DP-750 (Beta) Study Guide
Microsoft Certified: Azure Databricks Data Engineer Associate
Before You Start Studying
Before diving into the study sections, review the prerequisites, study guide status, and recommended background knowledge below to understand what will help you succeed.
Study Guide Under Construction
DP-750 is a Microsoft certification focused on implementing data engineering solutions using Azure Databricks. Because the exam and learning ecosystem are still relatively new, additional learning resources, community guides, and exam preparation materials may still be limited compared to more established exams such as DP-600, DP-700, or AZ-900.
For now, the best preparation path is to rely heavily on:
- The official Microsoft study guide
- The official DP-750T00 course
- Microsoft Learn modules
- Hands-on practice in Azure Databricks
- Azure Databricks product documentation
- CertiAce practice questions
This page will be updated as more reliable and current DP-750 learning resources become available.
Recommended Exam Path
DP-750 is an associate-level data engineering certification, so it is not usually the best first Microsoft data certification for complete beginners.
If you are new to data, analytics, or cloud platforms, DP-900: Microsoft Certified – Azure Data Fundamentals is strongly recommended before starting DP-750.
DP-900 helps you build:
- Foundational understanding of data concepts
- Awareness of relational and non-relational data workloads
- Understanding of analytics workloads
- Familiarity with Azure data services
If you already have hands-on experience with Spark, Delta Lake, Azure Databricks, or lakehouse architecture, you can proceed directly to DP-750.
Prerequisites
There are no strict prerequisites to start DP-750 preparation, but the exam assumes that you have practical exposure to Azure Databricks and data engineering concepts.
You should be comfortable with:
- Working with Azure Databricks workspaces
- Understanding Apache Spark concepts
- Reading and writing SQL
- Reading and writing basic Python
- Working with Delta Lake tables
- Understanding data ingestion and transformation patterns
- Using notebooks and jobs
- Understanding identity, access, and governance concepts
- Understanding basic software development lifecycle practices such as Git
Recommended Background Knowledge
DP-750 focuses on data engineering with Azure Databricks, not general Azure administration or basic data theory.
Azure Databricks Fundamentals
- What Azure Databricks is and what problems it solves
- How workspaces, clusters, notebooks, jobs, and catalogs fit together
- The role of Apache Spark in distributed data processing
- The purpose of Delta Lake in lakehouse architecture
Data Engineering Basics
- Batch ingestion patterns
- Incremental loading concepts
- Transformation logic
- Raw, curated, and serving layers
- Medallion architecture concepts
- File-based formats such as Parquet and Delta
SQL, Python, and Spark Awareness
- Read and write SQL queries
- Understand joins, filters, aggregations, and window functions
- Understand basic Python syntax
- Recognize PySpark DataFrame concepts
- Understand Spark jobs, partitions, and performance considerations
Delta Lake and Lakehouse Concepts
- Delta tables
- ACID transactions
- Schema enforcement and schema evolution
- Time travel
- Optimization and maintenance
- Change data capture concepts
Unity Catalog and Governance
- Catalogs, schemas, tables, and volumes
- Access control
- Data governance concepts
- Lineage awareness
- Secure access to storage
- Managed identities and service principals
Azure Integration Awareness
- Azure Data Lake Storage
- Azure Data Factory
- Microsoft Entra ID
- Azure Key Vault
- Azure Monitor
- Power BI integration
- Git integration and deployment workflows
Step-by-Step Study Guide
Step 1: Review the Official Study Guide
What to do:
- Open the official DP-750 study guide
- Read the skills measured sections
- Note any topics that are new to you
- Use it as your checklist throughout your prep
- Revisit the page regularly because DP-750 is still a newer exam
Link to The Official Study Guide
Step 2: Schedule Your Exam
What to do:
- Choose a date that gives you enough time for study and practice
- Schedule the exam through the official Microsoft certification page
- Put the date on your calendar and plan backwards
Recommended timing:
- If you already use Azure Databricks weekly: 3 to 5 weeks
- If you know data engineering but are new to Databricks: 6 to 8 weeks
- If you are new to data engineering: start with DP-900 first
Certification and Exam Details Page
Step 3: Go Through the Official Learning Path
What to do:
- Complete the official DP-750 course and modules
- Take notes on concepts you cannot explain in simple terms
- Flag areas that require additional hands-on practice
- Pay special attention to Unity Catalog, Delta Lake, ingestion, orchestration, monitoring, and optimization
Official Learning Path Course Page
Step 4: Use Microsoft Official Exam Prep Resources
What to do:
- Review Microsoft’s official certification and course pages
- Use the official study guide as your primary checklist
- Watch for Microsoft Learn updates as more DP-750 resources are released
- Compare every external resource against the official skills measured list
Step 5: Get Hands-On Practice
DP-750 is a practical data engineering exam. It rewards real experience building, securing, and maintaining Azure Databricks solutions.
Reading and watching content helps you understand the platform, but the exam expects you to recognize real implementation patterns, trade-offs, and operational decisions.
You should aim to get experience with:
- Creating and configuring Azure Databricks workspaces
- Working with notebooks
- Creating and using clusters or serverless compute
- Loading data from Azure Data Lake Storage
- Creating Delta tables
- Transforming data with SQL and Python
- Implementing medallion architecture patterns
- Managing permissions with Unity Catalog
- Creating and scheduling jobs
- Monitoring job runs and troubleshooting failures
- Optimizing tables and workloads
- Using Git or deployment workflows for development lifecycle management
The goal is not just to understand Databricks terminology. You should know how data engineering solutions are actually built and operated in Azure Databricks.
Step 6: Benchmark Your Knowledge
What to do:
- Use CertiAce to benchmark your readiness
- Practice exam-style questions
- Review explanations carefully, especially for wrong answers
- Return to Microsoft Learn and hands-on practice for weak topics
- Use the official Microsoft practice assessment if one becomes available
Recommended target:
- Aim for consistent performance, not one lucky high score
- If a topic is unstable, return to learning + hands-on
- Pay close attention to questions involving Unity Catalog, Delta Lake, job orchestration, monitoring, optimization, and secure access
Microsoft Practice Assessments
Step 7: Take the Exam
The day before:
- Review your weak topics only
- Revisit Unity Catalog, Delta Lake, ingestion, jobs, monitoring, and optimization
- Review key Azure integrations such as Azure Data Lake Storage, Key Vault, Entra ID, and Azure Monitor
- Avoid learning brand new topics
On exam day:
- Read questions carefully and identify what they are truly asking
- Eliminate wrong options first
- Watch for wording that implies security, governance, performance, cost, or operational simplicity
- Pay attention to whether the scenario requires SQL, Python, Spark, Unity Catalog, jobs, or Azure integration
- Remember that DP-750 tests practical Azure Databricks data engineering skills, not just product awareness
Additional Learning Resources
Microsoft Official Resources
- https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-750
- https://learn.microsoft.com/en-us/credentials/certifications/implementing-data-engineering-solutions-using-azure-databricks/
- https://learn.microsoft.com/en-us/training/courses/dp-750t00
- https://learn.microsoft.com/en-us/credentials/certifications/practice-assessments-for-microsoft-certifications
- https://learn.microsoft.com/en-us/shows/exam-readiness-zone/
- https://learn.microsoft.com/en-us/training/course-videos-on-shows
Microsoft Lab Resources
Databricks Documentation
- https://learn.microsoft.com/en-us/azure/databricks/
- https://learn.microsoft.com/en-us/azure/databricks/getting-started/
- https://learn.microsoft.com/en-us/azure/databricks/lakehouse/
- https://learn.microsoft.com/en-us/azure/databricks/delta/
- https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/
- https://learn.microsoft.com/en-us/azure/databricks/workflows/
- https://learn.microsoft.com/en-us/azure/databricks/optimizations/
- https://learn.microsoft.com/en-us/azure/databricks/security/
Azure Integration Documentation
- https://learn.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction
- https://learn.microsoft.com/en-us/azure/data-factory/
- https://learn.microsoft.com/en-us/entra/
- https://learn.microsoft.com/en-us/azure/key-vault/
- https://learn.microsoft.com/en-us/azure/azure-monitor/
- https://learn.microsoft.com/en-us/power-bi/connect-data/service-azure-databricks
Practice and Review Resources
Ready to test your knowledge?
Practice questions for DP-750 (Beta)