The present disclosure relates to determining the shareability of values of node profiles. Record objects and electronic activities of a system of record corresponding to a data source provider may be accessed. Each record object may correspond to a record object type and have one or more object field-value pairs. Node profiles may be maintained. Values of fields corresponding to a predetermined type of field including fewer than a predetermined threshold number of data source providers may be identified. A restriction tag used to restrict populating other node profiles may be generated. Provision of the value with a second data source provider may be restricted.

In some examples, policy-based application architecture generation may include generating, based on a knowledge model schema, data residency policies, and a data classification ontology, a knowledge model, and determining, based on the knowledge model, whether an application includes regulated data. Based on an analysis of application data and user data, user location and regulated data insights may be generated to determine location specific data residency policies. Location specific regulated data in-flow and data source hosted location insights may be analyzed to determine a location compliance assessment that includes an indication of whether a location associated with the application is compliant or not compliant with the location specific data residency policies. Based on an indication of non-compliance, a strategy may be generated for compliance of application architecture for the application with the location specific data residency policies, and re-architecting of the application architecture may be implemented.

A method includes displaying events that correspond to search results of a search query, the events comprising data items of event attributes, the events displayed in a table. The table includes columns corresponding to an event attribute, rows corresponding events, cells populated data items, and interactive regions corresponding to at least one data item and selectable to add one or more commands to the search query. A reference event attribute is determined based on an analysis of a data object. A supplemental column corresponding to a supplemental event attribute is added to the table based on the reference event attribute. Supplemental interactive regions are added to the table and correspond to supplemental data items.

A method of enrichment of data for digital product definition in a heterogeneous environment includes converting an input unstructured data into structured data by a mining engine. The mining engine also performs the assignment of a priority to the converted structured data and merges it with an input structured data. A matching engine is used for categorizing the merged converted structured data based on a predefined set of rules. A profiling engine validates the merged converted structured data against the digital product definition and the steps of converting, categorizing and validating are iterated till an optimized data for digital product definition is acheived.

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.

A deduplication engine maintains a deduplication hash table containing a plurality of fingerprint entries identifying a track of current data and a hash value computed from the data currently stored at the identified track. A hash table manager implements a dynamic deduplication hash table management process, that includes a fingerprint entry purge process and a fingerprint entry re-entry process. The purge process is implemented on the deduplication hash table to remove selected fingerprint entries of tracks of data currently stored on the managed drives from the deduplication hash table based on a first set of Thin Device (TDev) selection rules and a second set of track selection purge rules. The re-entry process is implemented on the deduplication hash table to re-enter selected fingerprint entries into the deduplication hash table based on a third set of TDev selection rules and a fourth set of track selection re-entry rules.

Techniques and solutions are described for storing and retrieving metadata for database artefacts. A client request is received that includes a relevancy identifier. The relevancy identifier is useable to determine a subset of metadata that should be provided in response to the request. Metadata, including in metadata objects or database artefacts, can be reviewed to determine whether it is relevant to the request, such as if the metadata is associated with the relevancy identifier. Different requests from the same client can specify different relevancy identifiers, as, for example, a first set of metadata may be relevant to one client process and another set may be relevant to another client process. While some metadata can be specific to a particular client, at least some of the metadata can be accessed by multiple clients, and at least in some cases different clients can specify the same relevancy identifier.

Described herein are systems and methods for generating automatic insights of analytics data. Generally, when data is uploaded or otherwise linked to or made accessible to an analytics environment, a skilled user is needed in order to generate meaningful data visualizations. The systems and methods described herein provide an automatic mechanism to generate for viewing and selection a set of meaningful data visualizations, wherein said generation is based upon a determined set of metrics, scored data columns, and scored visualizations.

A system receives a request for data stored in an OVSDB database server, wherein the request comprises a JSON RPC request. In response to the request, the system initiates a proxy session by: creating a first communication session between the requesting entity and a proxy daemon, wherein the request indicates a first version corresponding to the first communication session; and creating a second communication session between the proxy daemon and the database server, wherein the second communication session is associated with a second version corresponding to a model used by the database server. The system determines that the first version does not match the second version. The system extracts, from the request, a JSON RPC method and determines that the method requires translation. The system performs, based on the first and second version, translation of a payload of the request, and sends the translated payload to the database server.

The present disclosure relates to generating a filtered data set. Data from a plurality of systems of record of a plurality of data source providers may be accessed. A master data set generated using the data accessed from the plurality of systems of record may be maintained. Restriction policies including one or more rules for restricting sharing of data may be maintained. A filtered data set may be generated for a data source provider responsive to an application of restriction policies of other data source providers to the master data set. The filtered data set may be provisioned.