Abstract: A device, system and method for mode-based synchronization of data records is provided. Booking data is received, at one or more computing devices, from one of a first and second client device. When received from the first client device, in a first order mode for the booking data, the device(s): cause an order management system (OMS) to generate: order data at a first database; and cause a legacy system to generate a corresponding passenger name record (PNR) at a second database, the corresponding PNR being slaved to the order data. When received from the second client device, in a legacy mode for the booking data, the device(s): cause the legacy system to generate, a PNR and/or ticket data at the second database; and cause the OMS to generate corresponding order data at the first database, the corresponding order data being slaved to the PNR and/or the ticket data.

Abstract: Database requests are processed in a distributed database system comprising a central database subsystem and a plurality of local database subsystems comprising a first local database subsystem. The central database subsystem receives a second database request indicating at least one unique identifier of at least one database result of a plurality of database results which have been stored with corresponding unique identifiers by the first local database subsystem in response to a first database request received at the first local database subsystem. The at least one database result identified by the at least one unique identifier is retrieved from the first local database subsystem, processed and stored persistently in a database of the central database subsystem. At least the first local database subsystem and the central database subsystem may operate according to the New Distribution Capability (NDC) standard.

Abstract: A device, system and method for training machine learning models using messages associated with provider objects is provided. One or more computing devices: receives messages associated with provider objects representing items provided by provider systems, the messages having more than one format; stores harmonized objects corresponding to the messages, the harmonized objects generated using mappings of harmonized data of the harmonized objects to message data of the messages, the harmonized objects having common formats for a harmonized object type; extracts, from the harmonized objects, for a given machine learning model, given machine learning training data; generates, for the given machine learning model, using the given machine learning training data, at least one machine learning classifier; and provides the at least one machine learning classifier to the given machine learning model at one or more servers configured to implement the given machine learning model on received provider objects.