The answer is using surrogate keys in dimension tables to link to fact tables and adopting a star schema design. These are best practices for Power BI data model design because a star schema reduces data redundancy and query complexity by separating descriptive attributes into dimension tables, while surrogate keys provide a stable, integer-based link that avoids performance issues from natural keys. On the Microsoft Power BI Data Analyst PL-300 exam, this concept tests your understanding of dimensional modeling fundamentals, often appearing in questions that ask you to identify efficient model structures versus common pitfalls like bi-directional cross-filtering or storing full names in fact tables. A frequent trap is assuming calculated columns are as efficient as Power Query transformations, but the exam emphasizes that M-code-based steps are preferable. Remember the mnemonic “Star with Surrogates” to recall that a star schema paired with surrogate keys ensures optimal performance and clarity.
PL-300 Model the data Practice Question
This PL-300 practice question tests your understanding of model 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 TWO of the following are best practices for designing a Power BI data model?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use a star schema to reduce model complexity.
Options A and D are correct. Option A: Using a star schema reduces complexity. Option D: Using surrogate keys improves performance and stability. Option B is wrong because bi-directional cross-filtering can cause ambiguity. Option C is wrong because storing full names in the fact table increases size. Option E is wrong because calculated columns are less efficient than Power Query.
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 a star schema to reduce model complexity.
Why this is correct
Star schema is the recommended design.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✓
Use surrogate keys in dimension tables to link to fact tables.
Why this is correct
Surrogate keys ensure stable relationships.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Store dimension attributes directly in fact tables for faster queries.
Why it's wrong here
This increases model size and violates normalization.
✗
Enable bi-directional cross-filtering on all relationships.
Why it's wrong here
Bi-directional filtering can cause performance issues and ambiguity.
✗
Create calculated columns instead of Power Query transformations when possible.
Why it's wrong here
Power Query is more efficient for data transformation.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which PL-300 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Model the data — This question tests Model the data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use a star schema to reduce model complexity. — Options A and D are correct. Option A: Using a star schema reduces complexity. Option D: Using surrogate keys improves performance and stability. Option B is wrong because bi-directional cross-filtering can cause ambiguity. Option C is wrong because storing full names in the fact table increases size. Option E is wrong because calculated columns are less efficient than Power Query.
What should I do if I get this PL-300 question wrong?
Identify which PL-300 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Which TWO of the following are best practices for designing a data model in Power BI?
easy
A.Use calculated columns to perform all transformations.
B.Set all relationships to bidirectional cross-filtering to avoid ambiguity.
✓ C.Use surrogate keys (integer IDs) for relationships instead of natural keys.
D.Reference other queries as a single source to avoid duplication.
✓ E.Design the model with a star schema layout (fact and dimension tables).
Why C: Option C is correct because using surrogate keys (integer IDs) instead of natural keys improves relationship performance and reduces storage overhead. Integer joins are faster than string or composite key joins, and surrogate keys avoid issues with changing natural key values, ensuring referential integrity and stable model relationships.
Variation 2. Which THREE of the following are best practices for designing a Power BI data model?
hard
A.Use composite keys in relationships for better performance
B.Enable bidirectional cross-filtering by default
✓ C.Implement business logic in measures rather than calculated columns
✓ D.Use a star schema design with dimension and fact tables
✓ E.Use surrogate keys for dimension tables
Why C: Options A, C, and E are correct. A star schema is recommended. Relationships should be based on surrogate keys. Business logic should be in measures. Option B is wrong because composite keys are not recommended; use surrogate keys. Option D is wrong because bidirectional filtering is used sparingly, not by default.
Variation 3. Which TWO of the following are best practices when designing a Power BI data model?
medium
A.Use calculated columns instead of measures
✓ B.Use a star schema design
C.Denormalize all tables into a single flat table
D.Use bidirectional relationships as default
✓ E.Hide foreign key columns from report view
Why B: Options A and D are correct. Option B is wrong because calculated columns should be avoided when possible; measures are preferred. Option C is wrong because bidirectional relationships can cause ambiguity and should be used sparingly. Option E is wrong because star schema is the recommended approach.
Variation 4. Which TWO of the following are best practices for designing a star schema in Power BI?
medium
✓ A.Dimension tables should have a primary key and descriptive columns.
B.Fact tables should contain calculated columns for business logic.
✓ C.Fact tables should have foreign keys that relate to dimension tables.
D.Merge all tables into a single flat table for simplicity.
E.Use many-to-many relationships between fact and dimension tables.
Why A: Option A is correct because dimension tables in a star schema are designed to store descriptive attributes (e.g., product name, category) and must have a primary key column that uniquely identifies each row. This primary key is referenced by foreign keys in fact tables, enabling efficient filtering and slicing in Power BI. Without a primary key, relationships cannot be properly enforced, leading to ambiguous or incorrect query results.
Variation 5. Which THREE of the following are best practices when designing a Power BI data model for performance?
✓ C.Use star schema design with dimension and fact tables.
D.Use many-to-many relationships directly without bridge tables.
E.Use calculated columns instead of measures for aggregations.
Why A: Options A, C, and D are correct. Star schema design (A) reduces complexity. Avoiding bi-directional cross-filtering (C) prevents performance degradation. Hiding unnecessary columns (D) reduces model size and improves clarity. Option B is incorrect because calculated columns are generally slower than measures for dynamic calculations. Option E is incorrect because using many-to-many relationships without bridge tables can cause ambiguity and poor performance.
Variation 6. Which TWO of the following are best practices when designing star schemas in Power BI? (Select two.)
medium
✓ A.Store numeric measures in fact tables.
B.Use calculated columns in fact tables for row-level security.
✓ C.Place descriptive attributes in dimension tables.
D.Include many columns in fact tables for filtering.
E.Normalize dimension tables to reduce redundancy.
Why A: Option A is correct because fact tables in a star schema are designed to store quantitative, numeric measures (e.g., sales amount, quantity) that can be aggregated. This aligns with the star schema principle of separating measures (facts) from descriptive context (dimensions), enabling efficient compression and fast aggregations in Power BI's VertiPaq engine.
Variation 7. Which THREE are best practices for designing a star schema in Power BI?
medium
✓ A.Create a separate date dimension table
B.Create multiple relationships between fact and dimension
✓ C.Use surrogate keys for dimension tables
✓ D.Store measures in fact tables at the lowest grain
E.Use composite keys in fact tables
Why A: Options A, C, and D are correct. Descriptive keys, separate date dimension, and aggregations at grain are best practices. Option B is wrong because natural keys are preferred when available. Option E is wrong because multiple relationships complicate the model.
Last reviewed: Jun 21, 2026
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