Data Transfer
Data transfer is a mechanism that enables the exchange of data between publishing and subscribing systems. This process involves record groups, subscriber groups, and subscriptions. Record groups define the data to be shared and can include multiple levels of child records. Subscriber groups are composed of systems with a shared interest in the data being subscribed to, and subscriptions specify which record groups a subscriber group is entitled to access.
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When the export process runs, it checks for any changes in subscription data and audit logs and writes the data to a data server in JSON format. The import process for a given system checks the data server for data that needs to be applied to its database. Users review the queue of data that needs to be applied and approve the changes as required. The import process accommodates differences in the data structures between the local system and the data being sent by the publisher.
The benefits of the data transfer mechanism are as follows:
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Simplify integrations - The data transfer feature allows for integrations to be created using parameter-driven configuration rather than custom coding. This means that integrations can be set up much more quickly and with less effort, resulting in cost and time savings for the organization.
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Custom integrations - Although the data transfer process is automated, there may be situations where custom integrations are required. The data transfer feature can be used in conjunction with custom integration tools, providing flexibility in how integrations are implemented.
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Supports master data management - Master data management can be a complex and time-consuming task, especially in organizations with multiple systems and data sources. The data transfer feature simplifies master data management by ensuring that all systems are operating with the same master data, reducing the risk of errors and inconsistencies.
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Supports transactional changes - When updates occur, they are often transactional. The data transfer feature allows updates to be processed as a group, ensuring that all changes are made together and reducing the risk of errors.
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Controlled - The import process is fully customizable, allowing users to control how data is imported into their system. This can be fully automated or require manual review, depending on the needs of the organization.
Reduces errors and inconsistencies - By automating the data transfer process, the risk of errors and inconsistencies is greatly reduced. This is because the data transfer feature ensures that all systems are operating with the same data, reducing the risk of data entry errors and ensuring that data is consistent across all systems.
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Improves efficiency - The data transfer feature allows data to be transferred between systems quickly and efficiently, reducing the need for manual data entry and streamlining business processes.
Facilitates collaboration - The data transfer feature facilitates collaboration between systems, allowing teams to work together more effectively and share data easily.
Enhances data security - The data transfer feature allows data to be shared securely between systems, ensuring that sensitive information is protected and reducing the risk of data breaches or other security incidents.
Scalable - The data transfer feature is scalable, meaning that it can be used by organizations of all sizes and can grow as the organization grows. This allows organizations to future-proof their data management systems and ensure that they can handle increased data volumes over time.
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For more information on Data Transfer, please check out the following videos.
https://m1archive.s3.us-west-2.amazonaws.com/Videos/Data+Exchange+-+Part+1.mp4
https://m1archive.s3.us-west-2.amazonaws.com/Videos/Data+Exchange+-+Part+2a.mp4
https://m1archive.s3.us-west-2.amazonaws.com/Videos/Data+Exchange+-+Part+2b.mp4
https://m1archive.s3.us-west-2.amazonaws.com/Videos/Data+Exchange+-+Part+2c.mp4
https://m1archive.s3.us-west-2.amazonaws.com/Videos/Data+Exchange+-+Part+2d.mp4