The answer is that performance may be impacted if the report requires aggregations from both sources, and certain DAX functions like time intelligence may not work correctly when referencing DirectQuery tables. This is because in a composite model, DirectQuery tables remain in the source database rather than being loaded into memory, so DAX functions that require in-memory data—such as `DATESYTD` or `TOTALYTD`—cannot operate on them, while imported tables support full in-memory calculations. On the PL-300 exam, this tests your understanding of storage mode limitations within composite models, often appearing as a trap where you might assume all DAX works uniformly across DirectQuery and import tables. A common memory tip is to think of DirectQuery as a “pass-through” connection: if a function needs to hold data locally (like time intelligence or `DISTINCTCOUNT` with complex filters), it will fail or behave unexpectedly. Remember: “DirectQuery is for live queries, not local calculations.”
PL-300 Visualize and analyze the data Practice Question
This PL-300 practice question tests your understanding of visualize and analyze 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 report that uses a composite model with DirectQuery and imported tables. Which two considerations should you keep in mind?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Some DAX functions may have limitations when used across storage modes
Option A is correct because in a composite model, DAX functions that require data to be in-memory (like time intelligence functions) may not work correctly when referencing DirectQuery tables, as those tables remain in the source database. Additionally, certain DAX functions (e.g., `DISTINCTCOUNT`, `VALUES`) can behave differently or have restrictions when used across storage modes, such as returning limited results or requiring specific filter contexts.
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.
✓
Some DAX functions may have limitations when used across storage modes
Why this is correct
Functions like STOCK, etc., may have restrictions.
Related concept
Read the scenario before looking for a memorised answer.
✗
Relationships can only be defined between tables of the same storage mode
Why it's wrong here
Relationships can cross modes.
✓
Performance may be impacted if the report requires aggregations from both sources
Why this is correct
Queries to both sources can slow down.
Related concept
Read the scenario before looking for a memorised answer.
✗
DirectQuery tables cannot be related to imported tables
Why it's wrong here
They can be related.
✗
All measures must be created in the imported tables
Why it's wrong here
Measures can be in any table.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume all relationships must be within the same storage mode or that DirectQuery tables cannot be related to imported tables, but composite models explicitly allow cross-mode relationships, and the key limitation is on certain DAX functions and performance, not on relationship or measure placement.
Detailed technical explanation
How to think about this question
Under the hood, composite models use a dual-engine approach: the VertiPaq engine handles imported data, while the DirectQuery engine passes queries to the source database. When a measure references columns from both storage modes, Power BI may need to materialize intermediate results, which can lead to performance degradation or unexpected behavior with certain DAX functions (e.g., `CALCULATE` with `ALL` may not work as expected across modes). A real-world scenario is building a sales report where historical data is imported for fast slicing, but real-time inventory is DirectQuery; using `TOTALYTD` on the DirectQuery date column would fail because time intelligence functions require an in-memory date table.
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 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
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.
Visualize and analyze the data — This question tests Visualize and analyze the data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Some DAX functions may have limitations when used across storage modes — Option A is correct because in a composite model, DAX functions that require data to be in-memory (like time intelligence functions) may not work correctly when referencing DirectQuery tables, as those tables remain in the source database. Additionally, certain DAX functions (e.g., `DISTINCTCOUNT`, `VALUES`) can behave differently or have restrictions when used across storage modes, such as returning limited results or requiring specific filter contexts.
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.
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 →
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 report uses a composite model with a DirectQuery source and an imported table. The imported table has many rows, and the report is taking a long time to refresh. What is the most likely cause?
hard
A.Measures are using CALCULATE with multiple filter conditions
✓ B.The imported table is set to Dual storage mode, causing dependency on the DirectQuery source
C.The DirectQuery table is set to Import storage mode
D.The report contains many complex visuals that need to be rendered
Why B: In a composite model, when an imported table is set to Dual storage mode, it behaves as both Import and DirectQuery. During refresh, Power BI must check the DirectQuery source for consistency, which can significantly slow down the refresh process, especially with large imported tables. This dependency on the DirectQuery source is the most likely cause of the long refresh time.
Variation 2. You have a Power BI report that uses a composite model with both Import and DirectQuery sources. You need to ensure that a measure using SUMX performs well. What should you do?
medium
A.Disable relationships between tables
B.Use CALCULATE instead of SUMX
✓ C.Create a calculated column in the source system to pre-aggregate values
D.Replace SUMX with SUM and adjust the model
Why C: In composite models, iterating over DirectQuery tables can be slow. Option C is correct: move the calculation to the source (e.g., SQL view). Option A is wrong because reducing cardinality may not help. Option B is wrong because disabling relationships is not practical. Option D is wrong because changing to SUM might change logic.
Variation 3. You have a Power BI report that uses a composite model with a DirectQuery source (SQL Server) and a local imported table. The report includes a measure that calculates sales growth by comparing current year to previous year. Users report that the measure returns blank for months with no data in the current year. How should you modify the measure to show 0% growth instead of blank?
medium
A.Use ISBLANK(CurrentYear) in an IF statement.
B.Add a condition to check if PreviousYear = 0.
C.Use DIVIDE with an alternate result of 0.
✓ D.Use COALESCE(CurrentYear, 0) in the measure.
Why D: Option B is correct because COALESCE replaces blank with the next non-blank value, so if CurrentYear is blank but PreviousYear has data, it returns 0. Option A is wrong because ISBLANK would still return blank if CurrentYear is blank. Option C is wrong because it only handles division by zero. Option D is wrong because it replaces blank with 0 only for the denominator.
Variation 4. You have a Power BI report that uses a composite model with a DirectQuery source from Azure SQL Database and an imported table from Excel. You need to ensure that when a user filters the imported table, the DirectQuery table is also filtered accordingly. What should you configure?
hard
✓ A.Set the relationship direction to filter the DirectQuery table from the imported table.
B.Merge the imported table into the DirectQuery source.
C.Enable bidirectional cross-filtering on the relationship between the tables.
D.Create a calculated column in the DirectQuery table that references the imported table.
Why A: Option D is correct because setting a relationship between the DirectQuery table and the imported table, with the imported table as the filter direction, allows filtering across storage modes. Option A is wrong because a calculated column in the DirectQuery table would not automatically filter based on the imported table. Option B is wrong because enabling bidirectional cross-filtering on relationships between DirectQuery and imported tables is not supported in composite models. Option C is wrong because merging tables would change the data model and may not be necessary.
Variation 5. You have a Power BI report that uses a composite model with a DirectQuery source and an imported table. Users report that some visuals show incorrect totals when using measures that reference both sources. Which THREE conditions must be met to ensure correct results?
hard
✓ A.Ensure relationships are defined with appropriate cardinality and cross-filter direction
B.Set both sources to Dual storage mode
✓ C.Use measures that aggregate data at the appropriate granularity
D.Enable 'Reduce queries' in report settings
✓ E.Set 'Assume Referential Integrity' on relationships between sources
Why A: Options A, D, and E are correct. Setting 'Assume Referential Integrity' (A) allows Power BI to optimize queries. Ensuring compatible relationships (D) is crucial for composite models. Using measures that aggregate correctly across storage modes (E) is necessary. Option B is incorrect because dual storage mode is not required. Option C is incorrect because query reduction does not fix incorrect totals.
Last reviewed: Jun 24, 2026
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