Salesforce Data-Architect Exam With Confidence Using Practice Dumps

The recommended solution for the Cloud Kicks Data Architect to address the requirements is to create a custom object to track shipment requests and a child custom object to track shipment items. Implement an archiving process that moves data off-platform after three years. This solution would allow Cloud Kicks to store and manage their shipment data on Salesforce, and use Salesforce reports to analyze it. However, since Cloud Kicks expects a large volume of data over time, they should implement an archiving process that moves data off-platform after three years to avoid hitting the Org data storage limit and maintain optimal performance3. External objects are not a good option for this scenario, because they are stored off-platform in an external system, such as Heroku’s Postgres database, and they have limited functionality and performance compared to custom objects

Using an ETL tool to orchestrate the migration is the best strategy for this scenario, as it can handle the data model changes, the large volume of records, and the tight timeline. Writing a script to use the Bulk API (option C) is also possible, but it would require more coding and testing effort. Using Data Loader and Data Import Wizard (option B) is not suitable for migrating three million records, as they have limitations on the batch size and the number of records per operation. Using Salesforce CLI (option D) is also not recommended for large data migration, as it is mainly designed for development and testing purposes

Exporting in multiple batches and using PK Chunking are two steps that can help correct the issues with exporting large volumes of Order records using Informatica Cloud Loader. Exporting in multiple batches can reduce the load on the system and avoid timeouts or errors. Using PK Chunking can split a large data set into smaller chunks based on the record IDs and enable parallel processing of each chunk.