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Course
- Cloud
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 | 1m 58s
- Preliminary Definitions | 4m 40s
- Batch vs. Stream Processing | 1m 44s
- Azure Data Lake Storage Gen2 | 3m 23s
- Apache Spark | 1m 30s
- Demo: Create an ADLS Gen2 File System | 4m 23s
- Azure Databricks | 2m 19s
- Demo: Create and Configure the Azure Databricks Service | 5m 5s
- Demo: Create a Work in an Azure Databricks Notebook | 9m 9s
- Summary | 1m 10s
About the author
Timothy Warner is a Microsoft Most Valuable Professional (MVP) in Cloud and Datacenter Management who is based in Nashville, TN.
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