There is plenty of value in learning how to turn Kafka into a stream analytics engine. In this course, Building ETL Pipelines from Streaming Data with Kafka and KSQL, you’ll learn to shape and transform your Kafka streaming data. First, you’ll explore how ksqlDB and Kafka Streams both solve this problem. Next, you’ll discover how to transform your streams. Finally, you’ll learn how to aggregate and enrich data. When you’re finished with this course, you’ll have the skills and knowledge of ksqlDB and Kafka Streams needed to extract insights from Kafka streaming data.
Starting out as an accidental DBA and developer, Eugene Meidinger now focuses primarily on BI consulting. He has been working with SQL Server for five years now, and is certified in Querying and Administering SQL Server 2012. He regularly presents at various SQL Saturday events.
Course Overview Hi, everyone. My name is Eugene Meidinger, and welcome to my course, Building ETL Pipelines from Streaming Data with Kafka and ksqlDB. I'm a business intelligence consultant working at SQLGene Training, LLC. And in this course, we're going to turn Kafka into a stream analytics engine. Some of the major topics that we will cover include streaming data theory, writing ksqlDB queries, and writing Kafka Streams applications. By the end of this course, you'll know how to extract insights from your streaming data living in Apache Kafka. Before beginning this course, you should be familiar with Apache Kafka. I hope you'll join me on this journey to learn how to transform streaming data with the Building ETL Pipelines from Streaming Data with Kafka and ksqlDB course, at Pluralsight.