PL-300 Model the data Practice Test 13 — 15 Questions

Question 1

You have the above measure in a Power BI model. The 'Date' table is marked as a date table and has a relationship to Sales[OrderDate]. The measure returns blank for all months. What is the most likely cause?

Accepted Answer

The Date table does not contain all dates in the continuous range. Option C is correct because DATESYTD requires a continuous date range. If the Date table does not contain all dates (e.g., missing weekends or holidays), DATESYTD may not work correctly. Option A is wrong because the relationship direction is fine. Option B is wrong because the Date table is marked as date table, so date filter direction is not an issue. Option D is wrong because the measure syntax is correct.

Answer

The relationship is set to filter in the wrong direction

Answer

The measure uses incorrect syntax for DATESYTD

Answer

The 'Date' table is not marked as a date table

Question 2

You have the above Power Query M script. What is the result of this transformation?

Accepted Answer

A table with one row per ProductID and columns: ProductID, TotalQty. Option D is correct because the script filters rows where OrderDate >= Jan 1 2023, removes the ProductDescription column, and groups by ProductID summing Quantity. The result is a table with one row per ProductID and a TotalQty column. Option A is wrong because it does not retain all columns. Option B is wrong because it aggregates. Option C is wrong because it does not keep individual rows.

Answer

A table with one row per ProductID and columns: ProductID, Quantity

Answer

A table with all sales rows for 2023 and columns: ProductID, Quantity

Answer

A table with all sales rows for 2023 and columns: OrderDate, ProductID, Quantity, TotalQty

Question 3

You have the above calculated column in a Power BI model. Some rows show blank values for Profit Margin even though Profit and SalesAmount are not blank. What is the most likely cause?

Accepted Answer

SalesAmount is zero for those rows. Option A is correct because DIVIDE returns blank if the denominator is zero or blank. If SalesAmount is zero, the division is undefined. Option B is wrong because DIVIDE handles division by zero gracefully. Option C is wrong because data types are not an issue. Option D is wrong because the syntax is correct.

Answer

The calculated column syntax is incorrect

Answer

The columns are not numeric

Answer

The DIVIDE function cannot handle large numbers

Question 4

You are building a star schema in Power BI. Which table design best supports filtering a sales fact table by product category?

Accepted Answer

Create a separate Product dimension table with category, related to Sales by ProductID.. Option B is correct because in a star schema, dimension tables like Product are separate from fact tables. Relating Product to Sales by a common key (ProductID) enables filtering of sales by category. Option A is wrong because storing category directly in the fact table leads to redundancy and poor performance. Option C is wrong because a single table with all data is a flat table, not a star schema. Option D is wrong because merging into one table removes the benefits of star schema design.

Answer

Use a single table containing all sales and product attributes.

Answer

Merge Sales and Product tables into one by appending rows.

Answer

Store product category in the Sales fact table.

Question 5

You have a date table with columns: Date, Year, Month, Quarter, Day. To enable time intelligence functions like TOTALYTD, what is the minimum requirement?

Accepted Answer

A separate date table with a continuous range of dates and a relationship to the fact table.. Option B is correct because time intelligence functions require a date table with continuous dates and a many-to-one relationship to the fact table's date column. Option A is wrong because a date column alone is not sufficient; the date table must be marked as a date table. Option C is wrong because marking the date table is required. Option D is wrong because a single table is not required; a separate date table is preferred.

Answer

Mark the date table as a date table in Power BI.

Answer

Combine date and fact tables into one table.

Answer

A single date column in the fact table.

Question 6

You need to create a calculated column that categorizes products based on price: 'Low' (<$10), 'Medium' ($10-$50), 'High' (>$50). Which DAX expression should you use?

Accepted Answer

SWITCH(TRUE(), Product[Price] < 10, "Low", Product[Price] <= 50, "Medium", "High"). Option A is correct because SWITCH evaluates conditions in order and returns the first match, which is appropriate for this scenario. Option B is wrong because IF cannot handle three categories efficiently. Option C is wrong because the syntax is incorrect (no condition after SWITCH). Option D is wrong because LOOKUPVALUE is for looking up values in another table, not for conditional logic.

Answer

SWITCH(Product[Price], <10, "Low", <=50, "Medium", "High")

Answer

LOOKUPVALUE(Category, Product[Price], Product[Price])

Answer

IF(Product[Price] < 10, "Low", Product[Price] <= 50, "Medium", "High")

Question 7

When creating a many-to-many relationship between two tables, what is a common approach to model this in Power BI?

Accepted Answer

Introduce a bridge table that contains the unique combinations.. Option B is correct because a bridge table resolves many-to-many relationships by creating two one-to-many relationships. Option A is wrong because a single many-to-many relationship without a bridge table is not supported directly. Option C is wrong because CROSSJOIN creates a Cartesian product, which is not correct. Option D is wrong because merging tables into one removes the relationship structure.

Answer

Use the CROSSJOIN DAX function in calculated tables.

Answer

Merge both tables into a single table.

Answer

Create a direct many-to-many relationship in the model.

Question 8

Which TWO actions are valid for improving query performance in DirectQuery mode?

Accepted Answer

Create aggregated tables to pre-summarize data.. Option A is correct because reducing columns in the table reduces the data retrieved. Option C is correct because creating summarized tables can reduce data volume. Option B is wrong because disabling relationship enforcement can lead to incorrect results. Option D is wrong because calculated columns often degrade performance in DirectQuery. Option E is wrong because Import mode is not available in DirectQuery.

Answer

Disable relationship enforcement to speed up joins.

Answer

Convert the model to Import mode.

Answer

Use calculated columns in the fact table.

Question 9

Which THREE considerations are important when designing a date table for time intelligence?

Accepted Answer

The date table must be marked as a date table in Power BI.. Option A is correct because a continuous date range is required. Option B is correct because marking as a date table is required for time intelligence. Option D is correct because a date table should have a relationship to the fact table. Option C is wrong because calculated columns are not a requirement. Option E is wrong because multiple date tables are not a requirement.

Answer

All date columns must be calculated columns.

Answer

The model must have exactly one date table.

Question 10

Which TWO approaches can you use to implement row-level security (RLS) in Power BI?

Accepted Answer

Create roles with static filters.. Option A is correct because static RLS uses roles with filters based on fixed values. Option D is correct because dynamic RLS uses the USERNAME or USERPRINCIPALNAME function to filter based on the current user. Option B is wrong because column-level security is not RLS; it hides columns. Option C is wrong because object-level security restricts access to entire tables, not rows. Option E is wrong because Power BI does not support RLS based on groups directly; you need to use roles.

Answer

Assign users to security groups in the dataset.

Answer

Use column-level security to restrict row visibility.

Answer

Use object-level security to restrict rows.

Question 11

You have a table with a column 'Date' and a measure 'Total Sales'. You want to calculate the cumulative total of sales over time. Which DAX function should you use?

Accepted Answer

TOTALYTD(SUM(Sales[Amount]), 'Date'[Date]). Option C is correct because TOTALYTD calculates year-to-date cumulative totals. Option A is wrong because SUM adds all values, not cumulative. Option B is wrong because CALCULATE modifies filter context but does not inherently provide cumulative. Option D is wrong because DATESYTD returns a set of dates, not a cumulative sum.

Answer

SUM(Sales[Amount])

Answer

DATESYTD('Date'[Date])

Answer

CALCULATE(SUM(Sales[Amount]), ALL(Sales))

Question 12

You need to create a measure that calculates the average sales per transaction. The 'Sales' table has columns 'TransactionID' and 'Amount'. Which DAX expression is correct?

Accepted Answer

DIVIDE(SUM(Sales[Amount]), COUNTROWS(Sales)). Option D is correct because DIVIDE(SUM(Sales[Amount]), COUNTROWS(Sales)) calculates total sales divided by number of transactions. Option A is wrong because AVERAGE(Sales[Amount]) averages the amounts, not per transaction. Option B is wrong because AVERAGEX iterates over each row, averaging amounts, which is not per transaction if multiple rows per transaction. Option C is wrong because it sums amounts then divides by distinct transaction count, which would be correct if each transaction has one row, but not if multiple rows per transaction; however, DIVIDE is safer.

Answer

SUM(Sales[Amount]) / DISTINCTCOUNT(Sales[TransactionID])

Answer

AVERAGEX(Sales, Sales[Amount])

Answer

AVERAGE(Sales[Amount])

Question 13

Which THREE factors can cause a DAX measure to return BLANK unexpectedly?

Accepted Answer

Division by zero.. Option A is correct because division by zero returns BLANK. Option B is correct because referencing a column that doesn't exist causes BLANK. Option C is correct because BLANK propagation in arithmetic can cause BLANK. Option D is wrong because SUM ignores blanks. Option E is wrong because filters do not return BLANK; they return a table.

Answer

Using SUM on a column with blanks.

Answer

Using FILTER with a false condition.

Question 14

You have a table 'Orders' with columns: OrderID, CustomerID, OrderDate, Amount. You want to create a measure that shows the total number of orders. Which DAX function should you use?

Accepted Answer

COUNTROWS(Orders). Option B is correct because COUNTROWS counts the number of rows in a table. Option A is wrong because COUNT counts numeric values in a column, not rows. Option C is wrong because DISTINCTCOUNT counts distinct values. Option D is wrong because SUM adds values.

Answer

DISTINCTCOUNT(Orders[OrderID])

Answer

SUM(Orders[OrderID])

Answer

COUNT(Orders[OrderID])

Question 15

You are designing a data model for a report that shows sales by product category and by month. Which table configuration is most efficient?

Accepted Answer

A date dimension table, a product dimension table, and a sales fact table.. Option D is correct because a star schema with separate tables for date and product is the most efficient for filtering and performance. Option A is wrong because combining date and product into one dimension is not needed. Option B is wrong because a single table is inefficient. Option C is wrong because a bridge table is not needed for a simple star schema.

Answer

Two fact tables: one for date and one for product.

Answer

A single table with all columns.

Answer

One dimension table containing date and product attributes.

PL-300 Model the data Practice Test 13 — 15 Questions

Exhibit

PL-300 Model the data Practice Test 13 — 15 Questions

Exhibit