Exam Code: DP-750
Exam Name: Implementing Data Engineering Solutions Using Azure Databricks
Certification Provider: Microsoft
Corresponding Certification: Microsoft Certified: Fabric Data Engineer Associate

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Updated: Sep 15, 2026

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Microsoft DP-750 Exam Syllabus Topics:

Section	Weight	Objectives
Set up and configure an Azure Databricks environment	15–20%	- Integrate with Azure services 1. Connect to Azure Data Lake Storage, Azure Data Factory, Microsoft Entra ID 2. Configure monitoring with Azure Monitor and diagnostic settings - Select and configure compute resources 1. Choose compute types: serverless, job compute, SQL warehouse, classic compute 2. Manage workspace settings, permissions, and networking 3. Configure cluster policies, instance pools, and libraries
Secure and govern Unity Catalog objects	15–20%	- Implement data governance and security 1. Manage catalogs, schemas, tables, views, and volumes 2. Configure access control: row-level, column-level, attribute-based security 3. Enforce data quality, lineage, and auditing - Manage data sharing and permissions 1. Grant and revoke permissions, manage groups and service principals 2. Set up external locations and storage credentials
Prepare and process data	30–35%	- Ingest and transform data 1. Implement schema enforcement, schema drift, and slowly changing dimensions 2. Transform using Spark SQL, PySpark, Scala, and Delta Lake 3. Ingest batch and streaming data from multiple sources - Optimize and manage data storage 1. Optimize Delta tables: partitioning, Z-ordering, vacuum, optimize 2. Implement lakehouse architecture and manage table versions 3. Handle structured, semi-structured, and unstructured data
Deploy and maintain data pipelines and workloads	30–35%	- Build and orchestrate pipelines 1. Design and implement Lakeflow Spark Declarative Pipelines 2. Configure Lakeflow Jobs: schedules, triggers, alerts, retries 3. Implement CI/CD with Git, Databricks Asset Bundles, CLI, and APIs - Monitor, troubleshoot, and maintain workloads 1. Apply SDLC practices and version control 2. Monitor performance, logs, and execution metrics 3. Troubleshoot failures, repair and restart jobs

Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

Question #1

You have an Azure Databricks workspace named Workspace1 that contains a cluster named Cluster1.
You need to enable a user named User1 to install a Maven package on all the nodes of Cluster1. The solution must follow the principle of least privilege.
What should you do?

A. Grant User1 the CAN MANAGE permission for Cluster1.
B. Grant User1 the CAN RESTART permission for Cluster1.
C. Assign User1 the Contributor role for the resource group that contains Workspace1.
D. Assign User1 the workspace admins role for Workspace1.

Reveal Solution Discussion 0

Correct Answer: A 🗳️