Overview
In this 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.
Pre-requisites
Knowledge of Azure accounts and services
Knowledge of various data sources such as SQL Server and Azure Cosmos DB
Knowledge of the concepts around data governance
Audience
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.