Data-Architect Exam Dumps : Salesforce Certified Platform Data Architect (Plat-Arch-201)

Importing Account records first followed by order records after sorting orders by AccountID is the recommended way to avoid locking issues during import. This can reduce the number of lock contention errors by minimizing the number of parent records that are concurrently processed by multiple batches. Sorting orders by AccountID can also group the child records by their parent records and avoid updating the same parent record in different batches3. Importing Account records first followed by order records after sorting order by OrderID will not help with avoiding locking issues because it does not group the child records by their parent records. Changing the relationship to Lookup and updating the relationship to master-detail after import will not work because changing a relationship from Lookup to master-detail requires that all child records have a parent record, which may not be the case after import. Importing Order records and Account records separately and populating AccountID in orders using batch Apex will not help with avoiding locking issues because it still requires updating the parent records in batches.

Creating an account plan object with a lookup relationship to Account with validation rules to enforce the Account association can help UC meet their requirement. A lookup relationship allows different accessibility requirements for the account plan object and the account object, as well as different ownership and sharing settings. A validation rule can ensure that each account plan has an account associated with it.

According to the Salesforce documentation, a hub-and-spoke model is an integration architecture pattern that allows connecting multiple Salesforce orgs using a central org (hub) and one or more secondary orgs (spokes). The hub org acts as the master data source and orchestrates the data flow between the spoke orgs. The spoke orgs act as the consumers or producers of the data and communicate with the hub org.

To orchestrate data between the hub org and spoke orgs, a data architect should use:

A middleware solution that extracts and distributes data across both the hub and spokes (option A). This means using an external service or tool that can connect to multiple Salesforce orgs using APIs or connectors, and perform data extraction, transformation, and distribution operations between the hub and spoke orgs. This can provide a scalable, flexible, and reliable way to orchestrate data across multiple orgs.

Developing custom APIs to poll the hub org for change data and push into the spoke orgs (option B) is not a good solution, as it can be complex, costly, and difficult to maintain. It may also not be able to handle large volumes of data or complex transformations efficiently. Developing custom APIs to poll the spoke orgs for change data and push into the hub org (option C) is also not a good solution, as it can have the same drawbacks as option B. It may also not be able to handle conflicts or errors effectively. Using a backup and archive solution that extracts and restores data across orgs (option D) is also not a good solution, as it can incur additional costs and dependencies. It may also not be able to handle real-time or near-real-time data orchestration requirements.