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

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Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

1. Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
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 new native catalog in Unity Catalog.
Does this meet the goal?

A) No
B) Yes

2. Which Azure service is best integrated with Databricks Unity Catalog for centralized data governance?

A) Azure Automation
B) Microsoft Purview
C) Azure DevTest Labs
D) Azure Key Vault

3. What happens if incoming data violates Delta table schema?

A) Data is appended with nulls
B) Data is automatically cast
C) Table is overwritten
D) Data is rejected

4. You have an Azure Databricks workspace that uses Unity Catalog.
You have a Lakeflow Spark Declarative Pipelines (SDP) pipeline that ingests data into a managed Delta table named Table1. Table1 is used for analytics.
New columns are added to the source data, causing pipeline failures during writes to Table1.
You need to prevent the pipeline failures. The solution must ensure that schema changes are detected and handled.
What should you do?

A) Disable schema enforcement for Table1.
B) Enable schema evolution.
C) Use row filters to exclude records that have new columns.
D) Create a separate table for each schema version.

5. You use Databricks Asset Bundles to manage two jobs and an app.
You need to deploy the bundle to development and production environments. The solution must meet the following requirements:
- Deploy the app to both environments.
- Deploy only one job to development.
- Minimize administrative effort.
What should you use?

A) a variables node in a databricks.yml file
B) a targets node in a databricks.yml file
C) a resources node in a databricks.yml file
D) separate databricks.yml files for each environment

Solutions: