DP-750 Study Guide
A curated learning path for the DP-750 exam: the best documentation, videos, blog posts and tutorials for every exam objective.A curated learning path for the DP-750 exam: the best documentation, videos, blog posts and tutorials for every exam objective, in the order worth studying them.
Microsoft Certified: Azure Databricks Data Engineer Associate
Exam at a Glance
DP-750 measures whether you can do the day-to-day work of a data engineer in Azure Databricks: setting up compute and Unity Catalog, securing and governing data, building batch and streaming pipelines, and deploying and monitoring workloads that keep running fast.
| DP-750 | Implementing Data Engineering Solutions Using Azure Databricks |
|---|---|
| Certification | Microsoft Certified: Azure Databricks Data Engineer Associate |
| Level | Intermediate (associate role-based exam) |
| Exam length | 120 minutes |
| Questions | Typically 40 to 60; the number and format mix can vary |
| Passing score | 700 out of 1000 |
| Question formats | Multiple choice, multiple select, drag and drop, build list, hot area, case studies, possibly labs |
| Microsoft Learn access | Available within the exam; browsing is restricted and the timer continues |
| Skills measured version | March 11, 2026 |
| Renewal | Certification expires annually; renew with a free online assessment on Microsoft Learn |
| Cost | Depends on your country or region; shown when you schedule |
What the Exam Covers
The exam has four domains, and the weights are not equal: preparing and processing data and deploying and maintaining pipelines are the two highest-weight domains and together cover most of the exam. Environment setup and governance are smaller, but at 15 to 20 percent each you cannot skip them either.
Set up and configure an Azure Databricks environment — 15-20%
Choosing and configuring compute (job compute, serverless, SQL warehouse, classic and shared compute; autoscaling, termination, pools, Photon, runtime versions, libraries, access permissions) and creating and organizing Unity Catalog objects (catalogs, schemas, volumes, tables, views and materialized views, foreign catalogs through connections, DDL on managed and external tables, AI/BI Genie instructions).
Secure and govern Unity Catalog objects — 15-20%
Granting privileges to users, groups and service principals, table- and column-level access control and row-level security, accessing Azure Key Vault secrets, authenticating with service principals and managed identities, attribute-based access control with tags and policies, row filters and column masks, data retention, lineage tracking in Catalog Explorer, audit logging, and Delta Sharing.
Prepare and process data — 30-35%
Designing data modeling and ingestion: choosing between Lakeflow Connect, notebooks and Azure Data Factory; batch versus streaming; Parquet, Delta, CSV, JSON and Iceberg formats; partitioning, slowly changing dimensions and temporal tables; liquid clustering, Z-ordering and deletion vectors; managed versus unmanaged tables.
Ingesting data with SQL methods, CDC feeds, Spark Structured Streaming, Azure Event Hubs, and Lakeflow Spark Declarative Pipelines with Auto Loader.
Cleansing and transforming data (profiling, duplicates and nulls, joins and set operators, pivoting, merge and append loads) and enforcing data quality with validation checks, schema enforcement and pipeline expectations.
Deploy and maintain data pipelines and workloads — 30-35%
Designing pipelines (notebooks versus Lakeflow Spark Declarative Pipelines, task logic, error handling), implementing Lakeflow Jobs (triggers, schedules, alerts, automatic restarts), the development lifecycle (Git branching and pull requests, testing strategy, Databricks Asset Bundles, deploying with the CLI and REST APIs), and monitoring and optimization (cluster consumption and cost, repairing job runs, Spark performance tuning with the DAG, Spark UI and query profile, OPTIMIZE and VACUUM, log streaming to Azure Monitor and alerting).
The full bullet-level list lives in the official study guide. Treat it as your checklist:
The Official DP-750 Study Guide
How This Maps to CertiAce Practice Modules
The CertiAce question bank is organized into four practice modules that map one-to-one to the exam domains, so you can drill each area in isolation:
| CertiAce practice module | What you will drill there |
|---|---|
| Setup and configure the Azure Databricks environment | Compute type and configuration choices, Unity Catalog object creation and organization |
| Secure and govern data with Unity Catalog | Privileges, row and column security, ABAC, lineage, audit logging, Delta Sharing |
| Prepare and process data | Ingestion tools and patterns, table formats, clustering, transformations, data quality |
| Deploy and maintain data pipelines and workloads | Lakeflow Jobs, declarative pipelines, Git and Asset Bundles, monitoring and optimization |
Where DP-750 Fits
| Certification | What it validates | When to take it |
|---|---|---|
| DP-900: Azure Data Fundamentals | Core data concepts and Azure data services | Optional first step if you are new to data work or cloud platforms |
| DP-750: Azure Databricks Data Engineer Associate (this exam) | Building, securing and operating data engineering solutions in Azure Databricks | You are here |
| DP-700: Fabric Data Engineer Associate | The same data engineering discipline on Microsoft Fabric | A natural companion if you work across both platforms |
DP-750 has no official prerequisites. If you are new to data engineering, analytics, or cloud platforms, starting with DP-900 is strongly recommended: it builds the foundational vocabulary DP-750 assumes. If you already work hands-on with Spark, Delta Lake, or Azure Databricks, go straight to DP-750.
Before You Start
The exam assumes practical exposure to Azure Databricks, not just reading. Check yourself against this table. Anything unfamiliar is where your preparation should start:
| Area | You should be comfortable with |
|---|---|
| Azure Databricks fundamentals | What Azure Databricks is and the problems it solves; how workspaces, compute, notebooks and jobs fit together; Apache Spark's role in distributed processing; Delta Lake and the lakehouse; how Unity Catalog organizes catalogs, schemas, tables and volumes |
| Data engineering basics | Batch and incremental ingestion patterns, transformation logic, medallion architecture (raw, curated, serving layers), Parquet and Delta file formats |
| SQL and Python | Reading and writing SQL (joins, aggregations, window functions), basic Python, recognizing PySpark DataFrame code |
| Azure and SDLC awareness | Microsoft Entra ID, Azure Data Factory, Azure Key Vault and Azure Monitor at an awareness level; Git fundamentals such as branching and pull requests |
Step-by-Step Study Plan
How long you need depends on where you start. Treat these estimates as planning guidance and adjust them to your starting knowledge and weekly study hours:
| Your starting point | Suggested prep time |
|---|---|
| Working in Azure Databricks weekly | 3 to 5 weeks |
| You know data engineering, but are new to Databricks | 6 to 8 weeks |
Step 1: Read the Official Study Guide
Skim the full skills-measured list once, and mark every bullet you could not explain to a colleague. That marked-up list is your personal syllabus: everything else in this plan exists to clear it. Note the naming: the current skills list uses the Lakeflow names (Lakeflow Jobs, Lakeflow Connect, Lakeflow Spark Declarative Pipelines). Older materials call the same features Workflows and Delta Live Tables, so cross-check older product names and objectives against the current study guide.
Step 2: Schedule Your Exam
Choose a realistic target date after reviewing the skills list and your available study time. A date on the calendar turns studying into a countdown, so pick one using the prep-time table above and plan backwards from it.
Certification and Exam Details Page
Step 3: Work Through the Official Learning Path
Complete the DP-750 course modules on Microsoft Learn. Take notes on concepts you cannot explain in simple terms, and flag anything that needs hands-on practice. You will come back to those in Step 5. Pay special attention to Unity Catalog, Delta Lake, ingestion, Lakeflow Jobs, monitoring, and optimization.
Official Learning Path Course Page
Step 4: Use a Supplementary Video Resource
No dedicated DP-750 video course exists yet (the exam is still young). Until one appears, freeCodeCamp's free 7.5-hour Databricks Data Engineer course is the best full-length substitute: it targets the Databricks vendor certification, so it covers the platform core the two heavyweight domains test (Delta Lake, Spark, ingestion, Auto Loader, declarative pipelines, jobs, and Unity Catalog) but not the Azure-specific integration topics (Entra ID, Key Vault, Azure Monitor). Get those from the learning path and the labs.
freeCodeCamp Databricks Data Engineer Course
Step 5: Get Hands-On Practice
DP-750 is a practical exam: it rewards real experience building, securing, and operating Azure Databricks solutions, and the questions test whether you recognize real implementation patterns and trade-offs. Work through the official lab exercises for the DP-750 course; they are free, self-paced, and cover every domain. Make sure you personally touch:
- Configuring compute and installing libraries
- Creating and securing Unity Catalog objects
- Loading data from Azure Data Lake Storage into Delta tables
- Building a Lakeflow Spark Declarative Pipeline with Auto Loader
- Creating, scheduling, and repairing Lakeflow Jobs
- Reading the Spark UI and query profile for a slow job
Step 6: Benchmark Your Knowledge
Use CertiAce to benchmark your readiness module by module. The practice modules map to the exam domains as shown above, so use the module mapping and the topics behind your missed questions to identify the skills-measured areas to revisit. Microsoft also offers a free official practice assessment for DP-750 on AI Skills Navigator (sign in to launch it). Aim for consistent performance across every module, not one lucky high score; if a topic is unstable, go back to learning plus hands-on practice.
Official Practice Assessment on AI Skills Navigator
Step 7: Take the Exam
The day before, review only your weak topics: no brand-new material. On exam day, read each question for what it is truly asking, eliminate wrong options first, and watch for wording that implies constraints such as least privilege, cost, performance, or operational simplicity. Notice whether the scenario calls for SQL, Python, Unity Catalog, Lakeflow, or an Azure integration. That alone often eliminates half the options.
Worth knowing before you sit down:
- Microsoft Learn is available during the exam in a split screen. Use it to check details you genuinely need: the timer keeps running, and the exam is deliberately too long to look up every answer. Browsing is limited to Microsoft Learn itself (no Q&A, practice assessments, or profile), and personal notes and other websites are unavailable.
- You can take unscheduled breaks, but the clock keeps running and you cannot return to questions you already saw.
- Case studies lock when you leave them: finish each one before moving on, because you cannot revisit its questions afterwards.
- Labs may appear: DP-750's 120-minute allotment is the one Microsoft uses for role-based exams that may contain labs. The introduction screen tells you whether yours does; if it does, budget extra time for them.
- Try the exam sandbox beforehand so the question formats and interface hold no surprises: Exam Sandbox
Additional Learning Resources
| Resource | Type | Why it is useful |
|---|---|---|
| Official Practice Assessment (AI Skills Navigator) | Practice | Microsoft's free official practice assessment for DP-750 (sign in to launch it) |
| Official DP-750 Lab Exercises | Hands-on labs | The free lab repo behind the official course, with self-paced exercises for every domain |
| Databricks Free Edition | Hands-on | A free Databricks workspace for practicing Spark, Delta Lake and Unity Catalog at zero cost |
| Azure Databricks documentation | Docs hub | The source of truth the exam draws from: Delta Lake, Unity Catalog, Lakeflow, compute |
| Azure Databricks community hub | Community | Microsoft's official Azure Databricks blog and announcements |
| Exam Readiness Zone | Video series | Microsoft Certified Trainer prep videos. Watch for DP-750 episodes as they appear |
| Data Exposed | Video show | Short Microsoft data-platform episodes, good for passive learning between study sessions |
| DriveDataScience DP-750 study guide | Blog | Maps every exam objective to free Databricks and PySpark tutorials |
Realistic DP-750 exam-style questions with instant feedback and detailed explanations.
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