DP-700 Practice Test 3 — 10 Questions

Question 1

Your organization wants to implement near real-time data ingestion from an Azure SQL Database into Fabric for reporting. You must minimize the impact on the source database's performance and avoid manual pipeline scheduling. Which solution should you implement?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Fabric Mirroring for Azure SQL Database.. Mirroring in Fabric provides a low-latency, continuous synchronization path from supported databases. It uses the source database's transaction log to capture changes (CDC), which is much more efficient than traditional polling and does not require the user to manage complex schedules or orchestration pipelines to keep data synchronized.

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A Pipeline with a Copy Activity using a 'Tumbling Window' trigger.

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A Dataflow Gen2 with incremental refresh enabled.

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A Spark Notebook using the 'JDBC' connector in a loop.

Question 2

A data engineering team is using a service principal to automate the deployment and management of Fabric items via the REST API. Which THREE of the following actions must be completed to enable a service principal to work with Fabric APIs?

Accepted Answer

Register an application in Microsoft Entra ID.. Using service principals for automation is a standard practice in enterprise environments. It requires a specific set of configuration steps across both Microsoft Entra ID and the Fabric Admin portal. Ensuring all these steps are completed is necessary for successful authentication and authorization of the automated scripts.

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Grant the service principal the 'Global Administrator' role in Entra ID.

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Assign a Power BI Pro license directly to the service principal.

Question 3

You are implementing a multi-workspace architecture in Fabric. You need to enable a 'Managed Identity' for a specific Fabric workspace to allow it to securely access an Azure Data Lake Storage (ADLS) Gen2 account without managing service principal secrets. What is a key requirement for using Workspace Managed Identities in Fabric?

Accepted Answer

The workspace must be hosted on a Fabric (F-SKU) or Power BI Premium (P-SKU) capacity.. Workspace Managed Identities (WMI) provide a secure way for Fabric to interact with other Azure services. This feature eliminates the need for developers to handle credentials. Understanding the prerequisites, such as the capacity type and the role of the identity, is crucial for a secure and automated analytics infrastructure.

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The workspace must be assigned to a Pro or Premium Per User (PPU) license.

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The identity must be manually created in Microsoft Entra ID before it can be assigned to the workspace.

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The Managed Identity can only access resources within the same Azure region as the Fabric capacity.

Question 4

You have a large Delta table that is frequently queried. You notice that queries are slow due to small file overhead. Which command should you run to optimize this table?

Accepted Answer

OPTIMIZE table_name. The OPTIMIZE command is the standard Delta Lake maintenance operation that compacts small files into larger ones, drastically improving read performance. When combined with Z-Ordering, it also organizes data physically based on column values, which further accelerates query performance for filters. This is a critical task for maintaining high-performance analytical tables in a Lakehouse environment, preventing the performance degradation caused by file fragmentation.

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VACUUM table_name

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ANALYZE TABLE table_name COMPUTE STATISTICS

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REORG TABLE table_name APPLY

Question 5

You need to access data from an external Azure Data Lake Storage (ADLS) Gen2 account in a Fabric Lakehouse without duplicating the physical data. Which feature should you use?

Accepted Answer

Shortcut. Shortcuts provide a way to reference data stored in external locations without the need for data movement or replication. This approach reduces storage costs and ensures that the Fabric environment always sees the most current version of the source data. It is a fundamental concept in OneLake for maintaining a single source of truth across different cloud providers.

Answer

Dataflow Gen2

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Copy Activity

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Mirroring

Question 6

Refer to the exhibit. You are reviewing the JSON definition for a Spark Job Definition in Microsoft Fabric. The job is failing after exhausting all retries during periods of high capacity utilization. To ensure the job has a better chance of succeeding without increasing the maxRetryCount, which change should you implement in the job configuration?

Accepted Answer

Add a 'retryIntervalInSeconds' property to the retryPolicy.. When a Spark job fails due to capacity constraints or resource contention, the failure often happens quickly. By adjusting the retry policy to include an interval or delay, the job can wait for transient capacity spikes to subside before attempting the next run. This increases the likelihood of success in a busy Fabric environment where resources are shared.

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Increase the 'numExecutors' value to 10.

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Change the 'runtimeVersion' to 1.3.

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Change the 'driverSize' to 'Large'.

Question 7

You are setting up a Microsoft Fabric environment for a development team. You want to use Git integration to allow developers to work in their own branches. Which THREE Fabric items are currently supported for Git integration?

Accepted Answer

Lakehouse. Not all Fabric items are currently supported by Git integration. Knowing which items can be synchronized is vital for planning your development lifecycle and source control strategy. As Fabric evolves, more items are added, but the core items like Lakehouses, Notebooks, and Semantic Models form the basis of most synchronization workflows.

Answer

Data Pipeline

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KQL Queryset

Question 8

You are optimizing a Fabric Warehouse for complex analytical queries involving large fact tables. Which TWO actions should you perform to improve query performance?

Accepted Answer

Implement clustered columnstore indexes on the fact table.. Optimizing warehouse performance requires a combination of effective indexing strategies and data distribution management. By choosing the right clustering columns, you reduce data scanning requirements, while partition pruning ensures the engine only reads relevant segments. These techniques are fundamental for scaling analytical workloads in Microsoft Fabric, as they directly influence the amount of data processed during query execution and help maintain consistent performance under high concurrency.

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Convert all tables to heap structures.

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Increase the number of rows per file to 1 billion.

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Disable statistics collection for all columns.

Question 9

You are managing a Microsoft Fabric environment and need to implement 'Endorsement' for several high-quality datasets to help users find reliable data. Which TWO levels of endorsement can you apply to Fabric items?

Accepted Answer

Promoted. Endorsement helps users identify trustworthy and high-quality items in Fabric. It is a key part of data governance. There are two specific levels of endorsement that signify different degrees of validation, helping to distinguish between casual development items and certified, authoritative business assets used for critical reporting.

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Verified

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Approved

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Validated

Question 10

Which approach is most efficient for loading a large volume of historical data into a Fabric Lakehouse from an external source?

Accepted Answer

Use the Data Factory Copy activity.. Efficient data ingestion is critical for minimizing pipeline duration and cloud compute costs. Using the Copy activity in Data Factory, which is optimized for high-throughput, parallel data transfer, is the industry standard for this task. Understanding how to use the correct integration tools prevents performance bottlenecks and ensures that large-scale data migration projects remain within their performance and budget windows.

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Use a Python script in a notebook to read and write rows one-by-one.

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Download files locally and then upload them to the Fabric portal.

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Create a Power BI report and import the data.