PL-300 Model the data Practice Question
You need to create a relationship between two tables in Power BI. Both tables contain a column named 'ProductID', but the values in one table are integers and in the other are text. What should you do first?
⚠ Common exam trap
Test-takers frequently assume a many-to-many relationship can ignore data type mismatches, but Power BI still enforces type compatibility on the key columns used for the relationship.
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
✓
Ensure both columns have the same data type, either by changing the data type in Power Query or in the model view.
In Power BI, relationships require matching data types on both sides of the key columns. If one 'ProductID' column is integer and the other is text, the relationship engine cannot resolve the join because the data types are incompatible. Changing both columns to the same data type—either in Power Query (recommended for performance) or in the model view—resolves this mismatch and allows a valid relationship to be created.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Merge the two tables into one in Power Query.
Why it's wrong here
Merging the two tables in Power Query creates a single denormalized table, which duplicates data and increases model size, and it changes the query structure without addressing the need for a relationship. Relationships are the correct way to relate tables in a star schema, preserving the ability to filter and aggregate independently. Additionally, merging can cause row multiplication if the join key has duplicates, leading to incorrect measures.
- ✓
Ensure both columns have the same data type, either by changing the data type in Power Query or in the model view.
Why this is correct
Power BI relationships require that the key columns on both sides have identical data types; a mismatch between text and integer, for example, will prevent the relationship from being created. Changing the data type in Power Query is the preferred method because it transforms the data during load, while changing it in the Model view only alters the metadata and may not propagate back to the query. Ensuring the same data type is the foundational step before defining cardinality and cross-filter direction.
- ✗
Create a new calculated column that converts the integer to text using FORMAT.
Why it's wrong here
Using FORMAT to convert the integer ProductID to text creates a calculated column, but Power BI relationships require matching data types on the actual columns used in the relationship, not on derived columns. The relationship must be built directly on the original 'ProductID' columns, and a calculated column cannot serve as the relationship key. This option is tempting because FORMAT is commonly used to standardise display formats for reporting, and in a scenario where you needed to join tables in Power Query (not in the model), converting types with FORMAT would be a valid preparatory step.
- ✗
Set the relationship to 'Many-to-many' to bypass the type mismatch.
Why it's wrong here
Setting the relationship to 'Many-to-many' changes the cardinality, but it does not bypass the data type requirement; both columns must still have the same data type for the relationship to be valid. Many-to-many cardinality is specifically designed for cases where both tables have duplicate values and requires a bridge table in a proper star schema, not for resolving type mismatches. Without aligned types, Power BI will reject the relationship regardless of the cardinality setting.
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