbar options, and pages. During a runtime subsequent to the provisioning, an input to the application (such as a URL) is received from the tenant. Logic is executed to determine whether to apply the custom configuration or another configuration (e.g., default or other predefined) from a list. Based upon the configuration, the application renders output to the user according to the particular features. Particular embodiments may recognize a Line of Business (LoB) parameter of a URL input to the application in order to provide a configurations customized by the tenant.

Abstract: Systems, methods, and computer media for visualizing data are provided herein. The described examples allow one-dimensional data visualizations generated using visualization tools and backend components to be displayed in response to a request to view data that includes one or more sets of Cartesian columns. A data visualization request can specify data for inclusion in a data visualization and properties for the visualization, including transpose factors for data sources. The data sources having transpose factors can be cloned to represent respective combinations of the data source with each transpose factor, and then joined to other cloned or non-cloned data sources to generate the resulting one-dimensional visualization.

Abstract: Embodiments allow a tenant to customize a configuration that is used in accessing an application over the cloud. At a provisioning time, a user accesses a tenant Application Program Interface (API) and creates a customized configuration including a payload that defines particular features to be available from the application. Such features can include but are not limited to available buttons, toolbar options, and pages. During a runtime subsequent to the provisioning, an input to the application (such as a URL) is received from the tenant. Logic is executed to determine whether to apply the custom configuration or another configuration (e.g., default or other predefined) from a list. Based upon the configuration, the application renders output to the user according to the particular features. Particular embodiments may recognize a Line of Business (LoB) parameter of a URL input to the application in order to provide a configurations customized by the tenant.

Abstract: Systems, methods, and techniques for supporting feature customization based on data source capability. A first request is received from an external entity to provision an instance of an application. An application service of a plurality of application services is identified to be implemented to fulfill the first request. A configuration of the application corresponding to the application service is determined. Customization information regarding states of a set of features of the application instance is obtained as a result of determining that a customization is associated with the external entity. A modified configuration is generated for the application based on the customization information and the configuration. An application instance is provisioned to the external entity over the one or more networks having the modified configuration.

Abstract: Systems, methods, and techniques for implementing a defined configuration for an application. A request is received to provision an instance of an application for a external entity. A resource identifier is obtained based on the request. A defined configuration of a plurality of defined configurations for the application is identified based on the resource identifier. A set of features is determined that are specified in the defined configuration. The instance of the application is generated having the set of features. A connection is established with an application resource of a plurality of application resources of the application based on the resource identifier. The instance having the set of features is provisioned over one or more networks to the external entity.

Abstract: Systems, methods, and techniques for supporting feature customization based on data source capability. A first request is received from an external entity to provision an instance of an application. An application service of a plurality of application services is identified to be implemented to fulfill the first request. A configuration of the application corresponding to the application service is determined. Customization information regarding states of a set of features of the application instance is obtained as a result of determining that a customization is associated with the external entity. A modified configuration is generated for the application based on the customization information and the configuration. An application instance is provisioned to the external entity over the one or more networks having the modified configuration.

Abstract: Systems, methods, and computer media for visualizing data are provided herein. The described examples allow one-dimensional data visualizations generated using visualization tools and backend components to be displayed in response to a request to view data that includes one or more sets of Cartesian columns. A data visualization request can specify data for inclusion in a data visualization and properties for the visualization, including transpose factors for data sources. The data sources having transpose factors can be cloned to represent respective combinations of the data source with each transpose factor, and then joined to other cloned or non-cloned data sources to generate the resulting one-dimensional visualization.

Abstract: Methods, systems, and computer-readable storage media for receiving, by a semantic context service, a semantic context associated with a report generated by a first analytical tool, storing, by the semantic context service, the semantic context, receiving, by the semantic context service, a semantic context request from a second analytical tool, the semantic context request including a set of parameters, determining, by the semantic context service, a response to the semantic context request based on the set of parameters, the response including the semantic context, and returning, by the semantic context service, the response to the second analytical tool, the second analytical tool applying the semantic context to a report generated by the second analytical tool.

Abstract: Methods, systems, and computer-readable storage media for receiving, by a semantic context service, a semantic context associated with a report generated by a first analytical tool, storing, by the semantic context service, the semantic context, receiving, by the semantic context service, a semantic context request from a second analytical tool, the semantic context request including a set of parameters, determining, by the semantic context service, a response to the semantic context request based on the set of parameters, the response including the semantic context, and returning, by the semantic context service, the response to the second analytical tool, the second analytical tool applying the semantic context to a report generated by the second analytical tool.

Abstract: Methods and system are disclosed that optimize memory consumed, by sharing datasets between workspaces. In one aspect, multiple workspaces may be instantiated by retrieving multiple datasets from multiple data sources. An input to execute transformations on the multiple datasets may be received. Based on a determination of execution of a transformation on the multiple datasets, a dataset context analyzer may be executed to analyze a current context of data in the multiple datasets. Based on a result of execution of the dataset context analyzer, a transformation graph analyzer may be executed to compute a current context of transformations on the multiple datasets. Based on the determined current context of data and the current context of the transformations on the dataset, memory consumed may be optimized by sharing the multiple datasets between the multiple workspaces.

Abstract: Systems and methods for cross-report collaboration include receiving an identifier for a class of data underlying a first report. A collaboration associated with at least a portion of a second report is identified based on the class of data underlying the first report. Data regarding the identified collaboration is provided in conjunction with the first report to signify that at least a portion of the data underlying it is subject to the collaboration.

Abstract: Methods and system are disclosed that optimize memory consumed, by sharing datasets between workspaces. In one aspect, multiple workspaces may be instantiated by retrieving multiple datasets from multiple data sources. An input to execute transformations on the multiple datasets may be received. Based on a determination of execution of a transformation on the multiple datasets, a dataset context analyzer may be executed to analyze a current context of data in the multiple datasets. Based on a result of execution of the dataset context analyzer, a transformation graph analyzer may be executed to compute a current context of transformations on the multiple datasets. Based on the determined current context of data and the current context of the transformations on the dataset, memory consumed may be optimized by sharing the multiple datasets between the multiple workspaces.

Abstract: The present disclosure involves systems, software, and computer implemented methods for rendering interactive analytical graphic representations using a game engine. A set of processed data is received from an analytical system. The set of processed data is stored in a first format. The set of processed data comprises raw analytical data that are processed by an analytical application. The set of processed data is adapted into a set of game data. The set of game data is stored in a second format. An interactive analytical graphic representation is rendered based on the set of game data. The set of game data is stored for replay analytics.