Salesforce Certified Data Architecture Practice Test

What action can improve the scalability of data processing in Salesforce?

1. Reduce the number of triggers per object.

2. Cache data within Salesforce for faster access.

3. Implement asynchronous processing for heavy operations.

4. Migrate all data to external databases.

The correct answer is: Implement asynchronous processing for heavy operations.

Implementing asynchronous processing for heavy operations significantly enhances the scalability of data processing within Salesforce. This approach allows long-running tasks, such as complex calculations or data transformations, to execute in the background without blocking the main user interface or other operations. By using asynchronous processing, resources can be utilized more efficiently. For example, Salesforce's services like Queueable Apex and Future methods enable offloading substantial workloads, allowing for better management of limits and performance. Since heavy operations do not directly affect the user experience, this method optimizes overall system responsiveness and throughput, particularly as the volume of data and transactions increases. In contrast, while reducing the number of triggers or caching data can have benefits, they do not directly target the fundamental issue of executing heavy operations efficiently. Furthermore, migrating all data to external databases is more drastic and does not inherently improve data processing scalability within the Salesforce environment. It may even complicate data access and integration, which could lead to delays or bottlenecks. Thus, asynchronous processing emerges as the most effective and practical solution for enhancing performance in scalable applications within Salesforce.