- A
Create a separate date dimension table and mark it as a date table.
A date table is required for proper time intelligence and filter context.
- B
Connect the Sales table to Product and Store tables using relationships with many-to-one cardinality.
Star schema design uses dimension tables connected to fact tables via many-to-one relationships.
- C
Add calculated columns for year, month, and quarter to the Sales table.
Why wrong: Calculated columns in the fact table are inefficient; use a date dimension table instead.
- D
Create relationships between tables using the foreign key columns.
Why wrong: Relationships should be based on primary keys in dimension tables, not foreign keys.
- E
Combine all data into a single flat table to simplify the model.
Why wrong: A flat table leads to redundancy and poor performance; star schema is preferred.
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.
You are designing a Power BI semantic model for a retail company. The model must support reporting on sales by product, store, and date. You need to decide on the modeling approach. Which TWO actions should you take? (Select exactly two.)
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
Create a separate date dimension table and mark it as a date table.
Option A is correct because creating a separate date dimension table and marking it as a date table enables time intelligence functions (e.g., TOTALYTD, SAMEPERIODLASTYEAR) to work correctly in DAX. This also ensures that the date column is recognized as a continuous date hierarchy, allowing proper filtering and slicing by year, month, and quarter across all fact 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.
- ✓
Create a separate date dimension table and mark it as a date table.
Why this is correct
A date table is required for proper time intelligence and filter context.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Connect the Sales table to Product and Store tables using relationships with many-to-one cardinality.
Why this is correct
Star schema design uses dimension tables connected to fact tables via many-to-one relationships.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Add calculated columns for year, month, and quarter to the Sales table.
Why it's wrong here
Calculated columns in the fact table are inefficient; use a date dimension table instead.
- ✗
Create relationships between tables using the foreign key columns.
Why it's wrong here
Relationships should be based on primary keys in dimension tables, not foreign keys.
- ✗
Combine all data into a single flat table to simplify the model.
Why it's wrong here
A flat table leads to redundancy and poor performance; star schema is preferred.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often think adding calculated columns for date parts directly to the fact table is acceptable, but Microsoft explicitly tests the requirement for a separate, marked date table to enable time intelligence and maintain a proper star schema.
Detailed technical explanation
How to think about this question
In Power BI, marking a date table as a date table (via Table tools > Mark as date table) sets the table's date column as the model's primary date column, which is required for time intelligence DAX functions that rely on a continuous date range. The relationships between Sales and dimension tables should use many-to-one cardinality with a single cross-filter direction (from dimension to fact) to ensure proper aggregation and avoid ambiguous filter propagation. Under the hood, Power BI's VertiPaq engine optimizes storage and query performance when star schema design is used, as dimension tables are compressed and sorted for fast lookups.
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: Create a separate date dimension table and mark it as a date table. — Option A is correct because creating a separate date dimension table and marking it as a date table enables time intelligence functions (e.g., TOTALYTD, SAMEPERIODLASTYEAR) to work correctly in DAX. This also ensures that the date column is recognized as a continuous date hierarchy, allowing proper filtering and slicing by year, month, and quarter across all fact 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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jun 11, 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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