The answer is that the RANKX calculated column returns all 1s because the expression SUM(Sales[Amount]) in a calculated column aggregates only the current row, resulting in the same value for all rows. This happens because a calculated column operates in row context, meaning SUM(Sales[Amount]) evaluates the Amount for just that single row rather than the entire Sales table. Since every row produces the same single-row aggregate, RANKX sees identical values across all rows and assigns rank 1 to each. On the Microsoft Power BI Data Analyst PL-300 exam, this scenario tests your understanding of row context versus filter context, a common trap where candidates forget that calculated columns lack the automatic iteration of measures. To fix it, you must use a measure or explicitly include ALL(Sales) in the expression to remove the row context. Memory tip: “Row context locks you in a single row; to rank the whole table, you need filter context to flow.”
PL-300 Prepare the data Practice Question
This PL-300 practice question tests your understanding of prepare the data. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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.
Exhibit
Refer to the exhibit. The following Power BI DAX expression is used to create a calculated column:
Sales Rank = RANKX(ALL(Sales), SUM(Sales[Amount]),, DESC, Dense)
You have a Sales table with columns: ProductID, Amount, Date. You create the calculated column above. However, the rank values are not as expected; all rows show 1. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Refer to the exhibit. The following Power BI DAX expression is used to create a calculated column:
Sales Rank = RANKX(ALL(Sales), SUM(Sales[Amount]),, DESC, Dense)
A
The Dense parameter forces all ranks to 1.
Why wrong: Dense ranking still produces different ranks; it does not cause uniform rank.
B
The DESC parameter is misspelled; it should be 'Desc'.
Why wrong: DESC is a valid abbreviation; it is not the cause.
C
The expression SUM(Sales[Amount]) in a calculated column aggregates only the current row, resulting in the same value for all rows.
In a calculated column, SUM over a column without filter context sums the entire column, but because it's in a row context, it is not a proper measure; actually, SUM(Sales[Amount]) in a row context returns the sum of all rows, not per row. Wait, the statement in D is slightly off. More precisely, in a calculated column, SUM(Sales[Amount]) returns the total sum of Amount across all rows, which is constant for all rows, so all ranks are 1. The correct fix is to use a measure or use the column value directly.
D
The RANKX function requires a measure, not a calculated column.
Why wrong: RANKX can be used in calculated columns; the syntax is valid.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The expression SUM(Sales[Amount]) in a calculated column aggregates only the current row, resulting in the same value for all rows.
Option C is correct because in a calculated column, the SUM(Sales[Amount]) expression is evaluated in row context, meaning it aggregates only the current row's Amount value rather than the entire Sales table. Since every row has the same single-row aggregate, RANKX sees identical values for all rows and assigns rank 1 to each. To get correct ranking, you must use a measure or explicitly use ALL(Sales) in the expression to remove row context.
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.
✗
The Dense parameter forces all ranks to 1.
Why it's wrong here
Dense ranking still produces different ranks; it does not cause uniform rank.
✗
The DESC parameter is misspelled; it should be 'Desc'.
Why it's wrong here
DESC is a valid abbreviation; it is not the cause.
✓
The expression SUM(Sales[Amount]) in a calculated column aggregates only the current row, resulting in the same value for all rows.
Why this is correct
In a calculated column, SUM over a column without filter context sums the entire column, but because it's in a row context, it is not a proper measure; actually, SUM(Sales[Amount]) in a row context returns the sum of all rows, not per row. Wait, the statement in D is slightly off. More precisely, in a calculated column, SUM(Sales[Amount]) returns the total sum of Amount across all rows, which is constant for all rows, so all ranks are 1. The correct fix is to use a measure or use the column value directly.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The RANKX function requires a measure, not a calculated column.
Why it's wrong here
RANKX can be used in calculated columns; the syntax is valid.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse row context with filter context, assuming that SUM in a calculated column behaves like a measure and aggregates the whole table, when in reality it only sees the current row.
Detailed technical explanation
How to think about this question
In DAX, calculated columns evaluate expressions in row context, meaning any aggregation like SUM(Sales[Amount]) without an explicit table filter (e.g., ALL) will only see the current row's value. RANKX then compares these identical single-row sums, producing rank 1 for all rows. A common fix is to use CALCULATE(SUM(Sales[Amount]), ALL(Sales)) to transition to filter context and aggregate the entire table. This distinction between row context and filter context is a frequent source of errors in DAX calculations.
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: The expression SUM(Sales[Amount]) in a calculated column aggregates only the current row, resulting in the same value for all rows. — Option C is correct because in a calculated column, the SUM(Sales[Amount]) expression is evaluated in row context, meaning it aggregates only the current row's Amount value rather than the entire Sales table. Since every row has the same single-row aggregate, RANKX sees identical values for all rows and assigns rank 1 to each. To get correct ranking, you must use a measure or explicitly use ALL(Sales) in the expression to remove row context.
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.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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