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Azure Databricks Data Engineer Associate Exam (DP-750) - Microsoft Exam Questions

Last updated on August 20, 2026

97% Exam Compliance
49 Total Questions
1
Question
You need to configure an Azure Databricks Lakeflow job to run automatically every day at 02:00 UTC. The operations team also requires that, when the trigger is created, you can explicitly set the initial start time instead of letting Databricks choose it. Which trigger configuration should you use? Deploy and maintain data pipelines and workloads
Options
A Scheduled trigger with an Advanced schedule that runs daily at 02:00 and uses UTC as the time zone
B No trigger; have operators select Run now at 02:00 each day
C Continuous trigger
D Scheduled trigger with a Simple schedule set to every 24 hours
E Table update trigger on the source tables
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2
Question
A nightly Azure Databricks workflow runs on job compute that can autoscale and uses multiple notebooks attached to the same compute. The workflow must use a reproducible Python environment on every node, and the library artifacts must not be stored in a location that any workspace user can modify. What should you do? Deploy and maintain data pipelines and workloads
Options
A Store wheel files in DBFS root and install the latest available versions each run
B Place dependencies in the Shared workspace folder and use notebook-scoped %pip installs
C Upload wheels or requirements.txt to a restricted workspace path or Unity Catalog volume, pin exact versions, and install as cluster libraries
D Pass package names as task parameters and let each notebook install versions at runtime
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3
Question
A Unity Catalog managed Delta table uses automatic liquid clustering. A deployment runs CREATE OR REPLACE TABLE sales without CLUSTER BY AUTO. What happens? Prepare and process data
Options
A Automatic liquid clustering stays enabled but historical workload is cleared.
B Automatic liquid clustering stays enabled and previous clustering columns are preserved.
C Automatic liquid clustering is disabled and previous clustering columns are not preserved.
D The table switches to manual clustering on the last selected columns.
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4
Question
You are designing the warehouse layer of a gold sales mart in Azure Databricks. The fact table already contains SalesOrderNumber, analysts need to filter by that value, and there are no additional order attributes to model in the warehouse. What is the best dimensional modeling choice for the gold mart? Prepare and process data
Options
A Create a separate SalesOrder dimension table that contains only distinct SalesOrderNumber values. |
B Place SalesOrderNumber together with low-cardinality status flags in a junk dimension.
C Keep SalesOrderNumber in the fact table as a degenerate dimension.
D Create a bridge table between SalesOrderNumber and the fact table.
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5
Question
You run a Structured Streaming ingestion notebook as a production Lakeflow Job. The stream must restart automatically after failures and must never run two copies at the same time. Which configuration should you use? Deploy and maintain data pipelines and workloads
Options
A A continuous trigger on jobs compute
B A file arrival trigger on all-purpose compute
C A table update trigger on shared compute
D A scheduled trigger on all-purpose compute with autoscaling enabled
E A manual trigger with a task timeout
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