Every year, Ursa Major Solar has more than 1 million orders. Each order contains an average of 10 line items. The Chief Executive Officer (CEO) needs the Sales Reps to see how much money each customer generates year-over-year. However, data storage is running low in Salesforce.
Which approach for data archiving is appropriate for this scenario?

• A.1. Annually export and delete orders and order line items.
  2. Store them in a zip file in case the data is needed later.
• B.1. Annually export and delete order line items.
  2. Store them in a zip file in case the data is needed later.
• C.1. Annually aggregate order amount data to store in a custom object.
  2. Delete those orders and order line items.
• D.1. Annually delete orders and order line items.
  2. Ensure the customer has order information in another system.

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DreamHouse Realty has a data model as shown in the image. The Project object has a private sharing model, and it has Roll-Up summary fields to calculate the number of resources assigned to the project, total hours for the project, and the number of work items associated to the project.
There will be a large amount of time entry records to be loaded regularly from an external system into Salesforce.

What should the Architect consider in this situation?

• A.Calculate summary values instead of Roll-Up by using workflow.
• B.Calculate summary values instead of Roll-Up by using triggers.
• C.Load all data after deferring sharing calculations.
• D.Load all data using external IDs to link to parent records.

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