The answer is that orphaned foreign keys in the Sales table are causing the blank category in the visual. When ProductID values exist in the Sales table but have no matching entry in the Products table, the many-to-one relationship cannot resolve those rows, leaving CategoryID blank for those unmatched transactions. This is a classic data integrity issue where the fact table contains orphaned foreign keys, and it directly tests your understanding of relationship cardinality and cross-filtering on the PL-300 exam. A common trap is assuming the measure is broken, but the measure itself is correct—the visual simply cannot display a category for rows that have no product match. To remember this, think of the blank category as a “missing link” in your data model: if the foreign key has no home on the primary table, the visual will show a blank row.
PL-300 Model the data Practice Question
This PL-300 practice question tests your understanding of model the data. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
A data model contains a table 'Sales' with columns: Date, ProductID, Quantity, Amount. There is a 'Products' table with columns: ProductID, ProductName, CategoryID. A measure 'Total Sales' = SUM(Sales[Amount]) returns correct values. However, when a user creates a visual with CategoryID from 'Products' and 'Total Sales', some categories show blank. What is the most likely cause?
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.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
There are ProductID values in Sales that do not exist in Products table.
Option A is correct because when ProductID values in the Sales table do not have matching entries in the Products table, the relationship between the two tables will result in blank CategoryID values for those unmatched rows. In Power BI, a many-to-one relationship (the default) filters from the 'one' side (Products) to the 'many' side (Sales), but if a Sales row has a ProductID not present in Products, it cannot be matched, and any column from Products (like CategoryID) will appear as blank in visuals. This is a classic data integrity issue where the fact table contains orphaned foreign keys.
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.
✓
There are ProductID values in Sales that do not exist in Products table.
Why this is correct
This causes those rows to have no matching category, resulting in blank category in the visual.
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 'Total Sales' measure is not properly referencing the Sales table.
Why it's wrong here
The measure is correct and works; the issue is with the relationship.
✗
The relationship between Sales and Products is set to many-to-one, single direction.
Why it's wrong here
This is standard and should not cause blanks; it is the recommended configuration.
✗
The relationship is set to both directions (bidirectional).
Why it's wrong here
Bidirectional filtering does not cause blanks; it might cause duplicate results but not blanks.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume the relationship direction or cross-filter setting is the culprit, but the real issue is data integrity—orphaned foreign keys in the fact table—which is a common data modeling pitfall tested in the PL-300 exam.
Detailed technical explanation
How to think about this question
Under the hood, Power BI uses a star schema where the dimension table (Products) should contain all unique ProductID values referenced in the fact table (Sales). When orphaned keys exist, the relationship engine treats those rows as having no matching dimension record, resulting in blank values for any dimension attribute. This is often caused by data integration issues, such as incomplete product catalogs or historical sales of discontinued products. In a real-world scenario, you might use a 'Referential Integrity' assumption in Power BI (enforced via the relationship properties) to detect such mismatches, but the default behavior is to show blanks.
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.
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: There are ProductID values in Sales that do not exist in Products table. — Option A is correct because when ProductID values in the Sales table do not have matching entries in the Products table, the relationship between the two tables will result in blank CategoryID values for those unmatched rows. In Power BI, a many-to-one relationship (the default) filters from the 'one' side (Products) to the 'many' side (Sales), but if a Sales row has a ProductID not present in Products, it cannot be matched, and any column from Products (like CategoryID) will appear as blank in visuals. This is a classic data integrity issue where the fact table contains orphaned foreign keys.
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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Question Discussion
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