PL-300 Prepare the data Practice Question
Which THREE factors should you consider when designing an incremental refresh policy for a large fact table in Power BI?
⚠ Common exam trap
Many exam-takers assume incremental refresh requires a cloud source or DirectQuery mode, but Power BI's incremental refresh is designed for Import mode and works with any supported data source that provides a date/time column for filtering.
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 refresh policy must consider the data warehouse's maintenance windows
Option C is correct because an incremental refresh policy must be scheduled so that its refresh windows do not collide with the data warehouse's maintenance windows, since the source must be available and consistent when Power BI queries it for new or changed partitions. Option D is correct because incremental refresh works by partitioning the table in the Power BI model (typically by RangeStart/RangeEnd parameters on a date column), so only the newest partitions are refreshed while historical partitions are retained. Option E is correct because incremental refresh requires a date or datetime column in the source table to filter and define the partition boundaries; without it, Power BI cannot determine which rows are new or changed. Option A is not required, since incremental refresh is supported for Import mode (and DirectQuery is not a prerequisite). Option B is not required, as the source can be an on-premises database accessed via a data gateway, not only a cloud database.
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 table must be configured for DirectQuery mode
Why it's wrong here
Incremental refresh is a feature that only works when a table is loaded into memory using Import mode, because the refresh engine must physically reload data into the Power BI dataset. DirectQuery mode does not store a copy of the data, so there are no partitions to create or refresh; queries are sent live to the source. Therefore, configuring the table for DirectQuery would make incremental refresh impossible, making this option incorrect.
- ✗
The source data must be stored in a cloud database
Why it's wrong here
A cloud database is not a prerequisite for incremental refresh. The feature works with any source that supports filtering by date range, including on-premises databases like SQL Server, as long as a data gateway is installed and the source can handle query folding. The key requirements are a date column and a storage mode of Import, not the location of the source. Thus, requiring cloud storage is incorrect.
- ✓
The refresh policy must consider the data warehouse's maintenance windows
Why this is correct
Scheduling the refresh policy must align with the data warehouse's maintenance windows to avoid failures. During maintenance, the source database may be unavailable, have locked tables, or experience degraded performance, which can cause the incremental refresh to time out or return incomplete data. By scheduling refreshes outside these windows, you ensure source connectivity and consistent data loads, making this a valid design consideration.
- ✓
The table must be partitioned in the Power BI model
Why this is correct
Power BI's incremental refresh policy works by automatically partitioning the destination table in the model, usually by time periods such as days or months. When you configure the policy, you define how far back to load historical data and what range to refresh each time; these ranges become partitions. Because only changed partitions are re-queried, considering how these partitions are structured in the Power BI model is essential for efficient refresh performance, so this is a correct factor.
- ✓
The source table must include a date or datetime column for filtering
Why this is correct
Incremental refresh relies on the source table containing a column of data type date or datetime, which is used to split the data into ranges between the RangeStart and RangeEnd parameters. Without such a column, Power BI cannot determine which rows belong to which partition, and the entire table would have to be reloaded. Because this column drives the entire filtering and partition creation process, it must be present in the source data, making this option correct.
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