Learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR.
Module A: Overview of Data Analytics and the Data Pipeline
Module 1: Introduction to Amazon EMR
Module 2: Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage
Module 3: High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR
Module 4: Processing and Analyzing Batch Data with Amazon EMR and Apache Hive
Module 5: Serverless Data Processing
Module 6: Security and Monitoring of Amazon EMR Clusters
Module 7: Designing Batch Data Analytics Solutions
Module B: Developing Modern Data Architectures on AWS
IMPORTANT: This course prepares you for AWS Data Analytics Certification, among other courses of the Data Analytics job role track.
This course includes presentations, interactive demos, practice labs, discussions, and class exercises.
This course is intended for the following job roles:
We recommend that attendees of this course have the following prerequisites:
and have attended the following course (or have equivalent knowledge):
Building Data Analytics Solutions Using Amazon Redshift
Data Warehousing on AWS
The training is carried out in cooperation with an authorized training partner.
For the purpose of implementation, participant data will be transferred to the training partner and the training partner assumes responsibility for the processing of these data.