PL-300 Model the data Practice Question
Which THREE factors should you consider when designing a star schema for a Power BI semantic model? (Select three.)
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
✓
Fact tables should contain measures and foreign keys to dimension tables.
The correct factors are: Fact tables should contain measures and foreign keys to dimension tables (A). Dimension tables should contain descriptive attributes and be denormalized (B). Avoid creating many-to-many relationships between dimensions; instead, use a bridge table when necessary (E). Option C is incorrect because fact tables should not be normalized; they should be denormalized to improve query performance. Option D is incorrect because calculated columns in dimension tables can increase model size and processing time; they are better placed as measures or in the fact table.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Fact tables should contain measures and foreign keys to dimension tables.
Why this is correct
This is the core of star schema design.
- ✓
Dimension tables should contain descriptive attributes and be denormalized.
Why this is correct
Denormalized dimensions reduce the number of joins and improve query performance.
- ✗
Fact tables should be normalized to reduce data duplication.
Why it's wrong here
Normalization is not typical for fact tables in star schema.
- ✗
Use calculated columns in dimension tables to derive new attributes.
Why it's wrong here
Calculated columns increase model size and refresh time.
- ✓
Avoid creating many-to-many relationships between dimensions.
Why this is correct
They complicate the model and can cause performance issues.
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