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

Question 1

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?

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

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.

Answer

Normalize dimension tables into multiple related tables.

Answer

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

Question 2

You are connecting to a data source that contains Personally Identifiable Information (PII). You need to ensure that only authorized users can view the data in Power BI reports. Which TWO actions should you take?

Accepted Answer

Define row-level security (RLS) roles in Power BI Desktop.. Row-Level Security (RLS) allows you to restrict data access at the row level based on user roles defined in Power BI Desktop. By creating roles and using DAX filters, you can ensure that only authorized users see specific rows of PII data when the report is published to the Power BI service and users are mapped to roles.

Answer

Enable encryption at rest for the dataset.

Answer

Use Power Query to mask PII columns by replacing values with '***'.

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Apply sensitivity labels to the dataset.

Question 3

You are connecting to a SharePoint folder containing 100 Excel files. Each file has a similar structure but different column names. What is the best practice to combine these files into a single table while preserving the data?

Accepted Answer

Use Power Query's 'Combine Files' feature, selecting a sample file and promoting headers, then transforming column names to a standard set.. Power Query's 'Combine Files' feature is designed specifically for this scenario: it uses a sample file to infer the transformation logic (e.g., promoting headers), then applies that logic to all files in the folder. By transforming column names to a standard set within the sample file step, you ensure consistent column names across all files, preserving data integrity while combining them into a single table.

Answer

Load each file as a separate table and create relationships in the model.

Answer

Use Power Query's 'Merge Queries' to join all files into one table.

Answer

Use 'Append Queries' to stack all files, then rename columns manually.

Question 4

You are reviewing a Power BI dataset configuration in the service. The JSON shows a data source for an Azure SQL Database. Which statement about the configuration is correct?

Accepted Answer

The dataset uses cloud-only data sources and does not require a gateway.. Azure SQL Database is a cloud-native data source in Power BI, and cloud data sources do not require a gateway, whether using DirectQuery or Import. The configuration shown in the JSON is for an Azure SQL Database, which is inherently cloud-only, so no gateway is needed. Option A is incorrect because key-based authentication is not supported for Azure SQL Database; using 'Key' credential type would cause a connection failure. Option B is incorrect because the JSON does not indicate single sign-on (no 'SingleSignOn' property set to true). Option C is incorrect because a cloud gateway is not required for Azure SQL Database; it is only needed for on-premises or virtual-network sources.

Answer

The dataset uses key-based authentication and does not use single sign-on.

Answer

The dataset uses single sign-on with Azure AD.

Answer

The dataset is configured to use a cloud gateway for direct query.

Question 5

You are importing data from a CSV file that contains a column 'Date' with values like '2026-01-15'. After loading, Power Query detects the column as type 'text'. What is the recommended step to ensure the column is treated as a date?

Accepted Answer

In Power Query, select the column and change the data type to 'Date' using the 'Data Type' dropdown.. In Power Query, the recommended method to convert a text column containing date-formatted strings (like '2026-01-15') to a proper Date type is to select the column and change its data type using the 'Data Type' dropdown in the Transform tab. This ensures the column is treated as a date for downstream calculations and modeling. Power Query automatically parses the text into a date based on the locale and format of the data.

Answer

In Power BI Desktop, use the 'Format' pane to set the column as a date.

Answer

Use the 'Parse' -> 'Date' transformation in Power Query.

Answer

Use the 'Detect Data Type' button in Power Query to automatically detect all columns.

Question 6

You are loading data from an Excel workbook that has multiple sheets. Each sheet contains sales data for a different region. You need to combine all sheets into one table. What is the most efficient approach?

Accepted Answer

Use 'Append Queries' for each sheet individually.. Using 'Append Queries' in Power Query allows you to combine multiple queries (one per sheet) into a single table. You can load all sheets as queries, then use the Append Queries feature to union them all at once, which is efficient and avoids manual repetition. Power Query's Append operation is designed for this purpose and is more efficient than loading separate tables into the model (C) or using Merge (B) which performs joins, not unions. 'From Folder' (D) is intended for combining multiple files, not sheets within a single workbook.

Answer

Use 'Merge Queries' to join all sheets into one.

Answer

Load each sheet as a separate table in the model and create a calculated table to union them.

Answer

Use Power Query's 'From Folder' option to combine all Excel files in a folder, then select 'Combine & Transform' to use the workbook as a sample.

Question 7

Which THREE of the following are best practices for optimizing data load performance in Power BI?

Accepted Answer

Remove unnecessary columns and rows during the import process.. Removing unnecessary columns and rows during the import process reduces the amount of data loaded into the Power BI data model, which directly decreases memory usage and refresh time. By filtering out irrelevant data early in Power Query, you minimize the data volume that must be processed and stored, leading to faster load performance.

Answer

Split a large fact table into multiple smaller fact tables.

Answer

Use DirectQuery mode instead of Import mode to reduce data load time.

Question 8

You are preparing data from a CSV file that has inconsistent date formats. Some rows use 'MM/dd/yyyy' and others use 'dd/MM/yyyy'. You need to parse all dates correctly. What is the best approach in Power Query?

Accepted Answer

Use the 'Replace Values' to standardize the date format, then change data type.. 'Replace Values' allows you to standardize the inconsistent date strings (e.g., swapping day and month parts) before Power Query attempts to parse them as dates. After replacing the delimiters or reordering parts, you can change the column type to 'Date' using a consistent culture (e.g., 'en-US' for MM/dd/yyyy), ensuring all rows parse correctly regardless of original format.

Answer

Use the 'Parse' -> 'Date' transformation with a specific culture.

Answer

Use the 'Split Column' by delimiter to separate date parts.

Answer

Use the 'Detect Data Type' feature to automatically identify the format.

Question 9

You are building a Power BI data model that combines Sales data from SQL Server and Marketing data from a CSV file. The Sales table has a unique 'OrderID' column, and the Marketing table has a 'CampaignID' column. You need to create a relationship between Sales and Marketing to analyze campaign effectiveness. What should you do?

Accepted Answer

Create a bridge table containing unique combinations of OrderID and CampaignID.. A bridge table resolves the many-to-many relationship between Sales (OrderID) and Marketing (CampaignID). Since there is no direct key match, creating a bridge table with unique combinations of OrderID and CampaignID allows Power BI to model the relationship correctly and analyze campaign effectiveness without data duplication or ambiguity.

Answer

Use an inactive relationship between Sales and Marketing and activate it with USERELATIONSHIP in measures.

Answer

Create a separate table for each campaign and relate to Sales.

Answer

Merge the Marketing table into the Sales table using a left outer join.

Question 10

Refer to the exhibit. The Power Query M code connects to a SQL Server database and performs data transformation. However, the query is failing with a privacy level error. What is the most likely cause?

Accepted Answer

The query combines data from SQL Server and another data source with incompatible privacy levels.. A privacy level error in Power Query occurs when combining data from multiple sources with incompatible privacy levels. The query connects to SQL Server and performs transformations, but if it also references another source (e.g., from a previous step or additional data) with a privacy level that conflicts with SQL Server's privacy level, the Power Query firewall blocks the query. In this scenario, the most likely cause is that the query combines SQL Server data with another data source (such as a CSV file or another database) that has a privacy level set to 'Private' while SQL Server is set to 'Organizational' or 'Public', causing the error. Option D correctly identifies this. Options A and B are incorrect because a single data source cannot cause a privacy level error, and inconsistent privacy levels across environments do not trigger the firewall on a single source.

Answer

The SQL Server credentials are not correctly configured in the data source settings.

Answer

The privacy levels for the SQL Server data source are set inconsistently across the environment.

Answer

The query uses a CSV file from a local folder that has a privacy level set to 'Private'.

Question 11

You are importing data from an Excel workbook that contains multiple sheets. You only need data from the 'Sales' sheet. In Power Query Editor, what should you do to load only that sheet?

Accepted Answer

In the Navigator dialog, select the 'Sales' sheet and click 'Transform Data'.. In Power Query Editor, the Navigator dialog allows you to preview and select specific tables or sheets from a data source before loading. By selecting the 'Sales' sheet and clicking 'Transform Data', you load only that sheet into Power Query Editor for transformation, avoiding unnecessary data. This is the correct and efficient method to import a single sheet from a multi-sheet Excel workbook.

Answer

Load all sheets, then delete the queries for sheets you don't need.

Answer

Use a filter transform to exclude rows from other sheets.

Answer

Select the entire workbook and then filter out other sheets in Power Query.

Question 12

Which TWO actions can you take in Power Query Editor to improve data quality and reduce load time? (Choose two.)

Accepted Answer

Filter out empty rows.. Filtering out empty rows in Power Query Editor directly reduces the number of rows loaded into the data model, which decreases memory usage and improves refresh performance. This action also enhances data quality by removing incomplete records that could cause errors in measures or relationships. The other options either do not reduce load time or may increase it.

Answer

Split columns by delimiter to create more columns.

Answer

Sort the data by a key column.

Answer

Promote headers to use the first row as column names.

Answer

Merge queries to combine data from multiple sources.

Question 13

Which TWO are valid methods to handle null values in Power Query? (Choose two.)

Accepted Answer

Use the 'Fill Down' or 'Fill Up' option to propagate non-null values into null cells.. 'Fill Down' and 'Fill Up' propagate the last non-null value into adjacent null cells. Option C is correct because 'Replace Values' can replace nulls with a default value. Option B is incorrect: 'Remove Blank Rows' removes rows where all cells are blank, not rows with nulls in specific columns. Option D is not a direct method for handling nulls; merging may introduce new data but does not handle existing nulls. Option E is invalid because changing to a non-nullable type causes errors.

Answer

Remove rows that contain null values using the 'Remove Rows' > 'Remove Blank Rows' option.

Answer

Merge the table with another table that has no nulls.

Answer

Change the data type of the column to a non-nullable type.

Question 14

Which TWO are best practices for optimizing Power Query performance? (Choose two.)

Accepted Answer

Disable the 'Enable background refresh' option in the query settings.. Disabling 'Enable background refresh' prevents Power Query from running queries in the background while you continue working in Power BI Desktop. This ensures that query execution is synchronous, which can improve performance by avoiding resource contention and allowing you to monitor progress directly. Background refresh can cause delays and unexpected behavior when multiple queries run simultaneously, especially with large data sources.

Answer

Merge tables as early as possible in the query to combine data.

Answer

Keep all columns in the table to avoid missing data.

Answer

Split columns by delimiter to normalize data.

Question 15

You are importing data from a CSV file into Power BI. The file contains a column 'SalesAmount' with values like '$1,234.56'. When you load the data, the column is detected as text. What is the most efficient way to convert this column to a numeric type in Power Query?

Accepted Answer

Use 'Replace Values' to remove the dollar sign and comma, then change the column type to decimal.. It directly addresses the root cause: the dollar sign and comma are non-numeric characters that prevent automatic type conversion. By using 'Replace Values' to remove these characters first, you clean the data so that Power Query can then safely change the column type to decimal. This is the most efficient approach because it avoids error rows and preserves data integrity.

Answer

Use 'Detect Data Type' and hope it automatically converts.

Answer

Change the column type to decimal directly and ignore errors.

Answer

Split the column by delimiter ',' and then convert the first part.