A file system permission setting method and apparatus, where an access control list (ACL) permission for a parent node is set such that all child nodes of the parent node inherit the ACL permission for the parent node when a semantic type identifier of an access permission for the parent node is a permission root type.

Methods, systems, and devices for data validation are described. A user may store a set of data records on a source database and backup the set of data records at a target database through a data migration. A migration and validation server may initiate the data migration. After the data migration is complete, the migration and validation server may perform a validation process that includes comparing a calculated hash value from the source database and the target database that is based on unique identifiers and timestamps for each data record in the set of data records migrated from the source database to the target database. The migration and validation server may determine if the data migration was successful (e.g., the data was transferred correctly) if the hash value calculated for the data records at the target database equals the hash value calculated for the data records at the source database.

Computer-implemented methods, systems and products, the method comprising receiving, at a data server associated with a database, a command for data transfer between a client machine and the data server over a communications network, the data being stored in at least a data table comprising one or more columns; in response to receiving the command for data transfer, determining whether one or more columns of the data table are designated; identifying the one or more designated columns, such that data associated with the one or more designated columns is either considered or not considered for purpose of the data transfer; and executing the command to transfer the data in the database according to the designated columns.

A method is provided for reconfiguring a vehicle for transfer from a first operator to a second operator. The method includes accessing first datasets that define an initial configuration of the vehicle, importing second datasets that describe maintenance, repair or service of the vehicle during in-service operation with the first operator, and generating a first composite dataset defining a current configuration of the vehicle. The method also includes accessing third datasets that define requirements of the vehicle for in-service operation with the second operator, and generating a second composite dataset that defines a target configuration of the vehicle from the first composite dataset and based on data of the third datasets. The method includes comparing the first and second composite datasets to identify modifications to reconfigure the vehicle from the current configuration to the target configuration, and generating a visual presentation of the modifications to facilitate reconfiguration of the vehicle.

Described herein are systems, methods, and software to manage the downtime associated with updates and configuration modification to the database. In one implementation, a migration service initiates a migration of data from a first database to a second database. The migration service further identifies, in a transaction log, modifications to the data in the first database after initiating the migration of the data and, for each modification, applies one or more transformation rules to the modification to make a compliant modification and updates the second database with the compliant modification. Once the migration is complete and no more modifications exist in the transaction log, the migration service may transition from using the first database as an active database to using the second database as the active database.

A chat robot may be used to facilitate interaction with a user in the determination of whether to initiate and process a data subject access request (DSAR). At a DSAR submission webpage, the chatbot may interact with a user to determine the information the user is in need of and/or the actions that the user may take. The chatbot may provide the information, avoiding the processing overhead of submission and fulfillment of a DSAR. In addition, data stored on a data asset may be migrated to another data asset while maintaining compliance to applicable regulations. Based on the type of data stored by that data asset and the applicable regulations, requirements, and/or restrictions that relate to a transfer of that type data from that data asset, a target data asset may be determined. The data stored on the data asset may then be transferred to the target data asset.

The systems and methods provide for migrating database management system (DBMS) applications to cloud storage by automating a continuous replication of changes made to the DBMS from the DBMS to an associated cloud instance. For example, the systems and methods facilitate the migration of the DBMS via multiple processes performing in parallel—a process to create and provision a new machine instance (e.g., an EC2 instance), a process to clone and transfer parameters of the operating system/software of the DBMS, and a process that backs up and/or captures the application data of the DBMS. In some embodiments, the systems and methods, utilizing parallel processes, and combining outputs of the processes to a synchronization process, efficiently and quickly migrate DBMS applications to cloud storage, among other benefits.

A device may receive source code from a source data structure, and may receive information associated with a target data structure. The device may analyze the source code to extract statements, and may utilize natural language processing on the statements to identify functions and keywords associated with the source data structure. The device may train a machine learning model with the functions and the keywords to generate a trained machine learning model, and may process the information associated with the target data structure, with the trained machine learning model, to transform a source query to a target query compatible with the target data structure. The device may process the target query, with a neural network model, to generate an optimized target query, and may cause data from the source data structure to be migrated to the target data structure based on the optimized target query.

Migration results in specific action requests to move data from a source system instance to a target system instance. Migration may consume many resources. In an effort to monitor migration effects on source and/or target performance, one or more traffic lights are determined to monitor utilization of resources of the source and/or target. Based on the one or more traffic lights, migration is dynamically throttled. The one or more traffic light may be assigned a status based on how the migration affects performance of another data operation which may be contemporaneously operating on either the source and/or the target.

Systems and method for improving query performance by querying an appropriate database engine based on the operation of the query request is provided. In one aspect, this approach involves querying a row-oriented database, querying a column-oriented database, or blacklisting the query request. In particular, updating the column-oriented database involves delete and insert operations. By maintaining updated databases and querying appropriate database engines, the response time of a query request may be improved.