PL-300 Deploy and maintain assets Practice Question
You manage a Power BI deployment that uses deployment pipelines. After promoting content from Development to Test, you notice that the Test workspace dataset uses a different data source than expected. What is the most likely reason?
⚠ Common exam trap
A common mix-up: candidates confuse data source credentials with data source parameters, assuming that credential issues cause the wrong data source to appear, when in fact parameters control the actual connection string, while credentials only handle authentication after the connection is established.
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
✓
The dataset parameters were not configured in the deployment pipeline rules.
Deployment pipeline rules allow you to configure dataset parameters (such as data source paths) to differ between pipeline stages. If these rules are not set, the dataset retains the data source configuration from the source stage (Development), causing the Test workspace to use an unexpected data source. The pipeline deploys the dataset artifact, but without parameter overrides, the data source connection string remains unchanged.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The pipeline didn't deploy the dataset because it was already in Test.
Why it's wrong here
A deployment pipeline does not check whether an item already exists in the target workspace and then decide to skip it; every deployment copies all selected items from the source stage to the target stage and overwrites matching artifacts. Even if the Test workspace already contained a dataset with the same name, the pipeline would replace it with the version from the source stage. Thus, 'already in Test' would never prevent a dataset from being deployed.
- ✗
The data source credentials were not applied during deployment.
Why it's wrong here
Data source credentials are stored as workspace-level datasource settings and are not part of the deployment pipeline's content payload, so they cannot change a dataset's connection path. The symptom of a wrong data source points to the dataset's server/database properties, which are controlled by dataset parameters. Configuring credentials would only authenticate against whatever source the dataset already references; it would not redirect the dataset to the Test environment's data source.
- ✓
The dataset parameters were not configured in the deployment pipeline rules.
Why this is correct
Dataset parameters, such as server name or database name, can be overridden per stage using deployment pipeline rules. If no rule is configured for the relevant parameter, Test inherits the parameter values from Development, causing the dataset to keep pointing to the Dev data source. Creating a parameter rule that assigns the Test SQL server/database value for that parameter is the required fix. Without this rule, the pipeline will successfully deploy the dataset but still reference the wrong environment.
- ✗
The Test workspace has a separate dataset that was manually created.
Why it's wrong here
A manually created dataset in the Test workspace would be overwritten during a pipeline deployment, because the pipeline pushes the source item and replaces the target item of the same name. The presence of a separate dataset does not stop deployment or cause the deployed dataset to connect to the wrong server. This explanation confuses an unrelated workspace artifact with the actual root cause, which is a parameter configuration gap in the pipeline rules.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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