Abstract: A catalogue system automatically detects changes to configuration file at a service application. Based on the changes to the configuration file(s), the catalogue system stores mapping data that identifies a resource item type that can be processed by the service application and one or more user actions that are available for processing resource items of the resource item type. The techniques thus provide for dynamic interaction with service applications.

Abstract: Techniques related to a domain-specific language for transformations are disclosed. A server computer may process a table definition composed in a domain-specific language. The table definition may include a sequence of one or more transformations to be performed on one or more source tables to generate a target table. The sequence may include a customized transformation. A source dataset may be provided as input to an implementation of the customized transformation. An output dataset may be generated as a result of executing the implementation. An intermediate table may be generated based on performing at least one transformation on a particular source table. A supplemental portion for the intermediate table may be generated based on performing the at least one transformation on an appended portion of the particular source table. The target table may be generated based on combining the supplemental portion with the intermediate table.

Abstract: A catalogue system automatically detects changes to configuration file at a service application. Based on the changes to the configuration file(s), the catalogue system stores mapping data that identifies a resource item type that can be processed by the service application and one or more user actions that are available for processing resource items of the resource item type. The techniques thus provide for dynamic interaction with service applications.

Abstract: A time-sensitive cube data system is disclosed in which time-sensitive and/or time-series data objects are output in response to a user's operations on a time-sensitive OLAP cube. The time-sensitive and/or time-series data objects output by the time-sensitive cube data system may be displayed to the user in any way that may be advantageous to the user's understanding. The time-series objects output by the time-sensitive cube data system are more helpful than a single snapshot, as a user is able to see data trends over time.

Abstract: Techniques related to a domain-specific language for transformations are disclosed. A server computer may process a table definition composed in a domain-specific language. The table definition may include a sequence of one or more transformations to be performed on one or more source tables to generate a target table. The sequence may include a customized transformation. A source dataset may be provided as input to an implementation of the customized transformation. An output dataset may be generated as a result of executing the implementation. An intermediate table may be generated based on performing at least one transformation on a particular source table. A supplemental portion for the intermediate table may be generated based on performing the at least one transformation on an appended portion of the particular source table. The target table may be generated based on combining the supplemental portion with the intermediate table.

Abstract: A catalog system automatically detects changes to configuration file at a service application. Based on the changes to the configuration file(s), the catalog system stores mapping data that identifies a resource item type that can be processed by the service application and one or more user actions that are available for processing resource items of the resource item type. The techniques thus provide for dynamic interaction with service applications.

Abstract: Techniques related to a domain-specific language for dataset transformations are disclosed. A server computer may process a table definition composed in a domain-specific language. The table definition may include a sequence of one or more dataset transformations to be performed on one or more source tables to generate a target table. The sequence may include a customized transformation. A source dataset may be provided as input to an implementation of the customized transformation. An output dataset may be generated as a result of executing the implementation. An intermediate table may be generated based on performing at least one dataset transformation on a particular source table. A supplemental portion for the intermediate table may be generated based on performing the at least one dataset transformation on an appended portion of the particular source table. The target table may be generated based on combining the supplemental portion with the intermediate table.

Abstract: A time-sensitive cube data system is disclosed in which time-sensitive and/or time-series data objects are output in response to a user's operations on a time-sensitive OLAP cube. The time-sensitive and/or time-series data objects output by the time-sensitive cube data system may be displayed to the user in any way that may be advantageous to the user's understanding. The time-series objects output by the time-sensitive cube data system are more helpful than a single snapshot, as a user is able to see data trends over time.

Abstract: A time-sensitive cube data system is disclosed in which time-sensitive and/or time-series data objects are output in response to a user's operations on a time-sensitive OLAP cube. The time-sensitive and/or time-series data objects output by the time-sensitive cube data system may be displayed to the user in any way that may be advantageous to the user's understanding. The time-series objects output by the time-sensitive cube data system are more helpful than a single snapshot, as a user is able to see data trends over time.

Abstract: Techniques related to a domain-specific language for dataset transformations are disclosed. A server computer may process a table definition composed in a domain-specific language. The table definition may include a sequence of one or more dataset transformations to be performed on one or more source tables to generate a target table. The sequence may include a customized transformation. A source dataset may be provided as input to an implementation of the customized transformation. An output dataset may be generated as a result of executing the implementation. An intermediate table may be generated based on performing at least one dataset transformation on a particular source table. A supplemental portion for the intermediate table may be generated based on performing the at least one dataset transformation on an appended portion of the particular source table. The target table may be generated based on combining the supplemental portion with the intermediate table.

Abstract: Techniques related to a domain-specific language for dataset transformations are disclosed. A server computer may process a table definition composed in a domain-specific language. The table definition may include a sequence of one or more dataset transformations to be performed on one or more source tables to generate a target table. The sequence may include a customized transformation. A source dataset may be provided as input to an implementation of the customized transformation. An output dataset may be generated as a result of executing the implementation. An intermediate table may be generated based on performing at least one dataset transformation on a particular source table. A supplemental portion for the intermediate table may be generated based on performing the at least one dataset transformation on an appended portion of the particular source table. The target table may be generated based on combining the supplemental portion with the intermediate table.

Abstract: Techniques related to a domain-specific language for dataset transformations are disclosed. A server computer may process a table definition composed in a domain-specific language. The table definition may include a sequence of one or more dataset transformations to be performed on one or more source tables to generate a target table. The sequence may include a customized transformation. A source dataset may be provided as input to an implementation of the customized transformation. An output dataset may be generated as a result of executing the implementation. An intermediate table may be generated based on performing at least one dataset transformation on a particular source table. A supplemental portion for the intermediate table may be generated based on performing the at least one dataset transformation on an appended portion of the particular source table. The target table may be generated based on combining the supplemental portion with the intermediate table.

Abstract: A time-sensitive cube data system is disclosed in which time-sensitive and/or time-series data objects are output in response to a user's operations on a time-sensitive OLAP cube. The time-sensitive and/or time-series data objects output by the time-sensitive cube data system may be displayed to the user in any way that may be advantageous to the user's understanding. The time-series objects output by the time-sensitive cube data system are more helpful than a single snapshot, as a user is able to see data trends over time.

Abstract: A time-sensitive cube data system is disclosed in which time-sensitive and/or time-series data objects are output in response to a user's operations on a time-sensitive OLAP cube. The time-sensitive and/or time-series data objects output by the time-sensitive cube data system may be displayed to the user in any way that may be advantageous to the user's understanding. The time-series objects output by the time-sensitive cube data system are more helpful than a single snapshot, as a user is able to see data trends over time.

Abstract: A time-sensitive cube data system is disclosed in which time-sensitive and/or time-series data objects are output in response to a user's operations on a time-sensitive OLAP cube. The time-sensitive and/or time-series data objects output by the time-sensitive cube data system may be displayed to the user in any way that may be advantageous to the user's understanding. The time-series objects output by the time-sensitive cube data system are more helpful than a single snapshot, as a user is able to see data trends over time.