The answer is to promote headers and filter out empty rows. Promoting headers uses the first row as column names, which eliminates the generic Column1, Column2 labels that often introduce data type conflicts and messy transformations, directly improving data quality. Filtering out empty rows reduces the number of rows loaded into the data model, decreasing memory usage and speeding up refresh performance—a core technique to reduce load time in Power Query. On the PL-300 exam, this tests your understanding of query folding and data shaping best practices; a common trap is confusing row filtering with column removal, but remember that removing blank rows cuts physical data volume, while removing columns only cuts metadata. A useful memory tip: “Headers for clarity, blanks for speed”—promote headers to clean your structure, then filter blanks to lighten your load.
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.
Which TWO actions can you take in Power Query Editor to improve data quality and reduce load time? (Choose two.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Filter out empty rows.
Filtering out empty rows in Power Query Editor directly reduces the number of rows loaded into the data model, which decreases memory usage and improves refresh performance. This action also enhances data quality by removing incomplete records that could cause errors in measures or relationships.
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.
✗
Split columns by delimiter to create more columns.
Why it's wrong here
Splitting columns increases the number of columns, which can increase load time.
✓
Filter out empty rows.
Why this is correct
Removing empty rows reduces the amount of data loaded.
Related concept
Read the scenario before looking for a memorised answer.
✗
Sort the data by a key column.
Why it's wrong here
Sorting does not improve data quality or reduce load time; it may increase processing.
✓
Promote headers to use the first row as column names.
Why this is correct
Promoting headers ensures correct column names, improving data quality.
Related concept
Read the scenario before looking for a memorised answer.
✗
Merge queries to combine data from multiple sources.
Why it's wrong here
Merging increases data volume and complexity, often increasing load time.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse actions that improve data quality (like filtering or promoting headers) with actions that merely reorganize data (like sorting or splitting), leading them to select options that do not actually reduce load time or enhance data integrity.
Detailed technical explanation
How to think about this question
Filtering rows in Power Query Editor uses the Table.SelectRows M function, which applies a predicate to each row and discards those that don't match, reducing the dataset before it enters the data model. Promoting headers (Option D) uses Table.PromoteHeaders, which shifts the first row to column names, ensuring proper data typing and preventing the first row from being treated as data—this improves data quality by avoiding type mismatches and errors in relationships. Under the hood, Power Query's query folding can push these transformations back to the source (e.g., SQL WHERE clause) when supported, further optimizing load time.
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: Filter out empty rows. — Filtering out empty rows in Power Query Editor directly reduces the number of rows loaded into the data model, which decreases memory usage and improves refresh performance. This action also enhances data quality by removing incomplete records that could cause errors in measures or relationships.
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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