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DP-600 study materials
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DP-600 practice questions

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Question 1Plan, implement, and manage a solution for data analytics

A service principal must call the Microsoft Fabric REST APIs to create workspaces. What must a Fabric administrator configure?

  1. Enable the 'Service principals can use Fabric APIs' tenant setting for a security group. Correct answer.
  2. Enable the 'Users can create Fabric items' tenant setting for the service principal's group.
  3. Assign the principal as a capacity admin on the Fabric capacity in the Azure portal.
  4. Grant the principal the Fabric Administrator role in the Microsoft 365 admin center and consent to the Fabric API.

Explanation

Fabric API access for service principals is controlled by a developer tenant setting that must be enabled and scoped to a security group containing the principal. After that, the principal still needs workspace or item permissions to perform operations. Administrative Microsoft 365 roles are unrelated to this API gate.

Question 2Plan, implement, and manage a solution for data analytics

Which workspace role is required to add or remove workspace members and to delete the workspace?

  1. Contributor
  2. Admin Correct answer.
  3. Member
  4. Viewer

Explanation

Workspace roles are Admin, Member, Contributor, and Viewer. Only Admin can manage membership and delete the workspace, while Members can add users to lower roles and share items.

Question 3Plan, implement, and manage a solution for data analytics

A team wants to create lakehouses, notebooks, and pipelines in a new workspace. What is required for those items to work?

  1. Each team member must hold a Power BI Pro license and nothing else.
  2. Each team member must hold a Power BI Premium Per User license and nothing else.
  3. The tenant must have a Microsoft 365 E5 subscription assigned to the team.
  4. The workspace must be assigned to a Fabric capacity or a Power BI Premium capacity. Correct answer.

Explanation

Fabric workloads such as lakehouses, notebooks, pipelines, and warehouses run on capacity, so the workspace must be backed by Fabric capacity or Power BI Premium capacity. Pro and PPU licenses govern Power BI content consumption rather than Fabric compute.

Question 4Plan, implement, and manage a solution for data analytics

A deployment pipeline moves a semantic model from Development to Test. The model must connect to a different database in each stage. What should you configure?

  1. A separate pipeline per stage so that items can be copied manually.
  2. A workspace-level parameter that is edited after each deployment.
  3. A Git branch per stage and merge the branches after each deployment.
  4. A deployment rule on the semantic model that sets the parameter value for the target stage. Correct answer.

Explanation

Deployment rules allow parameter values and data source connections to differ per stage so that one item definition can target stage-specific resources. Rules are defined per item and per target stage inside the pipeline.

Question 5Plan, implement, and manage a solution for data analytics

Which source control systems can a Fabric workspace be connected to through native Git integration?

  1. Any Git provider that exposes an HTTPS endpoint.
  2. GitHub repositories only.
  3. Azure DevOps Git repositories and GitHub repositories. Correct answer.
  4. Azure DevOps Git repositories only.

Explanation

Fabric Git integration natively supports Azure DevOps Git repositories and GitHub repositories connected at the workspace level. A workspace is connected to one repository and one branch at a time.

Question 6Plan, implement, and manage a solution for data analytics

A user must be able to apply the Certified endorsement to semantic models without being a Fabric administrator. What is required?

  1. Membership in the Fabric Administrator role.
  2. The certify permission granted by a Fabric admin. Correct answer.
  3. Contributor role on every workspace that contains semantic models.
  4. A sensitivity label applied to the model.

Explanation

Promoted endorsement can be applied by anyone with write permission on the item, but Certified endorsement requires the certify permission. A Fabric admin grants that permission through the Certification tenant setting to selected users or groups.

Question 7Plan, implement, and manage a solution for data analytics

What is the primary purpose of Fabric domains?

  1. They determine which capacity a workspace's items are billed to.
  2. They control which users may sign in to the Fabric portal.
  3. They group workspaces by business area for delegated governance. Correct answer.
  4. They replace workspaces as the security boundary for Fabric items.

Explanation

Domains group workspaces along business or data-mesh lines so that Fabric admins can delegate administration to domain admins. Workspaces remain the security and permission boundary, and capacity assignment is handled separately.

Question 8Plan, implement, and manage a solution for data analytics

Which statement describes an OneLake shortcut?

  1. It encrypts data at rest in the target lakehouse.
  2. It copies source data into OneLake and refreshes the copy on a schedule.
  3. It stores a reference to data in another location without copying it. Correct answer.
  4. It materializes a physical table in the lakehouse for each source file.

Explanation

A shortcut is a virtual pointer to data held in another OneLake location or in supported external storage such as ADLS Gen2 or Amazon S3. Because the data is not copied, no additional OneLake storage is consumed and no refresh schedule is needed.

Question 9Plan, implement, and manage a solution for data analytics

Users report slow interactive queries and several scheduled refreshes are being rejected during peak hours. Which tool should you open first to confirm that the capacity is being throttled?

  1. The lineage view of the affected workspace.
  2. The Monitoring hub activity list for the capacity.
  3. The Microsoft Fabric Capacity Metrics app. Correct answer.
  4. The Fabric admin REST API.

Explanation

The Capacity Metrics app reports utilization over time together with throttling events and the interactive versus background breakdown, which identifies what is overloading the capacity. Monitoring hub and lineage show item activity and dependencies rather than capacity pressure.

Question 10Plan, implement, and manage a solution for data analytics

A lakehouse is labeled 'Highly Confidential'. A new semantic model imports data from that lakehouse. What happens to the label?

  1. The downstream item inherits the label from the item it consumes. Correct answer.
  2. The downstream item is blocked from being created without a new label.
  3. Labels apply only to Power BI semantic models and reports, not to lakehouses.
  4. Every new item in the workspace receives the label automatically.

Explanation

Sensitivity labels propagate to downstream items that are built on labeled data, and when several labels apply the most restrictive one wins. This keeps protection consistent without manually labeling every derived item.

Question 11Plan, implement, and manage a solution for data analytics

A workspace must read from an ADLS Gen2 account that is protected by a firewall, without storing credentials in the item. Which workspace feature enables this?

  1. The workspace identity, a service principal attached to the workspace. Correct answer.
  2. The user account that workspace members use to sign in to the portal.
  3. The workspace Admin role, which is extended to manage data source access.
  4. The credentials stored on an on-premises data gateway bound to the workspace.

Explanation

A workspace identity is a service principal created for the workspace and used for scenarios such as trusted workspace access to firewall-protected ADLS Gen2. Access is granted to the identity in the storage account instead of to individual users.

Question 12Plan, implement, and manage a solution for data analytics

An administrator wants one view that lists recent notebook, pipeline, and refresh runs with their status across several workspaces. Which feature provides this?

  1. The OneLake explorer.
  2. The capacity settings page in the admin portal.
  3. The Monitoring hub. Correct answer.
  4. The workspace lineage view.

Explanation

The Monitoring hub shows recent activity across the workspaces a user can access, including notebook, pipeline, and refresh runs with status, duration, and submitter. Lineage and capacity settings pages serve different purposes.

Question 13Plan, implement, and manage a solution for data analytics

A Fabric admin wants capacity admins to control one specific tenant setting for their own capacities while the tenant default stays centrally managed. What should the admin configure?

  1. Assign the capacity admins the Fabric Administrator role.
  2. Create a security group and add it to each workspace as Admin.
  3. Delegate that tenant setting to capacity admins in the Fabric admin portal. Correct answer.
  4. Enable the setting tenant-wide and ask capacity admins to behave carefully.

Explanation

Individual tenant settings can be delegated so that capacity admins manage the setting within their own capacities while the tenant-level default remains under central control. Delegation is configured per setting rather than by granting a broader role.

Question 14Plan, implement, and manage a solution for data analytics

A third-party modeling tool must be able to read and write a semantic model through the XMLA endpoint. Which configuration is required?

  1. Enable the XMLA endpoints tenant setting for a shared-capacity workspace.
  2. Grant Build permission and connect with any client that can issue DAX queries.
  3. Enable the XMLA endpoints tenant setting for a capacity-backed workspace. Correct answer.
  4. Publish the model to a Pro workspace with the large model storage format enabled.

Explanation

XMLA endpoints are available only for workspaces on Fabric or Premium capacity, and the tenant setting that allows XMLA endpoints must be enabled. Read/write connections additionally require the write-enabled option and suitable permissions on the model.

Question 15Plan, implement, and manage a solution for data analytics

Which items does Fabric Git integration keep synchronized with the connected repository?

  1. Only semantic models and reports.
  2. Only items that were created after the workspace was connected to Git.
  3. Only the item types that Fabric Git integration supports. Correct answer.
  4. Every item in the workspace, including preview item types that lack source control support.

Explanation

Git integration tracks only the item types that support source control; other items remain in the workspace but are untouched by commit and update operations. The supported list grows over time and is documented per item type.

Question 16Plan, implement, and manage a solution for data analytics

Which approach best isolates development, test, and production content in Fabric?

  1. A single workspace with a folder for each environment.
  2. A separate capacity allocated to each developer.
  3. Separate workspaces per stage connected by a deployment pipeline. Correct answer.
  4. Git branches that report consumers open directly.

Explanation

Deployment pipelines promote content between workspaces that represent stages, so production content and permissions stay isolated from in-progress development. Folders and branches share the same workspace permissions and therefore do not isolate environments.

Question 17Plan, implement, and manage a solution for data analytics

A team needs full T-SQL DML support, multi-table transactions, and T-SQL security over Delta tables in OneLake. Which Fabric item should they choose?

  1. A lakehouse with shortcuts to the Delta files.
  2. A KQL database.
  3. A mirrored database.
  4. A warehouse. Correct answer.

Explanation

A Fabric warehouse exposes a full T-SQL surface with DML, multi-table transactions, and T-SQL security over Delta-formatted tables. A lakehouse T-SQL endpoint offers read and limited write capabilities rather than full transactional DML.

Question 18Plan, implement, and manage a solution for data analytics

A user must be able to query one semantic model but must not see any other item in the workspace. What is the least-privilege approach?

  1. Assign the Viewer role on the workspace.
  2. Share the individual semantic model with the user. Correct answer.
  3. Assign the Contributor role on the workspace.
  4. Add the user to the security group that the workspace uses.

Explanation

Sharing an individual item grants permission only on that item, so the rest of the workspace stays invisible to the user. Workspace roles grant access across all items in the workspace and are therefore broader than needed.

Question 19Plan, implement, and manage a solution for data analytics

Which statement describes the Microsoft Fabric trial?

  1. It grants a Power BI Pro license that does not expire.
  2. It can be shared with any number of users indefinitely.
  3. It provides unlimited capacity for twelve months.
  4. It provides a 60-day trial Fabric capacity for the individual user. Correct answer.

Explanation

The Fabric trial gives a single user a 60-day trial capacity that behaves like a Fabric capacity for building and testing items. At the end of the period the trial expires and can be converted into a paid capacity.

Question 20Plan, implement, and manage a solution for data analytics

A Fabric admin must allow only members of the DataPlatform security group to create Fabric items while everyone else continues to view existing content. What should the admin do?

  1. Remove the Viewer role from all other users.
  2. Scope the 'Users can create Fabric items' tenant setting to that security group. Correct answer.
  3. Set every workspace to read-only in workspace settings.
  4. Disable the Fabric trial for the whole tenant.

Explanation

The 'Users can create Fabric items' tenant setting can be enabled for everyone, scoped to specific security groups, or disabled. Scoping it to one group prevents creation by others while leaving read access to shared content unaffected.

Question 21Plan, implement, and manage a solution for data analytics

Which statement about assigning workspaces to Fabric domains is correct?

  1. Workspaces are assigned to domains by the capacity administrator.
  2. A workspace can be assigned to only one domain. Correct answer.
  3. A workspace can belong to several domains at the same time.
  4. A workspace must belong to a domain before it can use capacity.

Explanation

A workspace belongs to at most one domain, and workspaces that are never assigned fall under the default domain. Domain assignment is a governance grouping that is independent of capacity assignment.

Question 22Plan, implement, and manage a solution for data analytics

A team wants a continuously updated copy of an Azure SQL Database in OneLake without authoring pipelines or schedules. Which Fabric feature should they use?

  1. A OneLake shortcut to the Azure SQL Database.
  2. An eventstream with a custom application endpoint.
  3. Database mirroring. Correct answer.
  4. A copy activity pipeline that runs every five minutes.

Explanation

Mirroring continuously replicates a source database into OneLake as Delta tables with no pipeline or schedule to maintain. Shortcuts reference external storage that Fabric can read directly, which does not include relational database tables.

Question 23Plan, implement, and manage a solution for data analytics

Scheduled refreshes of a semantic model that reads from an on-premises SQL Server fail in the Fabric service, and on-premises connectivity is mandatory. What should you do?

  1. Create a OneLake shortcut to the on-premises SQL Server.
  2. Install a standard on-premises data gateway and add the SQL Server data source. Correct answer.
  3. Enable the XMLA endpoint on the workspace.
  4. Install a personal gateway on the author's machine and use it for all refreshes.

Explanation

A standard on-premises data gateway gives the Fabric service a managed, highly available path to on-premises sources and can be shared across users and items. Personal gateways are intended for single-user scenarios and are not appropriate for shared production refreshes.

Question 24Plan, implement, and manage a solution for data analytics

What does surge protection do on a Fabric capacity?

  1. It pauses billing for the capacity during peak hours.
  2. It automatically adds capacity units to the SKU whenever usage exceeds the purchased limit.
  3. It holds back background jobs while interactive usage is over capacity limits. Correct answer.
  4. It moves workloads to another capacity in the same region.

Explanation

Surge protection activates when interactive usage exceeds the capacity limits and delays or rejects background operations so that interactive queries and reports can still complete. Fabric does not scale capacity automatically as part of surge protection; scaling is a separate administrative action.

Question 25Plan, implement, and manage a solution for data analytics

You commit changes in a Fabric workspace, and a colleague later pushes commits to the same branch. The workspace still shows the older item definitions. What should you do?

  1. Export the items and import them again manually.
  2. Delete the workspace and recreate it from the branch.
  3. Disconnect and reconnect the workspace to the repository.
  4. Run Update from Git in the workspace source control pane. Correct answer.

Explanation

Update from Git pulls the current repository state into the workspace, including commits made by others. Disconnecting or recreating the workspace is unnecessary and would discard items that are not tracked by source control.

Question 26Plan, implement, and manage a solution for data analytics

A Fabric administrator pauses the Fabric capacity that backs several workspaces over a weekend. What happens to those workspaces while the capacity is paused?

  1. Items in those workspaces are unavailable and scheduled jobs fail. Correct answer.
  2. Only workspace administration is blocked; queries and notebooks keep running.
  3. Scheduled jobs queue up and run automatically once capacity resumes.
  4. Items stay queryable in read-only mode using cached results.

Explanation

All Fabric compute runs on a capacity, so pausing it stops the compute that items in its assigned workspaces depend on. Users cannot open or query the items during the pause, and background activities such as scheduled refreshes or pipeline runs fail rather than completing. When the capacity is resumed, the workspaces become available again, but work that was attempted during the pause is not replayed automatically.

Question 27Prepare and serve data

A Spark notebook in a Fabric lakehouse runs df.write.saveAsTable("sales"). In which format are the table's files stored?

  1. CSV files
  2. JSON Lines files
  3. Parquet files with no transaction log
  4. Delta Lake Correct answer.

Explanation

Lakehouse tables in Microsoft Fabric are always Delta tables: the write creates Parquet data files plus a Delta transaction log in the Tables area of OneLake. The transaction log provides ACID transactions, time travel, and schema enforcement, and it is what the SQL analytics endpoint reads.

Question 28Prepare and serve data

You must query Parquet files that already sit in an ADLS Gen2 account from a Fabric lakehouse, without copying or duplicating the data. What should you create?

  1. A dataflow that copies the files hourly
  2. An eventstream that ingests the files continuously
  3. A mirrored database of the storage account
  4. A shortcut to the ADLS Gen2 location Correct answer.

Explanation

A OneLake shortcut is a zero-copy reference that makes data in external storage appear as a folder in the lakehouse, so queries read the original files in place. No data movement or scheduled copy job is involved.

Question 29Prepare and serve data

Which semantic model storage mode reads Delta tables directly from OneLake without importing data and without translating queries to the source?

  1. Direct Lake mode Correct answer.
  2. Dual mode over the lakehouse
  3. DirectQuery over the SQL analytics endpoint
  4. Import mode with scheduled refresh

Explanation

Direct Lake loads Delta Parquet columns into memory on demand and queries them directly, so there is no import refresh and no query translation against the source engine. This gives near-import performance over large OneLake tables.

Question 30Prepare and serve data

In a medallion architecture, which layer typically holds validated, deduplicated, and conformed data that multiple downstream consumers can reuse?

  1. Bronze
  2. Gold
  3. Silver Correct answer.
  4. Landing zone

Explanation

The silver layer stores cleansed, deduplicated, and conformed data that is still reasonably normalized so several consumers can reuse it. Gold is the curated, business-ready layer, while bronze or landing holds raw ingested data.

Question 31Prepare and serve data

A user must be able to create lakehouses and notebooks in a workspace but must not be able to add or remove workspace members. Which workspace role should you assign?

  1. Contributor Correct answer.
  2. Viewer, which grants read-only access
  3. Admin, which manages permissions
  4. Member, which allows sharing items

Explanation

The Contributor role allows a user to create and edit items in the workspace but not to manage workspace membership or settings. Only Admins can add or remove members and change workspace permissions.

Question 32Prepare and serve data

What does running VACUUM on a Delta table do?

  1. Compacts many small files into a smaller number of larger files
  2. Recomputes column statistics used by the query optimizer
  3. Removes unreferenced files past the retention period Correct answer.
  4. Converts Parquet files into the Delta Lake format

Explanation

VACUUM physically deletes data files that are no longer referenced by the Delta log and are older than the configured retention threshold. Files newer than the retention window are protected so that readers and time travel are not broken.

Question 33Prepare and serve data

Which pipeline activity copies data from a source dataset to a destination dataset?

  1. Copy Correct answer.
  2. Set variable
  3. ForEach
  4. Lookup

Explanation

The Copy activity is the data movement activity in Fabric data pipelines; it reads a source dataset and writes to a sink dataset. Lookup, ForEach, and Set variable are control-flow activities that do not move data.

Question 34Prepare and serve data

Which endorsement level can only be granted by users that a Fabric administrator has authorized for that purpose?

  1. Master data
  2. Verified
  3. Promoted
  4. Certified Correct answer.

Explanation

Certification is the highest endorsement level and requires a user who has been granted certification rights by a Fabric administrator. Promotion is self-service and can be applied by any user with write permission on the item.

Question 35Prepare and serve data

A 2 TB Delta sales table has columns SaleId (unique), OrderDate (six years of dates), CustomerName, and Notes. Most queries filter on a date range. Which column should you use as the partition key?

  1. OrderDate Correct answer.
  2. SaleId
  3. CustomerName
  4. Notes

Explanation

Partition on a column that is frequently used in filters and has moderate cardinality, such as a date, so queries can skip entire folders. A unique column creates an enormous number of tiny partitions, and high-cardinality text columns produce the same problem.

Question 36Prepare and serve data

A lakehouse table is optimized with OPTIMIZE sales ZORDER BY (CustomerId). What is the main benefit?

  1. It enforces a unique constraint on the CustomerId column
  2. It removes duplicate CustomerId values from every file
  3. It converts CustomerId into a numeric surrogate key at read time
  4. Related rows are co-located so more files can be skipped Correct answer.

Explanation

Z-ORDER reorganizes data during OPTIMIZE so that rows with similar CustomerId values are clustered into the same files. Queries that filter on CustomerId can then use file statistics to skip most files instead of scanning the whole table.

Question 37Prepare and serve data

A pipeline must load only the rows that changed since the previous successful run. Which pattern should you implement?

  1. Full load with a truncate-and-reload step
  2. Keep a watermark value and filter the source by modified date Correct answer.
  3. Change Data Capture on the source table, read through the SQL analytics endpoint
  4. Use a ForEach activity with a fixed batch size

Explanation

The watermark pattern stores the last successfully loaded timestamp (for example in a pipeline variable or a control table) and filters the source by the modified date using that value. After a successful load, the watermark is updated so the next run starts where the last one ended.

Question 38Prepare and serve data

You configure a Dataflow Gen2 query with a lakehouse data destination. What is created in the lakehouse when the dataflow runs?

  1. A CSV file in the Files area only
  2. A Delta table Correct answer.
  3. A shortcut to the dataflow definition
  4. A SQL view over the source system

Explanation

Writing a Dataflow Gen2 output to a lakehouse creates a Delta table in the Tables area of the lakehouse. The table can then be queried from the SQL analytics endpoint, notebooks, or a semantic model.

Question 39Prepare and serve data

A source file gains a new column, and an append to an existing Delta table fails because of the schema mismatch. Which Spark option allows the append to add the new column to the table schema?

  1. optimizeWrite enabled
  2. overwriteSchema set to true
  3. autoCompact enabled
  4. mergeSchema set to true Correct answer.

Explanation

Setting mergeSchema to true during a write allows Delta to evolve the table schema by adding the new column instead of failing. overwriteSchema replaces the schema and is appropriate only when the whole table is being rewritten.

Question 40Prepare and serve data

You need near real-time replication of an Azure SQL Database into OneLake without building or scheduling pipelines. Which Fabric feature should you use?

  1. A Copy activity with a tumbling window trigger
  2. Dataflow Gen2 with a refresh every 15 minutes
  3. Mirroring Correct answer.
  4. An eventstream with a custom app source

Explanation

Database mirroring continuously replicates the source database into OneLake as Delta tables with near real-time latency and no pipeline authoring. The replicated tables are available to the SQL analytics endpoint and to Direct Lake models.

Question 41Prepare and serve data

A semantic model must import a small Product dimension but query a very large FactSales table in DirectQuery. What should you configure?

  1. A Direct Lake model that points at the lakehouse
  2. A live connection to a shared Power BI dataset
  3. Import mode with incremental refresh for FactSales
  4. A composite model with mixed storage modes Correct answer.

Explanation

A composite model allows different tables in the same model to use different storage modes, so the dimension can be imported while the fact table stays in DirectQuery. Relationships between the two storage modes are supported.

Question 42Prepare and serve data

Which T-SQL statement applies inserts, updates, and deletes from a staging table to a warehouse dimension table in a single pass?

  1. MERGE Correct answer.
  2. UPDATE with a correlated subquery
  3. TRUNCATE TABLE followed by INSERT
  4. INSERT INTO ... SELECT

Explanation

MERGE compares a source and a target on a join key and applies the matching insert, update, or delete actions in one statement. This is the standard way to implement upserts into a warehouse dimension.

Question 43Prepare and serve data

A user runs an INSERT against a lakehouse table through the SQL analytics endpoint and receives an error. What explains the failure?

  1. The endpoint presents Delta tables as read-only Correct answer.
  2. The lakehouse must be attached to a Premium capacity
  3. The table must be converted to Parquet first
  4. The user needs db_owner on the endpoint

Explanation

The SQL analytics endpoint exposes lakehouse Delta tables as read-only T-SQL objects; writes must go through Spark notebooks, dataflows, pipelines, or the lakehouse load tools. Granting a higher database role does not enable writes.

Question 44Prepare and serve data

A lakehouse item has a sensitivity label applied. What happens to a Power BI report built on a semantic model that reads that lakehouse?

  1. The report is automatically moved to another workspace
  2. Only the report owner sees a warning banner
  3. Downstream items inherit the same label Correct answer.
  4. The label is dropped because reports cannot inherit labels

Explanation

Sensitivity labels propagate downstream, so items built on labelled data, such as semantic models and reports, inherit the label. This keeps protection consistent across the data estate without manual labelling of each item.

Question 45Prepare and serve data

You must ingest continuous device telemetry and land it in a lakehouse table with minimal latency. Which Fabric item should you use?

  1. A Dataflow Gen2 with a scheduled refresh
  2. A notebook run by a tumbling window trigger
  3. A data pipeline with a 15-minute schedule
  4. An eventstream with a lakehouse destination Correct answer.

Explanation

An eventstream consumes streaming data from sources such as Event Hubs or IoT devices and can write it to a lakehouse destination as a Delta table. This provides continuous, low-latency ingestion rather than scheduled batches.

Question 46Prepare and serve data

You want consumers of a Direct Lake semantic model to see only data from specific folders within a lakehouse. Which feature should you use?

  1. SQL analytics endpoint permissions
  2. OneLake data access roles Correct answer.
  3. Row-level security in the semantic model
  4. Workspace roles assigned as Viewer

Explanation

OneLake data access roles grant or restrict access at the folder level inside a lakehouse, and Direct Lake respects those role assignments when reading Delta files. This lets you scope which tables a model or user can consume.

Question 47Prepare and serve data

You disable V-Order for a Spark session, write a table, then re-enable V-Order and append more rows. What is the result?

  1. The append fails because V-Order is a table-level property
  2. The table becomes unreadable by the SQL analytics endpoint
  3. Only the new files are V-Ordered Correct answer.
  4. The whole table is rewritten with V-Order applied

Explanation

V-Order is applied by the Fabric engines at write time, so the setting in effect during each write determines the layout of the files produced by that write. Previously written files keep their original layout until a rewrite such as OPTIMIZE occurs.

Question 48Prepare and serve data

A Direct Lake semantic model begins returning slower results after a large Delta table is updated, and queries fall back to DirectQuery. Which condition explains the fallback?

  1. The query or column count exceeds Direct Lake guardrails Correct answer.
  2. The model has not been refreshed for more than 24 hours
  3. The workspace is assigned to a Fabric trial capacity
  4. The Delta table was converted to Parquet without a transaction log

Explanation

Direct Lake serves queries from in-memory column segments, but falls back to DirectQuery when a query cannot be satisfied that way, for example when it exceeds capacity guardrails or uses unsupported features. Watching for fallback events lets you tune the model or capacity to keep queries in Direct Lake mode.

Question 49Prepare and serve data

A deployment pipeline promotes a semantic model from Dev to Test, but the Test copy must point at a different database. What should you configure?

  1. A separate workspace for every stage
  2. A sensitivity label on the semantic model
  3. An XMLA read/write endpoint for the workspace
  4. A deployment rule on the Test stage Correct answer.

Explanation

Deployment rules let you change a parameter or data source for a specific stage, such as pointing the Test copy at the Test database, while the same item definition moves through the pipeline. Rules are defined per stage on the supported item types.

Question 50Prepare and serve data

A Delta table receives many small files from frequent streaming writes. You want to compact the files and reclaim space from old versions immediately, but the retention period is 7 days. What is the correct expectation?

  1. Drop and recreate the table to reset the transaction log
  2. Run OPTIMIZE; VACUUM only removes files past the retention window Correct answer.
  3. Set delta.logRetentionDuration to zero and then run OPTIMIZE on the table
  4. Set VACUUM retention to zero hours so every previous version is deleted first

Explanation

OPTIMIZE compacts small files into larger ones, while VACUUM can only delete files that are unreferenced and older than the retention threshold, which is 7 days by default. Space from recently written versions is therefore released only after the retention window elapses.