Course Description
In this 4-day Data Engineering on Microsoft Azure training course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.
The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure.
Course Summary
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Course Modules
Introduction to data engineering on Azure
- Introduction
- What is data engineering
- Important data engineering concepts
- Data engineering in Microsoft Azure
- Knowledge check
- Summary
Use Delta Lake in Azure Synapse Analytics
- Introduction
- Understand Delta Lake
- Create Delta Lake tables
- Create catalog tables
- Use Delta Lake with streaming data
- Use Delta Lake in a SQL pool
- Exercise – Use Delta Lake in Azure Synapse Analytics
- Knowledge check
- Summary
Get started with Azure Stream Analytics
- Introduction
- Understand data streams
- Understand event processing
- Understand window functions
- Exercise – Get started with Azure Stream Analytics
- Knowledge check
- Summary
