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QUESTION 1

Which two types of visualizations can be used in the balance sheet reports to meet the reporting goals?

Each correct answer presents part of the solution.

A) A line chart that shows 
balances by quarter filtered 
to account categories that are
 long-term liabilities.

B) A clustered column chart 
that shows balances by date 
(x-axis) and account category 
(legend) without filters.

C) A clustered column chart 
that shows balances by quarter
 filtered to account 
categories that are long-term 
liabilities.

D) A pie chart that show 
balances by account category 
without filters.

E) A ribbon chart that shows 
balances by quarter and 
accounts in the legend.

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Suggested Answer:

1. (A) A line chart that shows balances by quarter filtered to account categories that are long-term liabilities.

   • This visualization effectively displays trends over time for long-term liabilities, which is important in a balance sheet context.

2. (C) A clustered column chart that shows balances by quarter filtered to account categories that are long-term liabilities.

   • This chart can compare the balances of different long-term liabilities across quarters, making it easier to analyze changes.

Why not other options?

Option B describes a clustered column chart that shows balances by date (x-axis) and account category (legend) without filters. While this visualization can provide insights, it may not be ideal for a balance sheet report for several reasons:

1. Lack of Time Context: A balance sheet typically represents a snapshot of financial data at a specific point in time rather than over a range of dates. Using a date-based x-axis without filtering for specific reporting periods could lead to confusion, as balance sheets generally reflect balances at the end of reporting periods (e.g., quarterly or annually).

2. Clarity of Focus: The absence of filters means that the chart may include all account categories, which could overwhelm the viewer with too much information. Balance sheets focus more on specific categories, such as assets, liabilities, and equity.

Option D describes a pie chart that shows balances by account category without filters. While pie charts can effectively display proportions of a whole, they may not be the best choice for balance sheet reports for the following reasons:

1. Limited Data Points: Balance sheets typically contain multiple categories (assets, liabilities, equity, etc.). A pie chart can become cluttered and difficult to read if there are too many categories, especially if some categories have very small values.

2. Lack of Time Series Analysis: Balance sheets provide a snapshot at a specific point in time, and pie charts do not convey changes over time. They are primarily used for illustrating the composition of a single snapshot rather than trends or comparisons over periods.

3. Misleading Representations: Pie charts can sometimes mislead viewers regarding the importance of categories, especially if the differences in values are not visually clear. In financial reporting, clarity and precision are crucial.

Option E describes a ribbon chart that shows balances by quarter and accounts in the legend. While ribbon charts can be useful for visualizing data over time, they may not be the best fit for balance sheet reports for several reasons:

1. Complexity: Ribbon charts can become complex and difficult to interpret, especially with many accounts or categories. Balance sheets benefit from clear, straightforward representations of financial data.

2. Focus on Comparison: Ribbon charts are typically better suited for showing how values change over time or how different categories contribute to a total. Balance sheets, however, focus on specific balances at a point in time, making simpler visualizations like line or clustered column charts more effective.

3. Potential for Confusion: If the data has many fluctuations, a ribbon chart can make it hard to discern clear trends or balances, which are crucial in a balance sheet context.

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QUESTION 2

You need to calculate the last day of the month in the balance sheet data to ensure that you can relate the balance sheet data to the Date table.

Which type of calculation and which formula should you use?

Type of calculation?
A) A DAX calculated column
B) A DAX calculated measure
C) An M custom column



Formula?
A) 
Date.EndOfMonth(#date([Year],[Month],1))
B) 
Date.EndOfQuarter(#date([Year],[Month],1))
C) 
ENDOFQUARTER(DATE('BalanceSheet'[Year],BalanceSheet([Month],1),0)

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Answer:

To calculate the last day of the month in the balance sheet data, you want to ensure that the calculation aligns with the requirements for relating to a Date table.

Type of Calculation:

• (A) A DAX calculated column: This is appropriate for creating a date that can be used in relationships with the Date table, as each row in the balance sheet will need a specific last day of the month.

Formula:

• (A) Date.EndOfMonth(#date([Year],[Month],1)): This formula correctly calculates the last day of the month based on the year and month provided.

Why not … "?

Why not (B) A DAX Calculated Measure?

• Nature of Measures: Measures are aggregations or calculations that are evaluated in the context of the current filter. They do not store values in a column format for each row and are typically used for summaries (e.g., totals, averages).

• Use Case: Since you need the last day of the month for each specific row in the balance sheet data (not an aggregated value), a measure is not appropriate for this scenario.

Why not (B) An M Custom Column?

• M Language Context: M is used in Power Query for data transformation before loading the data into the model. While you could technically use an M custom column to calculate the last day of the month, it would not be useful for creating relationships in the data model after the data has been loaded.

• DAX Preference: Since the goal is to relate the balance sheet data to the Date table after loading, a DAX calculated column is more suitable, as it allows for row-level calculations directly in the model.

Why not (B) Date.EndOfQuarter(#date([Year],[Month],1))?

• Purpose of the Function: This formula calculates the last day of the quarter, not the last day of the month. Since balance sheets typically require the last day of a specific month, this formula does not meet the requirement.

• Inaccuracy: Using this formula would yield incorrect dates if you need the end of a month, as quarters can span multiple months.

Why not (C) ENDOFQUARTER(DATE('BalanceSheet'[Year],BalanceSheet([Month],1),0)?

• Function Misuse: Similar to option (b), this formula also focuses on the end of the quarter rather than the month. It’s not suitable for obtaining the last day of a month.

• Incorrect Syntax: Additionally, there is a syntax issue with the way the DATE function is used. It should reference the correct column name for the month instead of BalanceSheet([Month],1).

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QUESTION 3

You have a dashboard that contains tiles pinned from a single report .
You need to modify the dashboard so that it has a black background dashboard.

A) Edit the details of each tile.
B) Change the report theme.
C) Change the dashboard theme.
D) Create a custom CSS file.

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Answer:

To modify a Power BI dashboard to have a specific appearance, such as a black background, the most appropriate option is:

C. Change the dashboard theme.

Explanation:

• Changing the Dashboard Theme: This allows you to apply a consistent color scheme across all tiles in the dashboard, including background colors. A theme change is the simplest way to achieve the desired visual effect without needing to edit each tile individually.

Why Not the Others?

• A. Edit the details of each tile: While you could change the background of individual tiles, this approach would be time-consuming and would not ensure a consistent appearance across the dashboard.

• B. Change the report theme: Changing the report theme affects the report itself, not the dashboard. The dashboard can have a different theme from the underlying report.

• D. Create a custom CSS file: Power BI does not support custom CSS for dashboards, so this option is not feasible.

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QUESTION 4

You have a Power BI report that contains four pages.
All the pages contain a slicer for a field named Country.
You need to ensure that when a user selects a country on page 1, the selection is retained on page 2 and page 3. The solution must prevent page 4 from being affected by selections on the other pages.
What should you do?

A) Remove the country slicer 
from page 1, page 2, and page 
3. Add the Country field to 
the report-level filters.

B) Remove the Country slicer 
from page 1, page 2, and page 
3. Add the Country field to 
the page-level filters.

C) Sync the Country slicer on 
page 1, page 2, and page 3.

D) Move the Country slicer 
from page 2 and page 3 to page
 1.

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Answer:

C) Sync the Country slicer on page 1, page 2, and page 3.

Explanation:

• Slicer Syncing: By syncing the slicer across pages 1, 2, and 3, you ensure that any selection made on the slicer in any of these pages is carried over to the others. This allows for consistent filtering based on user selections.

• Isolation for Page 4: Since you are not syncing the slicer on page 4, it will remain unaffected by the selections made on the other pages, meeting the requirement.

Why Not the Others?

• A) Remove the country slicer from page 1, page 2, and page 3. Add the Country field to the report-level filters.

  • This approach would apply the filter globally across all pages, including page 4, which is not what you want.

• B) Remove the Country slicer from page 1, page 2, and page 3. Add the Country field to the page-level filters.

  • This would only allow filtering for the current page and would not retain selections across pages 1, 2, and 3.

• D) Move the Country slicer from page 2 and page 3 to page 1.

  • This would not provide the desired functionality of retaining the selection across multiple pages; users would have to return to page 1 to make selections.

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QUESTION 5

You have an app workspace named Retail Analysis in the Power BI service.
You need to manage members that have access to the app workspace.
What should you do?

A) From the Power BI Admin 
portal, click Usage metrics.

B) From the Office 365 Admin 
center, click Users.

C) From the Office 365 Admin 
center, click Groups.

D) From the Power BI Admin 
portal, click Tenant settings.

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Answer:

To manage members that have access to an app workspace in the Power BI service, you should:

C) From the Office 365 Admin center, click Groups.

Explanation:

• Managing Workspace Members: App workspaces in Power BI are linked to Office 365 groups. By navigating to the Office 365 Admin center and clicking on Groups, you can manage the members of the specific group associated with your app workspace, including adding or removing users.

Why Not the Others?

• A) From the Power BI Admin portal, click Usage metrics.

  • This option provides insights into usage statistics for reports and dashboards, not member management.

• B) From the Office 365 Admin center, click Users.

  • While you can manage individual users, this does not directly address managing members of a specific app workspace.

• D) From the Power BI Admin portal, click Tenant settings.

  • Tenant settings control overall settings for the organization but do not provide direct management of workspace members.

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QUESTION 6

You have a power BI tenant that hosts the datasets shown in the following table:

Datasets Overview

| Name        | Contents                  | Used to generate                                    |
|-------------|---------------------------|-----------------------------------------------------|
| Sales       | Sales targets             | Daily performance reports                           |
|             | Sales data                | Quarterly reports used to calculate bonuses         |
|             | Employee salary data      |                                                     |
|-------------|---------------------------|-----------------------------------------------------|
| Operations  | Environmental sensor data | Reports that show average sensor readings over time |

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You have the following requirements:

1. The export of reports that contain Personally Identifiable Information (PII) must be prevented.

2. Data used for financial decisions must be reviewed and approved before use.

For each of the following statements, select Yes if the statement is true. Otherwise select No.

Statements:

[1] The Sales dataset requires
 sensitivity label (Y/N).

[2] The Operations dataset 
requires a sensitivity label 
and must be certified (Y/N).

[3] The Finance dataset 
requires a sensitivity label 
and must be certified (Y/N).

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Answer:

Statements Assessment

1. The Sales dataset requires a sensitivity label (Y/N):

   • Yes (Y): The Sales dataset contains employee salary data, which is considered Personally Identifiable Information (PII). Therefore, it should have a sensitivity label to protect this information.

2. The Operations dataset requires a sensitivity label and must be certified (Y/N):

   • No (N): While the Operations dataset may contain sensitive data (depending on the context of the environmental sensor data), it typically does not contain PII. Therefore, a sensitivity label may not be strictly necessary, and certification is not required unless specified otherwise.

3. The Finance dataset requires a sensitivity label and must be certified (Y/N):

   • Yes (Y): The Finance dataset contains financial transaction data used for budget planning and decision-making, which requires a sensitivity label for protection. Additionally, since the data is used for financial decisions, it must be certified to ensure that it has been reviewed and approved before use.

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QUESTION 7

You have several reports and dashboards in a workspace.

You need to grant all organizational users read access to a dashboard and several reports.

Solution: You assign all the users the Viewer role to the workspace.

Does this meet the goal?

A) Yes
B) No

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Answer:

A. Yes

Assigning all organizational users the Viewer role to the workspace does meet the goal of granting them read access to the dashboard and several reports.

Explanation:

• The Viewer role allows users to view the contents of the workspace, including dashboards and reports, without the ability to edit or manage them. This effectively provides read-only access to all organizational users as intended.

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QUESTION 8

Dion have a Power BI dataset that contains a table named Temperature Readings. Temperature Readings contains the columns shown in the following table

The table has 12 million rows. All the columns are needed for analysis.

You need to optimize the dataset to decrease the model size. The solution must not affect the precision of the data.

What should you do?

A) Split the DateTime column 
into separate date and time 
columns.

B) Disable the Power Query 
load.

C) Round the Longitude column 
two decimal places.

D) Change the data type of the
 TempCelcius column to 
Integer.

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Answer:

To optimize the dataset and decrease the model size without affecting the precision of the data, the best option is:

C) Round the Longitude column to two decimal places.

Explanation:

• Rounding the Longitude: By rounding the Longitude (and potentially Latitude) column to two decimal places, you can significantly reduce the number of unique values while still maintaining sufficient precision for many geographical analyses. This typically results in a smaller model size without a notable loss of accuracy for most applications.

Why Not the Others?

• A) Split the DateTime column into separate date and time columns: This action would not reduce the model size. In fact, it might increase the size slightly due to the additional column, and it could complicate analysis if both date and time are needed together.

• B) Disable the Power Query load: Disabling the load would mean that the table does not get included in the model, which is not a viable solution if you need the data for analysis.

• D) Change the data type of the TempCelcius column to Integer: This would result in a loss of precision, as temperatures may not always be whole numbers (e.g., 12.5°C would become 12°C), which is not acceptable if the requirement is to maintain precision.

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QUESTION 9

You have a Power BI report that contains five pages.

Pages 1 to 4 are visible and page 5 is hidden.

You need to create a solution that will enable users to quickly navigate from the first page to all the other visible pages.

The solution must minimize development and maintenance effort as pages are added to the report.

What should you do first?

A) Add a blank button to page 
1.

B) Add a bookmark navigation 
button to page 1.

C) Create a bookmark for each 
page.

D) Add a page navigation 
button to page 1.

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Answer:

To enable users to quickly navigate from the first page to all the other visible pages while minimizing development and maintenance effort, the best first step is:

D) Add a page navigation button to page 1.

Explanation:

• Page Navigation Button: Adding a page navigation button allows you to create a direct link to each of the visible pages. This method is straightforward and requires minimal setup. Once the buttons are created, they will automatically adjust if pages are added or removed, thus reducing maintenance effort.

Why Not the Others?

• A) Add a blank button to page 1: A blank button wouldn't provide any functionality for navigation and would require additional steps to set up.

• B) Add a bookmark navigation button to page 1: While bookmark navigation can be useful, it typically requires more setup as you must manage bookmarks for each page, which can be cumbersome and less intuitive for simple page navigation.

• C) Create a bookmark for each page: This option adds complexity and requires ongoing maintenance, especially if pages are added or removed. Bookmarks are better suited for specific views or states within a page rather than basic navigation between pages.

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QUESTION 10

You have a Microsoft Power BI report. The size of PBIX file is 550 MB. The report is access by using an App workspace in shared capacity of powerbi.com

The report uses an imported dataset that contains one fact table. The fact table contains 12 million rows. The dataset is scheduled to refresh twice a day at 08:00 and 17:00.

The report is a single page that contains 15 custom visuals and 10 default visuals.
Users say that the report is slow to load the visuals when they access and interact with the report.

You need to recommend a solution to improve the performance of the report.

What should you recommend?

A) Split the visuals onto 
multiple pages.

B) Implement row-level 
security (RLS).

C) Replace the default visuals
 with custom visuals.

D) Increase the number of 
times that the dataset is 
refreshed.

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Answer:

To improve the performance of a Power BI report that is slow to load and interact with, the best recommendation is:

A) Split the visuals onto multiple pages.

Explanation:

• Performance Improvement: Splitting the visuals across multiple pages can significantly enhance the performance of the report. By reducing the number of visuals on a single page, you decrease the rendering load when the report is opened. This can lead to faster loading times and a smoother user experience, especially when dealing with complex custom visuals and a large dataset.

Why Not the Others?

• B) Implement row-level security (RLS): While RLS is important for data security, it does not directly address performance issues related to loading and rendering visuals.

• C) Replace the default visuals with custom visuals: Custom visuals can sometimes be more resource-intensive than default visuals. This option may not necessarily improve performance and could potentially worsen it.

• D) Increase the number of times that the dataset is refreshed: More frequent refreshes do not improve report performance for users accessing the report. They only impact data freshness and can lead to unnecessary load on the system.

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QUESTION 11

You have a Power BI report that imports a date table and a sales table from an Azure SQL database data source.

The sales table has the following date foreign keys:

1. Due Date

2. Order Date

3. Delivery Date

You need to support the analysis of sales over time based on all the date foreign keys.

Solution: From Power Query Editor, you rename the date query as Due Date. You reference the Due Date query twice to make the queries for Order Date and Delivery Date.

Does this meet the goal?

A) Yes.
B) No.

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Answer:

B. No.

Explanation:

While referencing the same date query multiple times can simplify the model, renaming the date query as "Due Date" and referencing it for both "Order Date" and "Delivery Date" will not adequately support analysis over all three date foreign keys.

Correct Approach:

• Single Date Table: You can use a single date table without renaming or referencing it multiple times.

• Multiple Relationships: Establish three relationships from the sales table to the date table:

  1. Active Relationship: For the Order Date.

  2. Inactive Relationships: For the Due Date and Delivery Date.

Additional Info:

• Active and Inactive Relationships: In Power BI, you can have multiple relationships between tables, but only one can be active at a time. By using inactive relationships for the other date fields, you can still use them in your analysis by utilizing DAX functions like USERELATIONSHIP to activate the necessary relationship when needed.

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QUESTION 12

You have a Microsoft power bi dashboard.

You need to ensure that consumers of the dashboard can give you feedback that will be visible to the other consumers of the dashboard.

What should you use?

A) Feedback.
B) Subscribe.
C) Comments.
D) Mark as favorite.

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Answer:

To enable consumers of a Power BI dashboard to give feedback that is visible to other consumers, you should use:

C) Comments

Explanation:

• Comments Feature: Power BI allows users to add comments directly on dashboard tiles or reports. These comments can be seen by other consumers, facilitating collaboration and feedback sharing among users.

Why Not the Others?

• A) Feedback: While feedback options may exist, they do not typically provide a visible thread for discussion among all consumers.

• B) Subscribe: Subscribing allows users to receive email notifications about updates to the dashboard but does not facilitate feedback or comments.

• D) Mark as favorite: This option allows users to bookmark the dashboard for personal use but does not enable any feedback or communication features.

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QUESTION 13

You have a line chart.
You need to modify so that the line chart can provide prediction for future movement.
What should you add to the visual?

A) a measure
B) an Average line
C) a trendline
D) a forecast

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Answer:

To modify a line chart in Power BI so that it can provide predictions for future movement, you should add:

D. a forecast

Explanation:

• Forecast Feature: Power BI allows you to add a forecast to line charts, which uses historical data to predict future values. This feature provides a visual representation of expected trends based on past performance, making it ideal for forecasting future movements.

Why Not the Others?

• A. a measure: While measures are important for calculations, they do not inherently provide predictive capabilities in a line chart.

• B. an Average line: An average line shows the mean of the data points but does not predict future data.

• C. a trendline: While trendlines can indicate the general direction of data, they are not specifically designed to provide forecasts in Power BI.

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QUESTION 14

You are reviewing a query that produces 10,000 rows in the Power Query Editor.

You need to identify whether a column contains only unique values.

Which two Data Preview options can you use? Each correct answer presents a complete solution.

A) Column profile
B) Column distribution
C) Show whitespace
D) Column quality
E) Monospace

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Answer:

To identify whether a column contains only unique values in the Power Query Editor, you can use the following two Data Preview options:

A) Column profile

• Explanation: The Column Profile option provides detailed statistics about the selected column, including the count of distinct values. If the count of distinct values equals the total number of rows, the column contains only unique values.

B) Column distribution

• Explanation: The Column Distribution option shows a histogram of the values in the column. If the bar chart displays each value as a separate bar with a count of 1, it indicates that all values are unique.

Why Not the Others?

• C) Show whitespace: This option is used to visualize whitespace characters in the data and does not provide information about uniqueness.

• D) Column quality: This option shows the quality of data (valid, error, empty) but does not specifically indicate whether values are unique.

• E) Monospace: This option pertains to text formatting and has no relevance to determining uniqueness.

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QUESTION 15

You have the Power BI model as follows:

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.

Answer:

To ensure that users can see only the data of their respective department in the Power BI model, you should:

B) Create a row-level security (RLS) role for each department, and then define the membership of the role.

Explanation:

• Row-Level Security (RLS): Implementing RLS allows you to restrict data access based on user roles. By creating a separate role for each department and defining the membership of those roles, you can ensure that users only see the data relevant to their specific department. This is the most effective and secure way to control access in Power BI.

Why Not the Others?

• A) Create a slicer that filters Departments based on DepartmentID: While a slicer can filter visuals for users, it does not restrict the data at the model level. Users could still access data from other departments if they are not restricted.

• C) Create a DepartmentID parameter to filter the Departments table: Parameters are not suitable for controlling access at the user level and do not provide the necessary security for sensitive data.

• D) To the ConfidentialData table, add a calculated measure that uses the CURRENTGROUP DAX function: This approach is not relevant for restricting data visibility based on user roles and does not provide the necessary security mechanism.

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QUESTION 16

You create a dataset sourced from dozens of flat files in Azure Blob storage. The dataset uses incremental refresh.

From powerbi.com, you deploy the dataset and several related reports to Microsoft Power BI Premium capacity.

You discover that the dataset refresh fails after the refresh runs out of resources.

What is a possible cause of the issue?

A) Query folding is not 
occurring.

B) You selected Only refresh 
complete periods.

C) The data type of the column
 used to partition the data 
changed.

D) A filter is missing on the 
report.

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Answer:

The most likely cause of the dataset refresh failing due to running out of resources is:

A) Query folding is not occurring.

Explanation:

• Query Folding: Query folding refers to the ability of Power Query to push transformations back to the data source rather than processing them in Power BI. If query folding is not occurring, Power BI must perform all transformations in memory, which can lead to excessive resource consumption and ultimately cause the refresh to fail due to lack of resources.

Why Not the Others?

• B) You selected Only refresh complete periods: This setting is used for incremental refresh to specify that only complete periods should be refreshed. While it could limit the data being refreshed, it is unlikely to directly cause a resource issue.

• C) The data type of the column used to partition the data changed: If the partitioning column's data type changed, it could lead to issues, but it wouldn’t necessarily be the primary cause of running out of resources during a refresh.

• D) A filter is missing on the report: Missing filters may affect the data displayed in the report but would not typically cause a refresh to fail due to resource limitations.

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QUESTION 17

From power query editor, you profile the data as following:

The IoT GUID and IoT columns are unique to each row in query.

You need to analyze IoT events by the hour and day of the year. The solution must improve dataset performance.

Solution: You remove the IoT GUID column and retain the IoT ID column.

Does this meet the goal?

A) Yes.
B) No.

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Answer:

A. Yes

Explanation:

• Removing the IoT GUID Column: Since both the IoT GUID and IoT ID columns are unique to each row, removing the IoT GUID column while retaining the IoT ID column can help improve dataset performance. This is because it reduces the overall size of the dataset by eliminating one unique identifier that is not needed for analysis.

• Performance Improvement: Keeping only the necessary columns for analysis (in this case, the IoT ID) can lead to a more efficient dataset, as it reduces memory usage and speeds up processing and querying.

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QUESTION 18

You have a Power BI imported dataset that contains the a data model.

Select the answer choice that completes each statement.

[1] Changing the ____ setting 
of the relationship will 
improve the report query 
performance.
A) Cardinality
B) Cross filter direction
C) Assume Referential 
Integrity



The data model is organized 
into a ____ .
A) Star Schema
B) Snowflake schema
C) Denormalized table

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Answer:

[1] Changing the ____ setting of the relationship will improve the report query performance.

C) Assume Referential Integrity

Explanation:

• Assume Referential Integrity: Enabling this setting can optimize performance by allowing Power BI to make certain assumptions about the data relationships, which can lead to more efficient query execution.

The data model is organized into a ____ .

A) Star Schema

Explanation:

• Star Schema: This is a common data modeling approach in Power BI where a central fact table is connected to multiple dimension tables. It simplifies the structure and improves performance for reporting and analysis.

Why the other options are not the best choices for each statement?

For the first statement:

Changing the ____ setting of the relationship will improve the report query performance.

1. A) Cardinality:

   • Explanation: While cardinality settings (like one-to-many or many-to-many) are important for defining relationships, merely changing the cardinality does not necessarily improve performance. In fact, incorrect cardinality settings can lead to performance issues or incorrect query results.

2. B) Cross filter direction:

   • Explanation: Changing the cross filter direction can help in certain scenarios, especially in complex models. However, it may also lead to ambiguous relationships and potential performance overhead if not managed carefully. It does not inherently guarantee performance improvements.

For the second statement:

The data model is organized into a ____ .

1. B) Snowflake schema:

   • Explanation: A snowflake schema normalizes the dimension tables, which can complicate queries and potentially reduce performance compared to a star schema. While it can be useful for certain scenarios, it is less common in Power BI due to increased complexity.

2. C) Denormalized table:

   • Explanation: A denormalized table refers to a single table that combines data from multiple sources, which can lead to redundancy. While denormalization can improve performance in certain contexts, it doesn't represent the typical structure of a Power BI model, which usually follows either a star or snowflake schema.

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QUESTION 19

You preview the data from a Microsoft Excel source in Power Query:

You plan to create several visuals from the data, including a visual that shows revenue split by year and product.

You need to transform the data to ensure that you can build the visuals. The solution must ensure that the columns are named appropriately for the data that they contain.

Which three actions should you perform in sequence?

A) Rename the Attribute column
 as Year

B) Rename the Measure column 
as Year

C) Use the first row as 
headers

D) Use headers as first row

E) Unpivot all the columns 
other than Measure

F) Transpose the table

G) Change the data type of the
 Year column to Date

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Answer:

To transform the revenue data from the provided Excel source for use in Power BI, you should perform the following three actions in sequence:

Correct Sequence of Actions:

1. (F) Transpose the table

   • Explanation: This action will switch the rows and columns.

2. (C) Use the first row as headers

   • Explanation: After transposing, this will convert the first row into column headers.

3. (B) Rename the Measure column as Year

   • Explanation: After using the first row as headers, the "Measure" column should be renamed to "Year" to reflect the data accurately, provided that it now contains the year values.

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QUESTION 20

You use Power Bi Desktop to create a Power BI data model and a blank report. You need to add the Word Cloud visual.

The solution must minimize development effort.

Which three actions should you perform in sequence?

A) From a web browser, 
download the PBIVIZ file for 
the Word Cloud visual from 
Microsoft AppSource.

B) Format the data colors and 
title.

C) From Power BI Desktop, get 
the Word Cloud visual from 
Microsoft AppSource.

D) Populate the drillthrough 
fields.

E) Populate the Category 
Value, Value, and Excludes 
fields.

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Answer:

To add the Word Cloud visual to your Power BI report while minimizing development effort, you should perform the following three actions in sequence:

1. C) From Power BI Desktop, get the Word Cloud visual from Microsoft AppSource.

• Explanation: This action allows you to add the Word Cloud visual directly within Power BI Desktop, streamlining the process without needing to download files from a web browser.

2. E) Populate the Category Value, Value, and Excludes fields.

• Explanation: After adding the visual, you need to populate it with the relevant data fields. This step is essential to define what words will appear in the Word Cloud based on their frequency or relevance.

3. B) Format the data colors and title.

• Explanation: Once the data is populated, you can format the visual to enhance its appearance, including adjusting colors and adding a title to improve readability and presentation.

Why not others?

Reasons Against Option A:

1. Additional Steps: Downloading the PBIVIZ file from a web browser involves more steps than necessary. It requires you to manually download the file, then import it into Power BI, which adds complexity and time to the process.

2. Direct Integration: Power BI Desktop allows you to access Microsoft AppSource directly within the application. This integration simplifies the process, as you can search for and add visuals without leaving the Power BI environment.

3. Minimizing Development Effort: The goal is to minimize development effort. Using the built-in functionality to get visuals directly from AppSource (option C) is more efficient and user-friendly.

Reasons Against Option D:

1. Drillthrough Fields Not Applicable: The Word Cloud visual typically does not support drillthrough functionality in the same way that other visuals (like tables or charts) do. Drillthrough fields are more relevant for visuals that can display detailed data based on user interactions.

2. Not Necessary for Initial Setup: When initially setting up the Word Cloud visual, the primary focus is on populating the necessary fields (Category Value, Value, and Excludes) that determine what appears in the Word Cloud. Drillthrough fields are not a fundamental requirement for the Word Cloud to function.

3. Sequence of Actions: The recommended sequence emphasizes adding the visual, populating its data fields, and formatting it. Including drillthrough fields does not align with the immediate need for setting up the Word Cloud, making it an unnecessary step at this stage.