PL-300 Practice Test 15 — 15 Questions

Question 1

You are designing a data model for a report that shows sales by region and product category. The source data includes a table 'Sales' with columns: Region, Category, SalesAmount. You also have separate tables 'Regions' and 'Categories' that contain additional attributes. You need to create a star schema. What should you do with the 'Region' and 'Category' columns in the 'Sales' table?

Accepted Answer

Remove them from the Sales table and use foreign keys to link to the dimension tables. Option C is correct because in a star schema, dimension tables contain the attributes, and fact tables contain foreign keys. Removing the columns and using foreign keys normalizes the model. Option A is wrong because keeping them duplicates data and increases model size. Option B is wrong because merging them is not necessary and can complicate the model. Option D is wrong because marking as date tables is irrelevant for region and category.

Answer

Keep them in the Sales table as attributes for simplicity

Answer

Merge the Regions and Categories tables into the Sales table

Answer

Mark the Sales table as a date table

Question 2

You need to create a calculated column in Power BI that categorizes sales amounts as 'Low', 'Medium', or 'High' based on the value. The column should be evaluated row by row. Which DAX function should you use?

Accepted Answer

SWITCH. Option B is correct. SWITCH is the appropriate DAX function for multiple conditions based on a single expression. Option A (IF) can be nested but is less efficient. Option C (CALCULATE) modifies filter context, not suitable for row-by-row categorization. Option D (FORMAT) changes data type, not categorization.

Answer

IF

Answer

CALCULATE

Answer

FORMAT

Question 3

You are designing a data model in Power BI that includes a fact table called 'Sales' and dimension tables 'Customer', 'Product', and 'Date'. The 'Sales' table contains columns: 'SalesID', 'CustomerID', 'ProductID', 'DateKey', 'Quantity', and 'Amount'. You need to ensure that the model follows star schema best practices and that filters from the 'Customer' table propagate correctly to the 'Sales' table. What should you do?

Accepted Answer

Create a one-to-many relationship from Customer (one side) to Sales (many side) based on CustomerID.. Option B is correct because a star schema requires a one-to-many relationship from dimension tables to fact tables, with the dimension table on the one side. Option A is wrong because many-to-many relationships would break star schema simplicity. Option C is wrong because bidirectional filtering can cause ambiguity and is not recommended by default. Option D is wrong because merging tables into a single flat table is the opposite of star schema.

Answer

Merge the Customer and Sales tables into a single flat table.

Answer

Set the cross-filter direction to Both on the relationship between Customer and Sales.

Answer

Create a many-to-many relationship between Customer and Sales using SalesID.

Question 4

Which TWO of the following are true about the Power BI composite model?

Accepted Answer

A composite model can combine DirectQuery and Import tables.. Option B is correct: composite models allow mixing DirectQuery and Import. Option D is correct: relationships can be created between tables from different sources. Option A is incorrect because composite models can have multiple storage modes. Option C is incorrect because calculated tables are limited. Option E is incorrect because composite models support many-to-many.

Answer

Composite models do not support many-to-many relationships.

Answer

All tables in a composite model must use the same storage mode.

Answer

Calculated tables are not supported in composite models.

Question 5

Refer to the exhibit. You are reviewing a DAX measure for month-over-month sales growth. The measure returns BLANK for all months. What is the likely issue?

Accepted Answer

The FILTER function removes all context from the Date table, causing PriorSales to be calculated over the entire table.. Option A is correct because the FILTER function uses ALL('Date') which removes all filters, so the PriorDate filter is not applied correctly. Option B is wrong because the date table has a relationship. Option C is wrong because the variable is correctly defined. Option D is wrong because the IF condition checks for zero, which may not be the issue.

Answer

The Date table is not marked as a date table.

Answer

The variable PriorDate returns a blank because MAX is used.

Answer

The IF condition incorrectly treats zero as blank.

Question 6

Refer to the exhibit. You are implementing row-level security (RLS) in Power BI. The JSON policy above is applied to the 'Sales' table. The user is in the 'SalesRegion' role. Which rows will the user see?

Accepted Answer

Rows where Region is 'North' only.. Option B is correct because the role filter overrides the table-level filter for users in that role. Option A is wrong because the role filter takes precedence. Option C is wrong because the role filter applies only to the role. Option D is wrong because RLS filters rows, not columns.

Answer

Rows where Region is 'North' and 'South'.

Answer

No rows, because there is a conflict.

Answer

Rows where Region is 'South' only.

Question 7

You have a table with columns 'Product', 'Category', and 'Sales'. You want to create a hierarchy that allows users to drill down from Category to Product. Which is the correct order to create the hierarchy?

Accepted Answer

Category -> Product. Option A is correct because hierarchies drill down from the highest level to the lowest. Option B is reverse. Option C is wrong because Sales is a measure, not a level. Option D is wrong because Product should be below Category.

Answer

Product -> Category -> Sales

Answer

Product -> Category

Answer

Sales -> Product -> Category

Question 8

You have a Power BI model with a table 'Sales' and a related 'Product' table. You want to count the number of distinct products sold. Which DAX expression should you use?

Accepted Answer

DISTINCTCOUNT(Sales[ProductID]). Option C is correct because DISTINCTCOUNT counts unique values. Option A is wrong because COUNT counts non-blank cells. Option B is wrong because COUNTA counts non-blank values. Option D is wrong because COUNTROWS counts rows.

Answer

COUNTROWS(Sales)

Answer

COUNT(Sales[ProductID])

Answer

COUNTA(Sales[ProductID])

Question 9

You need to create a calculated column that categorizes sales amounts into 'Low', 'Medium', and 'High' based on thresholds. Which DAX function should you use?

Accepted Answer

SWITCH. Option B is correct because SWITCH can evaluate multiple conditions. Option A (IF) can also work but becomes nested. Option C (LOOKUPVALUE) is for looking up values. Option D (CALCULATE) modifies filter context.

Answer

LOOKUPVALUE

Answer

CALCULATE

Answer

IF

Question 10

You have a data model with two relationships between Sales and Date: one active (OrderDateKey) and one inactive (ShipDateKey). The DAX expression uses USERELATIONSHIP(Sales[DateKey], 'Date'[DateKey]). Which date will be used for filtering?

Accepted Answer

Ship dates. Option B is correct because USERELATIONSHIP activates the specified relationship. The relationship is defined by the columns Sales[DateKey] and Date[DateKey]; if this matches the ShipDateKey relationship, it uses ship dates. Option A is incorrect because USERELATIONSHIP overrides the active relationship. Option C is incorrect because it activates the specified relationship. Option D is incorrect because the expression does not ignore filters.

Answer

Both order and ship dates

Answer

Order dates

Answer

No relationship, all dates

Question 11

You are analyzing a DAX query. What is the purpose of the 'Filter Context' column in the result?

Accepted Answer

It returns the total number of sales rows regardless of product category.. Option D is correct. CALCULATE(COUNTROWS('Sales'), ALL('Product')) counts all sales rows ignoring any filter on the Product table. This is useful to compare category-level sales against total sales. Option A is wrong because it does not count distinct products. Option B is wrong because it does not filter by current year. Option C is wrong because it counts sales rows, not product rows.

Answer

It returns the total sales for the current year, ignoring category.

Answer

It returns the number of product categories in the current context.

Answer

It counts the number of distinct products in the current filter context.

Question 12

You have a Power BI data model with a table 'Orders' that has columns: 'OrderID', 'OrderDate', 'CustomerName', 'Region', 'Product', 'Quantity', 'UnitPrice'. You want to create a measure that calculates total sales amount. Which DAX expression should you use?

Accepted Answer

Total Sales = SUMX(Orders, Orders[Quantity] * Orders[UnitPrice]). Option A is correct. The SUMX function iterates over each row and multiplies Quantity by UnitPrice, then sums the result. Option B is incorrect because SUM only works on a single column. Option C is incorrect because COUNTROWS counts rows, not amounts. Option D is incorrect because AVERAGE calculates average, not total.

Answer

Total Sales = COUNTROWS(Orders)

Answer

Total Sales = AVERAGE(Orders[Quantity]) * AVERAGE(Orders[UnitPrice])

Answer

Total Sales = SUM(Orders[Quantity] * Orders[UnitPrice])

Question 13

Which THREE of the following are valid data types in Power BI?

Accepted Answer

Whole Number. Option A, B, and D are valid data types in Power BI. Option C is not a standard data type; 'Currency' is not a separate type (it's Decimal). Option E is not a standard type; 'Time' is not separate from DateTime.

Answer

Currency

Answer

Time

Question 14

Which TWO of the following are best practices for designing a Power BI data model?

Accepted Answer

Use a star schema to reduce model complexity.. Options A and D are correct. Option A: Using a star schema reduces complexity. Option D: Using surrogate keys improves performance and stability. Option B is wrong because bi-directional cross-filtering can cause ambiguity. Option C is wrong because storing full names in the fact table increases size. Option E is wrong because calculated columns are less efficient than Power Query.

Answer

Store dimension attributes directly in fact tables for faster queries.

Answer

Enable bi-directional cross-filtering on all relationships.

Answer

Create calculated columns instead of Power Query transformations when possible.

Question 15

You have a table with columns 'Date', 'Sales', and 'Quantity'. You need to create a measure that calculates the average sales per transaction. Which DAX measure should you use?

Accepted Answer

AVERAGE(Sales[Sales]). Option B is correct because AVERAGE of Sales gives average per row. Option A totals sales, not average. Option C averages Quantity, not Sales. Option D divides total sales by total quantity, which is not average per transaction.

Answer

AVERAGE(Sales[Quantity])

Answer

DIVIDE(SUM(Sales[Sales]), SUM(Sales[Quantity]))

Answer

SUM(Sales[Sales])