Master end-to-end data engineering with Azure Databricks and Unity Catalog. In this course, learners move from foundational setup to production deployment, including environment configuration, data ingestion, data transformation, governance, security, and workload deployment. Students learn how to build scalable data engineering solutions using Azure Databricks, Apache Spark, Delta Lake, Unity Catalog, Lakeflow Declarative Pipelines, and Lakeflow Jobs. The course focuses on implementing, securing, and maintaining lakehouse solutions that support enterprise data engineering requirements. This course helps prepare learners for the Microsoft Certified: Azure Databricks Data Engineer Associate certification. Implement Data Engineering Solutions Using Azure Databricks (DP-750) Benefits You Will Learn How To• Use Azure Databricks for data engineering and analytics workloads• Ingest, transform, and analyze data using Spark, Spark SQL, and PySpark• Manage data with Delta Lake and Unity Catalog• Design and implement data models for Azure Databricks• Build and manage Lakeflow Declarative Pipelines• Deploy and orchestrate workloads using Lakeflow Jobs• Secure and govern data assets using Unity Catalog Prerequisites Fundamental knowledge of data analytics concepts Experience with SQL Experience using Python for data engineering tasks Familiarity with notebooks Basic understanding of cloud storage and data organization Familiarity with Azure Databricks workspaces and Unity Catalog Foundational knowledge of Azure security, including Microsoft Entra ID Familiarity with Git version control fundamentals Exam Information Microsoft Certified: Azure Databricks Data Engineer Associate Azure Databricks Training Outline Learning Objectives Set up and Configure an Azure Databricks Environment 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 Secure and Govern Unity Catalog Objects in Azure Databricks Secure Unity Catalog objects Govern Unity Catalog objects Prepare and Process Data with Azure Databricks 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 Deploy and Maintain Data Pipelines and Workloads with Azure Databricks 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
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