DP-700 Free Practice Questions — Page 6

Question 49

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have an Azure key vault named KeyVault1 that contains secrets. You have a Fabric workspace named Workspace1. Workspace contains a notebook named Notebook1 that performs the following tasks: • Loads stage data to the target tables in a lakehouse • Triggers the refresh of a semantic model You plan to add functionality to Notebook1 that will use the Fabric API to monitor the semantic model refreshes. You need to retrieve the registered application ID and secret from KeyVault1 to generate the authentication token. Solution: You use the following code segment: Use notebookutils.credentials.getSecret and specify the key vault URL and the name of a linked service. Does this meet the goal?

Question 50

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have an Azure key vault named KeyVault1 that contains secrets. You have a Fabric workspace named Workspace1. Workspace contains a notebook named Notebook1 that performs the following tasks: • Loads stage data to the target tables in a lakehouse • Triggers the refresh of a semantic model You plan to add functionality to Notebook1 that will use the Fabric API to monitor the semantic model refreshes. You need to retrieve the registered application ID and secret from KeyVault1 to generate the authentication token. Solution: You use the following code segment: Use notebookutils.credentials.putSecret and specify the key vault URL and key vault secret. Does this meet the goal?

Question 51

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have an Azure key vault named KeyVault1 that contains secrets. You have a Fabric workspace named Workspace1. Workspace contains a notebook named Notebook1 that performs the following tasks: • Loads stage data to the target tables in a lakehouse • Triggers the refresh of a semantic model You plan to add functionality to Notebook1 that will use the Fabric API to monitor the semantic model refreshes. You need to retrieve the registered application ID and secret from KeyVault1 to generate the authentication token. Solution: You use the following code segment: Use notebookutils.credentials.getSecret and specify the key vault URL and key vault secret. Does this meet the goal?

Question 52

DRAG DROP - Case Study - 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 - Litware, Inc. is a publishing company that has an online bookstore and several retail bookstores worldwide. Litware also manages an online advertising business for the authors it represents. Existing Environment. Fabric Environment Litware has a Fabric workspace named Workspace1. High concurrency is enabled for Workspace1. The company has a data engineering team that uses Python for data processing. Existing Environment. Data Processing The retail bookstores send sales data at the end of each business day, while the online bookstore constantly provides logs and sales data to a central enterprise resource planning (ERP) system. Litware implements a medallion architecture by using the following three layers: bronze, silver, and gold. The sales data is ingested from the ERP system as Parquet files that land in the Files folder in a lakehouse. Notebooks are used to transform the files in a Delta table for the bronze and silver layers. The gold layer is in a warehouse that has V-Order disabled. Litware has image files of book covers in Azure Blob Storage. The files are loaded into the Files folder. Existing Environment. Sales Data Month-end sales data is processed on the first calendar day of each month. Data that is older than one month never changes. In the source system, the sales data refreshes every six hours starting at midnight each day. The sales data is captured in a Dataflow Gen1 dataflow. When the dataflow runs, new and historical data is captured. The dataflow captures the following fields of the source: • Sales Date • Author • Price • Units • SKU A table named AuthorSales stores the sales data that relates to each author. The table contains a column named AuthorEmail. Authors authenticate to a guest Fabric tenant by using their email address. Existing Environment. Security Groups Litware has the following security groups: • Sales • Fabric Admins • Streaming Admins Existing Environment. Performance Issues Business users perform ad-hoc queries against the warehouse. The business users indicate that reports against the warehouse sometimes run for two hours and fail to load as expected. Upon further investigation, the data engineering team receives the following error message when the reports fail to load: “The SQL query failed while running.” The data engineering team wants to debug the issue and find queries that cause more than one failure. When the authors have new book releases, there is often an increase in sales activity. This increase slows the data ingestion process. The company’s sales team reports that during the last month, the sales data has NOT been up-to-date when they arrive at work in the morning. Requirements. Planned Changes - Litware recently signed a contract to receive book reviews. The provider of the reviews exposes the data in Amazon Simple Storage Service (Amazon S3) buckets. Litware plans to manage Search Engine Optimization (SEO) for the authors. The SEO data will be streamed from a REST API. Requirements. Version Control - Litware plans to implement a version control solution in Fabric that will use GitHub integration and follow the principle of least privilege. Requirements. Governance Requirements To control data platform costs, the data platform must use only Fabric services and items. Additional Azure resources must NOT be provisioned. Requirements. Data Requirements Litware identifies the following data requirements: • Process the SEO data in near-real-time (NRT). • Make the book reviews available in the lakehouse without making a copy of the data. • When a new book cover image arrives in the Files folder, process the image as soon as possible. You need to ensure that the authors can see only their respective sales data. How should you complete the statement? To answer, drag the appropriate values the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.

Question 53

Case Study - 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 - Litware, Inc. is a publishing company that has an online bookstore and several retail bookstores worldwide. Litware also manages an online advertising business for the authors it represents. Existing Environment. Fabric Environment Litware has a Fabric workspace named Workspace1. High concurrency is enabled for Workspace1. The company has a data engineering team that uses Python for data processing. Existing Environment. Data Processing The retail bookstores send sales data at the end of each business day, while the online bookstore constantly provides logs and sales data to a central enterprise resource planning (ERP) system. Litware implements a medallion architecture by using the following three layers: bronze, silver, and gold. The sales data is ingested from the ERP system as Parquet files that land in the Files folder in a lakehouse. Notebooks are used to transform the files in a Delta table for the bronze and silver layers. The gold layer is in a warehouse that has V-Order disabled. Litware has image files of book covers in Azure Blob Storage. The files are loaded into the Files folder. Existing Environment. Sales Data Month-end sales data is processed on the first calendar day of each month. Data that is older than one month never changes. In the source system, the sales data refreshes every six hours starting at midnight each day. The sales data is captured in a Dataflow Gen1 dataflow. When the dataflow runs, new and historical data is captured. The dataflow captures the following fields of the source: • Sales Date • Author • Price • Units • SKU A table named AuthorSales stores the sales data that relates to each author. The table contains a column named AuthorEmail. Authors authenticate to a guest Fabric tenant by using their email address. Existing Environment. Security Groups Litware has the following security groups: • Sales • Fabric Admins • Streaming Admins Existing Environment. Performance Issues Business users perform ad-hoc queries against the warehouse. The business users indicate that reports against the warehouse sometimes run for two hours and fail to load as expected. Upon further investigation, the data engineering team receives the following error message when the reports fail to load: “The SQL query failed while running.” The data engineering team wants to debug the issue and find queries that cause more than one failure. When the authors have new book releases, there is often an increase in sales activity. This increase slows the data ingestion process. The company’s sales team reports that during the last month, the sales data has NOT been up-to-date when they arrive at work in the morning. Requirements. Planned Changes - Litware recently signed a contract to receive book reviews. The provider of the reviews exposes the data in Amazon Simple Storage Service (Amazon S3) buckets. Litware plans to manage Search Engine Optimization (SEO) for the authors. The SEO data will be streamed from a REST API. Requirements. Version Control - Litware plans to implement a version control solution in Fabric that will use GitHub integration and follow the principle of least privilege. Requirements. Governance Requirements To control data platform costs, the data platform must use only Fabric services and items. Additional Azure resources must NOT be provisioned. Requirements. Data Requirements - Litware identifies the following data requirements: • Process the SEO data in near-real-time (NRT). • Make the book reviews available in the lakehouse without making a copy of the data. • When a new book cover image arrives in the Files folder, process the image as soon as possible. You need to ensure that processes for the bronze and silver layers run in isolation. How should you configure the Apache Spark settings?

Question 54

HOTSPOT - You have a Fabric workspace that contains an eventstream named EventStream1. You discover that an EventStream1 transformation fails. You need to find the following error information: The error details, including the occurrence time The total number of errors - What should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Question 55

DRAG DROP - You have a Fabric eventhouse that contains a KQL database. The database contains a table named TaxiData. The following is a sample of the data in TaxiData. You need to build two KQL queries. The solution must meet the following requirements: One of the queries must partition RunningTotalAmount by VendorID. The other query must create a column named FirstPickupDateTime that shows the first value of each hour from tpep_pickup_datetime partitioned by payment_type. How should you complete each query? To answer, drag the appropriate values the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.

Question 56

HOTSPOT - You have a Fabric workspace. You are debugging a statement and discover the following issues: Sometimes, the statement fails to return all the expected rows. The PurchaseDate output column is NOT in the expected format of mmm dd, yy. You need to resolve the issues. The solution must ensure that the data types of the results are retained. The results can contain blank cells. How should you complete the statement? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Question 58

HOTSPOT - You are building a data loading pattern for Fabric notebook workloads. You have the following code segment: For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

Question 59

HOTSPOT - You have an Azure Event Hubs data source that contains weather data. You ingest the data from the data source by using an eventstream named Eventstream1. Eventstream1 uses a lakehouse as the destination. You need to batch ingest only rows from the data source where the City attribute has a value of Kansas. The filter must be added before the destination. The solution must minimize development effort. What should you use for the data processor and filtering? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.