This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.

To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.

At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.

To start the case study -

To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.

Overview -

Contoso, Ltd. is a company that sells enriched financial data to a variety of external customers.

Contoso has a main office in Los Angeles and two branch offices in New York and Seattle.

Existing Environment -

Data Infrastructure -

Contoso has a 50-TB data warehouse that uses an instance of SQL Server on Azure Virtual Machines.

The data warehouse populates an Azure Synapse Analytics workspace that is accessed by the external customers. Currently, the customers can access all the data.

Contoso has one Power BI workspace named FinData that contains a single dataset. The dataset contains financial data from around the world. The workspace is used by 10 internal users and one external customer. The dataset has the following two data sources: the data warehouse and the Synapse Analytics serverless SQL pool.

Users frequently query the Synapse Analytics workspace by using Transact-SQL.

User Problems -

Contoso identifies the following user issues:

Some users indicate that the visuals in Power BI reports are slow to render when making filter selections.

Users indicate that queries against the serverless SQL pool fail occasionally because the size of tempdb has been exceeded.

Users indicate that the data in Power BI reports is stale. You discover that the refresh process of the Power BI model occasionally times out.

Planned Changes -

Contoso plans to implement the following changes:

Into the existing Power BI dataset, integrate an external data source in JSON that is accessible by using the REST API.

Build a new dataset in the FinData workspace by using data from the Synapse Analytics dedicated SQL pool.

Provide all the customers with their own Power BI workspace to create their own reports. Each workspace will use the new dataset in the FinData workspace.

Implement subscription levels for the customers. Each subscription level will provide access to specific rows of financial data.

Deploy prebuilt datasets to Power BI to simplify the query experience of the customers.

Provide internal users with the ability to incorporate machine learning models loaded to the dedicated SQL pool.

You need to identify the root cause of the data refresh issue.

What should you use?

This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.

To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.

At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.

To start the case study -To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.

Overview -Contoso, Ltd. is a company that sells enriched financial data to a variety of external customers.

Contoso has a main office in Los Angeles and two branch offices in New York and Seattle.

Existing Environment -

Data Infrastructure -Contoso has a 50-TB data warehouse that uses an instance of SQL Server on Azure Virtual Machines.

The data warehouse populates an Azure Synapse Analytics workspace that is accessed by the external customers. Currently, the customers can access all the data.

Contoso has one Power BI workspace named FinData that contains a single dataset. The dataset contains financial data from around the world. The workspace is used by 10 internal users and one external customer. The dataset has the following two data sources: the data warehouse and the Synapse Analytics serverless SQL pool.

Users frequently query the Synapse Analytics workspace by using Transact-SQL.

User Problems -Contoso identifies the following user issues:

• Some users indicate that the visuals in Power BI reports are slow to render when making filter selections.
• Users indicate that queries against the serverless SQL pool fail occasionally because the size of tempdb has been exceeded.
• Users indicate that the data in Power BI reports is stale. You discover that the refresh process of the Power BI model occasionally times out.

Planned Changes -Contoso plans to implement the following changes:

• Into the existing Power BI dataset, integrate an external data source in JSON that is accessible by using the REST API.
• Build a new dataset in the FinData workspace by using data from the Synapse Analytics dedicated SQL pool.
• Provide all the customers with their own Power BI workspace to create their own reports. Each workspace will use the new dataset in the FinData workspace.
• Implement subscription levels for the customers. Each subscription level will provide access to specific rows of financial data.
• Deploy prebuilt datasets to Power BI to simplify the query experience of the customers.
• Provide internal users with the ability to incorporate machine learning models loaded to the dedicated SQL pool.

Which two possible tools can you use to identify what causes the report to render slowly? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

DRAG DROP -

This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.

To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.

At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.

To start the case study -

To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.

Overview -

Contoso, Ltd. is a company that sells enriched financial data to a variety of external customers.

Contoso has a main office in Los Angeles and two branch offices in New York and Seattle.

Existing Environment -

Data Infrastructure -

Contoso has a 50-TB data warehouse that uses an instance of SQL Server on Azure Virtual Machines.

The data warehouse populates an Azure Synapse Analytics workspace that is accessed by the external customers. Currently, the customers can access all the data.

Contoso has one Power BI workspace named FinData that contains a single dataset. The dataset contains financial data from around the world. The workspace is used by 10 internal users and one external customer. The dataset has the following two data sources: the data warehouse and the Synapse Analytics serverless SQL pool.

Users frequently query the Synapse Analytics workspace by using Transact-SQL.

User Problems -

• Some users indicate that the visuals in Power BI reports are slow to render when making filter selections.
• Users indicate that queries against the serverless SQL pool fail occasionally because the size of tempdb has been exceeded.
• Users indicate that the data in Power BI reports is stale. You discover that the refresh process of the Power BI model occasionally times out.

Planned Changes -

• Contoso plans to implement the following changes:
• Into the existing Power BI dataset, integrate an external data source in JSON that is accessible by using the REST API.
• Build a new dataset in the FinData workspace by using data from the Synapse Analytics dedicated SQL pool.
• Provide all the customers with their own Power BI workspace to create their own reports. Each workspace will use the new dataset in the FinData workspace.
• Implement subscription levels for the customers. Each subscription level will provide access to specific rows of financial data.
• Deploy prebuilt datasets to Power BI to simplify the query experience of the customers.
• Provide internal users with the ability to incorporate machine learning models loaded to the dedicated SQL pool.
• You need to integrate the external data source to support the planned changes.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

DRAG DROP -

This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.

To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.

At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.

To start the case study -

To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.

Overview -

Contoso, Ltd. is a company that sells enriched financial data to a variety of external customers.

Contoso has a main office in Los Angeles and two branch offices in New York and Seattle.

Existing Environment -

Data Infrastructure -

Contoso has a 50-TB data warehouse that uses an instance of SQL Server on Azure Virtual Machines.

The data warehouse populates an Azure Synapse Analytics workspace that is accessed by the external customers. Currently, the customers can access all the data.

Contoso has one Power BI workspace named FinData that contains a single dataset. The dataset contains financial data from around the world. The workspace is used by 10 internal users and one external customer. The dataset has the following two data sources: the data warehouse and the Synapse Analytics serverless SQL pool.

Users frequently query the Synapse Analytics workspace by using Transact-SQL.

User Problems -

• Some users indicate that the visuals in Power BI reports are slow to render when making filter selections.
• Users indicate that queries against the serverless SQL pool fail occasionally because the size of tempdb has been exceeded.
• Users indicate that the data in Power BI reports is stale. You discover that the refresh process of the Power BI model occasionally times out.

Planned Changes -

• Into the existing Power BI dataset, integrate an external data source in JSON that is accessible by using the REST API.
• Build a new dataset in the FinData workspace by using data from the Synapse Analytics dedicated SQL pool.
• Provide all the customers with their own Power BI workspace to create their own reports. Each workspace will use the new dataset in the FinData workspace.
• Implement subscription levels for the customers. Each subscription level will provide access to specific rows of financial data.
• Deploy prebuilt datasets to Power BI to simplify the query experience of the customers.
• Provide internal users with the ability to incorporate machine learning models loaded to the dedicated SQL pool.

You need to create Power BI reports that will display data based on the customers’ subscription level.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.

To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.

At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.

To start the case study -

To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.

Overview -

Contoso, Ltd. is a company that sells enriched financial data to a variety of external customers.

Contoso has a main office in Los Angeles and two branch offices in New York and Seattle.

Existing Environment -

Data Infrastructure -

Contoso has a 50-TB data warehouse that uses an instance of SQL Server on Azure Virtual Machines.

The data warehouse populates an Azure Synapse Analytics workspace that is accessed by the external customers. Currently, the customers can access all the data.

Contoso has one Power BI workspace named FinData that contains a single dataset. The dataset contains financial data from around the world. The workspace is used by 10 internal users and one external customer. The dataset has the following two data sources: the data warehouse and the Synapse Analytics serverless SQL pool.

Users frequently query the Synapse Analytics workspace by using Transact-SQL.

User Problems -

Contoso identifies the following user issues:

Some users indicate that the visuals in Power BI reports are slow to render when making filter selections.

Users indicate that queries against the serverless SQL pool fail occasionally because the size of tempdb has been exceeded.

Users indicate that the data in Power BI reports is stale. You discover that the refresh process of the Power BI model occasionally times out.

Planned Changes -

Contoso plans to implement the following changes:

Into the existing Power BI dataset, integrate an external data source in JSON that is accessible by using the REST API.

Build a new dataset in the FinData workspace by using data from the Synapse Analytics dedicated SQL pool.

Provide all the customers with their own Power BI workspace to create their own reports. Each workspace will use the new dataset in the FinData workspace.

Implement subscription levels for the customers. Each subscription level will provide access to specific rows of financial data.

Deploy prebuilt datasets to Power BI to simplify the query experience of the customers.

Provide internal users with the ability to incorporate machine learning models loaded to the dedicated SQL pool.

You need to recommend a solution to add new fields to the financial data Power BI dataset with data from the Microsoft SQL Server data warehouse.

What should you include in the recommendation?