Azure Databricks Data Engineer Associate DP-750

• Set up and configure an Azure Databricks environment.
• Configure compute resources for data engineering workloads.
• Create and organize objects in Unity Catalog.
• Secure and govern Unity Catalog objects.
• Design and implement data models.
• Ingest, cleanse, transform, and load data.
• Build and manage data pipelines.
• Deploy and maintain data engineering workloads.
• Monitor, troubleshoot, and optimize Azure Databricks workloads.
• Apply data quality and governance practices.

1. Set up and configure an Azure Databricks environment

• Explore Azure Databricks
• Understand Azure Databricks integrations
• Select and configure compute resources
• Create and organize objects in Unity Catalog
• Configure Azure Databricks workspaces and data assets

2. Secure and govern Unity Catalog objects

• Secure Unity Catalog objects
• Configure access permissions
• Implement table-, column-, and row-level security
• Configure authentication using service principals and managed identities
• Govern data assets
• Configure data lineage
• Configure audit logging
• Implement secure data-sharing strategies

3. Prepare and process data with Azure Databricks

• Design and implement data modeling
• Configure data ingestion
• Select appropriate ingestion tools
• Work with batch and streaming data
• Choose appropriate data formats
• Implement partitioning and clustering
• Implement slowly changing dimensions
• Ingest data using Lakeflow Connect, notebooks, SQL, and streaming
• Cleanse and transform data
• Load data into Unity Catalog
• Implement data quality practices

4. Deploy and maintain data pipelines and workloads

• Design and implement data pipelines
• Build pipelines using notebooks and Lakeflow Spark Declarative Pipelines
• Create and orchestrate Lakeflow Jobs
• Configure triggers and schedules
• Implement error handling
• Use version control with Git
• Deploy pipelines across environments
• Use Declarative Automation Bundles
• Monitor and troubleshoot data workloads
• Optimize workload performance and reliability

4 Days

Certification: Microsoft Certified: Azure Databricks Data Engineer Associate
Exam: DP-750: Implementing Data Engineering Solutions Using Azure Databricks
Duration: 100 minutes

• Data engineers.
• Professionals responsible for implementing Azure Databricks data engineering solutions.
• Professionals working with data integration, modeling, pipelines, and workloads in Azure Databricks.
• Professionals working with Unity Catalog data governance and security.
• Data engineering professionals collaborating with data scientists, data analysts, architects, and administrators.

• Fundamental knowledge of data analytics concepts.
• Basic understanding of cloud storage.
• Familiarity with SQL and data organization principles.
• Experience with Python and notebooks for data engineering tasks.
• Understanding of Azure Databricks workspaces and Unity Catalog.
• Knowledge of fundamental data engineering and data warehouse concepts.
• Foundational knowledge of Azure security, including Microsoft Entra ID.
• Familiarity with Git version control fundamentals.