The answer is a many-to-one relationship with single cross-filter direction from Date to Sales. This configuration is optimal because it follows the star schema design principle where the Date table acts as a dimension filtering the fact table, ensuring that any slicer or filter on the Date table correctly limits the Sales data without unnecessary overhead. The single cross-filter direction prevents ambiguous filtering and avoids performance degradation from bi-directional cross-filtering, which is especially important given the date range mismatch—the Date table spans 2010 to 2025, but the Sales table only contains 2020 data. On the PL-300 exam, this scenario tests your understanding of relationship cardinality and filter propagation in a typical date dimension setup; a common trap is selecting bi-directional filtering, which can cause unexpected blank rows or slower queries. Remember the memory tip: “Date filters Sales, not the other way around”—keep the arrow pointing from the dimension to the fact for clean, efficient filtering.
PL-300 Prepare the data Practice Question
This PL-300 practice question tests your understanding of prepare 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 data model in Power BI. You have a 'Sales' table and a 'Date' table. The 'Sales' table has a 'SalesDate' column of type Date. You need to create a relationship between the tables, but the 'Date' table contains dates from 2010 to 2025, while the 'Sales' table only has data from 2020. Which type of relationship should you create to ensure optimal performance and correct filtering?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Many-to-one with single cross-filter direction from Date to Sales
Option B is correct because a many-to-one relationship with single cross-filter direction from Date to Sales ensures that filters applied to the Date table propagate to the Sales table, which is the standard star schema design. This configuration optimizes query performance by avoiding unnecessary bi-directional filtering and correctly handles the date range mismatch, as the Date table's larger range does not affect filtering of Sales data.
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.
✗
Many-to-one with bi-directional cross-filtering
Why it's wrong here
Bi-directional can lead to ambiguity and performance issues.
✓
Many-to-one with single cross-filter direction from Date to Sales
Why this is correct
Standard and efficient for filtering.
Related concept
Read the scenario before looking for a memorised answer.
✗
One-to-one (1:1)
Why it's wrong here
Not appropriate because multiple sales can occur on the same date.
✗
Many-to-many (M:M)
Why it's wrong here
This is not correct because each date in Date table corresponds to multiple sales but not vice versa.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume bi-directional filtering is needed for correct filtering, but in a star schema, single-direction filtering from the dimension to the fact table is both sufficient and optimal for performance.
Detailed technical explanation
How to think about this question
Under the hood, Power BI uses a storage engine (VertiPaq) that compresses and indexes data; a single-direction many-to-one relationship allows the engine to push filters efficiently from the dimension (Date) to the fact (Sales) without additional join overhead. In real-world scenarios, using bi-directional filtering on a large Date table can lead to unexpected row context and slower DAX measures, especially when the Date table contains future dates that do not exist in Sales.
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.
Prepare the data — This question tests Prepare the data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Many-to-one with single cross-filter direction from Date to Sales — Option B is correct because a many-to-one relationship with single cross-filter direction from Date to Sales ensures that filters applied to the Date table propagate to the Sales table, which is the standard star schema design. This configuration optimizes query performance by avoiding unnecessary bi-directional filtering and correctly handles the date range mismatch, as the Date table's larger range does not affect filtering of Sales data.
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.
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Question Discussion
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