Disclosed are systems and methods for improving interactions with and between computers in electronic messaging, and other, systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatically generating data extraction rules, which can then be used to automatically extract data from electronic messages.

Disclosed are systems and methods for improving interactions with and between computers in electronic messaging, and other, systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatically generating data extraction rules, which can then be used to automatically extract data from electronic messages.

A method includes receiving a request to modify a first value of a first field of a first item in a self-describing data system, and obtaining a domain comprising items in the self-describing data system. The first item and a second item are included in items, and the second item comprises a second field having a second value. The method includes calculating, based on a rule of the second field, a dependency of the second value on the first value. The rule specifies how the second value is to be calculated using the first value. The method includes modifying, based on the request, the first value. The method includes receiving an event triggered by the modification to the first value. The method includes, responsive to the event, calculating the second value based on the rule, and storing the second value in the second field.

Described herein are systems and methods for profiling structured or semi-structured datasets. An example computer-implemented method includes grouping, using a machine learning classifier, a plurality of tables in a dataset that are associated with an object into a cluster, where each of the tables of the cluster includes respective data and respective metadata, the respective metadata including at least one respective attribute, generating a metadata-profile for the cluster, where the metadata-profile includes the at least one respective attribute of each of the tables of the cluster; and querying the cluster using the metadata-profile.

Embodiments relate to a dynamic text provider that generates and communicates a text object to a text consumer (e.g., a table with a text header, a chart having text axis labels and/or title). An engine is positioned between a dynamic text service, and an underlying data set organized according to a model with hierarchical elements (e.g., measures, dimensions, pages). The engine receives an input from the text consumer. The input includes at least a first identifier of the text consumer, a second identifier of the data set, and a third identifier of a specific element (e.g., dimension) of the model. The engine references the model to create a context. Based upon that context, the engine queries the data set to generate a dynamic text object including a list of values (LOV) for the dimension. The dynamic text object including the LOV is communicated to the text consumer.

Embodiments relate to a dynamic text provider that generates and communicates a text object to a text consumer (e.g., a table with a text header, a chart having text axis labels and/or title). An engine is positioned between a dynamic text service, and an underlying data set organized according to a model with hierarchical elements (e.g., measures, dimensions, pages). The engine receives an input from the text consumer. The input includes at least a first identifier of the text consumer, a second identifier of the data set, and a third identifier of a specific element (e.g., dimension) of the model. The engine references the model to create a context. Based upon that context, the engine queries the data set to generate a dynamic text object including a list of values (LOV) for the dimension. The dynamic text object including the LOV is communicated to the text consumer.

A web service interface may receive a web service request that describes multiple objects. Each of the multiple objects may be associated with a common object, such as in a parent-child relationship. The web service can identify the common object and the multiple relationships between objects, and instead of creating duplicate versions of the common object, the web service can create a single record representing the common object in, for example, a database. Records for each of the multiple objects referring to the common object can reference the common object record in the database using, for example, foreign keys.

A web service interface may receive a web service request that describes multiple objects. Each of the multiple objects may be associated with a common object, such as in a parent-child relationship. The web service can identify the common object and the multiple relationships between objects, and instead of creating duplicate versions of the common object, the web service can create a single record representing the common object in, for example, a database. Records for each of the multiple objects referring to the common object can reference the common object record in the database using, for example, foreign keys.

Case management systems and techniques are disclosed. In various embodiments, searching case instances is facilitated. An indication to create a composite index across hierarchical case nodes comprising a case model is received. Case instance data associated with the case model is used to generate the composite index. The composite index is made available to be used to optimize searches of a plurality of case instances with which the case instance data is associated.

Case management systems and techniques are disclosed. In various embodiments, searching case instances is facilitated. An indication to create a composite index across hierarchical case nodes comprising a case model is received. Case instance data associated with the case model is used to generate the composite index. The composite index is made available to be used to optimize searches of a plurality of case instances with which the case instance data is associated.