The answer is to use the 'Expand to New Rows' transform on the list columns. This is correct because when Power Query imports nested JSON, arrays are represented as list-type columns; the 'Expand to New Rows' command, found under the Transform tab, unpacks each element of those lists into its own row, effectively flattening the hierarchical structure into a standard flat table. On the PL-300 exam, this scenario tests your understanding of M-language data shaping, often appearing in questions about REST API data ingestion where a single JSON record contains multiple sub-records. A common trap is confusing 'Expand to New Rows' with 'Extract Values' or 'Aggregate', which collapse data rather than expand it. Remember the memory tip: "Lists need rows, not commas"—if you see a list icon in a column, use Expand to New Rows to create new rows, not a concatenated string.
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.
You are importing data from a REST API that returns JSON. The JSON structure includes nested arrays. You need to transform the data into a flat table structure in Power Query. Which transform should you apply?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use 'Expand to New Rows' on the list columns
Option A is correct because the 'Expand to New Rows' transform (found under the 'Transform' tab in Power Query) is specifically designed to flatten nested list columns—such as arrays within JSON—by creating a new row for each element in the list. This converts the hierarchical JSON structure into a flat table, which is the required outcome for further analysis in Power BI.
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.
✓
Use 'Expand to New Rows' on the list columns
Why this is correct
Expanding list columns creates new rows for each element, flattening the structure.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use 'Merge Queries' to combine the nested data
Why it's wrong here
Merge queries combine two tables, not flatten a single JSON.
✗
Use 'Pivot Column' on the nested columns
Why it's wrong here
Pivoting turns rows into columns, not flattening nested arrays.
✗
Use 'Unpivot Columns' on the record columns
Why it's wrong here
Unpivoting turns columns into rows, but does not handle nested arrays.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse 'Expand to New Rows' (for lists) with 'Expand to New Columns' (for records), or mistakenly think 'Unpivot Columns' can flatten arrays, when in fact 'Unpivot' only works on record-type columns, not list-type columns.
Detailed technical explanation
How to think about this question
When Power Query imports JSON, it automatically detects nested structures and represents arrays as 'List' type columns and objects as 'Record' type columns. The 'Expand to New Rows' transform internally uses the List.Combine and Table.FromList functions to break each list element into its own row, preserving the parent row's other columns. A real-world scenario is flattening a JSON API response from Azure DevOps that contains nested work item fields, where each work item has an array of tags—expanding this list allows you to analyze each tag as a separate row.
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: Use 'Expand to New Rows' on the list columns — Option A is correct because the 'Expand to New Rows' transform (found under the 'Transform' tab in Power Query) is specifically designed to flatten nested list columns—such as arrays within JSON—by creating a new row for each element in the list. This converts the hierarchical JSON structure into a flat table, which is the required outcome for further analysis in Power BI.
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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Question Discussion
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