PL-300 Practice Test 21 — 15 Questions

Question 1

You have a Power BI report that uses a measure to calculate year-over-year growth. Users report that the measure returns blank for certain months. The measure is: YoY Growth = DIVIDE(SUM(Sales[Amount]) - CALCULATE(SUM(Sales[Amount]), SAMEPERIODLASTYEAR('Date'[Date])), CALCULATE(SUM(Sales[Amount]), SAMEPERIODLASTYEAR('Date'[Date]))). What is the most likely cause of the blank values?

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

Accepted Answer

The Date table is missing dates for the previous year, causing SAMEPERIODLASTYEAR to return no data.. The correct answer is C: the Date table is missing dates for the previous year, causing SAMEPERIODLASTYEAR to return no data. SAMEPERIODLASTYEAR requires a contiguous, complete date range in a marked Date table to shift the current period back exactly one year; if prior-year dates are absent, the CALCULATE denominator returns BLANK, and DIVIDE yields BLANK for those months. Option A is not the cause because an unmarked date table would typically break time intelligence entirely rather than only certain months, and marking it is a prerequisite, not the root cause here. Option B is incorrect because DIVIDE returns BLANK only when the denominator is zero or BLANK, which is a symptom of the missing prior-year data, not the underlying cause. Option D is wrong because TOTALYTD computes a year-to-date aggregate, not a prior-year comparison, so it would not fix the YoY calculation.

Answer

The Date table is not marked as a date table.

Answer

The measure uses DIVIDE which returns blank when denominator is zero.

Answer

The measure should use TOTALYTD instead of SAMEPERIODLASTYEAR.

Question 2

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 B is correct because a star schema with a date dimension, a product dimension, and a sales fact table is the most efficient design for reporting sales by product category and by month. The fact table stores numeric measures such as sales amount at the grain of each transaction or monthly aggregate, while the dimension tables provide descriptive attributes for filtering and grouping. This separation reduces redundancy, improves query performance, and supports clean time intelligence and category-level analysis. Option A is wrong because date and product are descriptive dimensions, not fact tables. Option C is wrong because a single wide table causes redundancy and poor scalability. Option D is wrong because combining date and product attributes into one dimension creates a snowflake-like or denormalized structure that complicates grouping and time analysis.

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.

Question 3

You want to allow users to filter a report by a specific date range (e.g., last 30 days) without requiring manual selection. Which approach should you take?

Accepted Answer

Add a relative date slicer to the report page.. The correct option is B: add a relative date slicer to the report page. A relative date slicer is a built-in Power BI slicer type that lets users pick dynamic ranges such as 'last 30 days', 'last 3 months', or 'this year', and it automatically recalculates based on the current date without any manual selection. Option A (bookmarks) only switches between pre-defined static views and cannot dynamically follow the current date. Option C (a calculated column flagging the last 30 days) hard-codes a fixed window at refresh time and doesn't give users an interactive range control. Option D (a filter on the date field in the Filters pane) requires users to manually specify explicit start and end dates, which is exactly the manual selection the scenario wants to avoid.

Answer

Use bookmarks to switch between fixed date ranges.

Answer

Create a calculated column that flags rows within the last 30 days.

Answer

Apply a filter on the date field in the Filters pane.

Question 4

You need to design a Power BI report that displays sales trend over time. The data includes dates with missing values for weekends and holidays. Which visualization type and approach should you use to ensure accurate trend representation?

Accepted Answer

Line chart with a continuous date axis. A line chart with a continuous date axis (option C) is correct because a continuous axis plots dates proportionally along the X-axis, so gaps for weekends and holidays are preserved as empty intervals rather than being collapsed, giving an accurate time-based trend. Line charts are also the appropriate visual for showing trends over time, and the continuous axis correctly reflects the true temporal spacing between data points. Option A is wrong because a categorical date axis treats each date as an evenly spaced label, which distorts the time scale and hides gaps. Options B and D are wrong because bar charts are suited to comparing discrete categories rather than depicting continuous trends over time, regardless of axis type.

Answer

Line chart with a categorical date axis

Answer

Bar chart with a categorical date axis

Answer

Bar chart with a continuous date axis

Question 5

You are creating a Power BI report for a marketing team. The data is stored in a folder of CSV files on a network drive that is accessible from your computer. You need to combine all CSV files into a single table in Power BI. The files have the same structure. What should you do in Power Query?

Accepted Answer

Use the 'Combine Files' transform after connecting to the folder.. Power Query's 'Combine Files' transform is specifically designed to handle multiple CSV files with identical schemas stored in a folder. When you connect to the folder as a data source, Power Query automatically generates a sample file query and a transformation function that applies the same steps to all files, then combines the results into a single table. This is the most efficient and recommended approach for this scenario, avoiding manual appending or merging.

Answer

Connect to each CSV file individually and use Append Queries.

Answer

Use Merge Queries to join the files based on a common column.

Answer

Change the data source settings to treat the folder as a single data source.

Question 6

You are building a Power BI data model with multiple fact tables and dimension tables. One of the dimension tables has a one-to-many relationship with two fact tables, but the relationships are inactive. You need to create measures that use both fact tables and the dimension table without relying on user interactions to activate relationships. What should you do?

Accepted Answer

Use the USERELATIONSHIP function in the measure definition.. The USERELATIONSHIP function in DAX allows you to temporarily activate an inactive relationship within a measure definition. This enables you to use a dimension table with multiple fact tables without changing the model's default active relationships or relying on user interactions. By specifying the inactive relationship in the measure, you can perform accurate aggregations across both fact tables while maintaining the intended data model structure.

Answer

Merge the fact tables into one table.

Answer

Create calculated columns in the dimension table to relate to each fact table.

Answer

Change both relationships to active.

Question 7

You are connecting to an on-premises Oracle database from Power BI Service. The gateway is installed and configured. However, the scheduled refresh fails with an error indicating that the data source credentials are invalid. Which TWO steps should you take to resolve the issue? (Choose two.)

Accepted Answer

Update the data source credentials in the gateway settings in Power BI Service.. The scheduled refresh failure indicates that the stored credentials for the on-premises Oracle data source in Power BI Service are invalid. You must update the data source credentials in the gateway settings under 'Manage gateways' in Power BI Service to provide a valid username and password that the gateway can use to authenticate against the Oracle database. Option C is correct because the gateway machine requires the Oracle client software (e.g., Oracle Data Access Components or ODP.NET) to be installed and configured, and the gateway must have network connectivity to the Oracle server; verifying these ensures the gateway can reach and authenticate with the database.

Answer

Re-publish the Power BI report from Power BI Desktop.

Answer

Edit the data source settings in Power BI Desktop and republish.

Answer

Reinstall the on-premises data gateway.

Question 8

You are preparing data for a Power BI report. The source data contains a column with values like '1,234.56' formatted as text. You need to convert this to a numeric value for calculations. What is the best approach?

Accepted Answer

In Power Query Editor, replace the comma with an empty string, then change the data type to Decimal Number.. Power Query Editor provides the most efficient and scalable method for cleaning and converting text-based numeric data. By replacing the comma with an empty string and then changing the column data type to Decimal Number, you perform the transformation directly in the data preparation layer (M language), which is optimized for performance and avoids the overhead of DAX calculated columns. This approach also ensures the data remains clean for all downstream calculations.

Answer

In Power Query Editor, split the column by comma and then use the second part.

Answer

In DAX, create a calculated column using VALUE() after removing commas.

Answer

In Power Query Editor, use the 'Clean' transform to remove non-numeric characters.

Question 9

You are modeling data in Power BI that includes a table named SurveyResponses with columns: ResponseID, QuestionID, RespondentID, and AnswerText. Each respondent answers multiple questions. You need to create a measure that counts the number of unique respondents who answered a specific question. Which DAX measure should you use?

Accepted Answer

DISTINCTCOUNT(SurveyResponses[RespondentID]). DISTINCTCOUNT(SurveyResponses[RespondentID]) counts the number of unique RespondentID values in the table, which directly gives the count of unique respondents who answered a specific question when used in a filter context (e.g., with a slicer or visual grouping by QuestionID). This is the standard DAX pattern for counting distinct entities in a column.

Answer

COUNT(SurveyResponses[RespondentID])

Answer

COUNTROWS(SurveyResponses)

Answer

COUNTA(SurveyResponses[RespondentID])

Question 10

You are designing a data model that will support self-service analytics. You have a Sales table with over 100 million rows. Which of the following modeling approaches would provide the best query performance while maintaining a user-friendly experience?

Accepted Answer

Design a star schema with a fact table and dimension tables. A star schema with a fact table and dimension tables is correct because it minimizes the number of joins needed for queries, allowing the engine to scan a narrow fact table and use smaller dimension tables for filtering and grouping, which delivers the best query performance at scale (100M+ rows) while keeping the model intuitive for self-service users. The denormalized dimensions also make it easy for business users to drag and drop fields without navigating complex relationships. A single flat table (B) or a Power Query merge into one table (C) creates a very wide table with redundant data, increasing storage and scan time and hurting performance. A snowflake schema (D) normalizes dimensions into multiple related tables, adding extra joins that slow queries and complicate the user experience.

Answer

Create a single flat table with all columns

Answer

Import all tables into a single table using Power Query merge

Answer

Use a snowflake schema with multiple levels of dimensions

Question 11

You have a Power BI dataset with a fact table containing sales transactions and a dimension table for customers. The customer dimension includes a calculated column that uses the LOOKUPVALUE function to retrieve a customer's region from another table. The report performance is slow. What should you do to improve performance?

Accepted Answer

Remove the LOOKUPVALUE column and instead create a relationship between the tables.. The correct option is C: remove the LOOKUPVALUE calculated column and instead create a relationship between the tables. LOOKUPVALUE is a row-by-row DAX function that forces the formula engine to scan the target table for every row during processing and can also cause expensive query-time evaluations, whereas a proper relationship lets the VertiPaq engine resolve the lookup through the model's relationship graph, which is far more efficient. Since the customer dimension and the other table share a key, a relationship is the native, performant way to propagate the region attribute. Option A is unrelated to DAX performance and concerns Power Query folding behavior, not calculated columns. Option B (incremental refresh) only reduces refresh time and data volume loaded, not the cost of a LOOKUPVALUE column during report queries. Option D (more RAM) may mask memory pressure but does not address the inefficient row-by-row lookup logic.

Answer

Disable the 'Reduce queries sent to the source' option.

Answer

Enable incremental refresh on the fact table.

Answer

Increase the amount of RAM on the Power BI service capacity.

Question 12

Which TWO of the following are valid reasons to use a calculated table instead of a calculated column in Power BI?

Accepted Answer

To create a summary table that is not present in the source.. Option A is correct because a calculated table is created with DAX table expressions (for example, SUMMARIZE, SUMMARIZECOLUMNS, or DISTINCT) and can materialize a new summary table that does not exist in the source system, which is exactly what calculated tables are designed for. Option C is correct because a calculated table can be generated with CALENDAR or CALENDARAUTO to produce a continuous, unbroken date range, which is the standard way to build a dedicated date table for time intelligence functions like TOTALYTD or SAMEPERIODLASTYEAR. Option B is not correct because calculated tables are computed at refresh and stored in the model, so they do not inherently reduce model size by storing only aggregated data; aggregation reduction is achieved through Import mode aggregations, DirectQuery, or composite models, not by the mere choice of a calculated table. Option D is not correct because a column that depends on other columns in the same row is precisely the definition of a calculated column, which is evaluated row by row in the table, whereas a calculated table produces a whole table and cannot serve that row-level purpose.

Answer

To reduce model size by storing only aggregated data.

Answer

To create a column that depends on other columns in the same row.

Question 13

You are designing a Power BI dashboard for executive management. Which TWO practices should you follow to ensure the dashboard is effective?

Accepted Answer

Use consistent color coding across visuals.. Option D is correct because consistent color coding across visuals lets executives instantly associate a color with a metric or category, reducing cognitive load and preventing misinterpretation when scanning multiple charts. Option E is correct because limiting the dashboard to the most important KPIs keeps the executive view focused on decision-relevant metrics, avoiding clutter and information overload that obscure the key message. Options A, B, and C do not belong: real-time refresh for all sources is unnecessary and costly when executives typically review daily or weekly trends, cramming many visuals onto one page harms readability rather than improving it, and a dark background is an aesthetic preference that can actually reduce contrast and legibility instead of guaranteeing effectiveness.

Answer

Configure real-time data refresh for all data sources.

Answer

Include as many visuals as possible on a single dashboard page.

Answer

Use a dark background to make visuals stand out.

Question 14

Refer to the exhibit. A user is a member of both 'HRManager' and 'Executive' RLS roles. The dataset uses DirectQuery. When the user views a report showing all employees, what data will they see?

Accepted Answer

Rows where Department is 'HR' or 'Executive' (union).. Rows where Department is 'HR' or 'Executive' (union). In Power BI row-level security, when a user belongs to multiple roles, the role filters are combined with OR logic, so the user sees the union of the rows permitted by each role. This behavior applies regardless of whether the dataset uses DirectQuery or Import mode, since RLS role membership is evaluated per user at query time. Options A, B, and C are incorrect because RLS does not grant all rows, does not intersect multiple role filters, and does not produce an empty result due to role conflicts.

Answer

All rows in the Employees table.

Answer

Only rows where Department is both 'HR' and 'Executive' (intersection).

Answer

No rows because roles conflict.

Question 15

You have a Power BI dataset that uses a live connection to an Azure Analysis Services (AAS) model. The AAS model has object-level security (OLS) that hides certain measures. Your Power BI report users need to see those measures. What should you do?

Accepted Answer

Modify the object-level security roles in Azure Analysis Services to include the measures.. Modify the object-level security roles in Azure Analysis Services to include the measures. Because the Power BI dataset uses a live connection, all security—including OLS that hides measures—is enforced by the AAS model itself, so the only way to expose those measures to report users is to edit the OLS roles in AAS to grant access to them. Power BI cannot override or bypass AAS security in a live connection, so options A and B are ineffective, and option C would require abandoning the live connection and rebuilding the model, which is unnecessary and changes the architecture.

Answer

Use Power BI Desktop object-level security to override AAS settings.

Answer

Configure row-level security (RLS) in Power BI to grant access.

Answer

Change the dataset to import mode and then apply OLS in Power BI.