Question 210 of 966

Prepare the data →hardMultiple SelectObjective-mapped

Power BI Data Load Performance: Remove Columns, Set Data Types, Use Query Folding

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 THREE of the following are best practices for optimizing data load performance in Power BI?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

A
Remove unnecessary columns and rows during the import process.
Reducing data volume improves load time.
B
Split a large fact table into multiple smaller fact tables.
Why wrong: This can complicate the model and may not improve performance.
C
Set data types correctly in Power Query to avoid type detection overhead.
Proper data types improve load efficiency.
D
Use DirectQuery mode instead of Import mode to reduce data load time.
Why wrong: DirectQuery does not load data, but it is not always a performance best practice.
E
Use query folding to push transformations to the source database.
Query folding reduces data transfer.

Full breakdown with real-world context →

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Remove unnecessary columns and rows during the import process.

Option A is correct because removing unnecessary columns and rows during the import process reduces the amount of data loaded into the Power BI data model, which directly decreases memory usage and refresh time. By filtering out irrelevant data early in Power Query, you minimize the data volume that must be processed and stored, leading to faster load performance.

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.

✓
Remove unnecessary columns and rows during the import process.
Why this is correct
Reducing data volume improves load time.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Split a large fact table into multiple smaller fact tables.
Why it's wrong here
This can complicate the model and may not improve performance.
✓
Set data types correctly in Power Query to avoid type detection overhead.
Why this is correct
Proper data types improve load efficiency.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use DirectQuery mode instead of Import mode to reduce data load time.
Why it's wrong here
DirectQuery does not load data, but it is not always a performance best practice.
✓
Use query folding to push transformations to the source database.
Why this is correct
Query folding reduces data transfer.
Clue confirmation
The clue word "best" in the question point toward this answer.
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 may confuse 'splitting tables' (Option B) with star schema design best practices, but splitting a fact table unnecessarily violates dimensional modeling principles and harms performance, whereas proper star schema involves splitting dimensions from facts, not splitting facts themselves.

Detailed technical explanation

How to think about this question

Under the hood, Power Query uses the M language to transform data, and query folding pushes these transformations (e.g., filters, column removals) to the source database as SQL statements, leveraging the source's indexing and processing power. This reduces the data transferred over the network and minimizes in-memory processing in Power BI. In real-world scenarios, folding a filter on a date column in a SQL Server source can reduce millions of rows to thousands before the data even reaches Power Query, dramatically improving load times.

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.

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FAQ

Questions learners often ask

What does this PL-300 question test?

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: Remove unnecessary columns and rows during the import process. — Option A is correct because removing unnecessary columns and rows during the import process reduces the amount of data loaded into the Power BI data model, which directly decreases memory usage and refresh time. By filtering out irrelevant data early in Power Query, you minimize the data volume that must be processed and stored, leading to faster load performance.

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.

Are there clue words in this question I should notice?

Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

About these practice questions

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Same concept, more angles

2 more ways this is tested on PL-300

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. Which THREE of the following are best practices for data preparation in Power BI to improve performance and maintainability? (Select THREE.)

hard

✓ A.Filter out unnecessary rows as early as possible in the query
B.Avoid renaming columns in Power Query; use original names
✓ C.Use query folding to push transformations back to the source
✓ D.Split complex queries into multiple steps for clarity
E.Keep all columns from the source to avoid missing data

Why A: Filtering out unnecessary rows early in Power Query reduces the amount of data loaded into memory and processed in subsequent transformation steps. This practice, known as early filtering, minimizes the data footprint and improves both refresh performance and report responsiveness. By applying filters as the first transformation, you leverage query folding to push the filter logic to the source database, further enhancing efficiency.

Variation 2. Which THREE of the following are best practices when preparing data in Power BI for optimal performance?

medium

A.Merge all tables into a single table for simplicity.
B.Create calculated columns instead of measures when possible.
✓ C.Set correct data types for all columns.
✓ D.Remove unnecessary columns and rows during import.
✓ E.Use query folding to push transformations to the data source.

Why C: Setting correct data types for all columns (Option C) is a best practice because it ensures that Power BI uses the most efficient storage and processing methods. Incorrect data types can lead to increased memory usage, slower query performance, and inaccurate calculations, as Power BI must perform implicit conversions at query time.

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