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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. Configure cluster policies, instance pools, and libraries
  • 3. Choose compute types: serverless, job compute, SQL warehouse, classic compute
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. Configure Lakeflow Jobs: schedules, triggers, alerts, retries
  • 3. Implement CI/CD with Git, Databricks Asset Bundles, CLI, and APIs
Secure and govern Unity Catalog objects15–20%- Manage data sharing and permissions
  • 1. Grant and revoke permissions, manage groups and service principals
  • 2. Set up external locations and storage credentials
- 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
Prepare and process data30–35%- 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
- Optimize and manage data storage
  • 1. Handle structured, semi-structured, and unstructured data
  • 2. Implement lakehouse architecture and manage table versions
  • 3. Optimize Delta tables: partitioning, Z-ordering, vacuum, optimize

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 Delta table named Sales_orders. Sales.orders stores historical sales data.
You receive a daily CSV file daily that contains new sales records only. The file does NOT contain updates to existing rows You need to load the daily data into Sales.orders. The solution must meet the following requirements:
* Preserve the existing data.
* Add only the new records.
* Minimize processing effort.
Which command should include in the loading strategy?

A) INSERT OVERWRITE
B) INSERT INTO
C) UPDATE


2. You have an Azure Databricks workspace that contains a Delta table named Table 1. Table 1 has accumulated obsolete files.
You need to reduce storage costs. The solution must preserve 30 days of time travel history. Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A) Set the delta.deletedFileRetentionDuration table property to 10 days
B) Run the vacuum command on Table1.
C) Reduce the deleted file retention period to one day.
D) Run the OPTIMIZE command on Table1
E) Set the delta. logRetentionDuration table property to 30 days.


3. You have an Azure Databricks workspace that is enabled for Unity Catalog and contains:
* A catalog named Finance
* A schema named Purchases in the Finance catalog
* A table named Transactions in the Purchases schema
You need to ensure that a user named finance_user can query the Transactions table. The solution must follow the principle of least privilege.
Which permission should you grant to finance_user for each object? To answer, drag the appropriate permissions to the correct objects. Each permission 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 attached to a Unity Catalog metastore named metastore1.
Metastore1 contains a catalog named catalog 1.
You need to create a new schema named schema2 that meets the following requirements:
* Is contained in catalog1
* Uses abfss://containergstorageaccount.dfs.core.windows.net/data as the Managed location Which SQL statement should you execute?

A) CREATE SCHEMA catalog1.schema2
LOCATION ' abfss://[email protected]/data ' ;
B) CREATE SCHEMA catalog1.schema2
MANAGED LOCATION ' abfss://[email protected]/data ' ;
C) CREATE CATALOG schema2
MANAGED LOCATION ' abfss://[email protected]/data ' ;
D) CREATE SCHEMA catalog1.schema2
WITH DBPROPERTIES (LOCATION= ' abfss://[email protected]/data
' );


5. You have an Azure Databricks workspace that is enabled for Unity Catalog.
You need to implement a data lifecycle and expiration solution that meets the following requirements
* Transaction logs and deleted data files that are older than 90 days must be removed from Delta tables to reclaim storage.
* All the tables must remain available for querying during the cleanup process.
* Administrative effort must be minimized
What should you do for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.


Solutions:

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

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