PL-300 Prepare the data Practice Question
You are a data analyst at a retail company. You have a Power BI semantic model that imports sales data from an Azure SQL Database. The database uses a timestamp column to track transaction time. You need to reduce the data refresh time and ensure that only the last 30 days of data are refreshed during each scheduled refresh. You have already created the necessary parameters rangeStart and rangeEnd in Power Query. What should you do next to implement incremental refresh?
⚠ Common exam trap
A common mix-up: candidates confuse filtering in Power Query Editor with setting an incremental refresh policy, not realizing that only the latter creates the partitioned refresh behavior required to reduce data refresh time.
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
✓
In Power BI Desktop, on the model view, select the table and set the incremental refresh policy.
Incremental refresh policies are defined in Power BI Desktop on the model view, not in the service or by simply filtering in Power Query. After creating the rangeStart and rangeEnd parameters, you must select the table in the Model view, open the incremental refresh policy dialog, and configure the policy to filter data based on those parameters, ensuring only the last 30 days are refreshed.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
In the Power BI service, go to the dataset settings and configure the scheduled refresh.
Why it's wrong here
Configuring a scheduled refresh in the dataset settings of the Power BI service only determines how often and at what time an existing refresh process runs; it does not establish any date-partitioning or incremental logic. Incremental refresh relies on a policy defined in Desktop's model metadata, not on the service refresh schedule, and without that policy the service will perform a full refresh of the entire table. Setting the schedule here cannot define which rows to load or which historical partitions to preserve, so this option cannot achieve incremental refresh.
- ✗
In Power Query Editor, apply the rangeStart and rangeEnd filters to the data and then close and apply.
Why it's wrong here
In Power Query Editor, creating rangeStart and rangeEnd parameters and filtering rows is a typical prerequisite for testing an incremental refresh, but applying a filter only produces a single static load of data. The actual incremental refresh behavior is controlled by a separate policy configured in the Model view table properties, where Power BI stores the partition structure and the refresh dates. If you skip that model-level policy, the service will not know to incrementally process only new or changed periods, so the query filter alone is insufficient.
- ✗
In the Power BI service, create a new refresh schedule and set the incremental refresh period.
Why it's wrong here
The Power BI service's refresh schedule dialog only lets you set the frequency, time zone, and failure notifications; it contains no controls for defining an incremental refresh period or range. An incremental refresh period is a property of the dataset model, set on a table's properties in Power BI Desktop's Model view, and the service simply honors it during a scheduled refresh. Creating a schedule cannot retroactively add an incremental refresh policy, so this action still results in a full refresh unless the policy exists in the model.
- ✓
In Power BI Desktop, on the model view, select the table and set the incremental refresh policy.
Why this is correct
In Power BI Desktop, selecting the table in Model view opens the Properties pane, where the Incremental refresh control lets you define the archive period, the incremental period, and the RangeStart/RangeEnd parameters. This policy is saved into the data model and, after publishing, the Power BI service uses it to create date-based partitions and refresh only the partitions that fall within the incremental window. This is the intended, supported way to establish incremental refresh.
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