DP-750 practice test
Microsoft Azure Databricks Data Engineer Associate
100 practice questions, spread across the exam's topics the same way Microsoft weights them, each with a full explanation and a link to the official documentation that proves the answer. Written by a Microsoft Certified Trainer who does this work for a living.
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What is inside
Every area the exam tests
Our questions are spread the same way Microsoft weights the exam, so your practice matches the real thing.
Environment and Unity Catalog setup
15 to 20%Choosing between job, serverless, warehouse, classic and shared compute, performance settings from autoscaling and node type to pooling and termination, Photon and runtime versions, installing libraries, access permissions on compute, naming conventions for isolation and sharing, creating catalogs, schemas and volumes, tables, views and materialized views, foreign catalogs and connections, and definition language operations on managed and external tables.
18 questionsSecuring and governing the catalog
15 to 20%Granting privileges to users, service principals and groups, table and column level access control and row-level security, reaching Key Vault secrets, authenticating with service principals and managed identities, definitions and descriptions for discovery, attribute-based access control through tags and policies, row filters and column masks, retention policies, lineage tracking through the catalog explorer, audit logging, and a secure strategy for Delta Sharing.
17 questionsPreparing and processing data
30 to 35%Designing ingestion logic and choosing a tool between Lakeflow Connect, notebooks and Data Factory, batch against streaming, table formats, partitioning, slowly changing dimensions, granularity, temporal tables, clustering strategies including liquid clustering, Z-ordering and deletion vectors, managed against unmanaged tables, ingestion through SQL, change data capture, structured streaming, Event Hubs and Auto Loader, profiling, cleansing and transforming, merge and append loading, and data quality constraints including schema drift and pipeline expectations.
32 questionsPipelines, deployment and operations
30 to 35%Ordering pipeline operations, choosing between notebooks and declarative pipelines, task logic and error handling, jobs with their triggers, schedules, alerts and automatic restarts, version control and branching, a testing strategy from unit tests to acceptance, asset bundles packaged and deployed through the command line or the interface, monitoring and managing cluster consumption, repairing jobs, tuning Spark jobs and resolving caching, skew, spilling and shuffle through the execution graph and the Spark interface, optimizing Delta tables, and log streaming and alerting through Azure Monitor.
33 questionsMicrosoft last updated this exam on 19 October 2026. Our questions match that version.
How you will use it
Practise the way that suits you
- Learn as you go. Answer, read why straight away, then move on. No clock, no pressure.
- Or sit it timed. A clock, no answers until the end, and two minutes a question, so you learn to pace yourself.
- Score by topic. See which area let you down instead of one number out of a hundred.
- Go back over it. Read every question again afterwards, right and wrong, with the full explanation.
Is it for you
Who takes DP-750
Data engineers building pipelines on Databricks rather than Fabric
Two thirds of it is ingestion, transformation, pipelines and the jobs that run them.
People responsible for governance in a lakehouse
Unity Catalog privileges, row filters, column masks, lineage and sharing are a whole area.
Anybody who has watched a Spark job spill and not known why
Skew, shuffle, caching and the Spark interface are examined directly.
Also worth doing
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