SF-Data-Arch Data Migration Practice Question
Exhibit
{
"operation": "insert",
"object": "Account",
"concurrencyMode": "Parallel",
"contentType": "CSV"
}Refer to the exhibit. Why might 'Parallel' concurrency mode cause errors during a large migration?
⚠ Common exam trap
Candidates often confuse parallel mode performance benefits with safety, assuming it prevents errors. They overlook how simultaneous processing of child records tied to identical parents triggers record locking contentions during high-volume data migrations.
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
✓
It leads to record locking contention on parent objects.
Refer to the exhibit. The JSON configuration shows a Bulk API 2.0 job using 'Parallel' concurrency mode. The Data Architect must be aware that parallel processing increases the risk of record locking when parent records have many children being processed simultaneously. This configuration requires careful monitoring of record contention to prevent failures, even though it provides the fastest throughput for independent records.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
It causes the API to exceed the daily limit for API calls.
Why it's wrong here
Parallel mode does not consume more API calls than serial mode; it only changes how the processing is distributed across the platform's resources. The number of calls is determined by the number of records and the batch size, not the concurrency setting used for the job.
- ✓
It leads to record locking contention on parent objects.
Why this is correct
Parallel processing attempts to update records as fast as possible. If multiple threads attempt to update or insert child records that share the same parent, they will contend for the parent record lock, resulting in 'UNABLE_TO_LOCK_ROW' errors that can stop the migration process.
- ✗
It prevents the data from being loaded in a specific order.
Why it's wrong here
While parallel mode does not guarantee order, this is rarely the cause of record-level errors. Most migrations are designed to be order-independent. The real issue with parallel mode in high-volume environments is resource contention, not the loss of sequence during the asynchronous job execution.
- ✗
It forces the data to be processed in a single thread.
Why it's wrong here
Parallel mode explicitly enables multi-threaded processing. The claim that it forces single-threaded execution is factually incorrect. Single-threaded processing occurs in serial mode, which is slower but eliminates the risk of record locking contention, which is why it is used for complex, highly relational data loads.
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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.