PL-300 Prepare the data Practice Question
You are importing data from a SQL Server view into Power BI. The view contains calculated columns that are expensive to compute. You want to minimize the load on the source database during refresh. What should you do?
⚠ Common exam trap
Watch out — candidates often assume pushing transformations to the source (via query folding or native SQL) is always more efficient, but the question specifically asks to minimize load on the source database, making offloading to Power Query the correct choice.
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
✓
Import the raw data and perform transformations in Power Query.
Importing raw data and performing transformations in Power Query offloads the computational burden from the SQL Server source to Power BI's mashup engine. This minimizes load on the source database during refresh, as expensive calculated columns are not executed on SQL Server. Power Query can apply transformations after the data is extracted, reducing the need for server-side processing.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Import the raw data and perform transformations in Power Query.
Why this is correct
By importing raw data, you offload transformation work to Power BI's mashup engine, which leverages Power Query's in-memory and streaming capabilities. This avoids pushing compute-intensive operations to SQL Server, preserving database resources for other workloads. Additionally, Power Query's step-based transformations are highly maintainable and can be refreshed on a schedule.
- ✗
Enable query folding to push transformations to SQL Server.
Why it's wrong here
While query folding generally improves performance for large datasets by letting SQL Server do the heavy lifting, in this scenario you specifically want to minimize load on the source database. Pushing transformations through folding executes them on SQL Server, consuming CPU and I/O, which contradicts the goal of reducing source load. Also, not all transformations can be folded, so some may still run in Power Query.
- ✗
Use a native SQL query in Power Query to perform calculations.
Why it's wrong here
Writing a native SQL query inside Power Query forces the entire calculation to execute on SQL Server, bypassing the folding optimizer and preventing Power Query from applying any downstream optimizations. This approach can also harm performance if the query is not properly optimized, and it tightly couples your data model to SQL Server-specific syntax. It inherently increases load on the source, which is the opposite of the recommended approach.
- ✗
Create a materialized view in SQL Server with the calculations.
Why it's wrong here
Materialized views (indexed views) require ongoing maintenance and storage on SQL Server, and their creation triggers processing that consumes database resources. While they can speed up eventual queries, they do not reduce initial load — the view must be built, indexed, and kept in sync with base tables. This shifts processing to the source rather than to Power BI, which contradicts the goal of offloading work.
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This PL-300 practice question is part of Courseiva's free Microsoft 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 PL-300 exam.