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In this course, you will learn how to perform data engineering with Azure Synapse Apache Spark Pools, which enable you to boost the performance of big-data analytic applications by in-memory cluster computing.
You will learn how to differentiate between Apache Spark, Azure Databricks, HDInsight, and SQL Pools and understand the use-cases of data-engineering with 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 and Apache Spark pools in Azure Synapse Analytics. You will also learn how to monitor and manage data engineering workloads with Apache Spark in Azure Synapse Analytics. This course is part of a Specialization intended for Data engineers and developers who want to demonstrate their expertise in designing and implementing data solutions that use Microsoft Azure data services for anyone interested in preparing for the Exam DP-203: Data Engineering on Microsoft Azure (beta). You will take a practice exam that covers key skills measured by the certification exam. This is the sixth course in a program of 10 courses to help prepare you to take the exam so that you can have expertise in designing and implementing data solutions that use Microsoft Azure data services. The Data Engineering on Microsoft Azure exam is an opportunity to prove knowledge expertise in integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions that use Microsoft Azure data services. Each course teaches you the concepts and skills that are measured by the exam. By the end of this Specialization, you will be ready to take and sign-up for the Exam DP-203: Data Engineering on Microsoft Azure (beta).
