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Question 53/124

Universal Containers has millions of rows of data in Salesforce that are being used in reports to evaluate historical trends. Performance has become an issue, as well as data storage limits. Which two strategies should be recommended when talking with stakeholders?

Recent Comments (The most recent comments are at the top.)

txhai - Mar 27, 2025

Not C or D
C (Data Loader): Manual and error-prone; not scalable for ongoing management.
D (Archiving): Solves storage but not performance, as Big Objects don’t support standard reporting for trends.

Afef - Oct 24, 2024

The two recommended strategies to address performance issues and data storage limits would be:

A. Use scheduled batch Apex to copy aggregate information into a custom object and delete the original records.
B. Combine Analytics Snapshots with a purging plan by reporting on the snapshot data and deleting the original records.

Explanation:
Option B: Combine Analytics Snapshots with a purging plan
Analytics Snapshots allow you to capture and store historical data at scheduled intervals. You can create a snapshot of your report data (such as weekly or monthly), which is saved into a custom object.
This allows you to keep historical trends and performance data while being able to purge the older records from the original objects to free up storage. This strategy effectively separates operational data from historical reporting data, improving both performance and storage utilization.
Option A: Use scheduled batch Apex to copy aggregate information
You can write a batch Apex job that periodically aggregates historical data and stores it in a custom object. This custom object would hold summarized information, allowing users to report on trends without the need to keep all detailed data.
This approach is efficient when stakeholders are primarily interested in aggregated data or summaries, rather than every individual record.
Once the aggregation is complete, the original detailed records can be safely deleted, reducing the volume of data stored.
Why Other Options Are Less Suitable:
C. Use Data Loader to extract data, aggregate it, and write it back to a custom object, then delete the original records:
While this method could work, it is manual and not scalable. It lacks automation, requires manual intervention with Data Loader, and is prone to errors, making it a less robust and scalable solution compared to using batch Apex or snapshots.

D. Configure the Salesforce Archiving feature to archive older records and remove them from the data storage limits:
Salesforce doesn...

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