PL-300 Deploy and maintain assets Practice Question
You are a Power BI administrator for a large organization. A team has published a shared dataset to a Premium workspace. They use an XMLA endpoint to programmatically refresh the dataset daily. Recently, the refresh started failing with the error: 'The operation was canceled because the session was terminated by a concurrent operation.' The dataset is not partitioned. You need to ensure the refresh completes without errors. What should you do?
⚠ Common exam trap
It's easy for candidates to assume the error is caused by the XMLA script itself (e.g., frequency or scheduling) and overlook the fact that the conflict is due to concurrent operations, which is directly solved by enabling conflict detection rather than changing the script's schedule or partitioning strategy.
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
✓
Enable the 'Refresh conflict detection' setting on the dataset to prevent concurrent operations.
The error 'The operation was canceled because the session was terminated by a concurrent operation' indicates that two refresh operations are conflicting on the same dataset. Enabling 'Refresh conflict detection' on the dataset prevents concurrent refreshes by queuing or blocking overlapping operations, ensuring the XMLA-triggered refresh completes without interruption.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Remove all scheduled refreshes and rely solely on the XMLA script.
Why it's wrong here
Removing all scheduled refreshes and relying solely on the XMLA script does not solve the underlying concurrency problem, because the XMLA script itself can be invoked from multiple sessions or by multiple automated jobs at the same time. The error occurs when two refresh requests overlap, and any source—scheduled or XMLA—can trigger that overlap. Furthermore, eliminating scheduled retrievals would degrade data freshness without addressing the root cause of lock conflicts.
- ✓
Enable the 'Refresh conflict detection' setting on the dataset to prevent concurrent operations.
Why this is correct
Enabling the 'Refresh conflict detection' setting on the dataset is the native solution for this scenario. In Power BI Premium, this setting detects when a second refresh request arrives while a refresh is already executing, and it blocks the conflicting request instead of allowing them to overlap. This eliminates the 'refresh already in progress' error while keeping both the scheduled and XMLA refresh workflows intact.
- ✗
Change the XMLA script to run less frequently, e.g., once per week.
Why it's wrong here
Lowering the refresh frequency to once per week does not prevent the error, because concurrency conflicts are not about how often refreshes occur, but about whether two executions touch the same model at the exact same instant. Even a weekly XMLA script can collide with a scheduled refresh or another ad-hoc run that happens to be in progress. This approach also compromises data freshness, so it is not a viable resolution.
- ✗
Partition the dataset and refresh partitions sequentially.
Why it's wrong here
Partitioning the dataset and refreshing partitions sequentially addresses performance and ingestion granularity, not the dataset-level concurrency conflict. In Power BI, a dataset (or a table) still has only one refresh process at a time, and separate XMLA refresh commands submitted concurrently will each try to acquire the same model lock. Sequential partition refreshes do not coordinate with other independent refresh sessions, so the error can still occur.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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