Quick Answer
The answer is to use the 'Combine Files' transform after connecting to the folder. This is correct because Power Query’s folder connector automatically detects multiple CSV files with identical structures, then generates a sample file query and a transformation function that applies the same steps to every file, merging them into one cohesive table without manual appending. On the PL-300 exam, this scenario tests your understanding of Power Query’s native folder-based ingestion, often appearing as a distractor against manual “Append Queries” or “Merge” options, which are inefficient for dozens of files. A common trap is trying to import each CSV individually; remember that the folder connector’s “Combine Files” button is purpose-built for this exact task. Memory tip: think “Folder + Combine = One Table,” and always let Power Query do the heavy lifting for bulk CSV imports.
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 creating a Power BI report for a marketing team. The data is stored in a folder of CSV files on a network drive that is accessible from your computer. You need to combine all CSV files into a single table in Power BI. The files have the same structure. What should you do in Power Query?
Connect to each CSV file individually and use Append Queries.
Why wrong: This is possible but less efficient.
Use the 'Combine Files' transform after connecting to the folder.
Correct. This automatically merges files.
Use Merge Queries to join the files based on a common column.
Why wrong: Merge is for joining, not combining rows.
Change the data source settings to treat the folder as a single data source.
Why wrong: No such setting exists.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use the 'Combine Files' transform after connecting to the folder.
Option B is correct because Power Query's 'Combine Files' transform is specifically designed to handle multiple CSV files with identical schemas stored in a folder. When you connect to the folder as a data source, Power Query automatically generates a sample file query and a transformation function that applies the same steps to all files, then combines the results into a single table. This is the most efficient and recommended approach for this scenario, avoiding manual appending or merging.
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.
Connect to each CSV file individually and use Append Queries.
Why it's wrong here
This is possible but less efficient.
Use the 'Combine Files' transform after connecting to the folder.
Why this is correct
Correct. This automatically merges files.
Related concept
Read the scenario before looking for a memorised answer.
Use Merge Queries to join the files based on a common column.
Why it's wrong here
Merge is for joining, not combining rows.
Change the data source settings to treat the folder as a single data source.
Why it's wrong here
No such setting exists.
Common exam traps
The trap here is that candidates often confuse 'Append Queries' (which stacks rows) with 'Combine Files' (which automates the same process for a folder), or mistakenly think 'Merge Queries' (which joins columns) is appropriate for combining files with identical structures.
Detailed technical explanation
Under the hood, the 'Combine Files' transform in Power Query uses a two-step process: it first creates a 'Sample File' query to infer the schema and transformation steps, then generates a 'Transform Sample File' function that is applied to each file via a custom column in the folder query. This leverages Power Query's M language to dynamically iterate over all files, handling variations in row counts or minor schema differences if the 'Combine Files' dialog is configured to use the first file as a template. In real-world scenarios, this approach is critical when dealing with daily or hourly CSV exports that accumulate in a folder, as it automatically includes new files on refresh without manual intervention.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
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: Use the 'Combine Files' transform after connecting to the folder. — Option B is correct because Power Query's 'Combine Files' transform is specifically designed to handle multiple CSV files with identical schemas stored in a folder. When you connect to the folder as a data source, Power Query automatically generates a sample file query and a transformation function that applies the same steps to all files, then combines the results into a single table. This is the most efficient and recommended approach for this scenario, avoiding manual appending or merging.
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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