Question 397 of 966

Model the data →hardMultiple ChoiceObjective-mapped

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.

Exhibit

Refer to the exhibit.
```json
{
  "relationships": [
    {
      "fromTable": "Sales",
      "fromColumn": "ProductID",
      "toTable": "Product",
      "toColumn": "ProductID",
      "crossFilteringBehavior": "oneDirection"
    },
    {
      "fromTable": "Sales",
      "fromColumn": "CustomerID",
      "toTable": "Customer",
      "toColumn": "CustomerID",
      "crossFilteringBehavior": "oneDirection"
    },
    {
      "fromTable": "Product",
      "fromColumn": "CategoryID",
      "toTable": "Category",
      "toColumn": "CategoryID",
      "crossFilteringBehavior": "both"
    }
  ]
}
```

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?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

Question 1hardmultiple choice

Full question →

Exhibit

Refer to the exhibit.
```json
{
  "relationships": [
    {
      "fromTable": "Sales",
      "fromColumn": "ProductID",
      "toTable": "Product",
      "toColumn": "ProductID",
      "crossFilteringBehavior": "oneDirection"
    },
    {
      "fromTable": "Sales",
      "fromColumn": "CustomerID",
      "toTable": "Customer",
      "toColumn": "CustomerID",
      "crossFilteringBehavior": "oneDirection"
    },
    {
      "fromTable": "Product",
      "fromColumn": "CategoryID",
      "toTable": "Category",
      "toColumn": "CategoryID",
      "crossFilteringBehavior": "both"
    }
  ]
}
```

A
All relationships are equally efficient
Why wrong: Bidirectional filtering is known to be less efficient than unidirectional.
B
The relationship between Sales and Customer
Why wrong: Unidirectional filtering is standard and performs well.
C
The relationship between Product and Category
Bidirectional filtering can lead to performance degradation and unintended filter propagation.
D
The relationship between Sales and Product
Why wrong: Unidirectional filtering is optimal and not likely to cause performance issues.

Full breakdown with real-world context →

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

✓

The relationship between Product and Category

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.

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.

✗
All relationships are equally efficient
Why it's wrong here
Bidirectional filtering is known to be less efficient than unidirectional.
✗
The relationship between Sales and Customer
Why it's wrong here
Unidirectional filtering is standard and performs well.
✓
The relationship between Product and Category
Why this is correct
Bidirectional filtering can lead to performance degradation and unintended filter propagation.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The relationship between Sales and Product
Why it's wrong here
Unidirectional filtering is optimal and not likely to cause performance issues.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often assume all relationships are equally performant if they are correctly defined, overlooking that many-to-many cardinality inherently requires more complex processing than one-to-many relationships.

Detailed technical explanation

How to think about this question

Under the hood, Power BI's VertiPaq engine stores many-to-many relationships by creating a hidden cross-join table that combines all matching rows from both sides, which can exponentially increase the number of rows processed during queries. This is distinct from one-to-many relationships, where the engine can use bitmap indexes and direct column lookups without materializing intermediate tables. In real-world scenarios, a many-to-many relationship between Product and Category (e.g., a product belonging to multiple categories) without a bridge table forces the engine to evaluate all combinations, leading to slower refresh times and sluggish report interactions.

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 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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this PL-300 question test?

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: The relationship between Product and Category — 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.

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: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

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

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