Spark SQL and Spark 3 using Scala Hands-On with Labs

About this course

As part of this course, you will learn all the key skills to build Data Engineering Pipelines using Spark SQL and Spark Data Frame APIs using Scala as a Programming language. This course used to be a CCA 175 Spark and Hadoop Developer course for the preparation of the Certification Exam. As of 10/31/2021, the exam is sunset and we have renamed it to Spark SQL and Spark 3 using Scala as it covers industry-relevant topics beyond the scope of certification.About Data EngineeringData Engineering is nothing but processing the data depending on our downstream needs. We need to build different pipelines such as Batch Pipelines, Streaming Pipelines, etc as part of Data Engineering. All roles related to Data Processing are consolidated under Data Engineering. Conventionally, they are known as ETL Development, Data Warehouse Development, etc. Apache Spark is evolved as a leading technology to take care of Data Engineering at scale.I have prepared this course for anyone who would like to transition into a Data Engineer role using Spark (Scala). I myself am a proven Data Engineering Solution Architect with proven experience in designing solutions using Apache Spark.Let us go through the details about what you will be learning in this course. Keep in mind that the course is created with a lot of hands-on tasks which will give you enough practice using the right tools. Also, there are tons of tasks and exercises to evaluate yourself.Setup of Single Node Big Data ClusterMany of you would like to transition to Big Data from Conventional Technologies such as Mainframes, Oracle PL/SQL, etc and you might not have access to Big Data Clusters. It is very important for you set up the environment in the right manner. Don't worry if you do not have the cluster handy, we will guide you through support via Udemy Q&A.Setup Ubuntu-based AWS