How can you gain business insights from data lakes and data warehouses? How can you use Hadoop, Spark, and Databricks in Microsoft Azure? In this course, Building Batch Data Processing Solutions in Microsoft Azure, you will gain the ability to implement scalable, performant, and accurate batch processing in the Microsoft Azure cloud. First, you will learn how to run batch processing jobs in Azure SQL Data Warehouse. Next, you will discover how HDInsight enables cloud-hosted Hadoop clusters. Finally, you'll explore Apache Spark and Azure Databricks, and learn how to integrate them with other Azure products. When you are finished with this course, you will have the skills and knowledge of batch data processing needed to advance your career as a data engineer.
Course Overview Hi everyone! My name is Tim Warner. Welcome to my course, Building Batch Data Processing Solutions in Microsoft Azure. I'm a Pluralsight staff author, Microsoft MVP, and your instructor. In this course, you'll learn how a Microsoft Azure data engineer can use Microsoft Azure data platform products to implement batch data processing workflows. Some of the major topics we'll cover include ingesting and exporting data with Azure SQL Data Warehouse, performing ETL and ELT processes with Azure HDInsight and Apache Spark, and implementing batch and stream processing with Azure Databricks. By the end of this course, you'll be ready to embrace big data processing in Microsoft Azure using native tools like Apache Hadoop and Databricks. I hope you'll join me on this journey to learn Azure data platform batch processing with the Building Batch Data Processing Solutions in Microsoft Azure course, at Pluralsight.