Building Batch Data Analytics Solutions on AWS Course Overview

Building Batch Data Analytics Solutions on AWS Course Overview

The "Building Batch Data Analytics Solutions on AWS" course offers an in-depth exploration into constructing robust data analytics pipelines on the AWS platform. It equips learners with the skills to leverage AWS services for high-performance analytics, focusing on Batch data processing using tools like Amazon EMR and Apache Spark.

Module 0 sets the stage by introducing key Data analytics use cases and the crucial role of Data pipelines for effective analytics. Module 1 dives into Amazon EMR, detailing its use in analytics solutions, Cluster architecture, Cost management, and includes an interactive demo for launching an EMR cluster. Module 2 looks at optimizing storage and Data ingestion techniques for Amazon EMR.

Module 3 is dedicated to high-performance analytics using Apache Spark on Amazon EMR, including practical labs for hands-on experience. Module 4 continues with processing and analyzing batch data using Apache Hive and HBase on Amazon EMR.

In Module 5, learners discover Serverless data processing and orchestrate workflows with AWS services like AWS Glue and AWS Step Functions. Module 6 covers the vital aspects of security, monitoring, and troubleshooting of EMR clusters, concluding with a design activity for a batch data analytics workflow. Finally, Module 7 provides insights into developing Modern data architectures on AWS, broadening the scope for learners to design comprehensive analytics solutions. This course is a valuable resource for professionals seeking to enhance their batch data analytics capabilities on the AWS cloud.

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Course Fee 675
Total Fees
(without exam)
675 (USD)
  • Live Training (Duration : 8 Hours)
  • Per Participant
  • Includes Official Coursebook
  • Guaranteed-to-Run (GTR)
  • Classroom Training fee on request
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  • Live Training (Duration : 8 Hours)
  • Per Participant
  • Classroom Training fee on request
  • Includes Official Coursebook

♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

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Target Audience for Building Batch Data Analytics Solutions on AWS

This course covers advanced data analytics on AWS, focusing on batch processing and data pipeline optimization for IT professionals.


  • Data Engineers
  • Data Scientists
  • Data Analysts
  • Solutions Architects
  • Cloud Computing Specialists
  • Business Intelligence Professionals
  • IT Managers overseeing data operations
  • Software Developers interested in data analytics
  • DevOps Engineers involved in data pipeline deployment
  • Technical Professionals looking to specialize in AWS analytics services
  • System Administrators aiming to expand their skill set into big data
  • AWS Certified Professionals seeking to deepen their expertise in data analytics services


Learning Objectives - What you will Learn in this Building Batch Data Analytics Solutions on AWS?

Introduction to Course Outcomes

This course empowers students with the skills necessary to build scalable batch data analytics solutions on AWS, leveraging tools such as Amazon EMR, Apache Spark, and Hive.

Learning Objectives and Outcomes

  • Understand data analytics use cases and how to implement data pipelines for effective analytics.
  • Learn the essentials of Amazon EMR, including cluster architecture and cost management strategies.
  • Gain hands-on experience in launching and managing Amazon EMR clusters through interactive demos.
  • Master storage optimization and data ingestion techniques specific to Amazon EMR.
  • Explore Apache Spark use cases on Amazon EMR, understand its benefits, and perform data transformations and analytics.
  • Acquire practical skills in connecting to an EMR cluster and executing Scala commands using the Spark shell.
  • Utilize notebooks with Amazon EMR for low-latency data analytics and gain proficiency with hands-on lab experience.
  • Process and analyze batch data efficiently using Amazon EMR with Apache Hive and HBase.
  • Discover serverless data processing options and learn to orchestrate data workflows using AWS Glue and Step Functions.
  • Enhance security measures, perform client-side encryption, and monitor EMR clusters, including troubleshooting and reviewing cluster history.

These objectives and outcomes are designed to provide a comprehensive understanding of building and optimizing batch data analytics workflows on AWS, preparing students to create robust, secure, and cost-effective data solutions.

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