Real-Time Data Stream Processing in Azure
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
June 29, 2020 | ISBN: 9781800563391 | English
Duration: 9 Lessons (1h 14m) | Size: 539.5 MB

Delve into big data streaming with Azure using Event Hubs, Data Lake, and Azure Stream Analytics Learn
Gain a thorough understanding of Azure Stream Analytics
Discover how to ingest data using Azure Event Hubs
Find out how to archive data from Event Hubs to Azure Data Lake
Provision Event Hubs, Data Lake, and SQL Server in Azure
Listen to an event hub and stream the data to a SQL Server table
Communicate with event hubs for effortless data transfer
Discover how event hub groups work

About
A modern digital company captures a large amount of data every day. This data gets locked in data islands such as caches, queues, and logs, and extracting this data and making it useful poses a major challenge. Real-time data processing is the most effective alternative to traditional extract, transform, and load (ETL) processes. This course will help you to think of data as an ever-flowing stream of events instead of data as islands locked away in databases.

This course employs live labs to get you up to speed with Azure Event Hubs and teach you how to create C# console applications for sending and receiving data from Event Hubs. As you advance, you'll learn how to capture and archive data from Azure Event Hubs to Azure Data Lake. The subsequent videos will show you how to provision Event Hubs, Data Lake, and SQL Server databases in Azure. Toward the end of the course, you'll write an analytics job to stream live data from an event hub to a SQL Server database.

By the end of this course, you'll have developed a solid understanding of how to stream big data using Azure Stream Analytics.