Knowledge Check

1.

A report author notices that a table visual takes longer to load than other visuals on the same page. In Performance analyzer, the DAX query time is 4,200 ms while the visual display time is 150 ms. What should the report author investigate first?

The rendering performance of the table visual

The measures or filter patterns used by the visual's DAX query

The network connection between the client and the Power BI service

2.

A measure calculates the same CALCULATE expression three times within its formula. What DAX optimization technique most directly addresses this inefficiency?

Replace iterator functions with aggregation functions

Use a VAR to store the CALCULATE result and reference it in the RETURN expression

Move the calculation to a Power Query computed column

3.

A semantic model contains a column that stores order timestamps to the millisecond, but reports only group data by date. Which cardinality reduction technique is most appropriate?

Remove the column entirely from the model

Convert the column data type from datetime to text

Truncate the column to date precision in Power Query before loading

4.

An organization has a DirectQuery model with a large fact table containing billions of rows. Reports frequently query the data at the monthly and regional level. What approach helps accelerate these summary-level queries?

Implement aggregations that store summarized data at the monthly and regional level

Add FILTER expressions to each measure to limit the data scanned

Convert all dimension tables to DirectQuery storage mode

5.

A report page with 25 visuals loads slowly. Performance analyzer shows that individual DAX query times are under 200 ms per visual, but the total page load exceeds 10 seconds. What is the most likely cause?

The individual measures need DAX optimization

The sheer number of visuals is generating too many sequential queries

The semantic model has high-cardinality columns that need to be reduced

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