In this course, delegates will gain knowledge about data engineering patterns and practices as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Delegates will understand the core computing and storage technologies that are used to build an analytical solution. They will then explore how to design analytical serving layers and focus on data engineering considerations for working with source files.

Who should attend

• 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. 

• Data analysts and data scientists who work with analytical solutions built on Microsoft Azure

Course Outcomes

After completing this course you should be able to: 

• Explore compute and storage options for data engineering workloads in Azure 

• Design and Implement the serving layer 

• Understand data engineering considerations 

• Run interactive queries using server-less SQL pools 

• Explore, transform, and load data into the Data Warehouse using Apache Spark 

• Perform data Exploration and Transformation in Azure Data bricks 

• Ingest and load Data into the Data Warehouse 

• Transform Data with Azure Data Factory or Azure Synapse Pipelines