Quick Answer
The answer is to click the expand icon on the column and select 'Expand to New Rows' in Power Query Editor. This is correct because Power Query’s 'Expand to New Rows' function is specifically designed to flatten nested JSON arrays into separate rows while duplicating all parent row information, using the `Table.ExpandListColumn` M function under the hood to unpack each array element into its own row. On the PL-300 exam, this scenario tests your ability to transform semi-structured data, often appearing in questions about importing JSON or API responses where a single row contains a list of sub-records. A common trap is choosing 'Extract Values' or 'Expand to New Columns', which would either collapse the data or spread it sideways instead of vertically. Remember the memory tip: "Rows for lists, columns for records"—when you see a list icon (two brackets), always expand to new rows to keep your data tidy and normalized.
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.
You are importing data from a JSON file that contains nested arrays. You need to expand the arrays into separate rows while maintaining the parent information. What should you do?
In Power Query Editor, click the expand icon on the column and select 'Expand to New Rows'.
This expands list values into new rows.
Use the Pivot Column feature to transform the array.
Why wrong: Pivot is for unpivoted data.
Use the Merge Queries feature to combine tables.
Why wrong: Merge is not for expanding nested arrays.
Use the Group By feature to flatten the data.
Why wrong: Group By aggregates, not expands.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
In Power Query Editor, click the expand icon on the column and select 'Expand to New Rows'.
Option A is correct because Power Query's 'Expand to New Rows' function is specifically designed to flatten nested arrays (e.g., lists or records within a JSON column) into separate rows while duplicating the parent row's other columns. This operation uses the `Table.ExpandListColumn` or `Table.ExpandRecordColumn` M function under the hood, which unpacks each element of the array into its own row, preserving the parent context.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
In Power Query Editor, click the expand icon on the column and select 'Expand to New Rows'.
Why this is correct
This expands list values into new rows.
Related concept
Read the scenario before looking for a memorised answer.
Use the Pivot Column feature to transform the array.
Why it's wrong here
Pivot is for unpivoted data.
Use the Merge Queries feature to combine tables.
Why it's wrong here
Merge is not for expanding nested arrays.
Use the Group By feature to flatten the data.
Why it's wrong here
Group By aggregates, not expands.
Common exam traps
The trap here is that candidates often confuse 'Expand to New Rows' with 'Extract Values' (which concatenates array elements into a single string) or mistakenly think Merge Queries or Pivot Column can flatten nested arrays, when in fact only the expand icon's 'Expand to New Rows' option correctly unpacks arrays into individual rows.
Detailed technical explanation
When you click the expand icon on a column containing JSON arrays, Power Query automatically detects the structure and offers 'Expand to New Rows' (which uses `Table.ExpandListColumn`) or 'Extract Values' (which concatenates). Under the hood, `Table.ExpandListColumn` applies a transformation that converts each list element into a new row, effectively performing an unpivot-like operation on the nested list. This is critical for scenarios like parsing IoT sensor logs where each device record contains an array of timestamped readings, and you need each reading as a separate row for time-series analysis.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
Prepare the data — This question tests Prepare the data — Read the scenario before looking for a memorised answer..
The correct answer is: In Power Query Editor, click the expand icon on the column and select 'Expand to New Rows'. — Option A is correct because Power Query's 'Expand to New Rows' function is specifically designed to flatten nested arrays (e.g., lists or records within a JSON column) into separate rows while duplicating the parent row's other columns. This operation uses the `Table.ExpandListColumn` or `Table.ExpandRecordColumn` M function under the hood, which unpacks each element of the array into its own row, preserving the parent context.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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