This course will look at consuming a stream of data in Azure. In this course, Design Principles for Implementing Stream Processing Solutions, you will learn design principles for Azure services that ingest streaming data. First, you will explore the Azure services to connect to stream processing like Event Hub. Next, you will discover how to ingest streaming data with Data Factory and Databricks. Finally, you will learn the design and test methodologies for cleansing the stream data that loads into analytics engines like Azure Stream Analytics. This will help with principles for machine and deep learning models. When you’re finished with this course, you’ll have the skills and knowledge of streaming design principles needed to create and manage a streaming solution.
MIT Sloan: Lead AI Adoption Across Your Organization — Not Just Pilot It
Power BI Fundamentals - Create visualizations and dashboards from scratch
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
This course will look at consuming a stream of data in Azure. In this course, Design Principles for Implementing Stream Processing Solutions, you will learn design principles for Azure services that ingest streaming data. First, you will explore the Azure services to connect to stream processing like Event Hub. Next, you will discover how to ingest streaming data with Data Factory and Databricks. Finally, you will learn the design and test methodologies for cleansing the stream data that loads into analytics engines like Azure Stream Analytics. This will help with principles for machine and deep learning models. When you’re finished with this course, you’ll have the skills and knowledge of streaming design principles needed to create and manage a streaming solution.
Syllabus
- Course Overview 1min
- Stream Processing and Storage 14mins
- Stream Consistency and Analytics 17mins
Taught by
Thomas LeBlanc