PL-300 Model the data Practice Question
Exhibit
Refer to the exhibit.
Exhibit: DAX query from Performance Analyzer
EVALUATE
SUMMARIZECOLUMNS(
'Date'[Year],
'Product'[Category],
"Total Sales", [Sales Amount]
)
ORDER BY 'Date'[Year], 'Product'[Category]
This query returns the following error: "The expression references multiple columns. Multiple columns cannot be converted to a scalar value."What is the most likely cause of the error in the DAX query shown in the exhibit?
⚠ Common exam trap
The trap here is that candidates often misdiagnose the error as a missing relationship or syntax issue, when the root cause is a measure returning multiple values due to improper aggregation or context.
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
✓
The [Sales Amount] measure is returning multiple values or is not a valid scalar measure.
The error 'A single value for column 'Sales Amount' in table 'Sales' cannot be determined' occurs because the [Sales Amount] measure is being used in a context that expects a scalar value, but the measure is defined to return multiple values (e.g., using SUMX over a table that returns multiple rows without proper aggregation). In DAX, measures used in EVALUATE statements must return a single scalar value; if the measure is not properly aggregated or contains a many-to-many relationship, it can produce multiple values, causing this error.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The [Sales Amount] measure is returning multiple values or is not a valid scalar measure.
Why this is correct
The error message indicates that the measure is not a valid scalar value. When a measure references a column without an aggregation function, such as Sales[SalesAmount] directly, or returns a table expression, SUMMARIZECOLUMNS fails because it expects a scalar for each column in its result set. Ensure the measure aggregates the underlying column using SUM, AVERAGE, or another scalar-returning function. Additionally, verify the measure is not using a calculated table or a row context that produces multiple results.
- ✗
There is no relationship between Date and Product tables.
Why it's wrong here
This option is incorrect because the absence of a relationship between Date and Product would not produce this specific error. SUMMARIZECOLUMNS can operate on any tables, and missing relationships would result in a cartesian product (if intentional) or a different evaluation behavior, but not a scalar measure failure. Relationship issues typically manifest as incorrect results or a 'related table not found' error, not this type of scalar mismatch. Therefore, this is not the most likely cause.
- ✗
The SUMMARIZECOLUMNS function does not support multiple group-by columns.
Why it's wrong here
This is not the cause because SUMMARIZECOLUMNS explicitly accepts multiple group-by columns; it is designed to return a table with one row per combination of the given columns. In fact, it accepts up to 76 columns in a single call, making multi-column grouping a core feature. The error occurs after the grouping is defined, during measure evaluation, so it is not about the number of group-by columns. The measure's inability to produce a scalar is the actual failure point.
- ✗
The ORDER BY clause is not allowed in EVALUATE statements.
Why it's wrong here
ORDER BY is a valid and commonly used clause in EVALUATE statements in DAX queries. The grammar for EVALUATE allows an optional ORDER BY clause that sorts the results based on expressions or columns, so it is fully supported in DAX. The error would occur before ordering is processed, because the measure is evaluated for each row in the result set. Thus, ORDER BY cannot be the cause of this error.
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