Microsoft Azure Databricks for Data Engineering

This course will teach you how to use the power of Apache Spark, powerful clusters on Azure Databricks to run large data engineering tasks in the cloud.

You'll learn about Azure Databricks, and how the Apache Spark notebook can be used to process large files. The Azure Databricks platform will be explained and the best tasks for Apache Spark will be identified. The architecture of an Azure Spark Cluster and the Spark Jobs will be explained to you. You will be working with large quantities of data, from different sources and in different formats. You will learn about Azure Databricks' support for data handling functions such as queries, reads, writes and writes. This course is part a specialization for Data engineers and developers that want to show their skills in designing and implementing Microsoft Azure data solutions. It's for anyone who wants to prepare for the Exam DP-203 Data Engineering on Microsoft Azure (beta). A practice exam will be given to assess your skills in preparation for the certification exam. This course is eighth in a series of 10 courses that will prepare you for the certification exam. It will help you design and implement data solutions using Microsoft Azure data services. Data Engineering on Microsoft Azure is a chance to demonstrate knowledge in integrating, transforming and consolidating data from different structured and unstructured systems into structures suitable for building analytics solutions using Microsoft Azure data services. The exam measures the skills and concepts that each course teaches. After this Specialization, it is possible to sign up for Exam DP-203 Data Engineering on Microsoft Azure (beta)