- A
Dimension tables should use natural keys instead of surrogate keys for better performance.
Why wrong: Surrogate keys are preferred as they are stable and perform better.
- B
Role-playing dimensions should be implemented by creating multiple dimension tables or using views.
Role-playing dimensions (e.g., OrderDate, ShipDate) need separate tables or views to function correctly.
- C
Fact tables should contain numeric measures and foreign keys to dimension tables.
Fact tables store measurements and connect to dimensions via foreign keys.
- D
Date dimensions should be created to enable time intelligence calculations.
A date dimension is essential for time-based analysis.
- E
Dimensions should be normalized (snowflaked) to reduce data redundancy.
Why wrong: Star schema denormalizes dimensions for better query performance; snowflaking is discouraged.
Quick Answer
The answer is that date dimensions should be created to enable time intelligence calculations, along with ensuring role-playing dimensions are properly handled and that dimension tables are connected to fact tables via surrogate keys. This is correct because a star schema in Power BI relies on a central fact table surrounded by conformed dimensions; when a single date dimension needs to serve multiple roles—like Order Date, Ship Date, and Due Date—you must create separate dimension tables or use calculated tables to maintain unique foreign key relationships, which is essential for accurate time-based measures like year-over-year growth. On the PL-300 exam, this tests your understanding of model relationships and DAX time intelligence functions, often appearing as a scenario where a single date table is incorrectly reused across multiple date columns, leading to ambiguous filters. A common trap is assuming Power BI can automatically handle multiple date references from one table, but the engine requires distinct dimension instances for each role. Memory tip: think "one date table, many roles—clone the table, not the column."
PL-300 Prepare the data Practice Question
This PL-300 practice question tests your understanding of prepare 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 considerations are important when designing a star schema for a Power BI semantic model? (Choose 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
Role-playing dimensions should be implemented by creating multiple dimension tables or using views.
Option B is correct because role-playing dimensions, such as a Date dimension used for Order Date, Ship Date, and Due Date, require multiple references to the same dimension table. In Power BI, you implement this by creating multiple dimension tables (e.g., via calculated tables or referencing the same source table) or using database views to provide unique foreign key relationships, enabling correct time intelligence and filtering.
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.
- ✗
Dimension tables should use natural keys instead of surrogate keys for better performance.
Why it's wrong here
Surrogate keys are preferred as they are stable and perform better.
- ✓
Role-playing dimensions should be implemented by creating multiple dimension tables or using views.
Why this is correct
Role-playing dimensions (e.g., OrderDate, ShipDate) need separate tables or views to function correctly.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Fact tables should contain numeric measures and foreign keys to dimension tables.
Why this is correct
Fact tables store measurements and connect to dimensions via foreign keys.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Date dimensions should be created to enable time intelligence calculations.
Why this is correct
A date dimension is essential for time-based analysis.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Dimensions should be normalized (snowflaked) to reduce data redundancy.
Why it's wrong here
Star schema denormalizes dimensions for better query performance; snowflaking is discouraged.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume natural keys are better for readability or that snowflaking is acceptable for reducing redundancy, but the PL-300 exam emphasizes that star schemas with surrogate keys and denormalized dimensions are optimal for Power BI performance and DAX time intelligence.
Detailed technical explanation
How to think about this question
In Power BI's VertiPaq in-memory engine, surrogate keys (typically 4-byte integers) enable efficient dictionary encoding and high-compression column storage, whereas natural keys (e.g., strings or composite keys) bloat the dictionary and slow down filtering. Role-playing dimensions are handled by creating multiple copies of the dimension table (e.g., 'Date' as 'OrderDate', 'ShipDate') because a single table cannot have multiple active relationships to the same fact table; Power BI only allows one active relationship per pair of tables, so additional inactive relationships or duplicate tables are required for time intelligence functions like TOTALYTD to work correctly.
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
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this PL-300 question test?
Prepare the data — This question tests Prepare the data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Role-playing dimensions should be implemented by creating multiple dimension tables or using views. — Option B is correct because role-playing dimensions, such as a Date dimension used for Order Date, Ship Date, and Due Date, require multiple references to the same dimension table. In Power BI, you implement this by creating multiple dimension tables (e.g., via calculated tables or referencing the same source table) or using database views to provide unique foreign key relationships, enabling correct time intelligence and filtering.
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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Last reviewed: Jun 24, 2026
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.
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