The answer is a table with total sales amount per customer for orders after 2023. This is correct because the Power Query M expression first applies a filtering step using `Table.SelectRows` to keep only rows where `OrderDate` is in 2024 or later, effectively removing all orders from 2023 and earlier. It then uses `Table.Group` to group the filtered rows by `CustomerID` and aggregate the `SalesAmount` column with a sum operation, producing one row per customer with their total post-2023 sales. On the PL-300 exam, this tests your ability to interpret the sequence of M steps in the advanced editor—a common trap is misreading the filter condition as inclusive of 2023, when the expression explicitly uses `>= #date(2024,1,1)`. To avoid this, remember that Power Query M evaluates steps in order: filter first, then group. A useful memory tip is “filter before group, date check is the key”—always verify the date boundary in the filter step before considering the grouping output.
PL-300 Prepare the data Practice Question
This PL-300 practice question tests your understanding of prepare the data. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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.
let
Source = Sql.Database("myserver.database.windows.net", "SalesDB"),
SalesTable = Source{[Schema="dbo",Item="Sales"]}[Data],
FilteredRows = Table.SelectRows(SalesTable, each [OrderDate] >= #date(2023,1,1)),
RemovedColumns = Table.RemoveColumns(FilteredRows,{"Discount"}),
GroupedRows = Table.Group(RemovedColumns, {"CustomerID"}, {{"Total", each List.Sum([Amount]), type number}})
in
GroupedRows
You are reviewing a Power Query M expression in the advanced editor. The exhibit shows the query. What is the final output of this query?
Refer to the exhibit.
let
Source = Sql.Database("myserver.database.windows.net", "SalesDB"),
SalesTable = Source{[Schema="dbo",Item="Sales"]}[Data],
FilteredRows = Table.SelectRows(SalesTable, each [OrderDate] >= #date(2023,1,1)),
RemovedColumns = Table.RemoveColumns(FilteredRows,{"Discount"}),
GroupedRows = Table.Group(RemovedColumns, {"CustomerID"}, {{"Total", each List.Sum([Amount]), type number}})
in
GroupedRows
A
A table with total sales amount per customer for all orders
Why wrong: The query filters for OrderDate >= 2023-01-01.
B
A table with total sales amount per customer for orders after 2023
The query filters, removes columns, and groups by CustomerID summing Amount.
C
A table with all sales records after 2023
Why wrong: Columns are removed and rows are grouped.
D
A table with all sales records after 2023, excluding Discount column
Why wrong: The query groups the data, so it's not individual records.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
A table with total sales amount per customer for orders after 2023
The query filters the Sales table to keep only rows where the OrderDate is in 2024 or later (i.e., after 2023), then groups by CustomerID, summing the SalesAmount for each customer. The final output is a table with one row per customer showing their total sales amount for orders placed after 2023.
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.
✗
A table with total sales amount per customer for all orders
Why it's wrong here
The query filters for OrderDate >= 2023-01-01.
✓
A table with total sales amount per customer for orders after 2023
Why this is correct
The query filters, removes columns, and groups by CustomerID summing Amount.
Related concept
Read the scenario before looking for a memorised answer.
✗
A table with all sales records after 2023
Why it's wrong here
Columns are removed and rows are grouped.
✗
A table with all sales records after 2023, excluding Discount column
Why it's wrong here
The query groups the data, so it's not individual records.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often overlook the filter step and assume the query returns all records or all customers, failing to recognize that the date filter and grouping fundamentally change both the row set and the structure of the output.
Detailed technical explanation
How to think about this question
The filter step uses a date comparison (e.g., [OrderDate] > #datetime(2023,12,31)) which in Power Query's M language is a row-level predicate that eliminates rows not meeting the condition. The subsequent Table.Group operation applies a SUM aggregation on SalesAmount, collapsing multiple rows per customer into a single row with the total. This pattern is common for creating summary tables from transactional data, and the order of steps matters: filtering before grouping reduces the data volume for the aggregation.
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: A table with total sales amount per customer for orders after 2023 — The query filters the Sales table to keep only rows where the OrderDate is in 2024 or later (i.e., after 2023), then groups by CustomerID, summing the SalesAmount for each customer. The final output is a table with one row per customer showing their total sales amount for orders placed after 2023.
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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