Microsoft DP-700 Practice Exam Questions & Answers

Explanation

An eventstream is the best solution for ingesting data from Azure Event Hub into Fabric, while applying filtering logic such as retaining only the events that have a Neighbourhood value of 'Chelsea.' Eventstreams in Microsoft Fabric are designed for handling real-time data streams and can apply transformation logic directly on incoming events. In this case, the eventstream can filter events based on the Neighbourhood field before storing the retained events in a Fabric lakehouse.

Eventstreams are well-suited for stream processing, such as this case where you need to filter out only specific data (events with a Neighbourhood of 'Chelsea') before storing it in the lakehouse.

Explanation

To allow Job1 in Workspace1 to access an Azure SQL database (Source1) with public internet access disabled, you need to create a managed private endpoint. A managed private endpoint is a secure, private connection that enables services like Fabric (or other Azure services) to access resources such as databases, storage accounts, or other services within a virtual network (VNet) without requiring public internet access. This approach maintains the security and integrity of your data while enabling access to the Azure SQL database.

Explanation

To meet the requirements of ensuring that the data engineer can write data to the Customer table without reading data from the Employee table (which contains Personally Identifiable Information, or PII), you can implement the following steps:

Share Lakehouse1 with the data engineer.

By sharing Lakehouse1 with the data engineer, you provide the necessary access to the data within the lakehouse. However, this access should be controlled through roles and permissions, which will allow writing to the Customer table but prevent reading from the Employee table.

Assign the data engineer the Contributor role for Workspace1.

Assigning the Contributor role for Workspace1 grants the data engineer the ability to perform actions such as writing to tables (e.g., the Customer table) within the workspace. This role typically allows users to modify and manage data without necessarily granting them access to view all data (e.g., PII data in the Employee table).

Migrate the Employee table from Lakehouse1 to Lakehouse2.

To prevent the data engineer from accessing the Employee table (which contains PII), you can migrate the Employee table to a separate lakehouse (Lakehouse2) or workspace (Workspace2). This separation of sensitive data ensures that the data engineer's access is restricted to the Customer table in Lakehouse1, while the Employee table can be managed separately and protected under different access controls.

Explanation V-Order is designed to optimize read performance by organizing data for faster queries, but it adds overhead during writes. Since DW1 has write-intensive staging tables that get dropped and recreated frequently, disabling V-Order removes this write penalty. The tables are only read once before deletion, so the read optimization benefits do not justify the write performance cost in this scenario.

Explanation

To monitor Spark workload performance with comprehensive information, identify slow stages and tasks, and minimize administrative effort, you should use the Spark History Server or the built-in Spark application UI available in Fabric. These tools provide detailed stage and task-level performance metrics, identify bottlenecks, and show execution timelines without requiring additional setup. They are part of the standard Spark runtime and provide all necessary performance insights for data engineering workloads.