Home AWS Training CoursesBuilding Batch Data Analytics Solutions on AWS

Building Batch Data Analytics Solutions on AWS

Guaranteed to Run
Price
$1.00
Duration
1 Day
Delivery Methods
Virtual Instructor Led Private Group
Delivery
Virtual
EST
Description
Objectives
Prerequisites
Course Description

This course provides in-depth, hands-on training for building batch data analytics solutions using Amazon EMR, AWS’s managed service for Apache Spark and Apache Hadoop. Participants learn how to design, implement, and operate scalable analytics pipelines that integrate Amazon EMR with open-source tools such as Apache Hive, HBase, and Hue, as well as AWS services including AWS Glue and AWS Lake Formation. The course covers the full analytics lifecycle—from data ingestion and storage to processing, security, monitoring, and cost optimization—while emphasizing best practices for performance and operational efficiency. By the end of the course, learners will be able to build and manage robust batch analytics solutions that deliver actionable insights at scale.

Course Objectives
  • Compare data warehouses, data lakes, and modern data architectures
  • Design and implement batch data analytics solutions using Amazon EMR
  • Select and deploy appropriate ingestion, transformation, and storage techniques
  • Optimize data storage using compression and efficient data formats
  • Configure EMR clusters, instance types, node roles, auto scaling, and networking for specific workloads
  • Use Apache Spark on Amazon EMR for high-performance batch analytics
  • Process and analyze batch data using Apache Hive and HBase on Amazon EMR
  • Use EMR Notebooks to support analytics and machine learning workloads
  • Integrate AWS Glue and serverless orchestration into EMR-based pipelines
  • Secure data at rest and in transit within EMR environments
  • Monitor, troubleshoot, and optimize EMR workloads
  • Apply cost management best practices to Amazon EMR operations
Who Should Attend?
  • Data Platform Engineers
  • Architects and operators responsible for building and managing data analytics pipelines
  • Technical professionals working with Spark, Hadoop, or large-scale batch analytics systems
Course Prerequisites
  • At least one year of experience managing open-source data frameworks such as Apache Spark or Apache Hadoop
  • Familiarity with data analytics pipelines and distributed data processing concepts
  • Prior experience with AWS analytics services is recommended
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