PL-300 Visualize and analyze the data Practice Question
You are building a Power BI report that uses a DirectQuery source. Which TWO of the following actions can improve report performance?
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
✓
Reduce the number of visuals on each report page.
Option C is correct because in DirectQuery mode every visual issues its own queries against the source, so reducing the number of visuals per page directly cuts the number of round trips and the volume of data the source must process. Option E is correct because pre-aggregating data into summary tables in the source means DirectQuery retrieves smaller, already-computed result sets instead of scanning large detail tables, which lowers query cost and latency. Option A is wrong because calculated columns in a DirectQuery model are computed at query time (or force the column to be materialized), adding processing overhead rather than reducing source load. Option B is wrong because disabling 'Reduce queries sent to the source' removes the optimization that consolidates and limits queries, increasing the number of queries hitting the source. Option D is wrong because complex, deeply nested DAX measures translate into more elaborate SQL and heavier source-side computation, degrading rather than improving performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add calculated columns to the model.
Why it's wrong here
Adding calculated columns in a DirectQuery model is counterproductive because each calculated column is evaluated row-by-row during query time and often forces Power BI to materialize the entire table, preventing efficient query folding to the source. This increases the number and complexity of SQL queries issued, adds memory pressure, and can cause noticeable performance degradation in reports that should be fast.
- ✗
Disable the 'Reduce queries sent to the source' option.
Why it's wrong here
The 'Reduce queries sent to the source' option is a built-in performance safeguard that consolidates multiple DAX operations into fewer source queries, especially when applying filters or sort orders. Disabling it removes that optimization, causing Power BI to send more granular and frequent queries to the underlying database, which increases round-trip latency and source server load — the opposite of what you want when tuning DirectQuery performance.
- ✓
Reduce the number of visuals on each report page.
Why this is correct
Every visual on a DirectQuery page issues its own set of DAX queries against the source, and filters from slicers/cross-filtering can cascade into additional queries. Reducing the number of visuals directly cuts the query count and the amount of data transferred, lowering page load time and easing the load on the data source while preserving performance.
- ✗
Use complex DAX measures with many nested functions.
Why it's wrong here
Complex DAX measures with deeply nested functions force the engine to construct intricate T-SQL statements with numerous subqueries and joins, which can exceed the source optimizer's ability to generate an efficient plan. This often results in slower query execution, higher source CPU usage, and longer timeouts — especially in DirectQuery where you cannot cache intermediate calculation results.
- ✓
Create summary tables in the data source to pre-aggregate data.
Why this is correct
Pre-aggregating data into summary tables at the source reduces the granularity of the rows Power BI must query, so each visual retrieves far fewer records and processes them faster. This shifts heavy calculation work to the source's scheduled ETL layer, letting DirectQuery run lean, indexed queries that return only the aggregated values needed by the report.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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