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:

Question #1
You have an Azure Databricks workspace and a remote Git repository named Repo1. Repo1 contains two branches named main and Branch1.
You are on a development team that works in Repo1.
You commit changes to Branch1 and must merge the changes into main.
Before completing the merge, you need to meet the following requirements:
* Ensure that Branch1 includes the changes committed to main since Branch1 was created.
* Ensure that merge conflicts are detected and resolved.
What should you do first?

A. Pull the latest changes from main.
B. Merge main into Branch1.
C. Create a pull request for Branch1.
D. Pull the latest changes from Branch1.

Question #2
You have an Azure Databricks workspace that is enabled for Unity Catalog.
You need to ensure that data lineage is captured and can be reviewed for tables accessed by Databricks notebooks and jobs. The solution must minimize administrative effort.
Which compute configuration should you use to capture the data lineage, and what should you use to review the data lineage? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Question #3
You need to develop the task logic for a new job in Lakeflow Jobs that processes telemetry data.
Each task must contain only the appropriate logic for its step in the pipeline. The solution must support the planned changes and meet the data ingestion and processing requirements.
What should you do?

A. Use a single Databricks notebook task that performs ingestion, cleansing, and curation in one script.
B. Create separate tasks for ingestion, cleansing, and curation.
C. Create three tasks that each contains the identical logic and use task retries.
D. Use a single SQL task that performs ingestion, cleansing, and curation by running merge commands.

Question #4
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 Azure Data Factory pipeline that uses data flows
B. a Lakeflow Spark Declarative Pipelines (SDPJ pipeline
C. an Apache Spark Structured Streaming job
D. a Databricks notebook triggered by a scheduled job

Question #5
You use Declarative Automation 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. separate databricks.yml files for each environment
C. a resources node in a databricks.yml file
D. a targets node in a databricks.yml file

Solutions: