Data Engineering with Apache Spark Pools in MS Azure Synapse

In this course, you will learn how to perform data engineering using Azure Synapse Apache Spark Pools, which improve the performance of big data analytics applications using in-memory cluster computing. You will learn how to differentiate between Apache Spark, Azure Databricks, HDInsight, and SQL Pools, and understand use cases for data engineering using Apache Spark in Azure Synapse Analytics. You will also learn how to ingest data using Apache Spark notebooks in Azure Synapse Analytics and transform data using DataFrames in Apache Spark pools in Azure Synapse Analytics. You will integrate SQL pools and Apache Spark in Azure Synapse Analytics. You will also learn how to monitor and manage data engineering workloads using Apache Spark in Azure Synapse Analytics. 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 the DP-203: Data Engineering on Microsoft Azure (beta) exam. You will take a practice exam that covers the key skills measured by the certification exam. This is the sixth course in a 10-course program that helps you prepare for the exam so that you can gain expertise in 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).