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Microsoft DP-750 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Configure and manage Azure Databricks environments | 15-20% | - Security and authentication setup
|
| Topic 2: Prepare and process data | 30-35% | - Data quality and validation
|
| Topic 3: Secure and govern data using Unity Catalog | 15-20% | - Data governance fundamentals
|
| Topic 4: Deploy and manage data pipelines and workloads | 30-35% | - Operational reliability
|
Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:
1. You have an Apache Spark DataFrame named salesDF that contains the following columns:
* Product
* Region
* Sales
* Date
You need to create a pivot table that shows the total sales by product for each region.
How should you complete the PySpark code segment? 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.
2. You need to deploy Declarative Automation Bundles to a development environment. The solution must support automated and repeatable deployments across environments.
What should you use?
A) Git folders
B) the Databricks SDK for Python
C) the Jobs UI
D) the Databricks CLI
3. 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) a task failure
B) a job failure
C) job success
D) task success
4. You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a Delta table named Orders.
You load the Orders table into an Apache Spark DataFrame named df.
You need to create a DataFrame that excludes rows where the order amount is null.
Solution: You run the following expression.
df.dropna(subset=[ " order_amount " ])
Does this meet the goal?
A) Yes
B) No
5. You have an Azure Databricks workspace that is enabled for Unity Catalog.
You plan to create a job in Lakeflow Jobs named Job1 that:
* Ingests data from cloud storage
* Runs two independent transformation tasks
The transformation tasks must run only after the ingestion completes and must run in parallel.
You need to design the task logic for Job1.
What should you configure?
A) two ingestion tasks, each followed by a transformation task
B) independent tasks with no defined dependencies
C) One ingestion task with two parallel downstream transformation tasks
D) a single task that performs ingestion and transformations sequentially
Solutions:
| Question # 1 Answer: Only visible for members | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: C |





