PL-300 Practice Test 16 — 15 Questions

Question 1

You are building a Power BI semantic model that uses a large fact table from a data warehouse. The fact table has a date column and you want to create a date dimension. The organization requires that the date dimension includes all dates from 2010 to 2030, including weekends and holidays. What is the best practice for creating the date dimension?

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

Accepted Answer

Create a date table in Power Query by generating a list of dates from 1/1/2010 to 12/31/2030 and then add columns for attributes. It follows the best practice of creating a dedicated date dimension table in Power Query, which ensures full control over the date range (2010–2030) and allows you to add custom attributes like holidays. This approach avoids relying on the fact table's date column, which may have gaps or missing dates, and ensures the date dimension is complete and independent for robust time intelligence calculations.

Answer

Use the CALENDAR function in DAX to generate the date range

Answer

Mark the date column from the fact table as a date table and disable Auto Date/Time

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Create a date dimension by using DISTINCT on the fact table's date column

Question 2

You need to create a measure that calculates the year-over-year growth percentage for sales. Which DAX function should you use?

Accepted Answer

SAMEPERIODLASTYEAR. The SAMEPERIODLASTYEAR function is the correct choice for calculating year-over-year growth because it shifts the current filter context back by one year, returning a set of dates exactly one year prior. This allows you to compute the prior year's sales and then derive the growth percentage using a formula like (Current Sales - Prior Year Sales) / Prior Year Sales.

Answer

DATEADD

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PARALLELPERIOD

Answer

PREVIOUSYEAR

Question 3

Which THREE factors should you consider when designing a star schema in Power BI?

Accepted Answer

A separate date table should be created for time intelligence.. A separate date table is required for time intelligence functions in Power BI because DAX time intelligence functions (e.g., TOTALYTD, SAMEPERIODLASTYEAR) rely on a continuous, contiguous date range with no gaps. Power BI automatically marks a table as a date table only if it contains a complete set of dates from the earliest to the latest transaction, enabling functions like DATEADD and DATESBETWEEN to work correctly across all granularities.

Answer

Use natural keys instead of surrogate keys in dimension tables.

Answer

Use a snowflake schema to reduce data redundancy.

Question 4

You need to create a Power BI data model that includes a date dimension. The source data contains a table with a Date column covering 2015-2025. You want to ensure that all dates in the model have a contiguous range for time intelligence. What should you do?

Accepted Answer

Create a calculated table using CALENDAR to generate a continuous date range and mark it as a date table.. The CALENDAR function creates a calculated table (not a column) that generates a contiguous range of dates, which is essential for accurate time intelligence calculations such as YTD or QoQ. After creating this calculated table, you can mark it as a date table to enable DAX time intelligence functions. Although the option wording mistakenly says 'calculated column', the intent is to create a separate date table using CALENDAR, which is the proper method to ensure no gaps in the date dimension.

Answer

Hide the existing Date column and rely on auto date/time.

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Add a calculated column for year and month from the existing Date column.

Answer

Use the existing Date column as the date table and mark it as a date table.

Question 5

You are building a Power BI report that uses a live connection to an Azure Analysis Services (AAS) tabular model. Users need to be able to filter data using a slicer that shows only products that have been sold in the current year. What should you do?

Accepted Answer

Create a calculated table in the AAS model that returns only products sold in the current year. A calculated table in the AAS model can be created using DAX to dynamically return only products sold in the current year (e.g., using FILTER, CALCULATETABLE, YEAR, and TODAY functions). This table is available in Power BI via live connection and can be used as the slicer source. Option A is wrong: a calculated column in the Product table is static at process time and does not dynamically filter to current year; it also adds a column to the entire table, not a subset. Option B is wrong: a visual-level filter on the slicer relies on the underlying data model; with live connection, you cannot create new tables in Power BI Desktop, and filtering on a date condition would require the slicer to use a field from a different table, which is not straightforward or recommended. Option D is wrong because live connections to AAS do not allow creating calculated tables in Power BI Desktop; all data modeling must be done in the source model.

Answer

Add a calculated column to the Product table in the AAS model that marks products sold this year

Answer

Use a filter on the slicer visual to show only products where sales year equals current year

Answer

Create a calculated table in Power BI Desktop using DAX to filter products

Question 6

Which THREE of the following are valid reasons to create a calculated table in Power BI?

Accepted Answer

To create a date table that is not available in the data source.. Calculated tables in Power BI are created using DAX and stored in memory, allowing you to generate a date table when no suitable date table exists in the data source. This is a common pattern to ensure a complete date range for time intelligence functions, as Power BI requires a continuous date table for functions like TOTALYTD or SAMEPERIODLASTYEAR.

Answer

To add a column that computes a value based on other columns in the same table.

Answer

To combine two tables by merging columns from one table into another.

Question 7

A Power BI developer needs to model data from two sources: an on-premises SQL Server database and a cloud-based Salesforce instance. The developer wants to create a star schema in Power BI. Which approach should the developer use to combine the data?

Accepted Answer

Use Power Query in Power BI Desktop to import both sources and merge/append queries as needed.. Power Query in Power BI Desktop is the appropriate tool to import data from both an on-premises SQL Server database and a cloud-based Salesforce instance, allowing the developer to merge or append queries as needed to shape the data into a star schema. This approach supports combining disparate sources into a single import model, which is essential for creating a star schema with fact and dimension tables. Using Power Query ensures that all data is loaded into memory, enabling fast query performance and full modeling capabilities.

Answer

Use DirectQuery for both sources and create relationships in the model.

Answer

Use Power BI dataflows to ingest both sources and then reference them in a dataset.

Answer

Create a composite model using DirectQuery for SQL Server and Import for Salesforce.

Question 8

You are preparing data from multiple sources for a Power BI report. You need to create a star schema with a single fact table and several dimension tables. Which of the following is a best practice when designing the data model?

Accepted Answer

Ensure each dimension table has a unique key and contains descriptive attributes.. In a star schema, dimension tables should have a unique key (surrogate or natural) and contain descriptive attributes to enable filtering and grouping in Power BI. This ensures efficient relationships with the fact table and supports intuitive report interactions. Option C directly aligns with this best practice.

Answer

Include calculated measures in dimension tables.

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Normalize dimension tables into multiple related tables.

Answer

Use natural keys from the source system as the primary key in dimension tables.

Question 9

Which THREE are best practices for managing relationships in Power BI? (Select exactly 3.)

Accepted Answer

Hide foreign key columns in dimension tables to prevent misuse. Options B, C, and E are correct. Option B: Hiding foreign key columns in dimension tables prevents users from accidentally using them in visuals, which is a best practice. Option C: Single-direction cross-filtering is recommended to avoid ambiguity and performance issues; bidirectional should only be used when necessary. Option E: Ensuring data types match between related columns is essential for creating valid relationships. Option A is incorrect because many-to-many relationships should be avoided when possible; they add complexity and can negatively impact performance. Option D is incorrect because setting cross-filter direction to both is not recommended by default—it can lead to ambiguous filtering and degraded performance.

Answer

Use many-to-many relationships whenever possible to simplify the model

Answer

Always set cross-filter direction to both to allow full interactivity

Question 10

You are a Power BI developer for a financial services company. You are preparing data from multiple sources: a CSV file containing daily stock prices (ticker, date, close_price), a SQL Server database with company information (ticker, company_name, sector), and an Excel file with quarterly earnings data (ticker, quarter, earnings_per_share). The CSV file has 5 years of daily data (approx 1.3 million rows). The SQL Server table has 5000 rows. The Excel file has 20,000 rows. You need to create a data model that allows users to filter by sector, company, and date range, and to calculate moving averages of stock prices and compare earnings over time. Performance is critical. You must decide the best approach to combine and model this data. What should you do?

Accepted Answer

Import all tables, create a date table with CALENDAR, and establish relationships: StockPrices[Date] -> DateTable[Date], StockPrices[Ticker] -> Company[Ticker], Earnings[Ticker] -> Company[Ticker], and create a many-to-many relationship between Earnings and DateTable using a bridge table.. Importing all tables into the in-memory VertiPaq engine ensures optimal performance for large datasets (1.3M rows) and complex calculations like moving averages. Creating a separate date table with CALENDAR enables proper time intelligence, while the bridge table resolves the many-to-many relationship between quarterly earnings and daily dates, allowing accurate filtering by sector, company, and date range without performance degradation.

Answer

Use DirectQuery for StockPrices (CSV) and import the other tables.

Answer

Import only StockPrices and Company, and use the auto date/time feature; ignore Earnings data.

Answer

Import all tables, then in Power Query merge StockPrices with Company and Earnings into a single flat table using left outer joins.

Question 11

A Power BI report uses a DirectQuery dataset connected to an Azure SQL Database. Users report that the report takes over 30 seconds to load. You need to improve performance without changing the data model. What should you recommend?

Accepted Answer

Enable 'Reduce cardinality by using aggregation' in the dataset settings.. Enabling 'Reduce cardinality by using aggregation' can improve DirectQuery performance by pre-aggregating data. Option A is wrong because increasing the maximum connections per user might help concurrency but not single query latency. Option C is wrong because converting to Import mode changes the data model approach and is not allowed if the requirement is to not change the data model. Option D is wrong because disabling 'Cross-report data binding' affects report interactivity but not query performance.

Answer

Increase the 'Maximum connections per user' setting in the Premium capacity.

Answer

Convert the dataset to Import mode.

Answer

Disable 'Cross-report data binding' in the report settings.

Question 12

You are preparing data from an Azure SQL Database. You need to ensure that sensitive columns (e.g., Social Security Numbers) are obfuscated in Power BI reports. Which TWO of the following approaches can you use? (Choose two.)

Accepted Answer

Configure dynamic data masking on the Azure SQL Database.. Azure SQL Database Dynamic Data Masking (DDM) obfuscates sensitive data at the database query level, so when Power BI connects to the database, the masked values are automatically returned for unauthorized users. This is a server-side approach that does not require changes to the Power BI report or data model.

Answer

Use row-level security (RLS) in Power BI to hide sensitive columns.

Answer

Use Microsoft Purview sensitivity labels to mask data.

Answer

Apply column-level security in Power BI Desktop.

Question 13

You manage a Power BI workspace used by the sales team. After updating a dataset with new columns, some users report that their reports show old data. You verify that the scheduled refresh completed successfully. What should you do first?

Accepted Answer

Open the report in Power BI Desktop, refresh the dataset, and republish.. When a dataset is updated with new columns in Power BI Desktop, the report's underlying data model must be refreshed and republished to the Power BI service. Even if the scheduled refresh completes successfully, it only refreshes the existing data structure; it does not automatically incorporate schema changes like new columns. Republishing the .pbix file ensures the service has the updated metadata and data.

Answer

Clear the users' browser cache.

Answer

Reconfigure the scheduled refresh to run more frequently.

Answer

Reset the on-premises data gateway.

Question 14

You are preparing data for a Power BI report that requires a date table with continuous dates from 2020 to 2025. Which TWO methods can you use to create this date table in Power Query?

Accepted Answer

Use the List.Dates function to generate a list of dates.. The List.Dates function in Power Query M generates a continuous list of dates by specifying a start date, a count of dates, and a step duration. This list can then be converted into a table, making it ideal for creating a date table directly in Power Query without leaving the data transformation environment.

Answer

Use the 'Enter Data' feature and manually type dates.

Answer

Use the CALENDAR DAX function in a calculated table.

Answer

Reference another query that already has dates.

Question 15

Which TWO data source types can be used with Power BI dataflows?

Accepted Answer

Power BI dataset. Power BI dataflows support a wide variety of data sources, including Power BI datasets (Option C), SharePoint Online lists (Option D), and Azure SQL Database (Option E). Therefore, all three options are valid data source types for dataflows. Option A (Exchange Online mailbox) and Option B (PDF file) are not supported as direct source types for dataflows.

Answer

Exchange Online mailbox

Answer

PDF file