Building Batch Data Processing Solutions in Microsoft Azure
Azure Data Engineers design and implement data solutions in the Microsoft Azure cloud. This course will teach you how to use Azure products to perform batch data processing operations.
What you'll learn
Long-running batch data processing can be difficult to manage locally - why not use Microsoft Azure? In this course, Building Batch Data Processing Solutions in Microsoft Azure, you’ll gain the ability to perform high-scale ETL and ELT operations entirely in the Azure public cloud. First, you’ll explore hosted Apache Spark processing with Azure Databricks. Next, you’ll discover how to transfer data in bulk with Azure Data Factory and Azure Data Explorer. Finally, you’ll learn how to handle stream data processing jobs with Azure Stream Analytics. When you’re finished with this course, you’ll have the skills and knowledge of batch data processing needed to earn your Azure Data Engineer certification and be productive with the Microsoft Azure Data Platform.
Table of contents
- Overview 2m
- Preliminary Definitions 5m
- Batch vs. Stream Processing 2m
- Azure Data Lake Storage Gen2 3m
- Apache Spark 2m
- Demo: Create an ADLS Gen2 File System 4m
- Azure Databricks 2m
- Demo: Create and Configure the Azure Databricks Service 5m
- Demo: Create a Work in an Azure Databricks Notebook 9m
- Summary 1m
About the author
Timothy Warner is a Microsoft Most Valuable Professional (MVP) in Cloud and Datacenter Management who is based in Nashville, TN. His professional specialties include Microsoft Azure, cross-platform PowerShell, and all things Windows Server-related. You can reach Tim via Twitter (@TechTrainerTim), LinkedIn or his blog, AzureDepot.com.