Abstract: Techniques are disclosed relating to a method that includes receiving, by a particular computer system included in an enterprise computer system, deployment instructions, from a user, for a particular version of a machine-learning model. One or more versions of the machine-learning model may be stored in a database. The particular computer system may select, based on the deployment instructions, a destination within the enterprise computer system for deploying the particular version. The selected destination may provide access to a particular data set. The particular computer system may schedule a deployment of the particular version from the database to the selected destination. The deployed version of the machine-learning model may operate on the particular data set. Performance data associated with operation of the deployed version of the machine-learning model is collected.

Abstract: There are provided systems and methods for a database synchronization system in networked zones using blockchain. An electronic service provider may maintain data stores across different zones that may need to synchronize data across these zones. As such, the subject technology provides for data storage using interplanetary file system (IPFS) technology according to some embodiments with blockchain technology to create a secure and reliable data synchronization system. IPFS may be implemented as a data storage layer and blockchain as a transaction management system, where the IPFS address of data files and synchronization points are stored in a distributed ledger. Integration of the IPFS network with a fabric network can enhance IPFS with the fabric network to create a more secure file sharing platform to improve the transfer of data and database synchronization between different zones.

Abstract: Techniques are disclosed relating to a method that includes receiving, by a particular computer system included in an enterprise computer system, deployment instructions, from a user, for a particular version of a machine-learning model. One or more versions of the machine-learning model may be stored in a database. The particular computer system may select, based on the deployment instructions, a destination within the enterprise computer system for deploying the particular version. The selected destination may provide access to a particular data set. The particular computer system may schedule a deployment of the particular version from the database to the selected destination. The deployed version of the machine-learning model may operate on the particular data set. Performance data associated with operation of the deployed version of the machine-learning model is collected.

Abstract: Techniques are disclosed relating to a method that includes receiving, by a particular computer system included in an enterprise computer system, deployment instructions, from a user, for a particular version of a machine-learning model. One or more versions of the machine-learning model may be stored in a database. The particular computer system may select, based on the deployment instructions, a destination within the enterprise computer system for deploying the particular version. The selected destination may provide access to a particular data set. The particular computer system may schedule a deployment of the particular version from the database to the selected destination. The deployed version of the machine-learning model may operate on the particular data set. Performance data associated with operation of the deployed version of the machine-learning model is collected.

Abstract: Techniques are disclosed relating to a method that includes accessing, by a failure management program, a failure log that includes a plurality of character strings corresponding to errors that are associated with execution of one or more batch processes. The failure management program may compare a particular character string of the plurality of character strings to a set of character strings that are associated with respective ones of a plurality of failure categories. This comparing may include determining whether particular keywords that are included in respective ones of the set of character strings are included in the particular character string. In response to the comparing, the failure management program may assign a particular error corresponding to the particular character string to a particular failure category, or may determine a new failure category if the particular character string does not match an existing failure category.

Abstract: There are provided systems and methods for duplicate table identification in enterprise database systems for data storage optimization. A service provider, such as an electronic transaction processor for digital transactions, may determine data duplication in database tables so that database storage resources may be optimized. In order to determine data duplication, within database tables, a data collector daemon operation and/or application may collect metadata for tables within a domain. Using the metadata, a master table and derived tables may be determined for a group of the tables. Further, a duplication factor may be determined based on matching columns in the tables, a usage factor may be determined using processing hits to the tables, and a size factor may be determine based on table size. This allows for determination of a relevance score of the group, which provides a measure of duplication of data within those tables.

Abstract: There are provided systems and methods for a database synchronization system in networked zones using blockchain. An electronic service provider may maintain data stores across different zones that may need to synchronize data across these zones. As such, the subject technology provides for data storage using interplanetary file system (IPFS) technology according to some embodiments with blockchain technology to create a secure and reliable data synchronization system. IPFS may be implemented as a data storage layer and blockchain as a transaction management system, where the IPFS address of data files and synchronization points are stored in a distributed ledger. Integration of the IPFS network with a fabric network can enhance IPFS with the fabric network to create a more secure file sharing platform to improve the transfer of data and database synchronization between different zones.

Abstract: There are provided systems and methods for a database synchronization system in high security zones using blockchain. A service provider, such as an electronic payment provider, may maintain data stores across different zones that may need to synchronize data across these zones. As such, the subject technology provides for data storage using interplanetary file system (IPFS) technology in compliment with blockchain technology to create a secure, scalable and reliable data synchronization system. The IPFS may be implemented as a data storage layer and the blockchain may be implemented as a transaction management system, where the IPFS address of data files and synchronization points are stored in a distributed ledger. In various aspects, the integration of the IPFS network with the fabric network can enhance IPFS with the fabric network to create a more secure file sharing platform to improve the transfer of data and database synchronization between different zones.

Abstract: Techniques are disclosed relating to a method that includes receiving, by a particular computer system included in an enterprise computer system, deployment instructions, from a user, for a particular version of a machine-learning model. One or more versions of the machine-learning model may be stored in a database. The particular computer system may select, based on the deployment instructions, a destination within the enterprise computer system for deploying the particular version. The selected destination may provide access to a particular data set. The particular computer system may schedule a deployment of the particular version from the database to the selected destination. The deployed version of the machine-learning model may operate on the particular data set. Performance data associated with operation of the deployed version of the machine-learning model is collected.

Abstract: There are provided systems and methods for a database synchronization system in high security zones using blockchain. A service provider, such as an electronic payment provider, may maintain data stores across different zones that may need to synchronize data across these zones. As such, the subject technology provides for data storage using interplanetary file system (IPFS) technology in compliment with blockchain technology to create a secure, scalable and reliable data synchronization system. The IPFS may be implemented as a data storage layer and the blockchain may be implemented as a transaction management system, where the IPFS address of data files and synchronization points are stored in a distributed ledger. In various aspects, the integration of the IPFS network with the fabric network can enhance IPFS with the fabric network to create a more secure file sharing platform to improve the transfer of data and database synchronization between different zones.

Abstract: There are provided systems and methods for duplicate table identification in enterprise database systems for data storage optimization. A service provider, such as an electronic transaction processor for digital transactions, may determine data duplication in database tables so that database storage resources may be optimized. In order to determine data duplication, within database tables, a data collector daemon operation and/or application may collect metadata for tables within a domain. Using the metadata, a master table and derived tables may be determined for a group of the tables. Further, a duplication factor may be determined based on matching columns in the tables, a usage factor may be determined using processing hits to the tables, and a size factor may be determine based on table size. This allows for determination of a relevance score of the group, which provides a measure of duplication of data within those tables.

Abstract: Techniques are disclosed relating to a method that includes accessing, by a failure management program, a failure log that includes a plurality of character strings corresponding to errors that are associated with execution of one or more batch processes. The failure management program may compare a particular character string of the plurality of character strings to a set of character strings that are associated with respective ones of a plurality of failure categories. This comparing may include determining whether particular keywords that are included in respective ones of the set of character strings are included in the particular character string. In response to the comparing, the failure management program may assign a particular error corresponding to the particular character string to a particular failure category, or may determine a new failure category if the particular character string does not match an existing failure category.

Abstract: A method for integrated retrieval and annotation of stored images involves running a user application in which text entered by a user is continuously monitored to isolate the context expressed by the text. The context is matched with metadata associated with the stored images, thereby providing one or more matched images, and the matched images are retrieved and displayed in proximity with the text. The context is then utilized to provide suggested annotations to the user for the matched images, together with the capability of selecting certain of the suggested annotations for subsequent association with the matched images. In a further extension, the method provides the user with the capability of inserting selected ones of the matched images into the text of the application, and further provides for automatically updating the metadata for the matched images.