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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 contains a job in Lakeflow Jobs named Job1.
Job1 runs every hour.
Occasionally, Job1 takes longer than one hour to complete.
You need to configure the job scheduling behavior to meet the following requirements:
* Overlapping runs must be prevented to avoid data corruption.
* Scheduled runs must not be discarded when another run is already active.
What should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

2. 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) a Lakeflow Spark Declarative Pipelines (SDPJ pipeline
C) a Databricks notebook triggered by a scheduled job
D) an Azure Data Factory pipeline that uses data flows

3. You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a managed Delta table named Sales. Sales stores transaction data and contains the following columns:
* transactionjd (string)
* transaction date (date)
* amount (decimal)
You need to implement the following data quality requirements by using table-level data quality enforcement:
* amount must be greater than 0.
* transaction id must never be null.
* Invalid records must be rejected when data is written to the Sales table.
What should you do?

A) Create a view that filters out rows where transactionjd is null or amount is less than or equal to 0.
B) Configure row-level security (RLS) where transactionjd is null or amount is less than or equal to 0.
C) Use a select statement with where conditions to validate the data before querying.
D) Add a not null constraint to transactionjd and a check constraint to amount.

4. 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) Apply the main branch changes to Branch! and resolve the conflicts.
B) From Workspace1, clone the mam branch as a new repository.
C) From Workspace1, clone Branch! as a new repository.
D) Apply the changes directly to the main branch.

5. You have an Azure Databricks workspace that contains a job in Lakeflow Jobs named Job1.
Job! processes raw data files stored in Azure Storage.
New files arrive at unpredictable intervals.
You need to ensure that Job1 starts automatically when new files arrive and does NOT consume compute resources when no data is available.
Which type of job trigger should you use?

A) file arrival
B) scheduled
C) manual
D) continuous

Solutions: