Microsoft DP-750 Q&A - in .pdf

Exam Code: DP-750
Exam Name: Implementing Data Engineering Solutions Using Azure Databricks
Updated: Sep 17, 2026
Q & A: 93 Questions and Answers
PDF Price: $59.99
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Microsoft DP-750 Q&A - Testing Engine

Exam Code: DP-750
Exam Name: Implementing Data Engineering Solutions Using Azure Databricks
Updated: Sep 17, 2026
Q & A: 93 Questions and Answers
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PC Test Engine Price: $59.99
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About Microsoft Implementing Data Engineering Solutions Using Azure Databricks - DP-750 Exam Actual Tests

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Microsoft DP-750 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Prepare and process data	30–35%	- Optimize and manage data storage 1. Implement lakehouse architecture and manage table versions 2. Handle structured, semi-structured, and unstructured data 3. Optimize Delta tables: partitioning, Z-ordering, vacuum, optimize - Ingest and transform data 1. Ingest batch and streaming data from multiple sources 2. Transform using Spark SQL, PySpark, Scala, and Delta Lake 3. Implement schema enforcement, schema drift, and slowly changing dimensions
Topic 2: Set up and configure an Azure Databricks environment	15–20%	- Select and configure compute resources 1. Manage workspace settings, permissions, and networking 2. Configure cluster policies, instance pools, and libraries 3. Choose compute types: serverless, job compute, SQL warehouse, classic compute - Integrate with Azure services 1. Configure monitoring with Azure Monitor and diagnostic settings 2. Connect to Azure Data Lake Storage, Azure Data Factory, Microsoft Entra ID
Topic 3: Deploy and maintain data pipelines and workloads	30–35%	- 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 - Build and orchestrate pipelines 1. Configure Lakeflow Jobs: schedules, triggers, alerts, retries 2. Implement CI/CD with Git, Databricks Asset Bundles, CLI, and APIs 3. Design and implement Lakeflow Spark Declarative Pipelines
Topic 4: Secure and govern Unity Catalog objects	15–20%	- Manage data sharing and permissions 1. Set up external locations and storage credentials 2. Grant and revoke permissions, manage groups and service principals - Implement data governance and security 1. Manage catalogs, schemas, tables, views, and volumes 2. Enforce data quality, lineage, and auditing 3. Configure access control: row-level, column-level, attribute-based security

Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

Question #1

You have an Azure Databricks workspace named Workspace1 that contains a takehouse 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 new native catalog in Unity Catalog. Does this meet the goal?

A. Yes
B. No

Reveal Solution Discussion 0

Correct Answer: B 🗳️