DP 700

You have a Fabric workspace. You have semi-structured data. You need to read the data by using T-SQL, KQL, and Apache Spark. The data will only be written by using Spark. What should you use to store the data?. a lakehouse. an eventhouse. a datamart. a warehouse.

You have a Fabric workspace that contains a warehouse named Warehouse1. You have an on-premises Microsoft SQL Server database named Database1 that is accessed by using an onpremises data gateway. You need to copy data from Database1 to Warehouse1. Which item should you use?. a Dataflow Gen1 dataflow. a data pipeline. a KQL queryset. a notebook.

You have a Fabric workspace that contains a warehouse named Warehouse1. You have an on-premises Microsoft SQL Server database named Database1 that is accessed by using an onpremises data gateway. You need to copy data from Database1 to Warehouse1. Which item should you use? A.an Apache Spark job definition B.a data pipeline C.a Dataflow Gen1 dataflow D.an eventstream. an Apache Spark job definition. a data pipeline. a Dataflow Gen1 dataflow. an eventstream.

You have a Fabric F32 capacity that contains a workspace. The workspace contains a warehouse named DW1 that is modelled by using MD5 hash surrogate keys. DW1 contains a single fact table that has grown from 200 million rows to 500 million rows during the past year. You have Microsoft Power BI reports that are based on Direct Lake. The reports show year-over-year values. Users report that the performance of some of the reports has degraded over time and some visuals show errors. You need to resolve the performance issues. The solution must meet the following requirements: Provide the best query performance. Minimize operational costs. Which should you do?. Change the MD5 hash to SHA256. Increase the capacity. Enable V-Order. Modify the surrogate keys to use a different data type. Create views.

You have a Fabric workspace that contains a lakehouse named Lakehouse1. Data is ingested into Lakehouse1 as one flat table. The table contains the following columns. You plan to load the data into a dimensional model and implement a star schema. From the original flat table, you create two tables named FactSales and DimProduct. You will track changes in DimProduct. You need to prepare the data. Which three columns should you include in the DimProduct table? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point. Date. ProductName. ProductColor. TransactionID. SalesAmount. ProductID.

You have a Fabric workspace named Workspace1 that contains a notebook named Notebook1. In Workspace1, you create a new notebook named Notebook2. You need to ensure that you can attach Notebook2 to the same Apache Spark session as Notebook1. What should you do?. Enable high concurrency for notebooks. Enable dynamic allocation for the Spark pool. Change the runtime version. Increase the number of executors.

You have a Fabric workspace named Workspace1 that contains a lakehouse named Lakehouse1. Lakehouse1 contains the following tables: Orders - Customer - Employee - The Employee table contains Personally Identifiable Information (PII). A data engineer is building a workflow that requires writing data to the Customer table, however, the user does NOT have the elevated permissions required to view the contents of the Employee table. You need to ensure that the data engineer can write data to the Customer table without reading data from the Employee table. Which three actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point. Share Lakehouse1 with the data engineer. Assign the data engineer the Contributor role for Workspace2. Assign the data engineer the Viewer role for Workspace2. Assign the data engineer the Contributor role for Workspace1. Migrate the Employee table from Lakehouse1 to Lakehouse2. Create a new workspace named Workspace2 that contains a new lakehouse named Lakehouse2. Assign the data engineer the Viewer role for Workspace1.

You have a Fabric warehouse named DW1. DW1 contains a table that stores sales data and is used by multiple sales representatives. You plan to implement row-level security (RLS). You need to ensure that the sales representatives can see only their respective data. Which warehouse object do you require to implement RLS?. STORED PROCEDURE. CONSTRAINT. SCHEMA. FUNCTION.

You have a Fabric workspace named Workspace1_DEV that contains the following items: 10 reports Four notebooks - Three lakehouses - Two data pipelines - Two Dataflow Gen1 dataflows - Three Dataflow Gen2 dataflows - Five semantic models that each has a scheduled refresh policy You create a deployment pipeline named Pipeline1 to move items from Workspace1_DEV to a new workspace named Workspace1_TEST. You deploy all the items from Workspace1_DEV to Workspace1_TEST. For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point. Answer: No/Yes/No.

You have a Fabric deployment pipeline that uses three workspaces named Dev, Test, and Prod. You need to deploy an eventhouse as part of the deployment process. What should you use to add the eventhouse to the deployment process?. GitHub Actions. a deployment pipeline. an Azure DevOps pipeline.

You have a Fabric workspace named Workspace1 that contains a warehouse named Warehouse1. You plan to deploy Warehouse1 to a new workspace named Workspace2. As part of the deployment process, you need to verify whether Warehouse1 contains invalid references. The solution must minimize development effort. What should you use?. a database project. a deployment pipeline. a Python script. a T-SQL script.

You have a Fabric workspace that contains a Real-Time Intelligence solution and an eventhouse. Users report that from OneLake file explorer, they cannot see the data from the eventhouse. You enable OneLake availability for the eventhouse. What will be copied to OneLake?. only data added to new databases that are added to the eventhouse. only the existing data in the eventhouse. no data. both new data and existing data in the eventhouse. only new data added to the eventhouse.

You have a Fabric workspace named Workspace1. You plan to integrate Workspace1 with Azure DevOps. You will use a Fabric deployment pipeline named deployPipeline1 to deploy items from Workspace1 to higher environment workspaces as part of a medallion architecture. You will run deployPipeline1 by using an API call from an Azure DevOps pipeline. You need to configure API authentication between Azure DevOps and Fabric. Which type of authentication should you use?. service principal. Microsoft Entra username and password. managed private endpoint. workspace identity.

Stores only. Products only. Stores and Products only. Products, Stores, and Trips. Trips only. Products and Trips only.

You have a Fabric workspace named Workspace1 that contains an Apache Spark job definition named Job1. You have an Azure SQL database named Source1 that has public internet access disabled. You need to ensure that Job1 can access the data in Source1. What should you create?. an on-premises data gateway. a managed private endpoint. an integration runtime. a data management gateway.

You have an Azure Data Lake Storage Gen2 account named storage1 and an Amazon S3 bucket named storage2. You have the Delta Parquet files shown in the following table. You have a Fabric workspace named Workspace1 that has the cache for shortcuts enabled. Workspace1 contains a lakehouse named Lakehouse1. Lakehouse1 has the following shortcuts: A shortcut to ProductFile aliased as Products A shortcut to StoreFile aliased as Stores A shortcut to TripsFile aliased as Trips The data from which shortcuts will be retrieved from the cache?. Trips and Stores only. Products and Store only. Stores only. Products only. Products, Stores, and Trips.

You have a Fabric workspace that contains a warehouse named DW1. DW1 contains the following tables and columns. You need to create an output that presents the summarized values of all the order quantities by year and product. The results must include a summary of the order quantities at the year level for all the products. How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. 1. SELECT CAST 2. SELECT CONVERT 3. SELECT YEAR: CORRECT (SO.ModifiedDate) AS OrderDate ,P.Name AS ProductName ,SUM(SO.OrderQty) AS OrderQty FROM [dbo]. [SalesOrderDetail] so INNER JOIN [dbo]. [Product] P ON P.ProductID = SO.ProductID GROUP BY 1. CUBE(YEAR(SO.ModifiedDate), P.Name) 2. GROUPING SETS ((YEAR(SO.ModifiedDate), P.Name), (YEAR(SO.ModifiedDate))) 3. ROLLUP(YEAR(SO.ModifiedDate), P.Name): CORRECT YEAR(SO.ModifiedDate), P.Name ORDER BY OrderDate CORRECT: SELECT YEAR(SO.ModifiedDate) AS OrderDate, P.Name AS ProductName, SUM(SO.OrderQty) AS OrderQty FROM [dbo].[SalesOrderDetail] SO INNER JOIN [dbo].[Product] P ON P.ProductID = SO.ProductID GROUP BY ROLLUP(YEAR(SO.ModifiedDate), P.Name) ORDER BY OrderDate.

You have a Fabric workspace named Workspace1 that contains the items shown in the following table. For Model1, the Keep your Direct Lake data up to date option is disabled. You need to configure the execution of the items to meet the following requirements: Notebook1 must execute every weekday at 8:00 AM. Notebook2 must execute when a file is saved to an Azure Blob Storage container. Model1 must refresh when Notebook1 has executed successfully. How should you orchestrate each item? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Your company has a sales department that uses two Fabric workspaces named Workspace1 and Workspace2. The company decides to implement a domain strategy to organize the workspaces. You need to ensure that a user can perform the following tasks: Create a new domain for the sales department. Create two subdomains: one for the east region and one for the west region. Assign Workspace1 to the east region subdomain. Assign Workspace2 to the west region subdomain. The solution must follow the principle of least privilege. Which role should you assign to the user?. workspace Admin. domain admin. domain contributor. Fabric admin.

You have a Fabric workspace named Workspace1 that contains a warehouse named DW1 and a data pipeline named Pipeline1. You plan to add a user named User3 to Workspace1. You need to ensure that User3 can perform the following actions: View all the items in Workspace1. Update the tables in DW1. The solution must follow the principle of least privilege. You already assigned the appropriate object-level permissions to DW1. Which workspace role should you assign to User3?. Admin. Member. Viewer. Contributor.

You have a Fabric capacity that contains a workspace named Workspace1. Workspace1 contains a lakehouse named Lakehouse1, a data pipeline, a notebook, and several Microsoft Power BI reports. A user named User1 wants to use SQL to analyze the data in Lakehouse1. You need to configure access for User1. The solution must meet the following requirements: Provide User1 with read access to the table data in Lakehouse1. Prevent User1 from using Apache Spark to query the underlying files in Lakehouse1. Prevent User1 from accessing other items in Workspace1. What should you do?. Share Lakehouse1 with User1 directly and select Read all SQL endpoint data. Assign User1 the Viewer role for Workspace1. Share Lakehouse1 with User1 and select Read all SQL endpoint data. Share Lakehouse1 with User1 directly and select Build reports on the default semantic model. Assign User1 the Member role for Workspace1. Share Lakehouse1 with User1 and select Read all SQL endpoint data.

DRAG DROP - You are implementing the following data entities in a Fabric environment: Entity1: Available in a lakehouse and contains data that will be used as a core organization entity Entity2: Available in a semantic model and contains data that meets organizational standards Entity3: Available in a Microsoft Power BI report and contains data that is ready for sharing and reuse Entity4: Available in a Power BI dashboard and contains approved data for executive-level decision making Your company requires that specific governance processes be implemented for the data. You need to apply endorsement badges to the entities based on each entity’s use case. Which badge should you apply to each entity? To answer, drag the appropriate badges the correct entities. Each badge 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.

HOTSPOT - You have three users named User1, User2, and User3. You have the Fabric workspaces shown in the following table. +--------------+-----------------+ | Name | Workspace admin | +--------------+-----------------+ | Workspace1 | User1 | | Workspace2 | User2 | +--------------+-----------------+ You have a security group named Group1 that contains User1 and User3. The Fabric admin creates the domains shown in the following table. +--------------+-----------------+ | Name | Domain admin | +--------------+-----------------+ | Domain1 | User1 | | Domain2 | User2 | +--------------+-----------------+ User1 creates a new workspace named Workspace3. You add Group1 to the default domain of Domain1. For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

You have two Fabric workspaces named Workspace1 and Workspace2. You have a Fabric deployment pipeline named deployPipeline1 that deploys items from Workspace1 to Workspace2. DeployPipeline1 contains all the items in Workspace1. You recently modified the items in Workspaces1. The workspaces currently contain the items shown in the following table. Items in Workspace1 that have the same name as items in Workspace2 are currently paired. You need to ensure that the items in Workspace1 overwrite the corresponding items in Workspace2. The solution must minimize effort. What should you do?. Delete all the items in Workspace2, and then run deployPipeline1. Rename each item in Workspace2 to have the same name as the items in Workspace1. Back up the items in Workspace2, and then run deployPipeline1. Run deployPipeline1 without modifying the items in Workspace2.

You have a Fabric workspace named Workspace1 that contains a data pipeline named Pipeline1 and a lakehouse named Lakehouse1. You have a deployment pipeline named deployPipeline1 that deploys Workspace1 to Workspace2. You restructure Workspace1 by adding a folder named Folder1 and moving Pipeline1 to Folder1. You use deployPipeline1 to deploy Workspace1 to Workspace2. What occurs to Workspace2?. Folder1 is created, Pipeline1 moves to Folder1, and Lakehouse1 is deployed. Only Pipeline1 and Lakehouse1 are deployed. Folder1 is created, and Pipeline1 and Lakehouse1 move to Folder1. Only Folder1 is created and Pipeline1 moves to Folder1.

DRAG DROP - Your company has a team of developers. The team creates Python libraries of reusable code that is used to transform data. You create a Fabric workspace name Workspace1 that will be used to develop extract, transform, and load (ETL) solutions by using notebooks. You need to ensure that the libraries are available by default to new notebooks in Workspace1. 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.

You have a Fabric workspace that contains a lakehouse and a notebook named Notebook1. Notebook1 reads data into a DataFrame from a table named Table1 and applies transformation logic. The data from the DataFrame is then written to a new Delta table named Table2 by using a merge operation. You need to consolidate the underlying Parquet files in Table1. Which command should you run?. VACUUM. BROADCAST. OPTIMIZE. CACHE.

You have five Fabric workspaces. You are monitoring the execution of items by using Monitoring hub. You need to identify in which workspace a specific item runs. Which column should you view in Monitoring hub?. Start time. Capacity. Activity name. Submitter. Item type. Job type. Location.

You have a Fabric workspace that contains a warehouse named DW1. DW1 is loaded by using a notebook named Notebook1. You need to identify which version of Delta was used when Notebook1 was executed. What should you use?. Real-Time hub. OneLake data hub. the Admin monitoring workspace. Fabric Monitor. the Microsoft Fabric Capacity Metrics app.

DRAG DROP - You have a Fabric workspace that contains a warehouse named Warehouse1. In Warehouse1, you create a table named DimCustomer by running the following statement. CREATE TABLE dbo.DimCustomer ( CustomerKey VARCHAR(255) NOT NULL, Name VARCHAR(255) NOT NULL, Email VARCHAR(255) NOT NULL ); You need to set the Customerkey column as a primary key of the DimCustomer table. Which three code segments should you run in sequence? To answer, move the appropriate code segments from the list of code segments to the answer area and arrange them in the correct order.

You have a Fabric workspace that contains a semantic model named Model1. You need to dynamically execute and monitor the refresh progress of Model1. What should you use?. dynamic management views in Microsoft SQL Server Management Studio (SSMS). Monitoring hub. dynamic management views in Azure Data Studio. a semantic link in a notebook.

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 a Fabric eventstream that loads data into a table named Bike_Location in a KQL database. The table contains the following columns: BikepointID - Street - Neighbourhood - No_Bikes - No_Empty_Docks - Timestamp - You need to apply transformation and filter logic to prepare the data for consumption. The solution must return data for a neighbourhood named Sands End when No_Bikes is at least 15. The results must be ordered by No_Bikes in ascending order. Solution: You use the following code segment: bike_location | filter Neighbourhood == "Sands End" and No_Bikes >= 15 | sort by No_Bikes | project BikepointID, Street, Neighbourhood, No_Bikes, No_Empty_Docks, Timestamp | project BikepointID, Street, Neighbourhood, No_Bikes, No_Empty_Docks, Timestamp Does this meet the goal?. Yes. No.

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 a Fabric eventstream that loads data into a table named Bike_Location in a KQL database. The table contains the following columns: BikepointID - Street - Neighbourhood - No_Bikes - No_Empty_Docks - Timestamp - You need to apply transformation and filter logic to prepare the data for consumption. The solution must return data for a neighbourhood named Sands End when No_Bikes is at least 15. The results must be ordered by No_Bikes in ascending order. Solution: You use the following code segment: bike_location | filter Neighbourhood == "Sands End" and No_Bikes >= 15 | order by No_Bikes | project BikepointID, Street, Neighbourhood, No_Bikes, No_Empty_Docks, Timestamp. Yes. No.

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 a Fabric eventstream that loads data into a table named Bike_Location in a KQL database. The table contains the following columns: BikepointID - Street - Neighbourhood - No_Bikes - No_Empty_Docks - Timestamp - You need to apply transformation and filter logic to prepare the data for consumption. The solution must return data for a neighbourhood named Sands End when No_Bikes is at least 15. The results must be ordered by No_Bikes in ascending order. Solution: You use the following code segment: bike_location | filter Neighbourhood == "Sands End" and No_Bikes >= 15 | sort by No_Bikes asc | project BikepointID, Street, Neighbourhood, No_Bikes, No_Empty_Docks, Timestamp Does this meet the goal?. Yes. No.

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 a Fabric eventstream that loads data into a table named Bike_Location in a KQL database. The table contains the following columns: BikepointID - Street - Neighbourhood - No_Bikes - No_Empty_Docks - Timestamp - You need to apply transformation and filter logic to prepare the data for consumption. The solution must return Question: 36 Exam Heist data for a neighbourhood named Sands End when No_Bikes is at least 15. The results must be ordered by No_Bikes in ascending order. Solution: You use the following code segment: SELECT BikepointID, Street, Neighbourhood, No_Bikes, No_Empty_Docks, Timestamp FROM bike_location WHERE neighbourhood = 'Sands End' AND no_bikes >= 15 ORDER BY no_bikes Does this meet the goal?. Yes. No.

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?. Disable high concurrency. Create a custom pool. Modify the number of executors. Set the default environment.