PL-300 Practice Test 5 — 25 Questions

Question 1

You are connecting to a SQL Server database using Import mode. The source table contains a column 'SalesAmount' with a few null values. You need to replace nulls with 0 before loading. What is the most efficient step to achieve this in Power Query Editor?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Use 'Replace Values' to replace null with 0. 'Replace Values' in Power Query Editor is the most efficient way to replace null values in a column with 0. It directly transforms the column in a single step without requiring additional logic or table scans, and it generates a clean M code step (Table.ReplaceValue) that operates natively on the column's nulls.

Answer

Use 'Replace Errors' with value 0

Answer

Use 'Fill Down' to propagate previous values

Answer

Add a custom column with an if statement

Question 2

You are a data analyst at a retail company. You are building a Power BI report to analyze sales performance across multiple stores. The source data comes from an Azure SQL Database that contains a table 'Sales' with columns: StoreID, ProductID, SaleDate, Quantity, and Amount. The database also has a 'Stores' table with StoreID and StoreName, and a 'Products' table with ProductID, ProductName, and Category. You need to create a data model that supports filtering by store, product category, and date, and also allows calculation of year-over-year sales growth. You want to minimize the model size and ensure optimal performance. The data volume is large (millions of rows). You must design the data model. What should you do?

Accepted Answer

Import Sales, Stores, and Products tables, create a separate date table using CALENDAR, and establish relationships between Sales and dimension tables.. It follows the star schema best practice: importing dimension tables (Stores, Products, a dedicated Date table) and the fact table (Sales) separately, then creating relationships. This minimizes model size by avoiding data duplication and enables efficient filtering by store, product category, and date. The separate date table is essential for accurate year-over-year calculations using DAX time intelligence functions like SAMEPERIODLASTYEAR, which require a continuous date range.

Answer

Import all tables as they are and create a single flat table by merging Sales, Stores, and Products in Power Query.

Answer

Import Sales table only and create calculated columns for StoreName and ProductName using RELATED.

Answer

Import Sales table and use the auto date/time feature for time intelligence.

Question 3

You have a Power BI report that shows sales by region. Users report that the map visual is not displaying data for some countries. What is the most likely cause?

Accepted Answer

The geographic data is not categorized correctly in the Data pane.. The most likely cause is that the geographic data is not categorized correctly in the Data pane. Power BI map visuals rely on the data category (e.g., Country, State, City) assigned to each field to correctly geocode and plot locations. If a field containing country names is left as 'Text' or 'Uncategorized', Power BI may fail to recognize the values as geographic entities, resulting in missing data points on the map.

Answer

The report page filter is excluding those countries.

Answer

The map visual is limited to 30 data points.

Answer

The map visual only supports US addresses.

Question 4

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. SWITCH is the correct DAX function because it evaluates an expression (the sales amount) against a series of conditions and returns a corresponding result for each condition. In this scenario, you can use SWITCH(TRUE(), [Sales] < 1000, 'Low', [Sales] < 5000, 'Medium', 'High') to create a calculated column that categorizes values row by row. SWITCH is designed for multiple conditional branches, making it the most efficient and readable choice for this three-tier categorization.

Answer

IF

Answer

CALCULATE

Answer

FORMAT

Question 5

You need to deploy a Power BI report from a development workspace to a production workspace. You want to ensure that the report uses the production dataset connection string without manual changes. What should you use?

Accepted Answer

Configure a deployment pipeline with parameter rules to override the data source.. Deployment pipelines in Power BI allow you to define parameter rules that automatically override data source connection strings when content is deployed from development to production. This ensures the report uses the production dataset without any manual post-deployment changes, maintaining consistency and reducing human error.

Answer

Manually update the data source in the production workspace after deployment.

Answer

Use a Power BI template (.pbit) and change the connection string before publishing.

Answer

Publish the report directly to the production workspace and update the dataset.

Question 6

A data model has a table 'Orders' with columns: OrderID, CustomerID, OrderDate, Amount. There is a 'Customers' table with columns: CustomerID, CustomerName. To analyze orders by customer, what is the best practice for modeling the relationship?

Accepted Answer

Create a one-to-many relationship from Customers to Orders with single direction.. In a star schema, the Customers table (dimension) should have a one-to-many relationship to the Orders table (fact) filtered from the dimension side. This single-direction filter propagation ensures that when a customer is selected, only their orders are shown, while preventing unwanted cross-filtering from orders back to customers. This is the standard best practice for modeling dimension-to-fact relationships in Power BI.

Answer

Create a one-to-one relationship between Customers and Orders based on CustomerID.

Answer

Create an inactive relationship and use USERELATIONSHIP in measures.

Answer

Create a many-to-one relationship from Orders to Customers with both directions.

Question 7

You are preparing a Power BI report that uses data from Azure SQL Database. The data includes a date column that needs to be used in time intelligence calculations. You want to ensure that the date column is recognized as a date table in the data model. What should you do?

Accepted Answer

In the model view, mark the table as a date table by selecting the date column.. Marking a table as a date table in the model view explicitly tells Power BI that the table contains a complete set of dates for time intelligence calculations. This ensures that DAX functions like TOTALYTD, SAMEPERIODLASTYEAR, and DATEADD work correctly by using the marked date column as the primary date reference for the model, rather than relying on auto-generated date hierarchies.

Answer

Set the data type of the date column to Date.

Answer

Use the DAX function DATEADD to create a date table.

Answer

Create a calculated column using DATEVALUE to convert the date.

Question 8

A company has a Power BI semantic model that uses DirectQuery to a SQL Server database. The model contains a large fact table with sales data. Users report that reports using this model are slow. Which design change would most improve query performance?

Accepted Answer

Remove unnecessary columns from the fact table.. Removing unnecessary columns from the fact table reduces the amount of data that must be transferred from SQL Server to Power BI for each query. In DirectQuery mode, every report interaction sends a query to the source database, so fewer columns mean smaller result sets and faster query execution. This directly addresses the performance bottleneck caused by a large fact table without changing the underlying storage mode.

Answer

Remove all relationships between tables.

Answer

Switch the model to Import mode.

Answer

Disable the 'Reduce queries' option in report settings.

Question 9

You are creating a Power BI report from a SQL Server database that contains a table Orders with columns: OrderDate, CustomerID, ProductID, Quantity, UnitPrice. You need to build a star schema. Which THREE tables should you create? (Choose three.)

Accepted Answer

Date dimension table with date attributes.. In a star schema, dimension tables contain descriptive attributes (e.g., dates, products, customers) and are connected to a central fact table. For the Orders table, a Date dimension (B) is essential for time-based analysis, a Product dimension (C) provides product details, and a Customer dimension (D) stores customer attributes. These three dimensions normalize the data and enable efficient slicing and dicing in Power BI.

Answer

OrderDetails table with line items.

Answer

Sales fact table with measures.

Question 10

You are building a Power BI model that includes a table 'Orders' with columns: OrderID, CustomerID, OrderDate, and TotalAmount. You also have a table 'Customers' with columns: CustomerID, CustomerName, and Segment. You need to create a relationship between Orders and Customers on CustomerID. Which relationship configuration should you choose to ensure that filtering Customers by Segment correctly filters Orders?

Accepted Answer

One-to-many relationship from Customers to Orders. A one-to-many relationship from Customers (one side) to Orders (many side) with single-direction cross-filtering ensures that filtering Customers by Segment correctly filters Orders. Option B (many-to-one) would reverse the cardinality and, by default, would not allow filtering from Customers to Orders. Option C is unnecessary and can cause ambiguity. Option D is inappropriate as one customer can have many orders.

Answer

Many-to-one relationship from Orders to Customers

Answer

Many-to-many relationship with a bridge table

Answer

One-to-one relationship

Question 11

You are transforming data in Power Query. A column named 'SalesAmount' contains values as text with a dollar sign and thousands separator, e.g., "$1,234.56". You need to convert this column to a decimal number for analysis. What is the most efficient sequence of transformations?

Accepted Answer

Use Replace Values to remove '$' and ',', then change data type to Decimal Number.. It explicitly removes both the dollar sign and the comma using Replace Values before changing the data type to Decimal Number, ensuring proper conversion without errors. Option A is inefficient; splitting the column is unnecessary when simple replacements work. Option B would fail because Power Query cannot automatically parse currency symbols and thousands separators from text when changing data type directly. Option D appears similar but specifies 'Decimal' instead of 'Decimal Number', which is not a valid data type in Power Query, leading to an error or incorrect result.

Answer

Split the column by delimiter and keep the numeric part, then change data type.

Answer

Change data type to Decimal Number directly; Power Query will automatically clean the values.

Answer

Use Replace Values to remove '$' and ',' then change data type to Decimal.

Question 12

A data model contains a Date table and a Sales table. You need to create a measure that calculates total sales for the previous year. Which DAX function should you use?

Accepted Answer

SAMEPERIODLASTYEAR. SAMEPERIODLASTYEAR is the correct DAX function for calculating total sales for the previous year because it returns a set of dates shifted back by exactly one year while preserving the current filter context (e.g., month, quarter). This function is specifically designed for year-over-year comparisons and works seamlessly with a Date table marked as a date table in the model. Option B: DATEADD can also shift dates by one year but requires specifying the interval and number of intervals, making it less direct for this specific requirement. Option C: PARALLELPERIOD returns the entire parallel period (e.g., full year) regardless of current granularity, which does not preserve the same relative period. Option D: PREVIOUSYEAR returns the entire previous year, not the same period shifted back, so it does not maintain month-over-month or quarter-over-quarter comparisons.

Answer

DATEADD

Answer

PARALLELPERIOD

Answer

PREVIOUSYEAR

Question 13

A Power BI report shows a bar chart with sales by region. When users click on a region, they expect a line chart on the same page to filter to that region's sales over time. However, the line chart does not respond to the click. What is the most likely cause?

Accepted Answer

The interaction between the bar chart and line chart is set to 'None'.. In Power BI, visual interactions control how one visual affects another when clicked. By default, cross-filtering and cross-highlighting are enabled, but if the interaction between the bar chart and line chart is explicitly set to 'None', clicking a region on the bar chart will not filter or highlight the line chart. This is the most common cause when a visual fails to respond to clicks on another visual.

Answer

The line chart uses a continuous axis that cannot be filtered.

Answer

The bar chart is not set as a slicer.

Answer

The line chart has a legend with too many items.

Question 14

A Power BI developer has a fact table that contains sales data at the transaction level. The table includes columns: TransactionID, ProductID, CustomerID, DateKey, Quantity, UnitPrice, Discount, and SalesAmount. The developer wants to create a measure for total sales after discount. Which approach is best for performance and accuracy?

Accepted Answer

Add a calculated column in Power Query: NetAmount = Quantity * UnitPrice - Discount, then create a measure: SUM(Sales[NetAmount]). It performs the net amount calculation at the row level in Power Query (M), which is computed during data refresh and stored in the table. This avoids runtime row-by-row iteration in DAX, making the measure SUM(Sales[NetAmount]) a simple, highly efficient aggregation. It ensures both performance and accuracy, as the discount is applied per transaction before aggregation.

Answer

Create a measure: SUM(Sales[SalesAmount]) - SUM(Sales[Discount])

Answer

Create a measure: SUMX(Sales, Sales[Quantity] * Sales[UnitPrice] - Sales[Discount])

Answer

Create a measure: SUM(Sales[Quantity] * Sales[UnitPrice]) - SUM(Sales[Discount])

Question 15

Drag and drop the steps to configure a scheduled refresh for a dataset in the Power BI service into the correct order.

Accepted Answer

Navigate to the dataset in the Power BI service and open its settings, then expand the 'Scheduled refresh' section, then set the refresh frequency and time windows, then click 'Apply' to save.. Scheduled refresh is configured in the dataset settings, enabling automatic updates at specified intervals.

Answer

Set the refresh frequency and time windows, then expand the 'Scheduled refresh' section, then navigate to the dataset in the Power BI service and open its settings, then click 'Apply'.

Answer

Navigate to the dataset in the Power BI service and open its settings, then expand the 'Scheduled refresh' section, then click 'Apply', then set the refresh frequency and time windows.

Answer

Expand the 'Scheduled refresh' section, then navigate to the dataset in the Power BI service and open its settings, then set the refresh frequency and time windows, then click 'Apply'.

Question 16

You are importing data from a SQL Server database. The source table has a column 'ModifiedDate' of type datetime2. In Power Query, you want to ensure that only rows modified within the last 7 days are loaded. Which THREE steps should you take?

Accepted Answer

Use a parameter for the date range and reference it in the filter.. Using a parameter for the date range and referencing it in the filter allows for dynamic, maintainable filtering in Power Query. This approach leverages Power Query's M language to apply a filter step that can be easily updated without modifying the query logic, ensuring only rows from the last 7 days are loaded during data refresh.

Answer

Load all rows and then use a DAX filter in the data model.

Answer

Split the column into date and time and then filter on the date part.

Question 17

Which TWO of the following are valid DAX functions for time intelligence?

Accepted Answer

TOTALYTD. TOTALYTD is a valid DAX time intelligence function that calculates the year-to-date value of an expression, typically used with a date column to aggregate data from the start of the year to the current context. It requires a properly marked date table with continuous dates to function correctly.

Answer

RANKX

Answer

SUM

Answer

CALCULATE

Question 18

You have a Power BI report with a page that contains a bar chart showing sales by product category. You want to allow users to click on a bar and navigate to a different report page that shows detailed sales for that category. Which feature should you use?

Accepted Answer

Drillthrough. Drillthrough is the correct feature for navigating from a summary visual to a detail page for a specific data point. Cross-filtering only filters other visuals on the same page. Bookmarks are for saved views. Report page tooltips are for hover details. Custom visuals are not needed.

Answer

Bookmarks

Answer

Report page tooltips

Answer

Cross-filtering

Question 19

You are a Power BI administrator for a large enterprise. You have a Power BI semantic model that uses a single large fact table named Sales (100 million rows) and several dimension tables. The model is used by multiple departments, each with different row-level security (RLS) rules based on the SalesRegion column. You have implemented RLS using static roles. However, you notice that when users from different departments view the same report page, the query performance varies significantly. You suspect that the RLS filters are causing the performance difference. You need to investigate and optimize the RLS performance. What should you do first?

Accepted Answer

Use Power BI Performance Analyzer to capture query performance for each user role and analyze the generated DAX queries in DAX Studio.. Using Power BI Performance Analyzer allows you to capture query performance for each user role, and analyzing the generated DAX queries in DAX Studio helps identify which queries are slow and whether RLS is the cause. This is the first logical step to diagnose the performance variation. Option A (increasing memory) may not address RLS-specific issues. Option C (converting to dynamic RLS) is a potential optimization but not the initial diagnostic step. Option D (removing RLS and using bookmarks) is not a recommended security approach and would not investigate the root cause.

Answer

Increase the data model's memory limit in Premium capacity.

Answer

Convert all RLS roles to use dynamic RLS with USERPRINCIPALNAME.

Answer

Remove all RLS roles and implement security at the report level using bookmarks.

Question 20

You have a Power BI semantic model that uses DirectQuery to an Azure Synapse Analytics dedicated SQL pool. The model is used by a real-time dashboard. Users report that the dashboard is slow. You need to improve query performance without changing the source system. Which action should you take?

Accepted Answer

Reduce the number of visuals on the dashboard and apply page-level filters. Reducing the number of visuals and applying page-level filters directly reduces the number of queries sent to the Azure Synapse Analytics dedicated SQL pool via DirectQuery. Since the source system cannot be changed, the only way to improve performance is to minimize the query load from the dashboard. Page-level filters ensure that only relevant data is queried, and fewer visuals mean fewer separate queries, which collectively reduces latency.

Answer

Create aggregations on the fact table

Answer

Enable dual storage mode for all tables

Answer

Disable the 'Reduce queries' option in Power BI Desktop