Microsoft DP-750 Q&A - in .pdf

  • Exam Code: DP-750
  • Exam Name: Implementing Data Engineering Solutions Using Azure Databricks
  • Updated: Jul 31, 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: Jul 31, 2026
  • Q & A: 93 Questions and Answers
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Microsoft DP-750 Exam Syllabus Topics:

SectionWeightObjectives
Set up and configure an Azure Databricks environment15–20%- 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
- Select and configure compute resources
  • 1. Manage workspace settings, permissions, and networking
  • 2. Choose compute types: serverless, job compute, SQL warehouse, classic compute
  • 3. Configure cluster policies, instance pools, and libraries
Prepare and process data30–35%- Optimize and manage data storage
  • 1. Implement lakehouse architecture and manage table versions
  • 2. Optimize Delta tables: partitioning, Z-ordering, vacuum, optimize
  • 3. Handle structured, semi-structured, and unstructured data
- Ingest and transform data
  • 1. Transform using Spark SQL, PySpark, Scala, and Delta Lake
  • 2. Implement schema enforcement, schema drift, and slowly changing dimensions
  • 3. Ingest batch and streaming data from multiple sources
Deploy and maintain data pipelines and workloads30–35%- Monitor, troubleshoot, and maintain workloads
  • 1. Troubleshoot failures, repair and restart jobs
  • 2. Monitor performance, logs, and execution metrics
  • 3. Apply SDLC practices and version control
- Build and orchestrate pipelines
  • 1. Design and implement Lakeflow Spark Declarative Pipelines
  • 2. Implement CI/CD with Git, Databricks Asset Bundles, CLI, and APIs
  • 3. Configure Lakeflow Jobs: schedules, triggers, alerts, retries
Secure and govern Unity Catalog objects15–20%- 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

Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

1. You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a managed Delta table named Table1. Table1 stores customer data.
You need to implement a data retention solution that meets the following requirements:
Deleted data must be retained for 30 days to support audits.
Deleted data that is older than 30 days must be removed permanently.
The solution must minimize administrative effort.
Which two properties should you configure? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A) delta.timeUntilArchived
B) delta.enableDeletionVectors
C) delta.autoOptimize.autoCompact
D) delta.deletedFileRetentionDuration
E) delta.logRetentionDuration


2. You have an Azure Databricks workspace that contains multiple all-purpose clusters. You discover that some clusters remain idle for long periods after users finish their work. You need to reduce compute costs without affecting active workloads. What should you do?

A) Convert the clusters into job clusters
B) Use spot instances.
C) Enable autoscaling.
D) Configure automatic termination.


3. You have an Azure Databricks workspace that contains the objects shown in the following table.
Name | Type
Catalog1 | Catalog
Schema1 | Schema
Sales1 | Table
Notebook1 | Notebook
Space1 | AI/BI Genie space
Users often use the following words to refer to a sale: transaction, event, order, and invoice.
You need to create a knowledge store. The solution must ensure that when the users use any of the words in Space1, Genie queries the Sales1 table. Any other Genie spaces must remain unaffected.
To which object should you add the instructions?

A) Notebook1
B) Space1
C) Sales1
D) Schema1


4. You have an Azure Databricks workspace that contains a job in Lakeflow Jobs named Job1. Job1 contains multiple tasks.
Failures of non-critical tasks must be logged but must NOT trigger notifications. Notifications must be triggered only when critical tasks have failed, and Job1 has completed You need to configure the job alerting behavior.
What should trigger a notification?

A) job success
B) a job failure
C) task success
D) a task failure


5. You manage Declarative Automation Bundles by using the Databricks CLI.
You run the following command in a terminal window.
databricks bundle init
What occurs when you run the command?

A) Jobs or pipelines defined in the bundle are run.
B) A new Declarative Automation Bundles project structure is created.
C) Bundle-defined resources are deployed to the Databricks workspace.
D) The bundle configuration is validated.


Solutions:

Question # 1
Answer: D,E
Question # 2
Answer: D
Question # 3
Answer: B
Question # 4
Answer: B
Question # 5
Answer: B

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