Program Outline
Implement data engineering solutions using Azure Databricks
Master end-to-end data engineering with Azure Databricks and Unity Catalog. This course moves from foundational setup to production deployment, covering environment configuration and enterprise-grade governance. Learn to build robust ingestion pipelines, implement security with Unity Catalog, and deploy optimized workloads. By the end, you will have the practical skills to implement, secure, and maintain scalable lakehouse solutions that meet rigorous enterprise requirements.
Delivery
Virtual, On-site, or Hybrid
Duration
4 days
Product
Azure
Role
Data Engineer
Databricks
Data EngineeringAzure Databricks Data Engineer Associate (beta)
Azure Databricks
Best Fit
Audience Profile
Who This Program Is For
The target audience is data engineers who have fundamental knowledge of data analytics concepts, a basic understanding of cloud storage, and familiarity with data organization principles. They should be comfortable working with SQL and have experience using Python, including notebooks, for data engineering tasks. Learners are expected to have a good understanding of Azure Databricks workspaces and Unity Catalog, along with familiarity with data access patterns and core data engineering and data warehouse concepts. In addition, they should have foundational knowledge of Azure security, including Microsoft Entra ID, and be familiar with Git version control fundamentals.
Overview
Program Summary
As a candidate for this Microsoft Certification, you should have subject matter expertise in integrating and modeling data, building and deploying optimized pipelines, and troubleshooting and maintaining workloads in Azure Databricks.
Course Outline
Complete Module Sequence
Review the full module sequence for this program, including the primary topic coverage in each module where available.
1Module 1
Set up and configure an Azure Databricks environment
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Module 1
Set up and configure an Azure Databricks environment
Build a solid foundation in Azure Databricks by understanding its architecture, integrations, compute options, and data organization capabilities. Learn how Azure Databricks provides a unified platform for data engineering, analytics, and AI workloads in the cloud.
- Explore Azure Databricks
- Understand Azure Databricks architecture
- Understand Azure Databricks Integrations
- Select and Configure Compute in Azure Databricks
- Create and organize objects in Unity Catalog
2Module 2
Secure and govern Unity Catalog objects in Azure Databricks
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Module 2
Secure and govern Unity Catalog objects in Azure Databricks
Learn to implement comprehensive security and governance for your data assets in Azure Databricks using Unity Catalog. Master access control strategies, fine-grained permissions, credential management, and governance practices to build a secure and compliant data platform.
- Secure Unity Catalog objects
- Govern Unity Catalog objects
3Module 3
Prepare and process data with Azure Databricks
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Module 3
Prepare and process data with Azure Databricks
Master the essential skills to build robust, scalable data engineering solutions with Azure Databricks and Unity Catalog. Learn to design effective data models, ingest data from diverse sources, transform raw data into analytics-ready formats, and ensure data quality across your lakehouse architecture.
- Design and implement data modeling with Azure Databricks
- Ingest data into Unity Catalog
- Cleanse, transform, and load data into Unity Catalog
- Implement and manage data quality constraints with Azure Databricks
4Module 4
Deploy and maintain data pipelines and workloads with Azure Databricks
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Module 4
Deploy and maintain data pipelines and workloads with Azure Databricks
Master the complete lifecycle of building, deploying, and maintaining production-ready data pipelines in Azure Databricks—from design and orchestration to monitoring and optimization.
- Design and implement data pipelines with Azure Databricks
- Implement Lakeflow Jobs with Azure Databricks
- Implement development lifecycle processes in Azure Databricks
- Monitor, troubleshoot and optimize workloads in Azure Databricks
Coverage Areas
Topic Coverage
Coverage Item 1
Set up and configure an Azure Databricks environment
Coverage Item 2
Secure and govern Unity Catalog objects
Coverage Item 3
Prepare and process data
Coverage Item 4
Deploy and maintain data pipelines and workloads
Customization
Adapt This Program for Your Team
We can adapt this program around your team structure, platform priorities, delivery goals, and the scenarios your people need to work through in practice.
- •Align labs to your Microsoft tenant and workload scenarios
- •Add readiness checks and exam preparation reviews
- •Extend delivery with role-specific implementation workshops
