You have a Fabric data warehouse that contains the following tables.You need to refresh the tables by using an automated pipeline. The solution must ensure that table updates occur in the correct order to maintain referential integrityWhich two tables should you refresh first? Each correct answer presents part of the solution.Note: Each correct selection is worth one point.
Answer(s): A,C
DimGeography and DimProduct must be started first.Because these two dimension tables have no dependencies on any other tables, they must be fully refreshed before the tables that rely on them can begin processing.
https://learn.microsoft.com/en-us/fabric/data-warehouse/tables
You have a Fabric deployment pipeline that contains the stages shown in the following table.Workspace1 contains a semantic model named Model1 and a report named Report1. Report1 is bound to Model1.You modify Report1 and Model1.You need to deploy the updated Report1 to Test. The solution must meet the following requirements: ● Ensure that Report1 remains bound to Model1 in Test. ● Minimize the number of items deployedWhat should you do?
Answer(s): A
To achieve both requirements, you must perform a Selective Deployment and select only the report for deployment.Remains bound to the semantic model: When using Fabric deployment pipelines, the platform features a native capability called autobinding. If identical or paired items exist across stages, deploying a report by itself automatically binds it to the corresponding semantic model in the target stage (Test/Workspace2), keeping the report working seamlessly.Minimize items deployed: By using selective deployment and checking only the box next to the report, you ensure that the semantic model is not redeployed, resulting in exactly one item being deployedSteps: 1. Open your Fabric deployment pipeline and look at Development.2. Switch to the Flat list view if you use folders to easily see individual items.3. Check the box only next to the report (leave the semantic model checkbox blank).4. Click Deploy to move the updated report to Test.
https://learn.microsoft.com/en-us/fabric/cicd/deployment-pipelines/intro-to-deployment-pipelines
HOTSPOT (Drag and Drop is not supported) (Drag and Drop is not supported)You have a Fabric tenant that contains a primary workspace named WS1 and a downstream workspace named WS2. WS1 contains curated Delta tables use by multiple teams at your company.You need to ensure that the company’s data science team can read the curated tables in WS2 without creating another physical copy of the data. The solution must ensure that source security is enforced for each user.What should you configure? To answer, select the appropriate options in the answer area.Note: Each correct selection is worth one point.Hot Area:
Box 1: Create OneLake Shortcuts To read curated Delta tables from the WS1 in the WS2 workspace without creating a physical copy of the data while ensuring that source security is enforced for each user, you should use OneLake Shortcuts configured with Passthrough authentication.No Physical Copies: OneLake Shortcuts act as virtual pointers (symbolic links). They mount the existing Delta tables directly from the primary workspace's Lakehouse or Warehouse into the downstream workspace without copying or moving any underlying data.Enforced Source Security: When using internal OneLake shortcuts with the passthrough authentication model, the identity of the user querying the shortcut is passed straight through to the source. This guarantees that OneLake security or item permissions (like Row-Level Security) defined in the primary workspace are strictly honored—meaning users can only see data they have explicit permissions to read at the source.Box 2: User identity mode You should use User identity mode for the SQL analytics endpoint in the downstream workspace.Using User identity mode ensures compliance with your security constraint—allowing data to be securely virtualized through OneLake shortcuts without duplicating any physical data or compromising data governance.Enforces Source Security: In User identity mode, the SQL analytics endpoint passes the signed-in user's identity directly down to OneLake. Read access is completely governed by the security rules, permissions, and OneLake roles/policies (such as Row-Level Security or Column-Level Security) defined at the source (primary workspace).Avoids Over-Privileged Access: If you were to use Delegated identity mode, the endpoint would query the data using the identity of the workspace or item owner instead. This would bypass the source system's individual user permissions and instead expose data to users based on what the owner is allowed to see.
https://learn.microsoft.com/en-us/fabric/fundamentals/fabric-terminology https://www.reddit.com/r/MicrosoftFabric/comments/1s5krz5/ how_do_you_structure_user_access_across_fabric/
HOTSPOT (Drag and Drop is not supported) (Drag and Drop is not supported)You have a Fabric workspace named WS1 that is connected to the main branch of an Azure DevOps Git repository. WS1 contains a lakehouse, a notebook, and a pipeline.Two data engineers must update the notebook and pipeline concurrently for separate features.You need to configure version control to support isolated feature development and controlled integration into the main branch. The solution must meet the following requirements: ● Prevent one engineer’s unreviewed workspace changes from affecting the other engineer’s workspace. ● Support a review before changes are integrated into the main branch. ● Track changes to the Fabric items in Git.How should you configure the development workflow? To answer, select the appropriate options in the answer area.Note: Each correct selection is worth one point.Hot Area:
Box 1: A dedicated Fabric workspace A dedicated Fabric workspace (per user or per feature via branched workspaces) is the best option to set up the development workflow.Isolation: Microsoft Fabric enforces a strict one-workspace-to-one-branch model. A single shared workspace makes live changes visible to everyone immediately. Giving each user a dedicated workspace prevents unreviewed changes from colliding.Review Process: Developers work in their own workspace linked to a feature branch. They submit changes through a pull request in Azure DevOps to review code before merging into the main branch.Tracking: Bi-directional Git integration tracks notebooks, pipelines, and other supported Fabric items directly in your Git repository.Box 2: A dedicated feature branch A dedicated feature branch must be used for the branch connected to each development environment.Workspace Isolation: Connecting each user's dedicated Fabric workspace to a separate feature branch keeps their work separate. Changes made in User A's workspace only affect User A's feature branch. They do not impact User B's workspace or branch.Controlled Reviews: Developers use pull requests in Azure DevOps to merge their feature branch into the main branch. This allows team members to review code and test items before integration.Git Tracking: Each feature branch records changes to the notebook, pipeline, and lakehouse metadata. Git tracks every commit made during development.Box 3: Merge by using pull request How to configure a dedicated feature branch Create Feature Branches: Create two new branches off the main branch in Azure DevOps. For example, feature/notebook-update and feature/pipeline-update.Connect User 1: Link the first user's dedicated Fabric workspace to the first feature branch.Connect User 2: Link the second user's dedicated Fabric workspace to the second feature branch.Merge via Pull Request: Require a pull request review before any feature branch merges back into main.
https://learn.microsoft.com/en-us/fabric/fundamentals/understand-best-practices-fabric-cicd
You need to create a workflow for the new book cover images.Which two components should you include in the workflow? Each correct answer presents part of the solution.Note: Each correct selection is worth one point.
Answer(s): C,E
Correct: * a streaming dataflow* a blob storage action Incorrect: * a data pipeline * a notebook that uses Apache Spark Structured Streaming * a reflex item * a time-based schedule * an activator itemNote: * a streaming dataflow Streaming dataflows allow authors to connect to, ingest, mash up, model, and build reports based on streaming in near real-time data directly in the Power BI service.* a blob storage action Azure Blob storage is Microsoft's object storage solution for the cloud. Blob storage is optimized for storing massive amounts of unstructured data. Unstructured data is data that doesn't adhere to a particular data model or definition, such as text or binary data.You can use Azure Blobs as a streaming or reference input. Streaming blobs are checked every second for updates. Unlike a streaming blob, a reference blob is only loaded at the beginning of the refresh. It's static data that isn’t expected to change, and the recommended limit for static data is 50 MB or less.Connect to Azure Blob Storage from workflows in Azure Logic Apps You can access your Azure Blob Storage account and container from a workflow in Azure Logic Apps using the Azure Blob Storage connector. This connector provides triggers and actions that your workflow can use for blob operations. You can then create automated workflows that run when triggered by events in your storage container or in other systems, and run actions to work with data in your storage container. For example, you can access and manage files stored as blobs in your Azure storage account.Scenario: Requirements. Data Requirements When a new book cover image arrives in the Files folder, process the image as soon as possible.Existing Environment. Data Processing 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.
https://learn.microsoft.com/en-us/azure/connectors/connectors-create-api-azureblobstorage https://learn.microsoft.com/en-us/power-bi/transform-model/dataflows/dataflows-streaming
Post your Comments and Discuss Microsoft DP-700 exam prep with other Community members:
Our website is free, but we have to fight against AI bots and content theft. We're sorry for the inconvenience caused by these security measures. You can access the rest of the DP-700 content, but please register or login to continue.