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Microsoft DP-750 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Secure and govern Unity Catalog objects | 15–20% | - Implement data governance and security
- 1. Enforce data quality, lineage, and auditing
- 2. Manage catalogs, schemas, tables, views, and volumes
- 3. Configure access control: row-level, column-level, attribute-based security
- Manage data sharing and permissions
- 1. Set up external locations and storage credentials
- 2. Grant and revoke permissions, manage groups and service principals
|
| Deploy and maintain data pipelines and workloads | 30–35% | - Monitor, troubleshoot, and maintain workloads
- 1. Monitor performance, logs, and execution metrics
- 2. Troubleshoot failures, repair and restart jobs
- 3. Apply SDLC practices and version control
- Build and orchestrate pipelines
- 1. Implement CI/CD with Git, Databricks Asset Bundles, CLI, and APIs
- 2. Configure Lakeflow Jobs: schedules, triggers, alerts, retries
- 3. Design and implement Lakeflow Spark Declarative Pipelines
|
| Prepare and process data | 30–35% | - Optimize and manage data storage
- 1. Handle structured, semi-structured, and unstructured data
- 2. Optimize Delta tables: partitioning, Z-ordering, vacuum, optimize
- 3. Implement lakehouse architecture and manage table versions
- 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
|
| Set up and configure an Azure Databricks environment | 15–20% | - 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. Choose compute types: serverless, job compute, SQL warehouse, classic compute
- 2. Configure cluster policies, instance pools, and libraries
- 3. Manage workspace settings, permissions, and networking
|
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 Databticks workspace that is enabled for Unity Catalog and contains a catalog named catalog1.
You have a group named group!
You plan to create a schema named schema1 in catalog1.
You need to ensure that group1 meets the following requirements:
* Can create tables in schema1
* Can modify and query tables
* Cannot grant permissions for the schema and its objects
How should you complete the SQL statements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

3. You have an Azure Databricks workspace named Workspace! that uses a Git repository. The repository contains a Databricks notebook named Notebook1.
From the main branch, you create a feature branch named Branch! and commit changes to Notebooks Another user commits changes to Notebook1 in main.
When you attempt to merge Branch! into main, the merge fails due to conflicts.
You need to merge Branch! into the main branch. The solution must ensure that Notebook1 includes all the changes from both the branches.
What should you do?
A) From Workspace1, clone Branch! as a new repository.
B) From Workspace1, clone the mam branch as a new repository.
C) Apply the main branch changes to Branch! and resolve the conflicts.
D) Apply the changes directly to the main branch.
4. You have an Azure Databticks workspace that contains an all-purpose compute cluster named Cluster1.
Cluser1 is used for
interactive development.
You need to configure Cluster1 to meet the following requirements:
* Automatically add and remove worker nodes based on workload demand
* Automatically shut down when the cluster has been idle for a specific period.
What should you configure for each requirement? To answer, drag the appropriate options to the correct requirements. Each option 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.

5. 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
Solutions:
Question # 1 Answer: B | Question # 2 Answer: Only visible for members | Question # 3 Answer: C | Question # 4 Answer: Only visible for members | Question # 5 Answer: B |