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Microsoft DP-750 Exam Syllabus Topics:

SectionWeightObjectives
Set up and configure an Azure Databricks environment15–20%- 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
- 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
Prepare and process data30–35%- Optimize and manage data storage
  • 1. Optimize Delta tables: partitioning, Z-ordering, vacuum, optimize
  • 2. Handle structured, semi-structured, and unstructured data
  • 3. Implement lakehouse architecture and manage table versions
- Ingest and transform data
  • 1. Implement schema enforcement, schema drift, and slowly changing dimensions
  • 2. Ingest batch and streaming data from multiple sources
  • 3. Transform using Spark SQL, PySpark, Scala, and Delta Lake
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. Implement CI/CD with Git, Databricks Asset Bundles, CLI, and APIs
  • 2. Design and implement Lakeflow Spark Declarative Pipelines
  • 3. Configure Lakeflow Jobs: schedules, triggers, alerts, retries
Secure and govern Unity Catalog objects15–20%- 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. Configure access control: row-level, column-level, attribute-based security
  • 2. Enforce data quality, lineage, and auditing
  • 3. Manage catalogs, schemas, tables, views, and volumes

Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

1. 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?

A) Yes
B) No


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


3. You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a catalog named finance, finance contains two schemas named default and procurement.
You need to create a table named assets in the procurement schema, assets must contain the following columns:
* asset.id
* asset, type
* asset_name
How should you complete the SQL statement? To answer, drag the appropriate values to the correct targets.
Each value 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 NOTE: Each correct selection is worth one point.


4. You have an Azure Databricks workspace that is enabled for Unity Catalog You have a complex job named Job1 that contains eight tasks. Job! takes multiple hours to complete During the last job run, the final task fails due to a transient issue.
You need to retry the last task without rerunning tasks that have already completed.
What should you do?

A) Disable and reenable the job schedule.
B) Update the job parameters.
C) Restart Job!
D) Repair the current job run.


5. 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 Databricks access connector.
Does this meet the goal?

A) Yes
B) No


Solutions:

Question # 1
Answer: B
Question # 2
Answer: A,B
Question # 3
Answer: Only visible for members
Question # 4
Answer: D
Question # 5
Answer: B

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