The correct answer is to use the Folder connector's 'Combine Files' transform, which handles schema merging automatically. This works because Power Query’s Combine Files feature uses a sample file to infer the column structure, then dynamically merges columns from all CSV files—even when column names or data types vary—by promoting headers and aligning data types across inconsistent columns. On the PL-300 exam, this scenario tests your understanding of the Folder connector’s built-in data ingestion logic, often appearing as a question where a manual Table.Combine or custom M code fails due to schema mismatches. A common trap is trying to manually rename columns or use error handling functions, which wastes time; the exam expects you to recognize that the Combine Files transform is designed specifically to combine CSV files with inconsistent columns in Power Query. Memory tip: think “Sample file = schema blueprint” — Power Query uses one file as a template to map all others, so let the tool do the merging.
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. The following Power Query M code is used to combine multiple CSV files from a folder:
let
Source = Folder.Files("C:\Data\Sales"),
Filtered = Table.SelectRows(Source, each [Extension] = ".csv"),
Combined = Table.Combine(Table.TransformColumns(Filtered, {{"Content", each Csv.Document(_)}}))
in
Combined
You are combining CSV files from a folder. The code above returns an error because some CSV files have inconsistent column names and data types. You need to modify the solution to handle variations in column structure. What should you do?
Refer to the exhibit. The following Power Query M code is used to combine multiple CSV files from a folder:
let
Source = Folder.Files("C:\Data\Sales"),
Filtered = Table.SelectRows(Source, each [Extension] = ".csv"),
Combined = Table.Combine(Table.TransformColumns(Filtered, {{"Content", each Csv.Document(_)}}))
in
Combined
A
Change the delimiter to a semicolon and reconfigure the CSV parser.
Why wrong: Delimiter is unrelated to column name and type inconsistencies.
B
Use Table.RemoveRows to remove rows that cause errors.
Why wrong: Removing rows does not resolve structural mismatches; the error occurs when combining tables with different schemas.
C
Add a custom column to each file to standardize data types before combining.
Why wrong: While you could add a custom column, the core issue is that column names and types vary across files. Manually standardizing is error-prone and not the most efficient built-in approach.
D
Use the Folder connector's 'Combine Files' transform, which handles schema merging automatically.
The built-in Combine Files feature in Power Query automatically detects column names and data types from the first file and merges subsequent files accordingly, handling variations gracefully.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the Folder connector's 'Combine Files' transform, which handles schema merging automatically.
Option D is correct because the 'Combine Files' transform in Power Query (Folder connector) automatically detects and merges columns from multiple CSV files, even when column names or data types vary. It uses a sample file to infer the schema and then applies transformations to handle inconsistencies, such as promoting headers and aligning data types, which resolves the error without manual intervention.
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.
✗
Change the delimiter to a semicolon and reconfigure the CSV parser.
Why it's wrong here
Delimiter is unrelated to column name and type inconsistencies.
✗
Use Table.RemoveRows to remove rows that cause errors.
Why it's wrong here
Removing rows does not resolve structural mismatches; the error occurs when combining tables with different schemas.
✗
Add a custom column to each file to standardize data types before combining.
Why it's wrong here
While you could add a custom column, the core issue is that column names and types vary across files. Manually standardizing is error-prone and not the most efficient built-in approach.
✓
Use the Folder connector's 'Combine Files' transform, which handles schema merging automatically.
Why this is correct
The built-in Combine Files feature in Power Query automatically detects column names and data types from the first file and merges subsequent files accordingly, handling variations gracefully.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often think they need to manually fix data types or remove errors (Options B or C), but the 'Combine Files' transform is designed specifically to automate schema merging, which is the correct solution for inconsistent column structures.
Detailed technical explanation
How to think about this question
The 'Combine Files' transform uses a sample file (first file by default) to define the schema, then applies a function (e.g., 'Transform File') to all files, merging columns by name and aligning data types using 'Table.Combine' with 'Union' semantics. In real-world scenarios, this is critical when dealing with CSV files from different sources (e.g., monthly reports) where column order or data types (e.g., 'Date' as text vs. datetime) vary, as it avoids manual schema reconciliation.
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 the Folder connector's 'Combine Files' transform, which handles schema merging automatically. — Option D is correct because the 'Combine Files' transform in Power Query (Folder connector) automatically detects and merges columns from multiple CSV files, even when column names or data types vary. It uses a sample file to infer the schema and then applies transformations to handle inconsistencies, such as promoting headers and aligning data types, which resolves the error without manual intervention.
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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