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 help reduce the size of a Power BI dataset when preparing data?
Include all historical data
Why wrong: Increases size.
Aggregate transaction data to daily level
Reduces number of rows.
Add calculated columns
Why wrong: Increases size.
Remove columns that are not used in reports
Reduces data volume.
Use DirectQuery mode
Why wrong: Does not reduce dataset size; data stays in source.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Aggregate transaction data to daily level
Aggregating transaction data to a daily level reduces the number of rows in the dataset, which directly decreases the storage footprint and improves refresh performance. Power BI compresses data more efficiently when cardinality is lower, and fewer rows mean smaller column dictionaries and reduced page compression overhead.
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.
Include all historical data
Why it's wrong here
Increases size.
Aggregate transaction data to daily level
Why this is correct
Reduces number of rows.
Related concept
Read the scenario before looking for a memorised answer.
Add calculated columns
Why it's wrong here
Increases size.
Remove columns that are not used in reports
Why this is correct
Reduces data volume.
Related concept
Read the scenario before looking for a memorised answer.
Use DirectQuery mode
Why it's wrong here
Does not reduce dataset size; data stays in source.
Common exam traps
Microsoft often tests the misconception that adding calculated columns is a harmless transformation, but in reality, they increase dataset size because they are stored as new columns in the VertiPaq engine.
Detailed technical explanation
Power BI uses VertiPaq column-store compression, which benefits from low-cardinality columns and fewer rows. Aggregating to daily level reduces row count, which in turn reduces the size of the fact table and improves compression ratios for date-related columns. In real-world scenarios, keeping granular transaction data (e.g., millisecond timestamps) can bloat the dataset unnecessarily when reports only need daily summaries.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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: Aggregate transaction data to daily level — Aggregating transaction data to a daily level reduces the number of rows in the dataset, which directly decreases the storage footprint and improves refresh performance. Power BI compresses data more efficiently when cardinality is lower, and fewer rows mean smaller column dictionaries and reduced page compression overhead.
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 30, 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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