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PL-900 Practice Question: A data analyst notices that a Power BI report…
A data analyst notices that a Power BI report takes a long time to load when filtering by a specific date range. The data source is a SQL Server view that contains millions of rows. What is the most effective way to improve performance?
⚠ Common exam trap
A common mix-up: candidates assume Import mode is always faster for large datasets, but they overlook that DirectQuery with source-side optimization avoids transferring all data and leverages the database's native query processing power.
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 DirectQuery and optimize the SQL view with indexes and filters
The performance bottleneck is at the data source level—millions of rows in a SQL Server view. Using DirectQuery with optimized indexes and filters pushes query execution back to SQL Server, allowing it to leverage database-level performance features like index seeks and query plan caching. This reduces the amount of data transferred and processed in Power BI, directly addressing the root cause of slow filtering.
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 calculated column for the date range filter
Why it's wrong here
Calculated columns are computed during load and do not help with filtering performance.
- ✓
Use DirectQuery and optimize the SQL view with indexes and filters
Why this is correct
DirectQuery with query folding pushes processing to the source, and indexes improve performance.
- ✗
Switch from DirectQuery to Import mode
Why it's wrong here
Import mode loads all data into memory, which may still be slow for millions of rows.
- ✗
Hide unnecessary columns in the report
Why it's wrong here
Hiding columns does not reduce data volume or query time.
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