Various examples are directed to systems and methods for administering data model metadata for a plurality of data models. A metadata service may receive a first retrieval request from a requesting system. The first retrieval request may comprise an indication of a first local object identifier referencing a definition of a first local object from a first data model and an indication of a target data model. The metadata service may retrieve a first record from a metadata identifier registry, where the first record comprises an indication of the first local object identifier and an indication of a first global object identifier corresponding to the first local object identifier. The metadata service may determine a second local object identifier referencing a definition of a second local object identifier referencing a definition of a second local object in the target data model and return the second local object identifier.

Provided are systems and methods for automatic search query refinement. An example method commences with identifying a plurality of electronic sources of data content of an entity stored at different network-accessible locations. The content may be dynamically assigned fields based on criteria specified by the entity. Thereupon, a unified search interface may be provided to authorized users to search the content. A search query subsequently received from a user may be parsed. The method continues with determining, upon the parsing and based on predetermined rules, triggers associated with the search query. In some embodiments, the triggers include search triggers to be used for searching content, filter triggers to be applied for filtering search results, and structural triggers to be used for ranking the search results. The method further includes searching the content based on the triggers to retrieve the search results and providing the search results to the user.

The present disclosure relates to systems and methods for matching electronic activities with record objects based on entity relationships. The method can include accessing a plurality of electronic activities, identifying an electronic activity, identifying a first participant associated with a first entity and a second participant associated with a second entity, determining whether a record object identifier is included in the electronic activity, identifying a first record object of the system of record that includes an instance of the record object identifier, and storing an association between the electronic activity and the first record object. The method can include determining a second record object corresponding to the second entity, identifying, using a matching policy, a third record object linked to the second record object and identifying a third entity, and storing, by the one or more processors, an association between the electronic activity and the third record object.

The present disclosure relates to systems and methods for matching electronic activities with record objects based on entity relationships. The method can include accessing a plurality of electronic activities, identifying an electronic activity, identifying a first participant associated with a first entity and a second participant associated with a second entity, determining whether a record object identifier is included in the electronic activity, identifying a first record object of the system of record that includes an instance of the record object identifier, and storing an association between the electronic activity and the first record object. The method can include determining a second record object corresponding to the second entity, identifying, using a matching policy, a third record object linked to the second record object and identifying a third entity, and storing, by the one or more processors, an association between the electronic activity and the third record object.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for indicating location status. A computing device can receive a query from a user device, a current time, and a location for the user device. The computing device identifies results responsive to the query, including one or more business results that are each associated with a business location and operating hours. The computing device can select a subset of the business results as open results based on the operating hours of the business results, the current time, and travel times from the device location to the respective business locations. Data can be provided for a search engine results page that designates the subset of the business results as open results.

Persistent storage contains a parent table and one or more child tables, the parent table containing: a class field specifying types, and one or more filter fields. One or more processors may: receive a first request to read first information of a first type for a first entity; determine that, in a first entry of the parent table for the first entity, the first type is specified in the class field; obtain the first information from a child table associated with the first type; receive a second request to read second information of a second type for a second entity; determine that, in a second entry of the parent table for the second entity, the second type is indicated as present by a filter field that is associated with the second type; and obtain the second information from a set of additional fields in the second entry.

One disclosed method involves determining, by at least one computing system and based at least in part on input provided to a meeting application, at least a first topic of interest for a first user accessing the meeting application via a first client device, in response to determining the first topic of interest, querying, by the at least one computing system, at least one data source, external to the meeting application, for information corresponding to the first topic of interest, and causing, by the at least one computing system, the first client device to display a representation of the information.

Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive data analysis with respect to structured data objects. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive data analysis with respect to structured data objects by utilizing at least one of cross-table data similarity score generation machine learning models and unsupervised anomalous table row detection machine learning models.

The present invention provides a robust and effective solution to an entity or an organization by allowing to visualize the flow of automotive data signals from a source system to a sink system with different metric signals at each step and creating a mechanism for creating automotive signal quality marker (ASQM) for high quality automotive data signals by determining high value data parameters, inter-parameter correlation, data quality variation with trip duration, and frequency of data collection/distribution across datasets. The quality criterion thus developed is applied to data generated from a plurality of data sources. The ASQM may be calculated by converting the developed automotive data signals quality criterion into a numeric value on a specified scale. It can be used by all stakeholders in the value chain for consistent measurement of automotive data signals quality.

The present invention provides a robust and effective solution to an entity or an organization by allowing to visualize the flow of automotive data signals from a source system to a sink system with different metric signals at each step and creating a mechanism for creating automotive signal quality marker (ASQM) for high quality automotive data signals by determining high value data parameters, inter-parameter correlation, data quality variation with trip duration, and frequency of data collection/distribution across datasets. The quality criterion thus developed is applied to data generated from a plurality of data sources. The ASQM may be calculated by converting the developed automotive data signals quality criterion into a numeric value on a specified scale. It can be used by all stakeholders in the value chain for consistent measurement of automotive data signals quality.