PL-300 Model the data Practice Question
You are a Power BI data analyst at a healthcare provider. Your semantic model contains a fact table named Visits with columns VisitID, PatientID, ProviderID, VisitDate, and ChargeAmount. You also have a dimension table named Patients with PatientID, PatientName, and PrimaryCareProviderID. You need to create a relationship between Visits and Patients so that filtering Patients by PrimaryCareProviderID correctly filters Visits. However, you discover that the Visits table has multiple rows per PatientID, and the Patients table has a unique PatientID. Which relationship should you create?
⚠ Common exam trap
The trap here is assuming that because Visits has many rows per patient, the relationship must be many-to-many or bidirectional, overlooking that a simple one-to-many from the unique dimension table is sufficient.
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 one-to-many relationship from Patients[PatientID] (one side) to Visits[PatientID] (many side).
The relationship must be one-to-many from Patients to Visits because Patients[PatientID] is unique and Visits[PatientID] has duplicates. This allows filters on Patients, such as PrimaryCareProviderID, to propagate to Visits and correctly aggregate ChargeAmount. A many-to-many or reversed cardinality would not enforce referential integrity and could yield incorrect results.
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-many relationship between Visits[PatientID] and Patients[PatientID].
Why it's wrong here
A many-to-many relationship is unnecessary because Patients[PatientID] is unique, making it the one side. Many-to-many relationships introduce ambiguity and require special handling, such as bridging tables, and can produce incorrect results when filtering by PrimaryCareProviderID. Since Visits has multiple rows per patient, the correct cardinality is one-to-many, not many-to-many.
- ✗
Create a many-to-one relationship from Visits[PatientID] (many side) to Patients[PatientID] (one side) and set the cross-filter direction to Both.
Why it's wrong here
The cardinality many-to-one from Visits to Patients is technically correct, but setting cross-filter direction to Both is unnecessary and can cause ambiguity. Bidirectional filtering is typically used for specific scenarios like many-to-many with a bridge table. Here, a standard single-direction relationship from Patients to Visits is sufficient and avoids performance and ambiguity issues.
- ✗
Create a one-to-many relationship from Visits[PatientID] (one side) to Patients[PatientID] (many side).
Why it's wrong here
This reverses the cardinality: Visits[PatientID] is not unique, so it cannot be the one side. Power BI would reject the relationship because the one side must have unique values. Even if forced, filtering would not propagate correctly from Patients to Visits, and you would see incorrect results when analyzing visits by primary care provider.
- ✓
Create a one-to-many relationship from Patients[PatientID] (one side) to Visits[PatientID] (many side).
Why this is correct
Because Patients[PatientID] is unique and Visits[PatientID] repeats, the correct cardinality is one-to-many from Patients to Visits. This relationship ensures that filtering Patients by PrimaryCareProviderID propagates to Visits, enabling accurate aggregation of ChargeAmount. It also avoids ambiguity and supports efficient query performance, as the one side acts as the lookup dimension.
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Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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