Question 609 of 217
Improve Import Refresh Performance: Remove Unused Columns
A company has a Power BI dataset that imports data from a SQL Server database. The dataset includes a table with 10 million rows. The data model uses a single table and does not include any calculated columns or measures. The report users report that the dataset refresh takes too long. Which action should you take to improve refresh performance?
Quick Answer
The answer is to remove unused columns from the table in Power Query. This is correct because every unnecessary column adds substantial I/O and memory overhead during the import process, especially with a 10 million row dataset; by stripping out these columns before the data is loaded, you directly reduce the volume of data transferred and processed, which is the most effective way to improve power bi import refresh performance. On the Microsoft Power BI Data Analyst PL-300 exam, this scenario tests your understanding of data shaping in Power Query as a foundational optimization technique—a common trap is to assume that adding indexes or changing the storage mode is the fix, but the simplest and most impactful step is to eliminate columns that aren’t used in reports or the model. Remember the memory tip: “If it’s not in the view, don’t let it through”—every column you keep is a column Power BI must refresh.
⚠ Common exam trap
Watch out — candidates often confuse refresh performance with query performance, leading them to choose DirectQuery (Option C) which solves query latency but does not improve the import refresh time that the question explicitly targets.
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 unused columns from the table in Power Query.
Removing unused columns from the table in Power Query reduces the amount of data loaded into the Power BI dataset. With 10 million rows, every unnecessary column adds significant I/O and memory overhead during refresh. This directly improves refresh performance by minimizing the data volume transferred and processed.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the scheduled refresh frequency to every 15 minutes.
Why it's wrong here
Increasing frequency does not reduce refresh time.
- ✗
Enable Query Folding on all steps in Power Query.
Why it's wrong here
Query Folding is already enabled by default; no steps are defined.
- ✗
Change the storage mode to DirectQuery.
Why it's wrong here
DirectQuery may reduce refresh time but changes query behavior and may not be suitable.
- ✓
Remove unused columns from the table in Power Query.
Why this is correct
Reduces data volume and improves refresh speed.
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Same concept, more angles
1 more way 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. A Power BI dataset is configured to use Import storage mode. The dataset includes a fact table with 100 million rows and several dimension tables. The report is slow when users interact with visuals. You need to improve query performance without changing the storage mode. Which action should you take?
medium- ✓ A.Create aggregations on the fact table.
- B.Increase the scheduled refresh frequency.
- C.Reduce the number of dimension tables.
- D.Enable 'Load to report' for all tables.
Why A: Creating aggregations on the fact table allows Power BI to pre-summarize data at higher granularity levels, reducing the amount of data scanned during query execution. Since the dataset uses Import mode, aggregations leverage the in-memory columnar storage to serve queries from pre-computed tables, significantly improving visual response times without altering the storage mode.
Last reviewed: Jun 11, 2026
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