Salesforce Data-Architect Exam With Confidence Using Practice Dumps

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.

 Using hard delete in Bulk API, identifying records that have not been modified or used in last 3 years, and archiving the records in EDW before deleting from Salesforce are all good recommendations to reduce the number of records from the org1. Using hard delete in batch Apex or Rest API may not be as efficient or scalable as Bulk API

 Using validation rules to mitigate this problem is the best option. Validation rules can help you prevent invalid data from being entered in your web order form. You can use validation rules to check for data quality, format, range, or consistency. For example, you can use validation rules to ensure that the order quantity is positive, the product code is valid, or the shipping address is complete.