- A
Create a composite model using DirectQuery for the fact table and Import for dimensions.
Why wrong: Composite models can improve query performance but do not minimize import refresh time because the fact table remains in DirectQuery; the import refresh of dimensions is minor. The primary goal is to minimize overall data refresh time, which is best achieved by reducing imported data.
- B
Use DirectQuery mode for the dataset.
Why wrong: DirectQuery does not import data, so there is no import refresh. However, the scenario explicitly asks to minimize data refresh time, implying an import scenario. DirectQuery may be slower for queries and does not address refresh time.
- C
Configure incremental refresh on the fact table.
Why wrong: Incremental refresh only reduces refresh time for subsequent refreshes by refreshing only new or changed data, but the initial full refresh still loads all data. The question does not specify a date column or partitioning strategy.
- D
Use Import mode but filter rows and reduce columns in Power Query to only those needed.
Importing only necessary data reduces the amount of data loaded, directly decreasing refresh time while still supporting fast query performance.
Quick Answer
The correct approach is to use Import mode but filter rows and reduce columns in Power Query to only those needed. This minimizes data refresh time because importing only the necessary data volume directly reduces the load on both the source system and Power BI’s VertiPaq engine, avoiding the overhead of querying a 500-million-row fact table on every report interaction. On the PL-300 exam, this scenario tests your understanding of when Import mode outperforms DirectQuery for large datasets, with the common trap being to assume DirectQuery is always faster for big data—when in fact, Import mode with proper filtering is typically more efficient for scheduled refreshes. The key is to remember that reducing row and column cardinality in Power Query before loading is the most effective way to minimize data refresh time while meeting reporting requirements. Memory tip: “Trim before you import” to recall that filtering and column reduction are your first steps to a lean, fast refresh.
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 creating a Power BI dataset from a SQL Server data warehouse. The warehouse contains a fact table with 500 million rows and dimension tables. You need to minimize the data refresh time while ensuring that the dataset meets the reporting requirements. Which approach should you recommend?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
Use Import mode but filter rows and reduce columns in Power Query to only those needed.
Option D is correct because importing only the necessary columns and rows reduces the data volume, which directly minimizes refresh time. With 500 million rows, Import mode is generally faster than DirectQuery for large fact tables in Power BI, as it avoids querying the source on every interaction. Filtering and column reduction in Power Query ensures the dataset remains lean while meeting reporting requirements.
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.
- ✗
Create a composite model using DirectQuery for the fact table and Import for dimensions.
Why it's wrong here
Composite models can improve query performance but do not minimize import refresh time because the fact table remains in DirectQuery; the import refresh of dimensions is minor. The primary goal is to minimize overall data refresh time, which is best achieved by reducing imported data.
- ✗
Use DirectQuery mode for the dataset.
Why it's wrong here
DirectQuery does not import data, so there is no import refresh. However, the scenario explicitly asks to minimize data refresh time, implying an import scenario. DirectQuery may be slower for queries and does not address refresh time.
- ✗
Configure incremental refresh on the fact table.
Why it's wrong here
Incremental refresh only reduces refresh time for subsequent refreshes by refreshing only new or changed data, but the initial full refresh still loads all data. The question does not specify a date column or partitioning strategy.
- ✓
Use Import mode but filter rows and reduce columns in Power Query to only those needed.
Why this is correct
Importing only necessary data reduces the amount of data loaded, directly decreasing refresh time while still supporting fast query performance.
Clue confirmation
The clue word "minimum / minimize" 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 often choose incremental refresh (Option C) thinking it always reduces refresh time, but it does not address the initial full load or the need to minimize data volume; the key is to reduce the data imported, not just partition it.
Trap categories for this question
Scenario analysis trap
DirectQuery does not import data, so there is no import refresh. However, the scenario explicitly asks to minimize data refresh time, implying an import scenario. DirectQuery may be slower for queries and does not address refresh time.
Detailed technical explanation
How to think about this question
Import mode in Power BI compresses data using the VertiPaq engine, which can achieve high compression ratios (often 5-10x) on large fact tables, significantly reducing storage and refresh time. Filtering rows and columns in Power Query before loading ensures that only relevant data enters the model, which also improves query performance by reducing the size of column dictionaries and segment tables. In real-world scenarios, a 500-million-row fact table might be reduced to 50 million rows after filtering, making Import mode feasible and fast.
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: Use Import mode but filter rows and reduce columns in Power Query to only those needed. — Option D is correct because importing only the necessary columns and rows reduces the data volume, which directly minimizes refresh time. With 500 million rows, Import mode is generally faster than DirectQuery for large fact tables in Power BI, as it avoids querying the source on every interaction. Filtering and column reduction in Power Query ensures the dataset remains lean while meeting reporting requirements.
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: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
3 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. You are preparing data from a SQL Server database for a Power BI report. The database contains a table with millions of rows of sales transactions. You need to minimize the data load time and reduce the model size. What should you do?
medium- A.Configure incremental refresh without filtering.
- B.Enable query folding in Power Query.
- C.Use DirectQuery instead of Import mode.
- ✓ D.Import only the required columns and apply row-level filters in Power Query.
Why D: Option D is correct because importing only the necessary columns and applying filters to reduce rows directly reduces the amount of data loaded into Power BI, minimizing load time and model size. Option A is wrong because DirectQuery would avoid import but not reduce load time for queries and may impact performance. Option B is wrong because Power Query folding is automatic for SQL Server but does not reduce data volume unless combined with filters. Option C is wrong because incremental refresh requires a date column and configured policy, but does not reduce initial load.
Variation 2. You are preparing data from an on-premises SQL Server database for a Power BI report. The source table contains 10 million rows and you only need the last 3 months of data. Which approach minimizes the data load time and memory consumption in the dataset?
medium- A.Use Power Query to group by month and then filter after aggregation.
- ✓ B.Use a SQL query in Power Query that includes a WHERE clause to filter the last 3 months.
- C.Load all data into Power Query and apply a filter on the date column using the 'Remove Rows' feature.
- D.Load all data into Power BI and then use a report-level filter to show only the last 3 months.
Why B: Option B is correct because query folding ensures that the filter is pushed to the source database, reducing the amount of data transferred. Option A is wrong because loading all data and then filtering in Power Query still transfers the full dataset. Option C is wrong because it still imports all data. Option D is wrong because importing all data and using a filter on the report is less efficient.
Variation 3. You are loading data from a SQL Server database into Power BI. You notice that the import takes a long time because the source table contains many rows. You only need a subset of rows based on a date filter. What should you do to improve performance?
easy- A.Remove unnecessary columns in Power Query.
- ✓ B.Use a SQL query with a WHERE clause in the Power Query Editor.
- C.Load all data and then apply a filter in Power BI.
- D.Enable incremental refresh on the dataset.
Why B: Option B is correct because using a SQL query with a WHERE clause in Power Query Editor pushes the date filter down to the SQL Server database, reducing the amount of data transferred over the network and imported into Power BI. This query folding technique leverages the database engine's indexing and processing power, which is far more efficient than filtering after import. By retrieving only the necessary rows upfront, you minimize both network latency and memory consumption in Power BI.
Last reviewed: Jun 24, 2026
This PL-300 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PL-300 exam.
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