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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prepare and process data | 30–35% | - Optimize and manage data storage
|
| Topic 2: Set up and configure an Azure Databricks environment | 15–20% | - Integrate with Azure services
|
| Topic 3: Secure and govern Unity Catalog objects | 15–20% | - Implement data governance and security
|
| Topic 4: Deploy and maintain data pipelines and workloads | 30–35% | - Build and orchestrate pipelines
|
>> DP-750 Vorbereitungsfragen <<
Wir wissen, wie bedeutend die Microsoft DP-750 Prüfung für die in der IT-Branche angestellte Leute ist. Deshalb entwickeln wir die Prüfungssoftware für Microsoft DP-750, die Ihnen große Hilfe leisten können. Die Prüfungsunterlagen, die Sie brauchen, haben unser Team schon gesammelt. Außerdem haben wir die Unterlagen wissenschaftlich analysiert und geordnet. Wir tun dies alles, um Ihr Stress und Belastung der Vorbereitung auf Microsoft DP-750 zu erleichtern.
57. Frage
You have an Azure Databricks workspace that uses serverless compute.
You need to ingest data by using Lakeflow Jobs. New records must be processed as soon as they become available.
Which type of job trigger should you use for the ingestion?
Antwort: C
Begründung:
The correct answer is D - Continuous trigger.
A Continuous trigger keeps the job running as a perpetual loop. As soon as one micro-batch or iteration completes, the next begins. New records are picked up with the shortest possible latency - as close to real- time as a Lakeflow Jobs pipeline gets.
File Arrival (Option B) is event-driven but introduces per-file trigger overhead and is best suited for file-based ingestion rather than continuous streaming workloads. Scheduled (Option C) runs at fixed clock intervals - if new data arrives between runs, it waits until the next scheduled execution. Manual (Option A) requires a human to start each run.
The question specifies serverless compute, which pairs naturally with Continuous trigger because serverless handles cluster lifecycle automatically - the job stays active without managing a persistent cluster. 'New records must be processed as soon as they become available' is the exact use case the Continuous trigger is designed for.
Reference: https://learn.microsoft.com/en-us/azure/databricks/jobs/triggers
58. Frage
Hotspot Question
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a catalog named catalog1.
You have a group named group1.
You plan to create a schema named schema1 in catalog1.
You need to ensure that group1 meets the following requirements:
- Can create tables in schema1
- Can modify and query tables
- Cannot grant permissions for the schema and its objects
How should you complete the SQL statements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Antwort:
Begründung:
59. Frage
You have an Azure Databricks workspace named Workspace1.
You have a user named User1 who is a non-admin user in Workspace1.
You need to ensure that User1 can perform the following tasks:
* Provision clusters of any size.
* Run Databricks jobs.
The solution must follow the principle of least privilege.
What should you do? To answer, drag the appropriate options to the correct requirements. Each option 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.
Antwort:
Begründung:
Explanation:
The Allow unrestricted cluster creation entitlement permits a non-admin user to create fully configurable compute resources rather than limiting the user to clusters governed by assigned compute policies. This enables User1 to provision clusters with the required size and configuration without granting the much broader workspace administrator role. Microsoft Learn The CAN RUN job permission permits User1 to execute the applicable Databricks jobs without allowing the user to edit job settings, delete jobs, change permissions, or perform other administrative operations. It is therefore the least-privileged job permission among the provided options.
The workspace admins role would grant excessive administrative control. Consumer access provides a restricted experience for consuming shared resources and does not authorize unrestricted cluster creation or job execution. The Azure Contributor role operates at the Azure resource-management level and does not grant the required permissions inside the Databricks workspace. Consequently, the unrestricted cluster- creation entitlement and the job-level run permission satisfy the requirements with minimum access.
60. Frage
You have an Azure Databricks workspace.
Users report that a Databricks notebook that runs each day takes longer than expected to run.
When reading the Directed Acyclic Graph (DAG), you discover the following issues concerning the Apache Spark stage:
* Most tasks in the stage finish quickly.
* A few tasks in the stage run more slowly.
* The CPU is underutilized at the end of the stage.
* The slow tasks process many more input records.
* The stage is blocked while it waits for the few slow tasks.
What is the root cause of the issues?
Antwort: B
61. Frage
You have an Azure Databricks workspace named Workspace1 that contains a lakehouse and is enabled for Unity Catalog.
You have a connection to a Microsoft SQL Server database named DB1.
You need to expose the schemas and tables of DB1 to meet the following requirements:
* The schemas and tables can be queried in Databricks.
* The schemas and tables appear alongside other Unity Catalog objects.
* The data is NOT copied into Databricks-managed storage.
Solution: You create a Lakeflow Connect pipeline and connect it to DB1. Does this meet the goal?
Antwort: B
Begründung:
The correct answer is B - No.
Lakeflow Connect is an ingestion service that physically copies data from external databases into Delta tables managed by Databricks. It's designed for scenarios where you want a replicated, writable Delta copy of external data - essentially a CDC-based ingestion pipeline.
That's the opposite of what's required here. The requirement states 'the data is NOT copied into Databricks- managed storage.' Lakeflow Connect would create Delta tables in Databricks and copy DB1's data into them
- a direct violation.
Additionally, Lakeflow Connect creates Databricks-native Delta tables rather than exposing DB1's original schemas and tables as virtual objects. Analysts querying through a Lakeflow Connect pipeline are querying a replicated copy, not the live source.
For zero-copy, live query federation of an external SQL Server into Unity Catalog, Lakehouse Federation (foreign catalog) is the correct tool.
Reference: https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/
62. Frage
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DP-750 Examengine: https://www.zertpruefung.de/DP-750_exam.html