Microsoft Azure Databricks for Data Engineering

In this course, you will learn how to leverage the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run large data processing workloads in the cloud. You will be introduced to the capabilities of Azure Databricks and Apache Spark Notebook for processing huge files. You will begin to understand the Azure Databricks platform and identify the types of tasks that are a good fit for Apache Spark. You will also be introduced to the architecture of the Azure Databricks Spark Cluster and Spark jobs. You will work with large volumes of data from a variety of sources in a variety of source formats. You will learn how Azure Databricks supports everyday data functions such as reading, writing, and querying. This course is part of a specialization designed for data engineers and developers who want to demonstrate their expertise in designing and implementing data solutions that use Microsoft Azure Data Services, for those interested in preparing for exam DP-203: Data Engineering on Microsoft Azure (beta). You will take a hands-on exam that covers the key skills measured by the certification exam. This is the eighth course in a 10-course program that helps you prepare for the exam so you can gain experience designing and implementing data solutions that use Microsoft Azure data services. The Data Engineering on Microsoft Azure exam is an opportunity to validate your knowledge of integrating, transforming, and consolidating data from a variety of structured and unstructured data systems into structures suitable for building analytical solutions that use Microsoft Azure data services. Each course teaches you the concepts and skills that are measured on the exam. By the end of this specialization, you will be prepared to take and register for exam DP-203: Data Engineering on Microsoft Azure (beta).