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DP-750Azure Databricks Data Engineer
DP-750 · 30 days left ›
PREDICTED786 ±37✓ Exam Ready · 87% confidence
Inside the app
Nine interactive practice formats, on iPhone
Azure Mastery has nine interactive formats for exam practice. The examples below show original DP-750 practice questions in Azure Mastery on iPhone and iPad. The exam simulator uses timed sessions with the published domain weights. Microsoft's live interface and question mix may differ.
In Lakeflow Jobs, which resource acts as the top-level container that coordinates, schedules, and runs one or more tasks as a single workflow?
A triggerA trigger only defines when a job starts, such as on a schedule or a file-arrival event; it does not own or coordinate the tasks themselves.
A jobA job owns and coordinates its tasks, trigger, parameters, and notifications, running them as one workflow that is shown as a DAG.
A taskA task is a single unit of work inside a job, like running a notebook, so it is orchestrated by the job rather than being the container.
A pipelineA Lakeflow Spark Declarative Pipeline processes data and can be invoked by a pipeline task, but it is not the resource that schedules multiple tasks.
Multiple choice
An original DP-750 practice question with one correct answer. Choose an option to read its written rationale.
Exam-specific sampleExplore more question formats
Which maintenance operations does predictive optimization run automatically on Unity Catalog managed tables? (Select three.)
OPTIMIZEAutomatic file-layout compaction and incremental clustering are queued to keep query performance healthy without manual runs.
VACUUMRemoving data files no longer referenced by the table is queued automatically to reduce cloud storage costs over time.
ANALYZECollecting table statistics for the cost-based optimizer is part of the automatic maintenance set, improving query planning.
ZORDERZ-ordering is never applied automatically; on Z-ordered tables the feature compacts but skips the already Z-ordered files.
REORG TABLERewriting soft-deleted data with a purge is an explicit manual operation, not something queued by the automatic maintenance feature.
Multi-select
An original DP-750 multi-select question. Select all the correct options to earn the mark.
All-or-nothing
Arrange the steps to give analysts governed, read-only access to a PostgreSQL database through Lakehouse Federation, from first to last.
⋮⋮1Create a connection in Unity Catalog with the JDBC URL and credentials
⋮⋮2Create a foreign catalog that mirrors the external database using the…
⋮⋮3Grant privileges on the foreign catalog's tables to the analyst group
⋮⋮4Run federated queries that push down to the external database
Drag-and-drop
An original DP-750 ordering question you can answer by touch on iPhone and iPad.
Interactive item
Complete the compute and runtime guidance for common Azure Databricks scenarios.
Dropdown selection
An original DP-750 question with a visual prompt, designed for touch on iPhone and iPad.
Choose in context
Productionizing the Contoso Retail analytics pipeline Contoso Retail runs a nightly pipeline that ingests sales files from cloud storage, cleanses them, and refreshes reporting tables. Today engineers deploy by manually…
1Which approach best meets this deployment requirement?
2How should the team configure this alerting?
3Which change best satisfies these cost goals?
Case studies
An original DP-750 case study with several questions about the same requirements and environment.
Multi-question
✕Your answer: A trigger
✨ Answer Coach:A trigger only defines when a job starts, such as on a schedule or a file-arrival event; it does not own or coordinate the tasks themselves.
— grounded in authored certification guidance
Answer Coach
Answer Coach explains why the answer is correct and, where available, why each option is right or wrong. It helps you understand a mistake and remember the distinction. Read explanations after each question or at the end of a practice test. On supported devices, optional AI can reword a note on your device after checking it against the written guidance.
App exclusive
DP-750 Practice Questions & Exam Prep — Azure Databricks Data Engineer
Get exam-ready for DP-750 (Implementing Data Engineering Solutions Using Azure Databricks) on iPhone or iPad. Azure Mastery uses on-device AI to predict your readiness score, build a personalised study plan, and surface topics you're forgetting. Core study stays on-device and works offline; optional sync uses your private iCloud account.
The exam
What is the DP-750 exam?
DP-750 — Implementing Data Engineering Solutions Using Azure Databricks — earns the Microsoft Certified: Azure Databricks Data Engineer Associate credential. It's a role-based, hands-on exam for working data engineers who integrate and model data, build and deploy optimised pipelines, and troubleshoot workloads on Azure Databricks.
The audience profile assumes you can ingest and transform data with SQL and Python, apply software-development-lifecycle practices including Git, and are familiar with Microsoft Entra, Azure Data Factory, and Azure Monitor. You'll work alongside administrators, platform and solution architects, data scientists, and data analysts to design, deploy, and secure data-engineering solutions.
This is not a vocabulary exam. DP-750 expects you to reason about real engineering decisions, covering:
Choosing and configuring compute — job, serverless, warehouse, classic, and shared
Creating catalogs, schemas, volumes, and tables in Unity Catalog
Governing data with grants, row-, column-, and table-level security, ABAC tags, row filters, and column masks
Modelling data with Delta tables, partitioning, SCD types, and liquid clustering
Ingesting batch and streaming data with Lakeflow Connect, Auto Loader, COPY INTO, CDC, and Spark Structured Streaming
Building Lakeflow Jobs and Declarative Pipelines with Databricks Asset Bundles
Optimising Spark workloads with OPTIMIZE, VACUUM, and the Spark UI
Microsoft's DP-750 skills outline is current as of 11 March 2026. Every question in Azure Mastery's DP-750 bank is mapped to the current outline — no leftover questions on retired features. Read the official outline at learn.microsoft.com.
Questions40–60 (mixed formats)
Duration~100 minutes
Pass score700 / 1000
CostUSD $165 (≈ £113 UK)
ValidityRenew yearly (Associate)
FormatOnline or test centre
Skills measured · 11 March 2026
DP-750 exam objectives
Four domains, skills measured as of 11 March 2026 — the two data domains carry the most weight (30–35% each), with environment setup and Unity Catalog governance at 15–20% each. Every domain below lists Microsoft's own skill groups verbatim from the official skills outline, so you always know which domain you're being tested on and where your weak spots cluster.
Data skill mapSourcesTransformStoreAnalyse
Set up and configure an Azure Databricks environmentPublished weight 15–20%
79 exam-scoped practice questions in the app
Explore Environment topics
Select and configure compute in a workspace
Create and organize objects in Unity Catalog
Tests matching a compute type, job, serverless, or classic, to a stated cost or startup-latency need.
Every Unity Catalog object often gets treated the same, missing when a scenario needs a foreign catalog specifically.
Learn which performance settings (autoscaling, pooling, Photon) actually solve the symptom the scenario describes.
Secure and govern Unity Catalog objectsPublished weight 15–20%
80 exam-scoped practice questions in the app
Explore Governance topics
Secure Unity Catalog objects
Govern Unity Catalog objects
Tests picking the right access control, a grant, a row filter, or ABAC, for the described governance scale.
A single row filter often gets reached for when a scenario governing hundreds of tables actually needs ABAC.
Check whether the scenario is protecting one table or standardising a rule across many before answering.
Prepare and process dataPublished weight 30–35%
138 exam-scoped practice questions in the app
Explore Process Data topics
Design and implement data modeling in Unity Catalog
Ingest data into Unity Catalog
Cleanse, transform, and load data into Unity Catalog
Implement and manage data quality constraints in Unity Catalog
Choosing a clustering and ingestion strategy that fits the stated table shape and update pattern is the core ask here.
Candidates default to partitioning out of habit when a scenario's changing query pattern calls for liquid clustering.
Match Lakeflow Connect, CTAS, or Structured Streaming to whether the source is batch or continuous.
Deploy and maintain data pipelines and workloadsPublished weight 30–35%
144 exam-scoped practice questions in the app
Explore Pipelines topics
Design and implement data pipelines
Implement Lakeflow Jobs
Implement development lifecycle processes in Azure Databricks
Monitor, troubleshoot, and optimize workloads in Azure Databricks
Choosing between a Lakeflow Job and a Declarative Pipeline for the stated orchestration or quality need is what's graded.
Candidates reach for a bare Job when a bronze-to-gold flow needing automatic quality checks wants Declarative Pipelines.
Learn to read the Spark UI for skew, spilling, and shuffle before assuming a job just needs more compute.
Common traps
Where DP-750 candidates slip
Five recurring misconceptions that trip up otherwise well-prepared DP-750 candidates, grounded in the current skills outline.
Managed and external tables leave the underlying data in different states when dropped.
A requirement to keep the underlying files after a drop points specifically at an external table, not a managed one.
Check whether Unity Catalog owns the storage before assuming a dropped table just removes a catalog entry.
Liquid clustering, Z-ordering, and partitioning solve the same problem at different levels of effort.
Liquid clustering adapts automatically; Z-ordering and partitioning both lock you into a fixed scheme upfront.
Pick liquid clustering by default for a new table unless the scenario names a reason to partition instead.
ABAC scales governance; a row filter or column mask is still the mechanism underneath it.
A requirement to apply "hundreds of tables the same way" points at ABAC, not one hand-written rule.
Reach for ABAC only when the scenario is about applying a rule at scale, not securing a single table.
A Lakeflow Job orchestrates a workflow; a Declarative Pipeline builds and enforces the ETL itself.
Automatic quality enforcement on a bronze-to-gold flow is the signal that points specifically at Declarative Pipelines.
Reach for a bare Job only when the requirement is scheduling and chaining, not built-in data-quality expectations.
Job compute and serverless compute trade isolation for a different cost and startup profile.
Near-zero startup latency for frequent, short jobs is what should point you at serverless compute.
Pick job compute when isolation matters more than startup delay for the described workload.
Designed for DP-750
How Azure Mastery helps you pass DP-750
Exam-specific practice
441 DP-750 practice questions, each written against the current 11 March 2026 skills outline.
Every question is tagged to one of DP-750's four official domains.
Practise reading Unity Catalog grants, Spark config, and pipeline YAML, the exam's actual scenario style.
Predicted score
Exam IQ forecasts your DP-750 score on-device after roughly 30 questions, with a confidence range attached.
It names the specific Unity Catalog or pipeline-design distinction dragging your score down.
It surfaces which of the four domains is furthest from ready before you book.
Adaptive study plan
Your plan leans hardest on preparing data and deploying pipelines, the two domains weighted 30–35%.
Miss a notebook vs Declarative Pipeline question and the next session surfaces that choice again.
Nail Unity Catalog grants three sessions running and the plan backs off it automatically.
Knowledge decay
The Structured Streaming syntax or Asset Bundle workflow you mastered weeks ago fades fastest if you stop revising.
The Today screen's padlock icon is your cue that a topic needs another look.
Decayed topics jump to the top of your next Focus Weak Spots session.
Exam rehearsal
The simulator runs a full 100-minute session with no backtracking, matching the real sitting.
It draws original questions only, weighted to the outline's own domain split.
The live DP-750 interface and question mix are Microsoft's to control, not ours.
Answer Coach
Untangles DP-750's near-identical calls: partitioning vs liquid clustering, a Lakeflow Job vs a Declarative Pipeline.
Each explanation names the deciding factor that separated the two options.
On supported hardware a note can be reworded on-device, only after the written guidance checks out.
Aura guidance
Aura adjusts what it suggests as your first week of DP-750 sessions goes on.
Every session ends with a short recap: what moved, what's next, where to focus.
Private by design
Your DP-750 answer history, readiness gauge, and Answer Coach notes stay private by default.
Practice, scoring, and coaching stay entirely on your device, with no separate account required.
Optional sync uses your private iCloud account.
4–8 week revision plan
Suggested DP-750 study plan
Allow four to eight weeks, with extra time for SQL or Python if needed. Work through these flexible phases alongside hands-on practice in Azure Databricks.
Refresh SQL and Python
Review the language you will use most.
Practise reading and modifying short examples.
Revisit unfamiliar syntax before starting the main phases.
Configure Databricks
Compare compute types, runtimes, autoscaling and Photon.
Configure libraries and access permissions.
Create Unity Catalog catalogs, schemas, volumes, tables and views.
Secure and govern
Practise grants, row filters, column masks and ABAC tags.
Review identities, Key Vault secrets and granular access controls.
Explore lineage, audit logs and Delta Sharing.
Ingest and model data
Review Delta modelling, partitioning, SCD types and liquid clustering.
Compare Lakeflow Connect, Auto Loader, COPY INTO, CTAS and CDC.
Explore streaming with Spark and Event Hubs.
Transform and validate
Practise cleansing, transformations and merges.
Apply pipeline expectations.
Handle schema drift and data-quality failures.
Deploy and operate
Review Lakeflow Jobs, Declarative Pipelines, triggers and recovery.
Use Git and Asset Bundles through CLI or REST workflows.
Investigate Spark skew, spill and shuffle; review OPTIMIZE, VACUUM and monitoring.
Rehearse and consolidate
Use Focus Weak Spots to revisit weaker topics.
Complete a timed simulator session of about 100 minutes.
Review mistakes and decide whether you need more practice.
Frequently asked
DP-750 FAQs
DP-750 vs DP-700 — which should I take?
Both are associate Microsoft data-engineering certs, but the platform differs. DP-750 (Databricks Data Engineer) covers Unity Catalog, Lakeflow, Delta tables, and Spark tuning on Azure Databricks. DP-700 (Fabric Data Engineer) covers the same craft on Microsoft Fabric — OneLake, Dataflows Gen2, Eventstream. Pick by platform; many engineers earn both.
Liquid clustering or partitioning — which does DP-750 expect for a Delta table?
Liquid clustering is the current recommendation when query patterns change over time or cardinality is high; it re-clusters incrementally without a full rewrite. Partitioning still suits low-cardinality columns with stable filters. DP-750 describes the query pattern, not the strategy name, so inferring the right approach is the real skill.
DP-750 vs DP-800 — different data engineering roles?
Both are Microsoft associate certs for hands-on data work, but the platform differs. DP-750 (Databricks Data Engineer) builds production pipelines on Azure Databricks — Unity Catalog, Lakeflow, Delta tables, Spark tuning. DP-800 (SQL AI Developer) builds AI-enabled database solutions — T-SQL, embeddings, vector search, RAG. Choose by platform and role.
What question formats does DP-750 use?
Microsoft's own guidance states 40–60 questions with formats that vary by sitting. Azure Mastery's bank runs a similar mix: mostly single-answer multiple choice, a real share of scenario-based questions, and a smaller mix of drag-to-match, yes/no, dropdown-select, and drag-and-drop items — Unity Catalog grants and pipeline YAML appear throughout.
What's the DP-750 voucher price?
The DP-750 voucher is USD $165 in the United States — associate-level pricing. Cost varies by region; in the UK it's typically around £113. Microsoft sometimes runs free-voucher promotions for events such as Microsoft Build or Microsoft Ignite, so check your Learn profile before booking.
Does a DP-750 pass need annual renewal?
Yes. DP-750 earns the Azure Databricks Data Engineer Associate credential, and like all Microsoft associate certifications it needs renewing every year. Renewal is free: a short online assessment on Microsoft Learn, available in the six months before expiry. Fundamentals certs such as DP-900 never expire.
Lakeflow Job or Declarative Pipeline — how does DP-750 tell them apart?
A Lakeflow Job orchestrates arbitrary tasks, notebooks, SQL, other jobs, on a schedule or trigger, useful when the work isn't purely a transform flow. A Declarative Pipeline expresses a transform graph with dependency management and data-quality expectations built in. Confusing the two is a recurring DP-750 miss.
I need to resit DP-750 — what's the wait?
How long you wait scales with your attempt count, and each one needs its own voucher.
First retake: after 24 hours.
Second and third retakes: a 14-day wait each.
Cap: five attempts per rolling 12 months.
Can I try Azure Mastery's DP-750 bank before paying?
Yes — the app is free to download, with 50+ free DP-750 questions and written explanations. The full bank of 441 DP-750 practice questions unlocks with a one-time exam-pack purchase, or unlock every exam with a subscription or lifetime upgrade. Advanced study tools require Pro.
Does DP-750 revision work without a connection?
Yes. Question practice, scoring, and the readiness prediction all run locally on your device, so studying with no signal works the same as with a full connection. No account is needed, and sync via iCloud stays optional and private.
Free study guides
Free guides that pair with DP-750
Where DP-750 fits
Certification paths that lead to DP-750
DP-750 is the associate-level destination of Microsoft's Azure Databricks data-engineering track. There's no formal prerequisite, but DP-900 (Azure Data Fundamentals) is a natural on-ramp if the data vocabulary is new, and many engineers pair DP-750 with DP-700 (Fabric Data Engineer) to cover data engineering on both Microsoft platforms.
DP-750 is the Azure Databricks data-engineering associate. Its closest neighbour is DP-700 (the same role on Microsoft Fabric); below are the related exams already covered in Azure Mastery — a fundamentals on-ramp and the Fabric data-engineering path that sits alongside it.
Ready to pass DP-750?
Download Azure Mastery free. 441 DP-750 practice questions, AI score prediction, and a personalised study plan that adapts to your weak spots. iPhone & iPad.
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