SF-Data-Arch Salesforce Data Management Practice Question
Exhibit
System.LimitException: Too many DML statements: 151; Trigger on Account: execution of AfterUpdate
Refer to the exhibit. An architect is reviewing an error log from a high-volume data load. Which pattern should be implemented to resolve this limit violation?
⚠ Common exam trap
Candidates look for asynchronous processing solutions like Queueable Apex, missing that the fundamental error is simply performing individual DML statements inside a loop rather than processing collections.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Implement the Bulk DML Pattern using collections.
The error indicates that DML operations are occurring inside a loop, exceeding the Salesforce governor limit of 150 DML statements per transaction. To resolve this, developers must use the Bulk Pattern, which involves collecting records in a collection (List or Map) and performing a single DML operation outside of the loop. This ensures efficient resource usage and prevents transactions from failing during high-volume data processing scenarios.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the batch size in the data loader settings.
Why it's wrong here
Increasing batch size actually exacerbates DML limit issues by creating more records per execution context. If the code is not optimized to handle bulk operations, a larger batch size will cause the transaction to hit governor limits faster, leading to systemic failures rather than resolving the existing logic flaw.
- ✓
Implement the Bulk DML Pattern using collections.
Why this is correct
Moving DML operations outside of loops is the fundamental requirement for Salesforce Apex development. By collecting records in a List and performing a single DML call, you stay within the 150 limit per transaction. This is a critical architectural pattern for ensuring scalable code during heavy data ingestion processes.
- ✗
Convert the trigger to an asynchronous future method.
Why it's wrong here
While future methods run in a separate context, they have their own limits and are not the correct way to handle trigger logic. Using them for this purpose is considered an anti-pattern, as it introduces complexity and may hit other limits like asynchronous apex queue depth or concurrency.
- ✗
Increase the Apex CPU time limit in the Setup menu.
Why it's wrong here
Governor limits such as DML statement counts cannot be increased via configuration changes in the Setup menu. These are hard limits imposed by the platform to protect multi-tenant performance. The only solution is to refactor the code to adhere to the platform's architectural standards for scalable data management.
Visual reference
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Salesforce exam blueprint
This SF-Data-Arch practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SF-Data-Arch exam.