The answer is to create a one-to-many relationship from Product to Sales. This configuration is correct because it establishes a standard star schema, where the smaller Product dimension table (10,000 rows) filters the larger Sales fact table (10 million rows) efficiently. Power BI’s VertiPaq engine leverages this one-to-many relationship to push filters from the “one” side to the “many” side, optimizing query performance through in-memory columnar compression and automatic aggregations. On the Microsoft Power BI Data Analyst PL-300 exam, this scenario tests your understanding of cardinality and direction in data modeling—a common trap is reversing the relationship or creating a many-to-many link, which degrades performance. Remember the memory tip: “One side filters, many side stores”—always point the relationship from the unique dimension to the repeating fact table for speed.
PL-300 Model the data Practice Question
This PL-300 practice question tests your understanding of model the data. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
You are designing a Power BI data model that includes a table named Sales with 10 million rows. You need to create a relationship between Sales and a Product dimension table. The Product table has 10,000 rows. Which configuration will provide the best query performance?
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
✓
Create a one-to-many relationship from Product to Sales
Option B is correct because a one-to-many relationship from Product (the dimension table with unique values) to Sales (the fact table with many rows) is the standard star schema design. This configuration allows Power BI to use the smaller Product table to filter the larger Sales table efficiently, leveraging in-memory columnar storage and automatic aggregations for optimal query performance.
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.
✗
Create a many-to-one relationship from Sales to Product
Why it's wrong here
While functional, this direction is less intuitive and may cause filter propagation issues in complex models.
✓
Create a one-to-many relationship from Product to Sales
Why this is correct
This is the standard cardinality for dimension-to-fact relationships, optimized for performance.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Do not create a relationship; use LOOKUPVALUE in measures
Why it's wrong here
Avoiding relationships would require manual lookups, which are slower and less maintainable.
✗
Create a relationship with cross filter direction set to Both
Why it's wrong here
Setting cross filter to Both can degrade performance and create ambiguity.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the direction of the relationship arrow, thinking the 'many' side should be the source, but Power BI requires the dimension table (unique values) to be on the 'one' side for correct filter propagation and optimal performance.
Detailed technical explanation
How to think about this question
Under the hood, Power BI's VertiPaq engine stores each column as a compressed, sorted, and indexed segment. A one-to-many relationship from Product to Sales allows the engine to use the Product table's key as a filter that directly maps to the Sales table's foreign key via hash joins, minimizing data movement. In real-world scenarios, this design also enables proper use of DAX functions like SUMX and CALCULATE, which rely on relationship direction for context transition, and avoids the cardinality mismatch that can lead to slow query plans.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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.
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: Create a one-to-many relationship from Product to Sales — Option B is correct because a one-to-many relationship from Product (the dimension table with unique values) to Sales (the fact table with many rows) is the standard star schema design. This configuration allows Power BI to use the smaller Product table to filter the larger Sales table efficiently, leveraging in-memory columnar storage and automatic aggregations for optimal query performance.
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.
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. You are reviewing the relationships in a Power BI data model as shown in the exhibit. The model has tables: Sales, Product, Customer, and Category. You need to evaluate the performance impact of the current configuration. Which relationship is most likely to cause performance issues?
hard
A.All relationships are equally efficient
B.The relationship between Sales and Customer
✓ C.The relationship between Product and Category
D.The relationship between Sales and Product
Why C: The relationship between Product and Category is most likely to cause performance issues because it is a many-to-many relationship without a bridge table. In Power BI, many-to-many relationships require the engine to materialize cross-join-like intermediate tables in memory, increasing query complexity and reducing performance. This is especially problematic when filtering or aggregating across these tables, as the VertiPaq engine must resolve ambiguity by creating additional internal tables.
Last reviewed: Jun 24, 2026
Question Discussion
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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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