Abstract: In some examples, a computer system computes a rate of operations that involves a first system, and classifies, using a classifier, a request for an operation. The computer system determines a relationship between the computed rate of operations and a dynamic threshold rate determined during a training phase, and based on the determined relationship and a classification of the request by the classifier, selectively activates or disables an operational feature of the first system.

Abstract: A method may include identifying an identifier field included in a first datatype of a seed data sample associated with a source system. The identifier field may store a first value that enables a differentiation between different instances of the first datatype. A relationship field, which stores a second value that define a relationship between the first datatype and a second data type, may be identified. A synthetic data sample may be generated by populating the identifier field of the synthetic data sample with a synthetically generated value and the relationship field of the synthetic data sample with the second value. The synthetic data sample may be sent to a target system to enable a performance of a task at the target system. The synthetic data sample may supplement a volume and/or a diversity of the data that occurs organically at the source system.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program may receive a request to extract data for a first entity type. The program may, in response to the request, determine a subset of a plurality of data extraction configurations associated with the first entity type. The program may, for each data extraction configuration in the subset of the plurality of data extraction configurations, process the data extraction configuration based on a set of transaction data to generate a set of data, the set of data comprising a first set of data included in a set of instances of the first entity type and a second set of data included in a set of instances of a second entity type.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program may receive a request to extract data for a first entity type. The program may, in response to the request, determine a subset of a plurality of data extraction configurations associated with the first entity type. The program may, for each data extraction configuration in the subset of the plurality of data extraction configurations, process the data extraction configuration based on a set of transaction data to generate a set of data, the set of data comprising a first set of data included in a set of instances of the first entity type and a second set of data included in a set of instances of a second entity type.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a set of data for a record in a first table. The set of data comprises a set of values for a set of attributes. The first table comprises a first set of columns. A first column in the first set of columns in the first table is configured to refer to a second column in a second set of columns in a second table. The program further generates the record in the first table. The program also generates a value for the first column in the first set of columns in the first table based on a subset of the set of values for a subset of the set of attributes. The program further stores the value in the first column in the first set of columns of the record.

Abstract: Some embodiments provide a program that receives a set of data for a first record in a first table. The set of data comprises a set of values for a set of attributes. In a data loading process configured to load a subset of the set of data into a subset of a first set of columns in the first table, the program determines that a first column in a first set of columns does not belong in the subset of the first set of columns. The program generates the first record in the first table. The program generates a value for the first column in the first set of columns that refers to a second record in the second table configured to represent a defined type of record. The program stores the value in the first column in the first set of columns of the first record.

Abstract: In some examples, a computer system computes a rate of operations that involves a first system, and classifies, using a classifier, a request for an operation. The computer system determines a relationship between the computed rate of operations and a dynamic threshold rate determined during a training phase, and based on the determined relationship and a classification of the request by the classifier, selectively activates or disables an operational feature of the first system.

Abstract: In some examples, a computer system computes a rate of operations that involves a first system, and classifies, using a classifier, a request for an operation. The computer system determines a relationship between the computed rate of operations and a dynamic threshold rate determined during a training phase, and based on the determined relationship and a classification of the request by the classifier, selectively activates or disables an operational feature of the first system.

Abstract: Systems and methods are describe herein for managing a transaction between two parties. A distributed ledger management service (DLMS) microservice receives an electronic document pertaining to a transaction from a user. The electronic document includes transactional data. A document type is determined by the DLMS microservice. A portion of the transactional data is extracted from the electronic document based on the document type. The portion of the transactional data is provided to a distributed ledger node for decentralized storage and further reporting to a third party.

Abstract: In some examples, a computer system computes a rate of operations that involves a first system, and classifies, using a classifier, a request for an operation. The computer system determines a relationship between the computed rate of operations and a dynamic threshold rate determined during a training phase, and based on the determined relationship and a classification of the request by the classifier, selectively activates or disables an operational feature of the first system.

Abstract: In some examples, a system includes a Fibre Channel (FC) interface to communicate over an FC network, and a network stack including a network layer and a transport layer. Machine-readable instructions are executable to produce a command packet including a payload including data for transmission to another system, the payload further including headers for the network layer and the transport layer, where the command packet is according to a storage interface protocol. The FC interface is to communicate the command packet over the FC network.

Abstract: A method may include allocating, based on a first load requirement of a first tenant, a first bin having a fixed capacity for handing the first load requirement of the first tenant. In response to the first load requirement of the first tenant exceeding a first threshold of the fixed capacity of the first bin, packing a second bin allocated to handle a second load requirement of a second tenant. The second bin may be packed by transferring, to the second bin, the first load requirement of the first tenant based on the transfer not exceeding the first threshold of the fixed capacity of the second bin. In response to the transfer exceeding the first threshold of the fixed capacity of the second bin, allocating a third bin to handle the first load requirement of the first tenant.

Abstract: A method may include receiving, at a data lake platform, a packet including a metadata corresponding to a data schema of a source system. A change in the data schema of the source system may be detected based on a first checksum of the metadata and a second checksum of a previous version of the metadata. In response to detecting the change in the data schema of the source system, the metadata may be sent to a target system to enable the target system to perform, based on the data schema of the source system, a task operating on a data from the source system. The task may include reporting, visualization, advanced analytics, and/or machine learning. Related systems and computer program products are also provided.

Abstract: A method may include identifying an identifier field included in a first datatype of a seed data sample associated with a source system. The identifier field may store a first value that enables a differentiation between different instances of the first datatype. A relationship field, which stores a second value that define a relationship between the first datatype and a second data type, may be identified. A synthetic data sample may be generated by populating the identifier field of the synthetic data sample with a synthetically generated value and the relationship field of the synthetic data sample with the second value. The synthetic data sample may be sent to a target system to enable a performance of a task at the target system. The synthetic data sample may supplement a volume and/or a diversity of the data that occurs organically at the source system.

Abstract: In some examples, a system includes a Fibre Channel (FC) interface to communicate over an FC network, and a network stack including a network layer and a transport layer. Machine-readable instructions are executable to produce a command packet including a payload including data for transmission to another system, the payload further including headers for the network layer and the transport layer, where the command packet is according to a storage interface protocol. The FC interface is to communicate the command packet over the FC network.

Abstract: Systems and methods are describe herein for managing a transaction between two parties. A distributed ledger management service (DLMS) microservice receives an electronic document pertaining to a transaction from a user. The electronic document includes transactional data. A document type is determined by the DLMS microservice. A portion of the transactional data is extracted from the electronic document based on the document type. The portion of the transactional data is provided to a distributed ledger node for decentralized storage and further reporting to a third party.

Abstract: A method for processing inbound and/or outbound data wherein a processing policy is determined for a quantum of data. A quantum of inbound data is received and a data notification for the received data is prepared. The notification for the quantum of received inbound data is delivered to a processor according to the processing policy. When selecting a quantum of outbound data, an outbound data work request for the outbound data is prepared and delivered to an output unit according to the processing policy.

Abstract: A method for analyzing database records using sampling includes querying a recipient database for recipients with attributes that match one or more specified recipient attributes, querying a sampling database for transactions with attributes that match one or more specified transaction attributes, where the sampling database stores a subset of transactions that are also stored in a transaction database, intersecting the recipients resulting from the querying of the recipient database and the transactions resulting from the querying of the sampling database based on attributes thereof to create a set of joined sample results, and determining an approximate full count value by extrapolating a count value associated with the set of joined sample results based on both a total number of recipients in the recipient database and a total number of transactions in the transaction database.

Abstract: This invention provides new pharmaceutically useful compounds that are prodrugs of inhibitors of plasma kallikrein and methods and compositions for preventing or treating plasma kallikrein dependent diseases or conditions, such as diabetic macular edema or hemorrhagic stroke, by administering prodrugs of the formula:

Abstract: A method for analyzing database records using sampling includes querying a recipient database for recipients with attributes that match one or more specified recipient attributes, querying a sampling database for transactions with attributes that match one or more specified transaction attributes, where the sampling database stores a subset of transactions that are also stored in a transaction database, intersecting the recipients resulting from the querying of the recipient database and the transactions resulting from the querying of the sampling database based on attributes thereof to create a set of joined sample results, and determining an approximate full count value by extrapolating a count value associated with the set of joined sample results based on both a total number of recipients in the recipient database and a total number of transactions in the transaction database.