PL-300 - Model the Data (35% of the exam) - Section 2.3

Optimize model performance by reducing cardinality, choosing storage modes, and using aggregations.

Select import, DirectQuery, or dual storage modes and configure aggregations to balance query speed against data freshness. Use Performance Analyzer to identify slow visuals, and apply cardinality reduction and query folding to reduce load on the source system.

storage modesaggregationsquery foldingcardinality reductionPerformance Analyzer

Practice question for this objective

Free sampleModel the Datamedium

Performance Analyzer reports that a card visual spent 1,400 ms in one duration category and only 80 ms elsewhere. The semantic model uses Import storage mode. Which duration category most likely represents the 1,400 ms reading?

AThe Direct query category, covering query time against the data source.
BThe Visual display category, covering rendering and geocoding work.
CThe Other category, covering query preparation and waiting work.
DThe DAX query category, covering query time against the semantic model. Correct

DAX query covers semantic-model query time; Direct query only appears for DirectQuery tables. On an Import model, the DAX query duration is the time between the visual sending the query and the semantic model returning results. A long DAX query duration on a simple card almost always points to expensive measure logic or relationship traversal.

Why A is wrong: Direct query only appears when a table uses DirectQuery storage mode; an Import model does not generate a Direct query duration.

Why B is wrong: Visual display covers drawing on screen and retrieving images; a single card with a number rarely spends 1,400 ms in render time.

Why C is wrong: Other covers query preparation and waiting on other visuals; it is rarely the dominant cost for an isolated card.

Why D is correct: Correct. On an Import model, the DAX query duration is the time between the visual sending the query and the semantic model returning results.

See more PL-300 practice questions, answers explained.

Exam traps in Model the Data

Answers that look right on this material and are not. Each one is a distractor from a different question in the PL-300 bank for this domain.

Expand the visual entry and select Export to write the query to a json file.
Why it is wrong: Export writes a json file with all logged entries; it does not open the query in DAX query view ready to run.
Network latency time spent shipping the query bytes between the client and the service.
Why it is wrong: Network latency is discussed as an environment optimisation topic, not as a per-visual duration category Performance Analyzer reports.
Switch every measure to a calculated column so Vertipaq can compress the result.
Why it is wrong: Calculated columns generally compress less efficiently than Power Query computed columns and lengthen refresh; the guidance prefers custom columns in Power Query.

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