PL-300 Prepare the data Practice Question
Which THREE of the following are best practices for optimizing data load performance in Power BI?
⚠ Common exam trap
Many candidates confuse 'splitting tables' (Option B) with star schema design best practices, but splitting a fact table unnecessarily violates dimensional modeling principles and harms performance, whereas proper star schema involves splitting dimensions from facts, not splitting facts themselves.
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
✓
Remove unnecessary columns and rows during the import process.
Removing unnecessary columns and rows during the import process reduces the amount of data loaded into the Power BI data model, which directly decreases memory usage and refresh time. By filtering out irrelevant data early in Power Query, you minimize the data volume that must be processed and stored, leading to faster load performance.
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 unnecessary columns and rows during the import process.
Why this is correct
Reducing data volume improves load time.
- ✗
Split a large fact table into multiple smaller fact tables.
Why it's wrong here
This can complicate the model and may not improve performance.
- ✓
Set data types correctly in Power Query to avoid type detection overhead.
Why this is correct
Proper data types improve load efficiency.
- ✗
Use DirectQuery mode instead of Import mode to reduce data load time.
Why it's wrong here
DirectQuery does not load data, but it is not always a performance best practice.
- ✓
Use query folding to push transformations to the source database.
Why this is correct
Query folding reduces data transfer.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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