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.

The present disclosure relates to systems and methods for creating and using personas. The method includes receiving a first set of input signals associated with data from one or more source; receiving a second set of input signals associated with data from one or more source; converting the first set of input signals and the second set of input signals to a wavelet; constructing a persona based on the wavelet; storing the persona in a ledger; receiving a request for a decision related to a transaction; converting the request to a new wavelet; determining a difference between the new wavelet and the stored persona; generating a score based on the difference; and authorizing the transaction based on the score.

The present disclosure relates to systems and methods for creating and using personas. The method includes receiving a first set of input signals associated with data from one or more source; receiving a second set of input signals associated with data from one or more source; converting the first set of input signals and the second set of input signals to a wavelet; constructing a persona based on the wavelet; storing the persona in a ledger; receiving a request for a decision related to a transaction; converting the request to a new wavelet; determining a difference between the new wavelet and the stored persona; generating a score based on the difference; and authorizing the transaction based on the score.

According to one embodiment, a DB integration device includes a receiver and a designator. The receiver is configured to receive at least a request for combining first data and second data. The designator is configured to designate, from among a plurality of DB systems, a DB system for executing a combining process of combining the first data and the second data on the basis of combining capability information. The combining capability information indicates at least one of: whether or not a first DB system is capable of reading the second data from a second DB system and executing the combining process; and whether or not the first DB system is capable of causing the second DB system to read the first data.

According to one embodiment, a DB integration device includes a receiver and a designator. The receiver is configured to receive at least a request for combining first data and second data. The designator is configured to designate, from among a plurality of DB systems, a DB system for executing a combining process of combining the first data and the second data on the basis of combining capability information. The combining capability information indicates at least one of: whether or not a first DB system is capable of reading the second data from a second DB system and executing the combining process; and whether or not the first DB system is capable of causing the second DB system to read the first data.

A data processing method, apparatus, and system, a computer device, a readable storage medium, and a computer program product relate to the field of cloud technologies and a blockchain technology, and the method includes: receiving, by using a transceiver component, collection indicator data sent by an edge cluster; performing pre-aggregation processing on the collection indicator data to obtain pre-aggregated indicator data, and sending the pre-aggregated indicator data to a coordinated write component; converting, by the coordinated write component, the pre-aggregated indicator data into conversion indicator data that has a target storage format, and performing merging processing on the conversion indicator data to obtain storage indicator data; writing the storage indicator data into a database component; and writing, by the database component, the storage indicator data into a storage disk.

A data processing method, apparatus, and system, a computer device, a readable storage medium, and a computer program product relate to the field of cloud technologies and a blockchain technology, and the method includes: receiving, by using a transceiver component, collection indicator data sent by an edge cluster; performing pre-aggregation processing on the collection indicator data to obtain pre-aggregated indicator data, and sending the pre-aggregated indicator data to a coordinated write component; converting, by the coordinated write component, the pre-aggregated indicator data into conversion indicator data that has a target storage format, and performing merging processing on the conversion indicator data to obtain storage indicator data; writing the storage indicator data into a database component; and writing, by the database component, the storage indicator data into a storage disk.

The present disclosure relates to merging database tables. Systems and methods may involve performing a comparison between the first set of records and the second set of records and identifying a plurality of record pairs based on the comparison. Each record pair may comprise a record in the first set of records and a record in the second set of records. In addition, A feature signature may be generated for each record pair by comparing field values in each record pair. The feature signature may be classified to identify at least one related record pair. A merged database table may be generated such that it comprises the at least one related record pair and comprises a set of unique records among selected from the first set of records and the second set of records.

A method enables on-demand delivery of data from a plurality of heterogeneous external data sources to a data analytics tool. With a mapping of one or more identified data connectors, a no-code client query, as formulated in a first data model, is dynamically translated to one or more external queries formulated in one or more alternate data models of the heterogeneous external data sources. With the mappings of the one or more identified connectors, each response to the one or more external queries is reformulated from the one or more alternate data models to the first data model to yield one or more client query results objects. The client query results objects are sent to the data analytics tool.