Microsoft Implementing Data Engineering Solutions Using Azure Databricks - DP-750

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Microsoft DP-750 Exam Syllabus Topics:

Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

1. You have an Azure Databricks workspace that is enabled for Unity Catalog.
You need to recommend a pipeline that ingests files from cloud storage, performs cleansing and enrichment transformations, and writes created Delta tables for analytics. The solution must minimize development effort and provide built-in monitoring and automatic retries.
What should you include in the recommendation?

A) an Apache Spark Structured Streaming job
B) an Azure Data Factory pipeline that uses data flows
C) a Databricks notebook triggered by a scheduled job
D) a Lakeflow Spark Declarative Pipelines (SDPJ pipeline

2. You need to configure resiliency for a job in Lakeflow Jobs named Job1 to meet the pipeline deployment and operation requirements.
What should you do?

A) Enable task-level retries on the ingestion task and leave downstream tasks unchanged.
B) Enable a restart upon a job failure and set the retry count to 0.
C) Disable retries and configure Job1 to run manually only.
D) Configure Job1 to start always from the first task when any task fails.

3. You have an Azure Databricks workspace.
You need to ingest streaming data from Azure Event Hubs by using Apache Spark Structured Streaming The solution must authenticate to Event Hubs and read the event payload.
How should you complete the PySpark code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

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 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 foreign catalog in Catalog Explorer.
Does this meet the goal?

A) Yes
B) No

Solutions: