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.
Apart from public, instructor-led classes, we also offer private in-house trainings for organizations based on their needs. Call us at +852 2116 3328 or email us at [email protected] for more details.
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.
Module 2:Secure and govern Unity Catalog objects in Azure Databricks
Unity Catalog provides centralized governance and security for data assets in Azure Databricks. This module explores how to secure Unity Catalog objects through access control strategies, fine-grained permissions, credential management, and authentication mechanisms.
You’ll learn how to implement table and schema-level security, enforce row and column filtering, securely access secrets from Azure Key Vault, and authenticate data access using service principals and managed identities.
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.
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.
Microsoft Certified: Azure Databricks Data Engineer Associate
Demonstrate expertise in integrating and modeling data, building and deploying optimized pipelines, and troubleshooting and maintaining workloads in Azure Databricks.