The answer is that the three factors to consider when designing a star schema in Power BI are ensuring relationships are one-to-many from dimension to fact, using dimension tables for descriptive attributes, and storing numeric, aggregatable measures in fact tables. This structure is correct because a star schema separates business processes (facts) from their descriptive context (dimensions), allowing Power BI to efficiently compress and query data by filtering on dimension columns and aggregating measures like sales amount or quantity. On the PL-300 exam, this question tests your understanding of foundational data modeling principles, often appearing as a scenario where you must identify which design choices support optimal performance and accurate DAX calculations. A common trap is confusing fact tables with dimension tables or assuming many-to-many relationships are standard; remember that fact tables are long and skinny with foreign keys, while dimensions are short and wide with unique keys. Memory tip: think of a star’s center (fact) holding numbers, and its points (dimensions) holding labels—always one-to-many from the points to the center.
PL-300 Visualize and analyze the data Practice Question
This PL-300 practice question tests your understanding of visualize and analyze the data. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which THREE factors should you consider when designing a Power BI data model for a star schema? (Select three.)
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 numeric measures and foreign keys
Option B is correct because fact tables in a star schema store numeric, aggregatable measures (e.g., sales amount, quantity) and foreign keys that reference dimension tables. This structure enables efficient summarization and slicing by dimensions, which is a core requirement for Power BI performance and DAX calculations.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Use many-to-many relationships between dimensions
Why it's wrong here
Many-to-many relationships are complex and not typical in star schemas.
✓
Fact tables should contain numeric measures and foreign keys
Why this is correct
Fact tables store quantitative data and relationships to dimensions.
Related concept
Read the scenario before looking for a memorised answer.
✗
Dimension tables should be normalized to reduce redundancy
Why it's wrong here
Star schemas denormalize dimensions for performance.
✓
Dimension tables should contain descriptive attributes
Why this is correct
Dimension tables store descriptive information for filtering and grouping.
Related concept
Read the scenario before looking for a memorised answer.
✓
Relationships should be one-to-many from dimension to fact
Why this is correct
Star schemas use one-to-many relationships between dimensions and facts.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Microsoft often tests the misconception that normalization (Option C) is beneficial for star schemas, when in fact denormalization is preferred to avoid performance penalties from extra join hops in Power BI's query engine.
Detailed technical explanation
How to think about this question
In Power BI, a star schema optimizes VertiPaq compression by storing dimension attributes as low-cardinality columns, which reduces memory usage and speeds up filter propagation. Fact tables with foreign keys and numeric measures allow Power BI to use its columnar storage engine to aggregate data without scanning entire tables, a key advantage over normalized snowflake designs that require multiple join operations.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Visualize and analyze the data — This question tests Visualize and analyze the data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Fact tables should contain numeric measures and foreign keys — Option B is correct because fact tables in a star schema store numeric, aggregatable measures (e.g., sales amount, quantity) and foreign keys that reference dimension tables. This structure enables efficient summarization and slicing by dimensions, which is a core requirement for Power BI performance and DAX calculations.
What should I do if I get this PL-300 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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